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LIFETIME IMPACT AND COST OF CHILDHOOD OBESITY IN EUROPE (PART 2) 1

THE LIFETIME IMPACTS AND COSTS OF CHILDHOOD OBESITY OVERWEIGHT IN EUROPE PART 2:

DATA AND DATA DOCUMENTATION

CHALLENGES AND LESSONS

FUTURE DEVELOPMENTS

Deliverable D4.7

Work Package WP 4: Evidence (the economic rationale for action on childhood obesity)

Responsible Partner: IPH IRL

Contributing partners: HZZO & HZJZ (Croatia), ATEITH & AHEPA (Greece), UCC-CHDR (IRL & NIR), ISS (Italy), MS (Portugal), NIMCH (Romania), NIJZ (Slovenia)

JANPA – Joint Action on Nutrition and Physical Activity (Grant agreement n° 677063) has received funding from the European Union’s Health Programme (2014-2020)


The content of this Deliverable represents the views of the author only and is his/her sole

responsibility; it cannot be considered to reflect the views of the European Commission

and/or the Consumers, Health, Agriculture and Food Executive Agency or any other body of

the European Union.

The European Commission and the Agency do not accept any responsibility for use that may

be made of the information it contains.


GENERAL INFORMATION

Joint Action full title Joint Action on Nutrition and Physical Activity

Joint Action acronym JANPA

Funding This Joint Action has received funding from the European Union’s Health Programme (2014-2020)

Grant Agreement Grant agreement n°677063

Starting Date 01/09/2015

Duration 27 Months

DOCUMENT MANAGEMENT

Deliverable D4.7

WP and Task WP4 and Task 4.4

Leader IPH IRL

Other contributors ATEITH, AHEPA (Greece) UCC-CHDR (IRL), NIMCH (Romania), NIJZ (Slovenia)

Due month of the deliverable M27

Actual submission month End of JANPA

Type

R: Document, report DEC: Websites, patent fillings, videos, etc. OTHER

R

Dissemination level PU: Public

PU


ROLES

COUNTRY ORGANISATION ROLE

Croatia HZZO

Vesna Kufrin

Zlatko Boni (past)

HZIZ

Sanja Music Milanovic

Country liaison, Data collation

Croatian Team Co-Leader




Greece

ATEITH

Maria Hassapidou

Anna Kokkinopoulou

AHEPA

Themistoklis Tzotzas

Despoina Komninou

Hara Dimitroula

Country liaison , Data collation

Greek Team Co-Leader

Data collation

Greek Team Co-Leader

Data collation

Data collation

Data collation

Ireland

(Republic of Ireland)

IPH-IRL

Kevin Balanda

WP4 Lead Team

WP4 Leader, D4.6 Author

UK HEALTH FORUM

Laura Webber

Sub-contractor (to IPH-IRL)

Pre-modelling data processing

Simulation modelling and cost

estimation

Ireland

(Republic of Ireland &

Northern Ireland)

UCC CHDR

Ivan J Perry

IPH-IRL

Kevin Balanda

Country liaison

Irish Team Leader


WP4 Team Leader

Italy ISS

Angela Spinelli

Laura Lauria

Country Liaison, Data collation

Italian Team Co-Leader

Italian Team Co-Leader

Portugal MS

Pedro Graça

Andrea Costa

Country liaison

Portuguese Team Co-Leader

Portuguese Team Co-Leader


Gisele Camara Data collation

Romania

NIMCH

Michaela Iuliana Nanu, National

Institute for Mother and Child

Health, Bucharest

Ioana Nanu, National Institute for

Mother and Child Health,

Bucharest


Romanian Team Co-Leader

Romanian Team Co-Leader

Slovenia

National Institute of Public Health

- NIJZ

Mojca Gabrijelcic Blenkus,


(NIJZ), Ljubljana

Aleš Korošec, National Institute of

Public Health (NIJZ), Ljubljana


Slovenian Team Co-Leader

Slovenian Team Co-Leader


ACKNOWLEDGEMENTS

International Scientific

Advisory Group

Associate Prof Jennifer Baker, Institute of Preventive Medicine in

Denmark and the University of Copenhagen. Denmark

Dr Margherita Caroli, Nutrition Unit, Department of Prevention,

Azienda Sanitaria Locale Brindisi. Italy

Dr Anne Dee, Health Service Executive. Republic of Ireland

Dr Tony Fitzgerald, Department of Statistics and & Department of

Epidemiology & Public Health. University College Cork. Republic of

Ireland

Prof David Madden, School Of Economics, University College Dublin.

Republic of Ireland

Dr Martin O’Flaherty, University of Liverpool. England

Dr Pepijn Vemer, Department of Pharmacoepidemiology &

Pharmacoeconomy, University of Groningen. Netherlands

Greece e-GOVERNMENT CENTER FOR SOCIAL SECURITY SERVICES (IDIKA S.A.)

Mathioudakis Kostas, Department of Electronic Prescriptions

HELLENIC STATISTICAL AUTHORITY

Eleni Katsorhi, Department for Statistical Information Provision

CANCER REGISTRY OF CRETE (CRC)

Dimitra Sifaki-Pistolla, School of Medicine, University of Crete

MINISTRY OF HEALTH

Ioanna Kontele, Dpt. of Public Health

Irene Grimani, Dpt. of Health Data Processing and Analysis

Italy Dr. Roberto Da Cas, Dr. Giuseppe Traversa National Centre for Drug Research and Evaluation, Istituto Superiore di Sanità Dr. Luigi Palmieri, Dr. Chiara Donfrancesco, Dr. Simona Giampaoli Department of Cardiovascular, Dismetabolic and Ageing-associated diseases, Istituto Superiore di Sanità; Dr. Daniela Pierannunzio, Dr. Valentina Minardi, Dr. Gianluigi Ferrante, Dr. Benedetta Contoli, Dr. Maria Masocco, Mr. Massimiliano Caldora National Center for Disease Prevention and Health Promotion, Istituto Superiore di Sanita


Dr. Claudio Cricelli, Dr. Francesco Lapi, Dr. Serena Pecchioli Italian College of General Practitioners and Primary Care

Portugal Carla Lopes, The National Food, Nutrition and Physical Activity Survey (IAN AF), Faculdade de Medicina da Universidade do Porto

Carla Rêgo e Margarida Nazareth, EPACI study

Carlos Dias, The National Health Examination Survey 2013-2016 (INSEF), Instituto Nacional de Saúde Doutor Ricardo Jorge, I.P.

Joana Sousa, Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL)

Julian Perelman, Universidade Nova de Lisboa / Escola Nacional de Saúde Pública

Margarida Gaspar de Matos, HBSC Portugal study

Rita Horgan, trainee nutritionist at Directorate-General of Health

Vanessa Silva, Administração Central do Sistema de Saúde, I.P.

Pedro Barras, Administração Central do Sistema de Saúde, I.P.

Slovenia National Institute of Public Health – NIJZ, Health Data Unit Blaženka Jeren, Nevenka Kelšin, Miloš Kravanja, Mojca Simončič, Poldka Suhadolc, Metka Zaletel, Ana Zgaga, Irena Zupanc,

National Institute of Public Health – NIJZ, Health Survey and Health Promotion Unit Sonja Paulin, Tatjana Kofol Bric, National Institute of Public Health – NIJZ, Prevention and Promotion Programes Unit Rade Pribakovič Brinovec National Institute of Public Health – NIJZ, Health Care System Unit Sabina Sedlak

Faculty of Sport, University of Ljubljana,

Gregor Starc, for providing SLOfit data

Collaborating Partners

Ursula O’Dwyer, Department of Health, Republic of Ireland

Cliodha Foly-Nolan, safefood, Republic of Ireland

EU Joint Research Centre (EU JRC)

WHO Europe


CONVENTIONS AND DEFINITIONS

Adult 18 or more years

Adult Healthy Weight (HW) 18.5 ≤ BMI < 25.0

Adult obesity (OB)1 Defined by WHO cut-off point (30.0 ≤ BMI)

Adult Overweight (OW) 25.0 ≤ BMI < 30.0

Advanced study A more involved participation in WP4

Adult Underweight (UW) BMI < 18.52

Basic study A less involved participation in WP4

Body Mass Index (BMI)

Two BMI categories will be used throughout the life course:

Healthy weight (HW)

Obese/Overweight (OB/OW)

Bottom-up methods Methods used to estimate impact-related and cost-related model

inputs and outputs that are based on analysis of disease and

healthcare data in cross-sectional studies or longitudinal studies

that also include BMI data

Child 0-17 years

Childhood age categories for

reporting

Age categories for children that are used in the tables of model

outputs:

Younger children: 0 – 6 years

Older children: 7 -11 years

Adolescents: 12 – 17 years

Childhood obesity Based on an individual’s BMI at age 18 years as they exit childhood

(using IOTF cut-off points).

Closed Cohort Simulation

Model (CCSM)

A simulation model that takes an initial cohort (representative of

the population at the time), ages them and simulates their

experiences throughout their lives. No additional entries or exits

from the cohort (except by death of existing cohort members) are

allowed. A broad approach to burden of disease and cost of illness

studies; their primary interest is in the current and future

experiences of the initial cohort and not the whole population

living in any future year.

Current year 2015

1 WHO defines three sub-categories of obesity: these are not considered in this study because of lack of data.

Obesity category I (OB-I): 30.0 ≤BMI < 35.0)

Obesity category II (OB-II): 35.0 ≤ BMI < 40.0)

Obesity category III (OB-III): 40.) ≤ BMI

2 Underweight individuals are included in the Healthy Weight (HW) category


Current value Cost expressed in 2016 euros

Direct healthcare costs Costs that result from outpatient and inpatient health services

(including surgery), laboratory and radiological tests, and drug

therapy.

Discounting

Discounting of future disease and disability and costs (because

people tend to devalue future disease and disability and costs

compared to present) is considered to be best practice.

Effect metric

Describes the effect of a reduction in mean childhood BMI

Excess metric

Describes an excess in some impact-cost indicator (e.g. direct

healthcare costs) that can be associated with current childhood

obesity/overweight.

Friction-cost approach An alternative approach for estimating value of productivity losses

(see Human-capital l approach)

Globcan IARC / WHO data portal for cancer statistics

(http://globocan.iarc.fr/Default.aspx)

Human-capital approach The approach used while estimating value of losses (see Friction-Loss approach)

Impact-cost indicators Indicators that capture the impacts and costs that are incur as a

result of childhood obesity and overweight

Indirect healthcare costs Healthcare costs that are borne by the patient, their family and

community. They are not included in the JANPA costing model.

IOTF cut-off points

IOTF (now called World Obesity Federation) cut-off points used to

categorise childhood BMI. They apply to 2–17 year olds and map to

WHO’s adult BMI cut-off points

Lifetime BMI trajectory Lifetime trajectory of an individual’s annual BMI values throughout

their life

Life Expectancy at birth (LE) Measured in the year of birth

Obesity or overweight

(OW/OB)

A generic term used for a group of individuals who are either

overweight or obese (Jonoula et al)

Obesity-related impacts

Two types of consequences of childhood obesity and overweight

are considered:

Health impacts (diseases, disability and death)

Societal impacts (adult productivity losses and lifetime

income loss)

per case

Based on the number of cases of a disease and not the underlying

population size

Population Attributable

Fraction (PAF)

The proportion of an impact that would be avoided if a particular

risk factor was eliminated

Open Cohort Simulation

Model (OCSM)

A simulation model that takes an initial cohort (representative of

the population at the time), ages its members and simulates their

experiences throughout their lives. Additional entries (births and

immigration) and exits (emigration) are allowed to join as the

cohort ages so that the boosted cohort remains representative of


the whole population living in any future years. A broad approach

to burden of disease and cost of illness studies; the primary

interest here is in the current and future experiences of the whole

population in a particular year

Presenteeism Not covered in the JANPA costing model. It is reduced productivity

while attending work that is associated with obesity-related

disease or disability.

Private costs Costs incurred privately by patients, their families and

communities and not by the health and social care system

Relative Risk (RR) Also Odds Ratio (OR)

Sensitivity analysis

To represent the uncertainties inherent in data and modelling

assumptions

Societal costs These are the other resources that society and its citizens and

communities forego as a result of a health condition

Societal economic perspective

Includes impacts experienced and cost incurred by society and its

communities

Start-year First year of the simulation (2015)

Stochastic models Statistical models that operate probabilistically with random model

parameters having known distributions. For example:

The virtual individuals (virtual cohort) are sampled from a

theoretical population that has a pre-specified population

distribution. At least asymptotically, the sample and the

population of interest have the same distribution

Transition probabilities and other model inputs are

random variables unknown and sampled from pre-

assigned distributions

Top-down methods Methods used to estimate impact-related and cost-related model

inputs and outputs that are based on the application of Population

Attributable Fractions (PAFs) to national disease and healthcare

data

Years of Life Lost (YLL) Years of life lost up to an individual’s national life expectancy in

their birth year

zBMI scores Because cut-off points for overweight and obesity vary with age,

gender-specific standardised z-score cut-off points will be used to

define BMI status at different ages.


TABLE OF CONTENTS

ROLES ............................................................................................................................... 4

ACKNOWLEDGEMENTS ..................................................................................................... 6

CONVENTIONS AND DEFINITIONS ..................................................................................... 8

TABLE OF CONTENTS ...................................................................................................... 11

SUMMARY ..................................................................................................................... 14

BACKGROUND ............................................................................................................................................ 14

CHALLENGES AND LESSONS .................................................................................................................. 15

RECOMMENDATIONS .............................................................................................................................. 15

CONCLUSION .............................................................................................................................................. 16

1. INTRODUCTION .......................................................................................................... 17

1.1 THE JANPA COSTING MODEL ......................................................................................................... 17

1.2 PROJECT STATUS ............................................................................................................................... 18

1.3 OUTLINE OF THIS DOCUMENT ...................................................................................................... 19

2. GLOBAL DATA DOCUMENTATION ............................................................................... 20

3. CROATIA .................................................................................................................. 22

3.1 LOCAL CONTEXT ................................................................................................................................ 22

3.2 LOCAL EVIDENCE ............................................................................................................................... 24

3.2.1 Childhood Obesity / Overweight ............................................................................................ 24

3.2.2 Childhood Impacts .................................................................................................................. 25

3.2.3 Inequalities.............................................................................................................................. 25

3.3 DATA DOCUMENTATION ................................................................................................................ 25

3.4 DATA ...................................................................................................................................................... 30

CROATIAN REFERENCES ........................................................................................................................ 31

4. GREECE .................................................................................................................... 33

4.1 LOCAL CONTEXT ................................................................................................................................ 33

4.2 LOCAL EVIDENCE ............................................................................................................................... 36



4.2.3 Adult Impacts .......................................................................................................................... 37

4.2.4 Lifetime Costs.......................................................................................................................... 38

4.2.5 Inequalities ............................................................................................................................. 39



4.4 DATA ...................................................................................................................................................... 45

GREEK REFERENCES ................................................................................................................................ 46

5. REPUBLIC OF IRELAND ............................................................................................. 33

5.1 LOCAL CONTEXT ................................................................................................................................ 49

5.2 LOCAL EVIDENCE ............................................................................................................................... 52

5.2.1 Childhood Obesity / Overweight ........................................................................................... 52


5.2.5 Inequalities.............................................................................................................................. 53


5.3.1 Irish Disease Data Quality Scores ............................................................................................ 54

5.4 DATA ...................................................................................................................................................... 58

REPUBLIC OF IRELAND AND NORTHERN IRELAND REFERENCES........................................... 60

6. ITALY ....................................................................................................................... 62

6.1 LOCAL CONTEXT ................................................................................................................................ 62

6.2 LOCAL EVIDENCE ............................................................................................................................... 64



6.2.5 Inequalities.............................................................................................................................. 66


6.4 DATA ...................................................................................................................................................... 75

ITALIAN REFERNCES ............................................................................................................................... 75

7. NORTHERN IRELAND .......................................................................................................................... 78


7.2 DATA ...................................................................................................................................................... 81

8. PORTUGAL............................................................................................................... 84

8.1 LOCAL CONTEXT ................................................................................................................................ 84

8.2 LOCAL EVIDENCE ............................................................................................................................... 88

8.2.1 Overweight / Obesity .............................................................................................................. 88


8.2.5 Inequalities ...................................................................................................................................... 91


8.4 DATA ...................................................................................................................................................... 91

PORTUGUESE REFERENCES .................................................................................................................. 92

9. ROMANIA ................................................................................................................ 94


9.1 LOCAL CONTEXT ................................................................................................................................ 94

9.2 LOCAL EVIDENCE ............................................................................................................................... 95



9.2.3 Adult Impacts .......................................................................................................................... 97

9.2.5 Inequalities.............................................................................................................................. 97


9.4 DATA ................................................................................................................................................... 103

9.5 COMMENTS ....................................................................................................................................... 104

ROMANIAN REFERENCES .................................................................................................................... 106

10. SLOVENIA .............................................................................................................. 109

10.1 LOCAL CONTEXT .......................................................................................................................... 109

10.2 LOCAL EVIDENCE ......................................................................................................................... 110

10.2.1 Childhood Obesity / Overweight ........................................................................................ 110

10.2.2 Childhood Impacts .............................................................................................................. 111

10.3 DATA DOCUMENTATION ........................................................................................................... 111

10.4 DATA ............................................................................................................................................... 114

SLOVENIAN REFERENCES ................................................................................................................... 116

11. CHALLENGES AND LESSONS, RECOMMENDATIONS AND CONCLUSIONS ................... 117

11.1 CHALLENGES AND LESSONS ..................................................................................................... 117

11.2 RECOMMENDATIONS .................................................................................................................. 119

11.3 CONCLUSIONS ............................................................................................................................... 120


SUMMARY

BACKGROUND

Cohort Simulation Cohort Models were developed to estimate the lifetime impacts and costs attributable to childhood obesity/overweight as well as the effects of 1% and 5% reductions in mean childhood BMI in participating countries. Deliverable D4.6 “The Lifetime Impacts and Costs Of Childhood Obesity Overweight In Europe. Part 1” described the modelling methodology; the data and research requirements and the final results for Republic of Ireland and Northern Ireland.

During the JANPA WP4 , data was collated from six particpating countries (Croatia, Greece, Republic of Ireland, Italy, Romania and Slovenia) and Northern Ireland (with additional funding from safefood (www.safefood.eu)). Initial modelling was completed for the seven countries and finalised for the Republic of Ireland and Northern Ireland. At the date of publication, initial model outputs for Croatia, Greece, Italy, Romania and Slovenia were still under review. Portuguese data collation was suspended. Progress is summarised in the figure below.

Figure: JANPA WP4 status (30 November 2017 – end of JANPA)

COUNTRY DATA COLLATION

PRE-SIMULATION

DATA PROCESSING

SIMULATION MODELLING

POST-SIMULATION

REVIEW

REPORTING

CROATIA (HRV) GREECE (GRC) REPUBLIC OF

IRELAND (IRL) ITALY (ITA) NORTHERN IRELAND

(NIR) PORTUGAL (PTG) ROMANIA (ROM) SLOVENIA (SVN)

Finalised

In progress

This report, Deliverable D4.7 “The Lifetime Impacts And Costs Of Childhood Obesity

Overweight In Europe. Part 2”, describes

Collated data for the seven countries (Croatia, Greece, Republic of Ireland, Italy,

Northern Ireland, Romania and Slovenia);

The challenges encountered and lessons learnt during the post-simulation review

of the model outputs

Recommendations for future development of the JANPA costing model


CHALLENGES AND LESSONS

JANPA WP4 encountered a number of significance challenges a number of which only emerged

during the project. These challenges concerned both scientific issues (Conceptual challenges, Data

demands, Software implementation, Documentation) and organisational issues (Organisationally

complex, Challenging communications, Inadequately resourced).

RECOMMENDATIONS

Recommendations about modelling methodology and data and research requirements are included

in Deliverable D4.6.

With regard to the future development of the JANPA costing model we recommend sharing it with

the OECD so that its management and development can be incorporated in their ongoing project to

improve on the modelling capacity on the economics of prevention / public health.

This would include:

Conducting an independent scientific review of the JANPA costing model and how it was developed

Developing stand-alone dedicated software, written in open source code, to fully implement

the JANPA costing model and making it available to all researchers

Conducting a detailed sensitivity audit and validation of the JANPA costing model once the open source code is available

Deploying the JANPA costing model in all European countries for which good-quality data are available, building on the OECD economics of public health project, for the next two years (2018-2019) with a dedicated European budget. This would include the six countries for which data has already been collated (Croatia, Greece, Italy, Portugal, Romania and Slovania)

Organising a high-level European conference in 2020, for example at the European Parliament, to draw comprehensive conclusions based on these estimates.

Exploring the extension of the JANPA (childhood obesity/overweight) costing model to other childhood risk factors that have significant short term and long term consequences that are, in part, mediated through a similar adult risk factor. Early uptake of smoking and alcohol are two examples.


CONCLUSION

JANPA WP4 was a very ambitious project. It is the first lifetime costing study of childhood

obesity/overweight that developed and applied a standard modelling methodology in more than

one country. JANPA WP4 had eight participating countries.

JANPA WP4 encountered significant challenges but nevertheless established that reliable estimates

of the lifetime impacts and costs of childhood obesity/overweight could be obtained in more than

one country (see Deliverable D4.6). These estimates highlight the staggering human impact and

financial costs of childhood obesity/overweight and the substantial savings that could follow from a

modest change in mean childhood BMI.

The recommendations, incorporating the lessons learnt, plot a practical way of dealing with these

challenges. If implemented, the other valuable data that have been collated in all participating

countries during JANPA WP4 can be converted into reliable and meaningful estimates in those

countries as well as other EU countries.

Finally, the JANPA costing methodology is applicable to other childhood risk factors which,like

childhood obesity/overweight, have significant short term and long term consequences that are, in

part, mediated through a similar adult risk factor (like adult obesity/overweight). In particular,

the early uptake of alcohol or smoking has several conceptual similarities with childhood obesity.


1. INTRODUCTION

1.1 THE JANPA COSTING MODEL

The modelling objectives of JANPA WP4 were to:

1. Estimate the lifetime impacts and costs of childhood obesity/overweight in eight European countries

2. Describe how these impacts and costs are expected to occur over time. 3. Assess the effect of reducing the mean population childhood BMI by 1% and 5%.

Evidence reviews were used to develop the JANPA costing model based on a “closed cohort

simulation model (CCSM)” that can be deployed in a country to estimate the lifetime impacts and

costs (direct healthcare costs and societal costs) attributable to childhood obesity/overweight as

well as the effects of 1% and 5% reductions in mean childhood BMI.

A country’s Closed Cohort Simulation Model (CCSM) takes a cohort of virtual children representative of their childhood population in 2015; models their lifetime BMI trajectories using historical BMI data, and records the mortality and morbidity, the (direct) healthcare costs and societal costs they experience over their lifetimes as a result of their modelled BMI trajectories. A range of impacts-costs are recorded over a period of 90 years of follow-up from 2015 to 2105.

Figure: Closed Cohort Simulation Model (CCSM)


Six broad phases are required to deploy the JANPA costing model in a country:

1. Data Collation

2. Pre-modelling Data Processing

3. Simulation Modelling

4. Cost Estimation

5. Post-Modelling Review

6. Reporting.

Further details can be found in Deliverable D4.6.

1.2 PROJECT STATUS

Data was collated from six particpating countries (Croatia, Greece, Republic of Ireland, Italy, Romania and Slovenia) and Northern Ireland (with additional support from safefood (www.safefood.eu)). Portuguese data collation was not completed. Final results for Republic of Ireland and Northern Ireland were published in Deliverable D4.6. Initial modelling was completed for the remaining five countries but, at the date of publication, model outputs were withheld because of issues identified durung the Post-simulation reviews. Progress is summarised in the figure below

Figure: JANPA WP4 Project status (30 November 2017)

COUNTRY DATA COLLATION

PRE-SIMULATION

DATA PROCESSING

SIMULATION MODELLING

POST-SIMULATION

REVIEW

REPORTING

CROATIA (HRV) GREECE (GRC) REPUBLIC OF

IRELAND (IRL) ITALY (ITA) NORTHERN IRELAND

(NIR) PORTUGAL (PTG) ROMANIA (ROM) SLOVENIA (SVN)

Finalised

In progress

http://www.safefood.eu/


1.3 OUTLINE OF THIS DOCUMENT

Following an introduction to the JANPA WP4 (childhood obesity) costing model in Chapter 1:

Data and its documentation that relates to all participating countries is outlined in Chapter 2

Then, in Chapter 3 to Chapter 10, we present that data and its documentation that relates to

each of the particpating countries (Croatia, Greece, Republic of Ireland, Italy, Northern

Ireland, Portugal, Romania and Slovenia).

Finally, in Chapter 11 we give an overview of the challenges and lessons learnt during the

JANPA WP4 and make recommendations about any future development of the JANPA

(childhood obesity) costing models.

As we noted in Section 1.2, by the end of JANPA on 30 November 2017, the work in the particpating countries was at different stages. Consequently, only the data and their documentation that are finalised in each country are provided in a country’s chapter. The country chapters start with local context and evidence that supplements the international material in Deliverable D4.6. Data and its documentation for each country is categorised according to the phase of the workflow it relates to: 1) Data Collation, 2) Pre-modelling Data Processing, 3) Disease Modelling, 4) Cost Estimation, 5) Post-Modelling Review or 6) Reporting. Nearly all the data used in the JANPA costing model are aggregated and collected from public sources. However, when the data was requested we did not indicate that it would be made availbale on-line. Since most models were still under review at the end of JANPA on 30 November 2017, a country’s data could be made available, with the country’s permission, on-line on the JANPA website (www.janpa.eu ).

http://www.janpa.eu/


2. GLOBAL DATA DOCUMENTATION

This chapter includes some details of some of the initial simulation models that are still being

reviewed in the post-simulation review phase.

In existing UKHF software, all country models have an initial cohort has 20,000,000 virtual

individuals. THis was not changed for the JANPA costing model.

The table below gives survivorship (sourced from initial Model Output Workbooks).

Table 2.1 Percentage of original cohort of children alive at the end of 2105 and after 91 years

follow up (Initial models under review) except Republic of Ireland and Northern Ireland)

Sex

In initial cohort (2015)

Alive at end of

2105 % alive at end of 2105

IRL Male 10219024 288927 2.83%

Female 9780976 683861 6.99%

Persons 20000000 972788 4.86%

NIR Male 10262464 463102 4.51%

Female 9737536 751491 7.72%

Persons 20000000 1214593 6.07%

SVN Male 10294365 476131 4.63%

Female 9705635 893294 9.20%

Persons 20000000 1369425 6.85%

ROM Male 10294693 339901 3.30%

Female 9705307 479081 4.94%

Persons 20000000 818982 4.09%

ITA Male 10295105 483127 4.69%

Female 9704895 1122650 11.57%

Persons 20000000 1605777 8.03%

GRC Male 10239415 143414 1.40%

Female 9760585 560275 5.74%

Persons 20000000 703689 3.52%

CRO Male 10277810 1218507 11.86%

Female 9722190 2024528 20.82%

Persons 20000000 3243035 16.22%


These surviving individuals are aged between 91 years and 108 years at the end of 2015. Of concern,

particularly in Croatia (CRO), Italy (ITA), and Slovenia (SVN), are the very large percentage of

individuals, (particularly females) who are alive after 91 years follow-up. These country models were

under review when the JANPA project ended.


3. CROATIA

3.1 LOCAL CONTEXT

In Croatia, The Ministry of Health is responsible for planning and evaluation, public health

programmes, and the regulation of capital investments in health care providers in public ownership.

In addition, one of their tasks is creating and maintaining links with other ministries and sectors

concerning all health-related issues.

Croatian health system does not function exclusively according to one financing model. It is the

combination of the Bismarck model (based on the social insurance i.e. contributions that the citizens

pay out of their salaries), and the Beveridge model (based on budget revenue), all because of the

revenue deficit as per Beveridge financing model exclusively.

The Croatian Health Insurance Fund (HZZO) is the sole insurer in the mandatory health insurance

system, which provides universal health insurance coverage to the whole population. In accordance

with the European Directive on Cross-Border Healthcare (Directive 2011/21/EU), HZZO was

appointed by the Ministry of Health as National Contact Point, in charge of providing information on

the rights of insured persons to the healthcare in another Member State, all in accordance with

European Union Regulations. HZZO provides both mandatory and voluntary health insurance.

Mandatory insurance is social insurance which means that it is in its biggest part financed through a

special tax on employees’ salaries (15% contribution), and it enables the universal use of health

services for all categories of population, under equal conditions. Every citizen of the Republic of

Croatia and foreigners with approved permanent residence are obliged to apply for mandatory

health insurance. Mandatory health insurance covers the following: primary health care, specialist-

consiliary healthcare, hospital healthcare, medicines defined by the HZZO list of medicines, right to

prosthodontic help and prosthodontic substitutes and other aids, right to healthcare abroad (under

certain conditions), right in case of injury at work or occupational disease, salary compensation

during the time of temporary inability to work (sick leave), compensation of transportation costs in

relation to the realization of the right to healthcare, maternity and parental supports. Voluntary

health insurance can be supplemental, additional or private. Supplemental health insurance is

provided by HZZO and by other registered insurance companies. Along with supplemental health

insurance, those companies can also provide additional and private health insurance and certain

rights that are not covered by mandatory health insurance. After the accession of Croatia to the

European Union, Croatian citizens got a wider spectrum of possibilities for treatment in EU Member

States. A universal price of supplemental insurance policy for all population categories has been

introduced, thus making the HZZO supplemental insurance more accessible to its insurants.

MAIN POLICIES:

The main policy regarding health is the Health Care Act (Official Gazette No. 150/08, 155/09, 71/10,

139/10, 22/11, 84/11, 154/11 - Uredba, 12/12, 35/12 - odluka Ustavnog suda RH, 70/12, 144/12 -

Uredba, 82/13, 159/13, 22/14 - odluka Ustavnog suda RH, 154/14, 70/16 - Uredba) 2012. This Act

regulates the principles of health care organization, the rights and obligations of health care users,


types and responsibilities of health care institutions (at various levels of care) and establishes the

principles of monitoring of health care institutions. Public health activities for the protection and

improvement of health, disease prevention, early detection, timely treatment, medical care and

rehabilitation. Public health activities are also defined by this Act. Main carrier and the coordinator

of public health activities at the national level is the Croatian Institute of Public Health, while county

level activities are coordinated and implemented by County Public Health Institutes.

The Mandatory Health Insurance Act of Foreigners (Offical Gazette No. 80/13, 15/18) 2013 regulates

the scope of the right to health care and other rights and obligations of persons insured under the

MHI scheme, supervision, financing, organization, and tasks of the HZZO and the conclusion of

contracts between the HZZO and health care providers and suppliers of medical goods.

Measures of Health Care (Official Gazette 126/2006) represent a set of measures to preserve and

improve health of every member of the community.

The provision and financing of services are largely public, although private providers and insurers

also operate in the health sector. Provision of health care services in specific areas of care is

regulated in separate legal acts. The key acts include: the Medical Practice Act, the Pharmacy Act,

the Nursing Act and the Dental Care Act (all in force since 2003 with amendments in 2008 and/or

2013); the Midwifery Act of 2008; the Physical Therapy Activities Act of 2008; and the Act on the

Health Care Technical Services of 2009. The quality of health care services is regulated in the Act on

Quality of Health and Social Care of 2011 and the provision of voluntary health insurance by the

Voluntary Health Insurance Act of 2006 (with amendments in 2008 and 2010).

STRATEGIES:

National Health Care Strategy 2012-2020 (Official Gazette 116/12). The fundamental framework of

the National Health Care Strategy 2012 – 2020 is formed by the Health Care Act. As the main

document directing development in the future period, the Strategy makes the basis for bringing

policies and decisions in health care, including decisions on distribution of budgetary funds in the

health care sector. It forms a basis for drawing up new planning and operative documents, as well as

for evaluating and revising the existing ones that elaborate development measures and concrete

activities in individual health care segments (e.g. human resources, hospital system, palliative care,

public health etc.).

The Strategic Plan for Public Health Development 2013-2015 is an integral part of the National

Strategy for Health Care 2012-2020 and the umbrella document of the Public Health of the Republic

of Croatia defining the development priorities, objectives, activities and responsibilities of the

relevant partners. New Strategic Plan for the period 2017-2020 in currently being developed.

ACTION PLANS:

Action Plan for the Prevention and Control of Noncommunicable Diseases 2015-2020 issued by the

Ministry of Health is based on a series of international and Croatian strategic documents on

prevention of chronic non-communicable diseases.


PUBLIC HEALTH PROGRAMMES:

National health promotion programme “Living Healthy” administered by the Ministry of Health and

the Croatian Institute of Public Health and County Public Health Institutes has a goal to inform,

educate and raise awareness among the citizens of the Republic of Croatia of all ages on positive

aspects of healthy lifestyles – healthy nutrition, physical activity, obesity prevention, decreasing

overweight, decreasing morbidity from chronic non-communicable (cardiovascular diseases,

tumours, type 2 diabetes, chronic obstructive pulmonary disease, mental illness), promotion of

physical, sexual and reproductive, and mental health. Due to its comprehensiveness, “Living

Healthy” is composed of five components, Health Education, Health and Physical Activity, Health and

Nutrition, Health and the Workplace, and Health and the Environment. In the implementation of this

National Programme intersectorial bodies, government authorities and other institutions also take

part.

School Fruit and Vegetables Scheme aims to increase the consumption of fruit and vegetables and

decrease the consumption of food rich in trans-fatty acids, sugar and salt at school to encourage

healthier eating habits, in the context of declining consumption of fresh fruit and vegetables and

increasing incidence of child obesity.

The School Milk Scheme is intended to encourage consumption of dairy products among school-

children.

National Cancer Screening Programmes administered by the Ministry of Health and the Croatian

Institute of Public Health and County Public Health Institutes aims at early detection of cancer. The

aim of preventive screening programmes is early detection, and reduction in morbidity and mortality

of colon, cervical and breast cancer, improvement in the quality of life and the health of the entire

Croatian population.

3.2 LOCAL EVIDENCE

We give a summary of the four systematic reviews (conducted by the Croatian Team with additional

support for safefood) along with local materials provided by the Croatian Team in the “Local

Materials Survey”

3.2.1 Childhood Obesity / Overweight

Information on the prevalence of overweight and obesity in Croatia was found in eight sources.

Three are considered here. Sample sizes are generally small and samples are not nationally

representative. A study of children aged 3 to 7 in Osijek conducted in 2011 (Farkas et al., 2015)

estimated that about 24% of boys and 16% of girls were overweight or obese (WHO cut-points).

Among children aged 6-7 from a small nationally representative sample surveyed in 2003-2004,

about 22% of boys and 20% of girls were overweight or obese (Juresa et al., 2012). In Zagreb, a

survey of adolescents aged 15 to 19 resulted in estimates of overweight and obesity of 23% among

boys and 13% among girls (Petranowic et al., 2014). Croatia collected data for COSI for the first time

in the autumn of 2015; these results are not yet published.


3.2.2 Childhood Impacts

Nine papers from Croatia examined health impacts of overweight/obesity during childhood. Two of

these examined trends in the incidence of type 1 diabetes in children. Stipancic et al. (2008)

estimated a 9% average annual increase in incidence for the period 1995-2003, while Putarek et al.

(2015) estimated a 6% average annual increase from 2004-2012. While not empirically linked to

rates of overweight or obesity, they nonetheless show a worrying trend.

Two papers examined cardio-metabolic risk factors. Ille et al. (2012) found, in a sample of children

and adolescents, all with BMI > 90th percentile, that 10.4% had impaired glucose tolerance, 17.3%

had increase cholesterol, and 30.1% had elevated triglyceride levels. Musil et al. (2012) reported

significant associations between raised blood pressure and overweight/obesity among 8th grade

adolescents.

A further three sources examined associations between BMI and musculo-skeletal/motor and

aerobic function. Delas et al. (2008) tested adolescents (mean age 13 years) on speed, power,

reaction time and balance. Among overweight/obese boys tested, motor performance was

significantly lower on all tests than healthy weight boys except balance, while in girls, only lower leg

repetitive movement was significantly lower. Bozanic et al. (2011) reported lower performance on

tests of speed and agility among overweight and obese 7 year-old children of both sexes compared

to healthy weight children. Kunjesic et al. (2015) found that higher BMI was significantly associated

with lower aerobic capacity among children aged 7 to 11 years.

Croatia is the only country for which information was located on two further areas – idiopathic

intracranial hypertension (IIH), and hormonal/reproductive health. In a clinical sample of children

(mean age 10.7 years), Sindicic Dessardo et al. (2010) reported that 75% of children suffering from

IIH were overweight or obese. Bralic et al. (2012) reported a significant association between early

onset of menarche and overweight/obesity3.

3.2.3 Inequalities

Five studies on inequalities were found for Croatia. Two of these confirmed associations between

parental and child BMI (Bralic et al., 2005; Petricevic et al., 2012), a further two indicated the

protective effects of breastfeeding (Mandic et al. 2011; Skledar & Milosevic, 2015), and the fifth

found a higher prevalence of overweight and obesity in children of lower birth order, and in families

with fewer children and lower levels of parental education (Juresa et al., 2012).

3.3 DATA DOCUMENTATION

Phase 1: Data Collation

3 Early onset of menstruation is a risk factor for breast cancer (Collaborative Group on Hormonal Factors in Breast Cancer,

2012).


20171130 Phase 1 (Croatia) Data Calculations (1).xlsx

20171130 Phase 1 (Croatia) Data Calculations (2).xlsx

20171130 Phase 1 (Croatia) Data Collation Workbook.xlsx

20171130 Phase 1 (Croatia) Data Sources.xlsx

Phase 2: Pre-simulation Data Processing

20171130 Phase 2 (Croatia) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Croatia) Data Documentation (Part 2).docx

Phase 3: Simulation Modelling

Phase 4: Cost Estimation

Phase 5: Post Simulation Review

20171130 Phase 5 (Croatia) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Croatia) Model Outputs Workbook - UNDISC.xlsm

Table. Phase 1: Croatian Disease Data Quality Scores

1 2 3 4 5 6

No acceptable

data

Must be

estimated

from other

data1

International

proxy

"Approximate"

data only2

Not

applicable

(non-fatal

disease)

Acceptable

data

1. For disease parameters: prevalence, incidence, survival mortality)

2. "Approximate" data only:

ICD code mismatch

Hospital data used for prevalence or incidence

Self-reported BMI

Regional (sub-national) data


Adult diseases

Disease Mortality Incidence Survival Prevalence

Oesophageal

Cancer

Croatian Bureau

of Statistics Globocan

Eurocare 5

Database Globocan

Colorectal

Cancer

Croatian Bureau

of Statistics

C18 to C21

Globocan

Eurocare 5

Database

C18 to C21

Globocan

Liver Cancer

Croatian Bureau

of Statistics

C22

Globocan

Eurocare 5

Database

C22

Globocan

Gallbladder

Cancer

Croatian Bureau

of Statistics

C23 to C24

Globocan

Eurocare 5

Database Globocan

Pancreatic

cancer

Croatian Bureau


Eurocare 5

Database Globocan

Cancer-Breast,

post-

menopausal

(females only

aged 50+)

Croatian Bureau


Eurocare 5

Database Globocan

Endometrial

cancer

Croatian Bureau

of Statistics

C54

Globocan

C54

Eurocare 5

Database

C54

Globocan

Ovarian

Cancer

Croatian Bureau


Eurocare 5

Database Globocan

Prostate

cancer (males

only)

Croatian Bureau


Eurocare 5

Database Globocan

Kidney Cancer

Croatian Bureau

of Statistics

C64 to C66

Globocan

Eurocare 5

Database Globocan

Urothelial

Cancer (males

only)

Croatian Bureau


Eurocare 5

Database Globocan


Thyroid

cancer

Croatian Bureau


Eurocare 5

Database Globocan

Type 2

Diabetes

GBD 2015 GBD 2015 Not required for

the model

European Health

Interview Survey

(EHIS)

Polycystic

Ovarian

Syndrome

Croatian Bureau

of Statistics GBD 2015 GBD 2015

Multiple

Sclerosis

Croatian Bureau

of Statistics

http://www.jns-

journal.com/article

/S0022-

510X(06)00168-

7/pdf

http://www.jns-

journal.com/article/

S0022-

510X(06)00168-

7/pdf

Stroke

Croatian Bureau

of Statistics

Calculate incidence

from prevalence

European Health

Interview Survey

(EHIS)

Hypertension

Croatian Bureau

of Statistics

Calculate incidence

from prevalence

Not required for

the model

European Health

Interview Survey

(EHIS)

Ischaemic

Heart Disease

Croatian Bureau

of Statistics GBD 2015 GBD 2015

Pulmonary

Embolus

Croatian Bureau

of Statistics UK proxy

Calculate

prevalence from

incidence

Deep Vein

Thrombosis

Croatian Bureau

of Statistics UK proxy

Calculate

prevalence from

incidence

Asthma

Croatian Bureau

of Statistics

J45 to J46

Primary health care

data J40-J44, J47

European Health

Interview Survey

(EHIS)

Non-alcoholic

fatty liver

disease

(NAFLD)

Croatian Bureau

of Statistics

K76

Primary health care

data K70-K77

Global

epidemiology of

nonalcoholic fatty

liver disease-Meta-

analytic assessment

of prevalence,

incidence, and

outcomes.


https://www.ncbi.nl

m.nih.gov/pubmed/

26707365

Gallbladder

Disease

Croatian Bureau

of Statistics

K80, K81, K85

Hospital discharge

data GBD 2015

Psoriasis

Croatian Bureau

of Statistics

https://www.ncbi.n

lm.nih.gov/pubme

d/2609862

https://goo.gl/xzCS

kd

GBD 2015

Gout

Croatian Bureau

of Statistics

M10

Primary health care

data M05-M14

zero deaths - so

assume prob

survival = 1

http://www.tandfo

nline.com/doi/pdf/

10.3109/02813432.

2015.1132886?nee

dAccess=true

Osteoarthritis

–

Gonarthrosis

Knee Pain

Croatian Bureau

of Statistics

M17

Primary health care

data M15-M19

zero deaths - so

assume prob

survival = 1

GBD 2015

Chronic Back

Pain

Croatian Bureau

of Statistics

M54

Primary health care

data M50-M54

zero deaths - so

assume prob

survival = 1

European Health

Interview Survey

(EHIS)

Hypertension

in pregnancy

Croatian Bureau

of Statistics

Primary health care

data O13-O14

zero deaths - so

assume prob

survival = 1

Childhood diseases

Diseases Mortality Incidence Survival Prevalence

Wheezing disorders

ISAAC study http://erj.ersjournals.com/content/38/S


uppl_55/p4132

Metabolic syndrome

https://www.hindawi.com/journals/ije/2016/1823561/

Hyperlipidemia

Depression Slovenia proxy - using pharma data??

Musculoskeletal pain

Primary health care data M50 - M54

Obstructive sleep apnoea

proxy https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3004499/#B8

High blood pressure

Not required for the model


CRO-KOP study http://www.collantropol.hr/antropo/article/view/459/164

Type 2 diabetes


Primary health care data E10-E14


Asthma Croatian Bureau of Statistics

Primary health care data - Bronchitis, emphysema, asthma and other chronic obstructive pulmonary disease (J40-J44, J47)

ISAAC study http://erj.ersjournals.com/content/38/Suppl_55/p4132

Non-alcoholic fatty liver disease

Croatian Bureau of Statistics

Primary health care data K70-K77

http://bmcpediatr.biomedcentral.com/articles/10.1186/1471-2431-13-40

3.4 DATA


20171130 Phase 1 (Croatia) Data Collation Workbook.xlsx


Data not available (see Data Documentation files)

Phase 3 and 4: Simulation Modelling and Cost Estimation


20171130 Phase 3&4 (Croatia) Initial Model Output Workbook.xlsx


20171130 Phase 5 (Croatia) Initial Resturctured Model Output Workbook.xlsx

20171130 Phase 5 (Croatia) Initial Core tables and Graphs Workbook.xlsx

Phase 6: Reporting

20171130 (Croatia) Final Restructured Model Output Workbook.xlsx

20171130 (Croatia) Final Combined Model Outputs SAS Dataset.ssd

20171130 (Croatia) Final Combined Model Outputs Worksheet.xlsx

20171130 (Croatia) Final Core Tables and Graphs Workbook.xlsx

UNDISCOUNTED and DISCOUNTED versions of thesae data files are available .

As a result of the feedback loops include in the workflow, the software was sometimes rerun with

corrected inputs. Only the final model outputs from the simulation software are listed.

CROATIAN REFERENCES

Bozanic, A., Beic, J., & Mumanovic, D. (2011). “OVERWEIGHT AND OBESITY AS LIMITATION FACTORS OF AGILITY AND STRENGTH DEVELOPMENT.” Proceedings of the 6

th International Scientific Conference on

Kinesiology Zagreb, September, pp. 207-210.

Bralic, I., Tahirovic, H., Matanic, D., Vrdoljak, O., Stojanovic-Spehar, S., Kovacic, V., & Blazekovic-Milakovic, S. (2012). “Association of early menarche age and overweight/obesity.” Journal of Pediatric Endocrinology and Metabolism 25(1-2): 57-62.

Bralic, I., Vrdoljak, J., & Kovacic, V. (2005). “Associations between parental and child overweight and obesity.” Collegium Antropologicum 29: 481-486.

Delas, N., Tudor, A., Ruzic, L., & Sestan, B. (2008). “Obesity indicators and athletic performance in 11-15 year-old children.” Hrvatski Športskomedicinski Vjesnik 23(1): 35-44.

Farkas, D., Tomak, Z., Petric, D., & Novac, D. (2015). “Anthropometric characteristics and obesity indicators among preschool children in an urban area in Croatia.” Graduate Journal of Sport, Exercise & Physical Education Research 3: 13-27.

Ille, J., Furic-Cunko, V., Cigrovski, A, Bogdanic, A., Rojnic Putarek, N., Radica, A., & Dumic, M. (2012). “Incidence of glucose and lipid metabolism disorders in overweight children and adolescents in Croatia.” Endocrine Abstracts 29: 1269.

Juresa, V., Musil, V., Majer, M., Ivankovic, D., & Petrovic, D. (2012). “Behavioral Pattern of Overweight and Obese School Children.” Collegium Antropolicum 36 Suppl 1: 139-146.

Kunjesic, M., Badric, M., & Prskalo, I. (2015). “RELATIONS BETWEEN OBESITY INDICATORS AND AEROBIC CAPACITY OF PUPILS.” Sport SPA 12(1): 17-24.

Mandic, Z., Piricki, A.P., Kenjeric, D., Hanicar, B., & Tansic, I. (2011). “Breast vs. bottle: differences in the growth of Croatian infants.” Maternal & Child Nutrition 7: 389-396.

Musil, V., Majer, M., & Juresa, V. (2012). “Elevated Blood Pressure in School Children and Adolescents –

Prevalence and Associated Risk Factors.” Collegium Antropologicum 36 Suppl 1: 147-155.


Petranovic, M.Z., Thomas, Z., Narancic, N.S., Skaric-Juric, T., Vecek, A., & Milicic, J. (2014). “A six decades long

follow-up on body size in adolescents from Zagreb, Croatia (1951-2010).” Economics & Human Biology 13: 155-

164.

Petricevic, N., Puharic, Z., Posavic, M., Simetin, I.P., & Franelic, I.P. (2012). “Family history and parental recognition of overweight in Croatian children.” European Journal of Pediatrics 171: 1209-1214.

Putarek, N.R., Ille, J., Uroic, A.S., Skrabic, V., Stipancic, G., Krnic, N., Radica, A., Marjanac, I., Severinski, S., Svigir, A., Bogdanic, A., & Dumic, M. (2015). “Incidence of type 1 diabetes mellitus in 0 to 14-yr-old children in Croatia – 2004 to 2012 study.” Pediatric Diabetes 16: 448-453.

Sindicic Dessardo, N., Dessardo, S., Sasso, N., Sarunic, A.C., & Dezulovic, M.S. (2010). “Pediatric Idiopathic Intracranial Hypertension: Clinical and Demographic Features.” Collegium Antropologicum 34 Suppl 2: 217-221.

Skledar, M.T., & Milosevic, M. (2015). “BREASTFEEDING AND TIME OF COMPLEMENTARY FOOD INTRODUCTION AS PREDICTORS OF OBESITY IN CHILDREN.” Central European Journal of Public Health 23: 26-31.

Stipancic, G., La Grasta Sabolic, L., Malencia, M., Radica, A., Skrabic, V., & Tiljak, M.K. (2008). “Incidence and trends of childhood Type 1 diabetes in Croatia from 1995 to 2003.” Diabetes Research & Clinical Practice 80: 122-127.


4. GREECE

4.1 LOCAL CONTEXT

Main policies

- School food policy (mandatory) - Physical activity in kindergartens and schools (mandatory) - Restrict marketing and advertising in school canteens.

The Greek school canteen policy aims to protect and promote health of the sensitive student

population by creating a supportive school environment that promotes healthy eating. The

policy clearly defines the food and drink list allowed to be sold and served by the school

canteens, whereas marketing or advertising of products not listed above in the school canteens

is prohibited.

Main strategies

- To create a national program aiming to promote healthy eating and lifestyle in schools and halt childhood obesity increase, in collaboration with all Ministries. The national program will be based and will use the experience and the results collected from previous projects .It will also use the educational material that has been produced by the ministry of health and the ministry of education.

- To promote the collaboration of different health professionals, such as doctors, nutritionists, psychologists and physical activity trainers in prevention and treatment programs, in order to result in more trustworthy results.

Main action plans

- The EU Action Plan on Childhood Obesity 2014-2020 - The European Food and Nutrition Action Plan 2015-2020 - Physical activity strategy for the WHO European Region 2016-2025 - Promote breastfeeding (WHO baby-friendly hospitals) - The Ministries are sensitive regarding the childhood obesity epidemic, therefore they co-

fund projects related to the prevention or reduction of childhood obesity with the EU. Examples of some projects are the following.

o The Ministry of Health supports Rhea mother-child cohort, o The Ministry of Rural Development and Food supports EU School Milk Programme

and EU School Fruit Scheme o The Ministry of Education, Research and Religious Affairs supports Kids’ Athletics

and EU School Fruit Scheme o The Ministry of Culture and Sports supports the program:” Be active.”


Main public health programs for childhood obesity

- ADONUT study; from 2010 to 2012 measuring children aged 12-18 years, assessing overweight and obesity and nutritional status.

- COSI study; Greece firstly participated in the 2009/2010 round until today measuring children aged 7 and 9 years old every 3 years.

- GRECO study; in 2009 measuring children aged 10-12 years, assessing overweight and obesity and nutritional status.

- Vyronas study; from 2004 to 2005 measuring children aged 12-17 years, assessing overweight and obesity and nutritional status.

- FETA project; from 2011 to 2014 measuring children aged 12-18 years, assessing overweight and obesity and nutritional status.

- National Epidemiological Survey; from 2010 to 2012 measuring children aged 6 to 12 years assessing overweight and obesity ,clinical and nutritional status.

Main public health programs for adult obesity.

- EHIS; in 2014 measuring people above 18 years old, assessing overweight and obesity and clinical and nutritional status.

- ATTICA; from 2001 to 2002, participants above 20 years old, assessing overweight and obesity and nutritional status.

- HYDRIA; from 2012 to 2014, participants above 18 years old, assessing overweight and obesity and nutritional status.

Main public bodies involved in health promotion and prevention issues

- The Hellenic Ministry of Health is the main policy-making authority. It decides on health policy issues and national health strategies, sets priorities, determines the funding for activities, and allocates resources, while it proposes legislative changes and undertakes the implementation of laws and/or reforms.

- The Directorate for Nutrition, the Department for Nutrition Policy has responsibilities such as:

o Development of regular reports with data about nutrition and nutrition-related diseases (e.g. prevalence data on obesity and diabetes).

o Development of national nutrition policy, as well as dietary guidelines and patterns for the population in Greece.

- The Department for Actions on Nutrition Issues has responsibilities such as: o Determining standards for food provided in school canteens, in collaboration with

other organisations. o Planning, implementing and overseeing prevention programmes concerning

nutrition. - The seven Health Region Administrations (YPEs) are responsible for implementing national

priorities at the regional level, coordinating regional activities and organising and managing the delivery of health and welfare services.

- The National Council for Public Health (ESYDY) is an independent authority consisting of experts in epidemiology, health promotion and public health, and is responsible for the scientific supervision and coordination of public health organisations for the monitoring and promotion of the health of the population.


- The National Organization for Health Care Services Provision (EOPYY) is a public corporate body which provides health services to insured active members and pensioners, as well as their family dependents.

- At the prefectural level, public health directorates of the Prefectural Authorities include health prevention and promotion departments, with competences such as the implementation of immunization and preventive medicine programmes, the implementation of programmes to protect mothers and children, the implementation of programmes for chronic ailments and illnesses not easily susceptible to treatment, as well as health education activities.

- Health centres provide services which include prevention (mainly immunization) and health promotion.

- Municipalities are responsible for running several public health programmes and for the provision of primary health care services and health prevention and promotion programmes (e.g. services in the municipal health clinics, the open care centres (KAPIs) and the programme “Home Assistance” for the elderly).

- The Centre for the Control and Prevention of Diseases (KEELPNO) is responsible for the control of communicable diseases and HIV/AIDS.

- The Institute of Child Health (IYP) is responsible for research, educational and preventive activities relating to children.

- The National Centre for Diabetes Mellitus (EKEDI) is responsible for the monitoring and coordination of research, prevention and treatment of diabetes mellitus.

- The Hellenic Food Authority (EFET) is the main body responsible for inspection of foodstuffs in Greece.

- The purpose of the National School of Public Health (ESDY) is to offer postgraduate and further education to graduates of universities and technical colleges, to carry out scientific research and to provide services related to public health, health promotion, health service administration and social policy.

Other organisations involved in health promotion and prevention issues

- Institute of Preventive Medicine, Environmental and Occupational Health Prolepsis - National Network of Health Promoting Hospitals (HPH) - National Network of Healthy Municipalities Cities - Health Promotion - Hellenic Medical Association for Obesity - Hellenic Dietetics Association - Dietitians & Nutritionists Association of Greece - Hellenic Society for Clinical Nutrition and Metabolism - Hellenic Foundation of Gastroenterology and Nutrition - Hellenic Heart Foundation - Hellenic Cardiology Foundation - Hellenic Society of Internal Medicine - Hellenic Endocrine Society - Hellenic Paediatric Association - Paediatric Association of Northern Greece - Internal Medicine Society of Northern Greece - Atherosclerosis Society of Northern Greece - Hellenic Diabetes Association - Northern Greece Diabetes Association - Hellenic Society of Lipidology and Atherosclerosis - Hellenic Society for the Study of Obesity, Metabolism and Nutrition Disorders - IBFAN Greece


- Child Health Institution

4.2 LOCAL EVIDENCE


Local materials from Greece resulted in 34 published sets of prevalence estimates since 2000. Four

are considered here. A systematic review by Kotanidou et al. (2013) identified 25 papers (covering

31 studies) that assessed prevalence of overweight and obesity in children aged 1 to 12 (using IOTF

cut-points, surveys conducted between 2004 and 2010). Meta-analysis indicated that 10.2% (CI95%:

9.8-10.7%) of Greek children were obese, 23.7% (CI95%: 22.7-24.8%) were overweight and the

combined prevalence of overweight and obesity was approximately 34% (CI95%: 32.7-35.3%).

Analysis by gender showed that 11.0% of boys and 9.7% of girls were obese, while 24.1% of boys and

23.2% of girls were overweight.

Among children aged 1 to 5 (from five regions in Greece surveyed in 2003-2004; Manios et al., 2007),

about 19% of boys and 24% of girls were overweight or obese. A survey conducted six years later

(2009-2010) in pre-schoolers of same age in the city of Thessaloniki, identified 22% boys and 20%

girls as overweight or obese ( Hassapidou et al, 2015).In a nationally representative sample of 8 and

9 year-olds (surveyed in 2007; Tambalis, 2010), similar percentages of boys (39%) and girls (38%)

aged 8 to 9 were overweight or obese. These results are similar to those reported for round 2 of

COSI (ages 7 and 9; Wijnhoven et al., 2014a)4. Among adolescents, a first representative panhellenic

study conducted in 2003 (Tzotzas et al, 2008) showed that 29% of boys and 17% of girls aged 13 to

19 were overweight or obese. A second nationally representative survey in 2010-2012

(Grammatikopoulou et al., 2014), demonstrated increasing prevalence: 37 % of boys and 25% of girls

were overweight or obese.In this study, rates of overweight and obesity in adolescents were highest

at ages 12-14, but among adolescents at all ages, they exceeded 33% in boys and 20% in girls5.

Trends

Five sources examining trends in prevalence were located for Greece (Papadimitriou et al., 2006;

Tambalis et al., 2010; Roditis et al., 2009; Kotanidou et al., 2013; Kleanthous et al., 2016; the

narrative review by Roditis et al. is not considered in detail here). One of these sources (Kotanidou et

al., 2013) is a systematic review of prevalence in children 1 to 12 , which indicated, on the basis of 25

papers (31 sets of estimates, all using the IOTF cut-points), that increases in prevalence between

2001-2003 have been followed by a period of stabilisation from 2003-2010. The results of analyses

by Tambalis et al. (2010), which examined trends in overweight and obesity among 8 and 9 year-old

children from nationally representative surveys conducted annually between 1997 and 2007 are

partially consistent with those of Kotanidou et al. (2013). Tambalis et al. (2010) reported a

stabilising in prevalence of obesity (IOTF cut-points) among both boys (at around 12.2-12.3%) and

girls (around 11.2-11.3%) from 2004 to 2007. However, prevalence of overweight showed an

4 Results for round 3 of COSI are not yet published for Greece. 5 This study also included estimates of abdominal obesity (using cut-points of the International Diabetes Federation, IDF). Across all adolescents, about 9% of boys and 9% of girls were classified as being abdominally obese. Rates of abdominal obesity peaked in boys at age 13 and in girls at age 12, thereafter showing small declines with increasing age.


increasing trend during the same time period (from 21.2% to 26.5% in boys and 22.1% to 26.7% in

girls).

Trends in the Attica region have been examined in two papers. Papadimitriou et al. (2006) reported

increases in the prevalence of overweight and obesity among children aged 6 to 11 between 1994

and 2005, but these were not statistically significant. Kleanthous et al. (2016) compared the

prevalence of overweight and obesity among children in Grades 1, 4, 7 and 10 in 2009 and 2012

(using the IOTF criteria) and found that rates of overweight and obesity declined significantly in both

boys and girls over the 2.5 year time period.

In summary, trends in the prevalence of child overweight and obesity in Greece show rapid increases

in both children and adolescents during the 1990s and early 2000s, followed by a slowing down of

increases in prevalence, and some evidence of stabilisation in young children but not in adolescents,

since around 2004.

Limitations of this report are the heterogeneity of the studies included and their cross-sectional

design, making difficult to accurately determine secular trends in the prevalence of childhood

obesity in Greece. Moreover, the data on predisposing factors does not enable us to draw

conclusions on possible causes. Finally, it would be urgent to investigate whether the current

financial crisis in Greece has a deteriorating or a protective effect in the obesity prevalence.


The following paragraph deals with associated (or predisposing) factors for obesity and not with

impacts; it has to be placed into the previous chapter, just after the Trends paragraph.

Associated factors

Twenty-four studies on this topic were found for Greece. Consistent findings emerged for higher

prevalence of overweight and obesity associated with lower parental education, boys, Greek-born

(rather than foreign-born) children, higher parental BMI, lower dietary quality, skipping breakfast,

less frequent meals, lower levels of physical activity, and higher levels of sedentary activity. Results

concerning variations in prevalence by rural and urban areas are not entirely consistent: this may be

due to the regional nature of some samples and/or more complex associations between local

environment and overweight/obesity. For example, Farajian et al. (2011) found that some aspects of

children’s diet were associated with rates of overweight/obesity, while dietary quality in turn varied

depending on urban/rural environment. Chalkias et al.’s (2013) analyses of children’s environments

indicated that areas characterised by low education and income levels, high population densities and

limited recreation facilities were associated with higher prevalence.

4.2.3 Adult Impacts

The impacts of overweight and obesity on adult Greek population are described in many

publications. Concerning the cardio-metabolic health, the ATTICA cohort study examined the


incidence of cardiovascular disease (CVD) and cardiovascular risk factors in the Attica region

(Panagiotakos et al, 2015; Koloverou et al 2014; Panagiotakos et al, 2009). The 10-year incidence of

fatal and non- fatal CVD (coronary heart disease, acute coronary syndromes, stroke) was 19.7% in

men and 11.7% in women, the 10-year incidence of type 2 diabetes was 13.4% in men and 12.4% in

women, while the 5-year incidence of hypertension was 8.8% in men and 10.8% in women. HYDRIA

study examined the prevalence of chronic diseases in a representative sample of the Greek adult

population and found that the prevalence of acute myocardial infarction was 2.8%, of stroke was

1.9%, of diabetes was 11.4%, of hypertension was 41.7% and of asthma was 8.6%.

Reliable data covering cancer epidemiology in Greek adults come from the Globocan project that

was carried out by the International Agency for Research on Cancer. The 5-year prevalence of

obesity- associated cancers in Greece was estimated to 19.5% for breast cancer, 10.8% for colorectal

cancer, 11.8% for prostate cancer, 9.5% for bladder cancer, 3.2% for endometrial cancer, 3.2% for

kidney cancer, 2.2% for ovarian cancer, 1.1% for liver cancer, 1% for thyroid cancer, 0.9% for

pancreatic cancer, 0.4% for gallbladder cancer and 0.2% for oesophageal cancer. Regarding the

musculoskeletal disorders related to obesity, the prevalence of symptomatic knee and hip

osteoarthritis was 6% and 0.9% respectively in the general adult population (Andrianakos et al,

2006), the prevalence of gout was 4.75% (Anagnostopoulos et al, 2010), while the prevalence of low

back pain was 15% (Billis et al, 2017).

4.2.4 Lifetime Costs

In Greece, the economic burden of obesity alone has not been calculated yet in terms of productivity

losses, costs of disability and other sickness related costs. Some limited data come from studies on

obesity related illnesses, such as type 2 diabetes, hypertension and cardiovascular diseases

(Athanasakis et al., 2010; Migdalis et al., 2015; Boubouchairopoulou et al, 2014; Holstenson et al.,

2011).

An estimation of the annual direct cost of treating type 2 diabetes had first been calculated by

Athanasakis et al. (2010) presenting an average cost of € 1,297 per patient. However, costs for

comorbidities and hospitalizations due to diabetic complications were not included. In another

study, Migdalis et al. (2015) calculated most of the cost components reflecting more accurately the

real burden of diabetes which was estimated at € 7,111 total annual cost per patient excluding

disability pensions. The cost for comorbidities was the largest percentage (48%) averaging at € 3,353

followed by the cost of diabetic and non-diabetic medication at € 2,506 (36%). Therefore, type 2

diabetes alone is a costly disease accounting for approximately 6.3 billion Euros, a significant

percentage of the total National Health System budget.

The lack of a centralized patient record database has been encountered as the major limitation for

adequate and reliable data collection and analysis. In 2012, a national electronic database system

was established in Greece and has started collecting data which have not yet been analyzed. The

present report would be the first document to attempt national health data analysis calculating most

of the lifetime costs for obesity associated diseases. In this way, obesity control, starting from

childhood, has to be recognized as a primary goal which would contribute to healthy and active

aging and offer significant potential for economic and societal gain.


4.2.5 Inequalities

A relatively large number of sources on impacts of childhood overweight/obesity were retrieved for

Greece. Nineteen of these covered aspects of cardio-metabolic health. Of these, 10 examined

multiple risk factors associated with the metabolic syndrome (Kollias et al., 2011; Mazaraki et al.,

2011; Hatzis et al., 2012; Kollias et al., 2013; Mirkopoulou et al., 2010; Manios et al., 2004; Sakka et

al., 2015; Papadopoulou-Alataki et al., 2004; Lydakis et al., 2012; Sakou et al., 2015). For example, in

a sample of 17 year-olds, Mirkopoulou et al. (2010) reported that central obesity increased the

chances of impaired fasting glucose (eight-fold) and doubled the prevalence of dyslipidaemia and

elevated serum cholesterol. Among younger children (age 4-7 years) all with a waist circumference >

90th percentile, Hatzis et al. (2012) found 77% had an increment in at least one risk factor for

atherogenesis. The factors with the highest prevalence were overweight (18.1%) and obesity (9.9%)

followed by hyperlipidemia (about 15%) and hypertension (7.7%). Mazaraki et al. (2011) reported a

significant negative relationship between BMI and albumin to creatinine ratio, (ACR, an indicator of

risk of diabetes and hypertension) among adolescents aged 12-17 years.

Three more of these 19 papers examined blood pressure (BP) (Mavrakanas et al., 2009;

Angelopoulos et al., 2009; Kollias et al., 2009). For example, Mavrakanas et al. (2009) reported that

7.9% of a sample of children aged 4-7 years had elevated systolic or diastolic BP (≥95th percentile),

and that this was more common in obese children, from 17.8% to 27.5% depending on the method

used to define obesity.

Two papers examining the associations between insulin resistance/impaired glucose tolerance found

strong, significant associations with measures of adiposity in children (Xekouki et al., 2007; Manios

et al., 2007). For example, among children aged 10 to 12 years, insulin resistance (IR) was 5-10 times

higher in obese compared to healthy weight children (Manios et al., 2007).

The four remaining papers covering aspects of cardio-metabolic health examined liver abnormalities

and iron deficiency. Papandreou et al. (2008, 2012) reported a prevalence of around 42% for non-

alcoholic fatty liver disease among a sample of obese children and adolescents aged 8-15 years.

Moschonis et al. (2012) and Manios et al. (2013) reported associations between adiposity and iron

deficiency. For example, among children aged 9 to 13 years, Manios et al. (2013) reported odds

ratios for iron deficiency and iron deficiency anaemia were 2.46 and 3.13 in obese boys and 2.05 and

3.28 in obese girls relative to healthy weight children6.

Spathopoulos et al. (2009) examined lung function among children aged 6-11 years and found that

BMI remained an independent risk factor for reduced lung function, asthma and atopy. Trikaliotis et

al. (2011) found that overweight Greek pre-school children were at a significantly higher risk of

dental caries (with a mean of 1.88 caries in the overweight group compared with 0.74 caries in the

healthy weight group).

6 It is thought that sub-clinical inflammation plays a central role in the association between iron deficiency and overweight;

i.e. hepcidin levels are higher in obese individuals and are linked to subclinical inflammation; this may reduce iron

absorption and blunt the effects of iron fortification (Cepeda-Lopez et al., 2010).


Three sources from Greece concerned psychological/emotional impacts of childhood

overweight/obesity (Pervanidou et al., 2013, 2015; Koroni et al., 2009). For example, in a sample of

110 obese and 31 healthy weight children (mean age 11.2 years), Pervanidou et al. (2013) found that

obese children were 3.1 and 2.3 times more likely to report state and trait anxiety, respectively, and

3.6 times more likely to report depressive symptoms, than healthy weight children of the same age.

Greece was the only country for which a study on academic performance was retrieved. In a sample

of children aged 10 to 12 and using multiple regression, Vassiloudis et al. (2014) found that academic

performance was significantly associated with BMI, dietary quality, TV viewing, sleep, physical

activity, parents' education, mother's ethnicity and family income. Note, however that academic

performance in this study was based on teachers’ ratings rather than standardised test results.


Table. Phase 1: Greek Disease Data Quality Scores

1 2 3 4 5 6

No acceptable

data

Must be

estimated

from other

data1

International

proxy

"Approximate"

data only2

Not

applicable

(non-fatal

disease)

Acceptable

data



ICD code mismatch


Self-reported BMI


Adult diseases

DISEASE MORTALITY INCIDENCE SURVIVAL PREVALENCE

Oesophageal Cancer

EUROSTAT Globocan Cancer Registry of Crete

Globocan

Colorectal Cancer

C18 to C21 EUROSTAT

C18 to C21 Globocan

Cancer Registry of Crete

C18 to C21 Globocan

Liver Cancer

C22 EUROSTAT

C22 Globocan


C22 Globocan


Gallbladder Cancer

C23 to C24 Globocan

C23 to C24 Globocan


Globocan

Pancreatic cancer


Globocan

Cancer-Breast, post-menopausal (females only aged 50+)


Globocan

Endometrial cancer

EUROSTAT C54 Globocan


Ovarian Cancer EUROSTAT Globocan


Globocan

Prostate cancer (males only)


Globocan

Kidney Cancer EUROSTAT

C64 to C66 Globocan


Globocan

Urothelial Cancer (males only)


Globocan

Thyroid cancer EUROSTAT Globocan


Globocan

Type 2 Diabetes


ATTICA 5 year and 10 year incidence


HYDRIA prevalence based on prescription medication https://www.researchgate.net/publication/304491483_The_prevalence_and_treatment_patterns_of_diabetes_in_the_Greek_population_based_on_real

Polycystic Ovarian Syndrome

proxy data - assume zero deaths

have prevalence

Proxy data - assume zero deaths (so prob survival = 1)

https://www.ncbi.nlm.nih.gov/pubmed/10566641

Multiple Sclerosis

WHO Global Health Estimates; and Hellenic statistical authority



Stroke

Includes I60 to I69 EUROSTAT I60-I69, G450, G451, G452, G454, G458, G459 Directorate

ATTICA Incidence (5 yr incid) of fatal or non-fatal CVD (coronary heart disease, acute coronary syndromes, stroke, or other

HYDRIA


of Population and Labour Market Statistics

CVD)

Hypertension


ATTICA 5 year and 10 year incidence


HYDRIA

Ischaemic Heart Disease

Excludes I46 & I50 EUROSTAT

ATTICA Incidence (5 yr incid) of fatal or non-fatal CVD (coronary heart disease, acute coronary syndromes, stroke, or other CVD)

HYDRIA - Acute Myocaridal Infarction EHIS - CHD/Angina; heart attack

Pulmonary Embolus

Hellenic Statistical authority

have prevalence based on hospital discharge?? Global proxy https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2020806/#R6

Hospital discharge data http://www.statistics.gr/en/statistics/-/publication/SHE12/-

Deep Vein Thrombosis


Global proxy https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2020806/#R6

have incidence

Asthma


have prevalence HYDRIA

Non-alcoholic fatty liver disease (NAFLD)


have prevalence

https://www.researchgate.net/publication/6452830_High_prevalence_of_elevated_liver_enzymes_in_blood_donors_Associations_with_male_gender_and_central_adiposity

Gallbladder Disease





Psoriasis


have prevalence


http://www.pagepress.org/journals/index.php/ar/article/view/ar.2011.e1/html_93

Gout

M10 WHO Global Health Estimates

have prevalence zero death - prob survival = 1

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2890601/

Osteoarthritis – Gonarthrosis Knee Pain


have prevalence


ESORDIG study. https://www.ncbi.nlm.nih.gov/pubmed/17143985

Chronic Back Pain


have prevalence


European Health Interview Survey (EHIS) Billis et al https://goo.gl/0R3nHr

Hypertension in pregnancy


have prevalence


http://www.sciencedirect.com/science/article/pii/S0020729214000174

Childhood diseases DISEASE MORTALITY INCIDENCE SURVIVAL PREVALENCE

Wheezing disorders


have prevalence



Metabolic syndrome


have prevalence



Hyperlipidemia proxy data - assume zero deaths

have prevalence



Depression proxy data - assume zero deaths

have prevalence





have prevalence





have prevalence




High blood pressure


have prevalence Not required for the model

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3475909/?report=printable http://www.nature.com/jhh/journal/v23/n6/full/jhh2008166a.html http://www.nature.com/ejcn/journal/v60/n10/full/1602442a.html#tbl1 http://www.rrh.org.au/articles/subviewnew.asp?ArticleID=1150 https://www.ncbi.nlm.nih.gov/pubmed/18025822

Type 2 diabetes Not required for the model

have prevalence Not required for the model

based on prescription medication https://www.researchgate.net/publication/304491483_The_prevalence_and_treatment_patterns_of_diabetes_in_the_Greek_population_based_on_real

Asthma Hellenic Statistical authority

have prevalence

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1934355/ https://www.ncbi.nlm.nih.gov/pubmed/19253125



have prevalence

NAFLD in obese children https://www.researchgate.net/publication/229327166_Are_Dietary_Cholesterol_Intake_and_Serum_Cholesterol_Levels_Related_to_Nonalcoholic_Fatty_Liver_Disease_in_Obese_Children


4.4 DATA


20171130 Phase 1 (Greece) Data Calculations (1).xlsx

20171130 Phase 1 (Greece) Data Calculations (2).xlsx

20171130 Phase 1 (Greece) Data Collation Workbook.xlsx

20171130 Phase 1 (Greece) Data Sources.xlsx


20171130 Phase 2 (Greece) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Greece) Data Documentation (Part 2).docx


20171130 Phase 5 (Greece) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Greece) Model Outputs Workbook - UNDISC.xlsm

UNDISCOUNTED and DISCOUNTED versions of the data files are available

As a result of the feedback loops include in the workflow; thesoftware was sometimes rerun with



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Pervanidou, P., Bastaki, D., Chouliaras, G., Papanikolaou, K., Laios, E., Kanaka-Gantenbein, C., & Chrousos, G.P. (2013). "Circadian cortisol profiles, anxiety and depressive symptomatology, and body mass index in a clinical population of obese children." Stress 16(1): 34-43.

Roditis, M.L., Parlapani, E.S., Tzotzas, T., Hassapidou, M., & Krassas, G.E. (2009). “Epidemiology and Predisposing Factors of Obesity in Greece: From the Second World War Until Today.” Journal of Pediatric Endocrinology & Metabolism 22: 389-405.

Sakka, S., Siahanidou, T., Voyatzis, C., Pervanidou, P., Kaminioti, C., Lazopoulou, N., Kanaka-Gantenbein, C., Chrousos, G.P., & Papassotiriou, I. (2015). "Elevated circulating levels of lipoprotein-associated phospholipase A2 in obese children." Clinical Chemistry & Laboratory Medicine 53(7): 1119-1125.

Sakou, I.I., Psaltopoulou, T., Sergentanis, T.N., Karavanaki, K., Karachaliou, F., Ntanasis-Stathopoulos, I., Tzanninis, S., Sdogou, T., Greydanus, D., & Tsitsika, A. (2015). “Insulin resistance and cardiometabolic risk factors in obese children and adolescents: a hierarchical approach.” Journal of Pediatric Endocrinology & Metabolism 28 (5-6): 5589-596.

Spathopoulos, D., Paraskakis, E., Trypsianis, G., Tsalkidis, A., Arvanitidou, V., Emporiadou, M., Bouros, D., & Chatzimichael, A. (2009). "The effect of obesity on pulmonary lung function of school aged children in Greece." Pediatric Pulmonology 44(3): 273-280.

Tambalis, K.D., Panagiotakos, D.B., Kavouras, S.A., Kallistratos, A.A., Moraiti, I.P., Douvis, S.J., Toutouzas, P.K., & Sidossis, L.S. (2010). "Eleven-year prevalence trends of obesity in Greek children: first evidence that prevalence of obesity is leveling off." Obesity 18(1): 161-166.

Trikaliotis, A., Boka, V., Kotsanos, N., Karagiannis, V., & Hassapidou, M. (2011). “dmfs and BMI in pre-school Greek children. An epidemiological study.” European Archives of Paediatric Dentistry 12(3): 176-178.

Tzotzas, T., Kapantais, E., Tziomalos, K., Ioannidis, I., Mortoglou, A., Bakatselos, S., Kaklamanou, M., Lanaras, L., & Kaklamanos, I. (2008). "Epidemiological survey for the prevalence of overweight and abdominal obesity in Greek adolescents." Obesity 16(7): 1718-1722.

Vassiloudis, I., Yiannakouris, N., Panagiotakos, D.B., Apostolopoulos, K., & Costarelli, V. (2014). "Academic performance in relation to adherence to the Mediterranean diet and energy balance behaviors in Greek primary schoolchildren." Journal of Nutrition Education & Behaviour 46(3): 164-170.

Wijnhoven, T. M., van Raaij, J.M., Spinelli, A., Starc, G., Hassapidou, M., Spiroski, I., Rutter, H., Martos, E., Rito, A.I., Hovengen, R., Peréz-Farinós, N., Petrauskiene, A., Eldin, N., Braeckevelt, L., Pudule, I., Kunesova, M., & Breda, J. (2014a). "WHO European Childhood Obesity Surveillance Initiative: Body mass index and level of overweight among 6-9-year-old children from school year 2007/2008 to 2009/2010." BMC Public Health 14.

Xekouki, P., Nikolakopoulou, M., Papageorgiou, A., Livadas, S., Voutetakis, A., Magiakou, M.A., Chrousos, G.P., Spiliotis, B.E., & Dacou-Voutetakis, C. (2007) “Glucose Dysregulation in Obese Children: Predictive, Risk, and Potential Protective Factors.” Obesity 15(4): 860-869.


5. REPUBLIC OF IRELAND

5.1 LOCAL CONTEXT

The pictures of obesity-- its prevalence, causes, and human outcomes—are similar across the

Republic of Ireland and Northern Ireland, although their financial costs and losses differ. Each

government has responded to the epidemic with a similar multi-departmental, multi-sector strategy

policy that is aimed at prevention across the lifetime.

Republic of Ireland Context: The government of the Republic of Ireland has very actively promoted

partnership among government bodies and across sectors. It has developed and funded internal

programs and outside agencies with a remit to address the obesity epidemic and has initiated and

funded internal and external: investigations into the scale of the problem in Ireland, into the best

interventions to address and prevent obesity, and into the financial and lifetime costs of overweight

and obesity to the person and society. The Government’s current range of initiatives rely on the

multi-sectorial approach outlined in Healthy Ireland (HI) – A Framework for Improved Health and

Well-Being 2013-2025 (Department of Health, 2013). The approach was adopted by the Irish

Government to serve as a tool to frame multi-sector action in response to not only the obesity

epidemic, but to Ireland’s changing health and wellbeing profile of increased life expectancy, rising

morbidity trends, and increasing associated costs. The framework includes arrangements that

promote cooperation among the health sector and other areas of Government and public services.

The framework also focuses on research and evidence to ensure goals, programmes, policy, and

programming decisions are based on robust evidence, best practice approaches, and integrated with

service delivery to maximise impact. The Healthy Ireland team evaluated Ireland’s health status in

the Healthy Ireland Survey 2015 and specifically evaluated Weight Management and found the same

profound and rising weight epidemic (Department of Health, 2015) that existed in 2013 when the

program started.

The HSE has incorporated Healthy Ireland into the health services strategy. Healthy Ireland in the

Health Services – National Implementation Plan 2015-2017 describes a 3-pronged strategy aimed at

health service reform, reducing the burden of chronic disease, and improving staff and well-being.

Reducing overweight and obesity are listed among the plan’s strategic priorities (HSE, 2015). The

Government has continued it’s ideal of agency collaboration with the 2016 Program for a

Partnership Government that sets out the agreed government program between Fine Gael, the

Independent Alliance, and some Independent TDs, has listed the implementation of a national

obesity plan among the key public health interventions it will make. The program will include a focus

on child health and targeted investment in the early years that will include a Prevention and Early

Intervention Unit in the Department of Public Expenditure and Reform/Finance focused on early

intervention policies to improve life outcomes. The Government developed the Obesity Policy and

Action Plan 2016-2025 called A Healthy Weight for Ireland aimed at assisting people to achieve

better health and specifically reduce levels of overweight and obesity. This approach is also based on

the Government’s 2013 framework for improved health and well-being, Healthy Ireland. A Healthy

Weight for Ireland covers a 10-year period (2016-2025) setting targets and actions to produce results


and includes: a sugar levy; a whole school approach; food establishments posting calorie content of

dishes; food industry reducing sugar, fat, and salt; and a code of practice for food and drink

marketing. (Department of Health, 2016) The critical point in the success of the plan relies on the

meaningful application of the Ten Steps Forward by government and non-government bodies. The

Ten Steps Forward:

1. Embed multi-sectoral actions on obesity prevention with the support of government departments and public sector agencies.

2. Regulate for a healthier environment.

3. Secure appropriate support from the commercial sector to play its part in obesity prevention.

4. Inform and empower change through a clear communications strategy.

5. The Department of Health will provide leadership.

6. Mobilise the health services with a focus on prevention.

7. Develop a service model for specialist care for children and adults.

8. Acknowledge the key role of physical activity in the prevention of overweight and obesity.

9. Allocate resources according to need, in particular children and disadvantaged groups.

10. Monitor research and review

The Government has partnered with non-government and external agencies across sectors to

actualize its policies and plans, to continue evaluation of the epidemic, and to advise on policy, and

regularly works with:

Ireland Department of Public Health (IPH) who assisted the Government with policy development

and implementation of A Healthy Weight for Ireland. IPH contributed to the evidence base on a

sugar sweetened drinks tax in 2012, when commissioned by the Department of Health in the

Republic of Ireland to undertake a Health Impact Assessment. With the support of the EC, IPH is

currently evaluating the lifetime impact of childhood overweight and obesity as measured by body

mass index (BMI), on the individual and the society in terms of financial and human costs.

SafeFood has collaborated with IDPH, University College Cork, the European Commission and other

agencies to provide the first estimate of the financial costs of overweight and obesity to Ireland in

2012, and are continuing to advance these investigations with a report of the Lifetime Cost of

Childhood Obesity (2017). In 2013, SafeFood worked with the Special Advisory Group on Obesity

(SAGO) and with the Regional Obesity Prevention Implementation Group (ROPIG) in Northern Ireland

on an obesity awareness public health campaign.

Children and Young People's Services Committees (CYPSC) operate on a county level to secure better

outcomes for children and young people in their area through more effective integration of existing

services and interventions. The Government identified them as a key to plan and co-ordinate

services for children and young people in every country in Ireland. One of CYPSC’s priorities is

obesity prevention and are developing initiatives to raise awareness of the issue of childhood

obesity. (CYPSE, 2017)

http://www.publichealth.ie/sites/default/files/documents/files/HIA%20Proposed%20Sugar%20Sweetened%20Drinks%20Tax%20Report.pdf


The European Union designed the Action Plan on Childhood Obesity 2014-2020 that aims halting the

rise in people’s ages 0-18 by 2020, requiring the involvement of many stakeholders within each

member state to develop relevant policy.

The Irish Government’s understanding of the complexity of the causes and contributors to the

obesity epidemic has culminated into the multi-sector solution strategy and an active collaboration

stance with internal and external agencies. This has provided a welcoming environment to support

and nurture results-oriented investigations, policy, and programs to bring results.

Northern Ireland Context: The government of Northern Ireland has very actively developed and

implemented programs to address the obesity and overweight epidemic and regularly evaluates

program effectiveness and modifies programs based on program outcomes and new evidence. The

Government’s acknowledgement of the complex solution required to address overweight and

obesity, due to the obesogenic environment, resulted in the current evidence-based, intergrated,

cross-sector, life course policy approach.

Leading up to the current approach, the Government had addressed obesity with Fit Futures, a

nutrition and exercise approach. The 2007 UK-wide Foresight Report, Tackling Obesities: Future

Choices, suggested policy ineffectiveness due to the obesogenic environment requiring

comprehensive interventions. The report also evaluated how to address obesity over the next 40

years. The Department of Health, Social Services and Public Safety (DHSSPS) established the cross-

sectoral Obesity Prevention Steering Group (OPSG) in 2008 to promote Fit Futures and develop a life

course framework to tackle obesity that would replace Fit Futures. A whole system approach to

health became the foundation for A Fitter Future for All - Framework for Preventing and Addressing

Overweight and Obesity in Northern Ireland 2012-2022 and for Making Life Better - A Whole System

Strategic Framework for Public Health 2013 -2023, which is aimed at overall health and wellbeing

and includes tackling obesity as one of its aims. Both programs involve steering committees to

oversee progress and the Public Health Agency to facilitate implementation and delivery. (DHSSPS

2012; 2013) In 2012, various efforts had accomplished: the development of public information

campaigns and supporting materials; delivery of relevant training and support; development of

nutritional guidelines in key settings, particularly schools; community based initiatives on food and

physical activity; the introduction of the curriculum sports programme for primary schools, which

enables pupils to develop their physical literacy skills working with coaches from the GAA and IFA;

support, advice and guidance for professionals; improved support in health care settings, including

physical activity referrals; strengthened code of conduct for advertising high fat, sugar, or salt foods

to children; improved evidence and research base; and work with industry, including progress on

reformulation and improved labelling (DHSSPS).

Additional action include: Healthy Child, Healthy Future (DHSSPS, 2010), a framework for the

Universal Child Health Promotion Programme that involves the family in adopting health-enhancing

behaviours for children age 0-19; Healthy Foods for Health Outcomes (DHSSPS & DE, 2013) that

advocates a whole school approach to all food provided in schools; and the Public Health Agency’s

Obesity Awareness Week. The government also partners with regional government and external

agencies to actualize and extend its policies, including: district councils; schools; leisure centers and

healthy living centers; Regional Obesity Prevention Implementation Group (ROPIG) who developed

an obesity awareness public health campaign; Ireland Department of Public Health, who is currently


evaluating the lifetime impact of childhood overweight and obesity as measured by body mass index

(BMI), on the individual and the society in terms of financial and human costs; the Food Standards

Agency (FSA); Safefoods, who investigated the financial and healthcare costs to the local economy as

a result of obesity (2011), collaborated with IDPH, UCC, the EC, and other agencies to provide the

first estimate of the financial costs of overweight and obesity to Ireland (2012), and the Lifetime Cost

of Childhood Obesity (2017); and the Chartered Institute of Environmental Health (CIEH) to develop a

healthier eating award for catering establishments across Northern Ireland; and The European

Union, who designed the Action Plan on Childhood Obesity 2014-2020 that aims halting the rise in

peoples ages 0-18 by 2020, requiring the involvement of many stakeholders within each member

state to develop relevant policy.

The Government’s policies aimed at the obesity epidemic are many and varied to address the

multiple causal factors through interventions delivered from multiple sectors of most government

organizations. The integrated environment is hospitable to actualizing these programs.

5.2 LOCAL EVIDENCE

This section should be read in conjunction with the international evidence outlined in Chapter 1.


The literature from Ireland provided 18 sets of estimates of the prevalence of overweight and

obesity. Five are considered here. They come from four sources. The first is the Growing Up in

Ireland (GUI) study, a national longitudinal survey of representative samples of children in two

cohorts, and followed every 2-3 years. The Infant Cohort of about 11,150 children was first surveyed

at age 9 months in 2008-2009, while the Child Cohort of about 8,550 children was first surveyed at

age 9 years in 2007-2008. The second is the third round of COSI (2012). Estimates for adolescents

come from a study on second-level students’ participation in sport (Fahey et al. 2005), while the

most recent estimates, based on data collected in 2013-2014, come from the Fluoride and Caring for

Children’s Teeth (FACCT) study (McCarthy et al., 2016a)37.

Among infants aged 9 months who took part in GUI, on the basis of the UK-WHO growth charts,

24.8% of all children were classified as overweight and 15.7% as obese (Mangan & Zgaga, 2014). Also

based on GUI, at age 9, it was reported that 22% of boys and 30% of girls were overweight or obese

(Layte & McCrory, 2011). The FACCT study indicated that 21% of children aged 4-7 years (18% of

boys and 25% of girls), and 26% of adolescents (aged 11-14 years; 23% of boys and 28% of girls)

were overweight and obese.

The COSI results for Ireland for round 3, conducted in 2012 (Heinen et al., 2014) indicated that

among children aged 7, the prevalence of overweight and obesity was higher in girls (22%) than in

boys (17%). These estimates are lower than those from the FACCT study for children aged 4-7 years


but the gender difference is consistent. At age 9, COSI estimates indicated that prevalence was

similar for girls (22%) and boys (20%).

Fahey et al. (2005) surveyed a representative sample of adolescents aged 13 to 18 in 2004 and

estimated that about one in five (19.9% of boys and 20.4% of girls) was overweight or obese. The

pattern of prevalence followed a U-shape with age, being lowest among adolescents aged 15 and 16.


Three papers from Ireland examined aspects of cardio-metabolic health. Finucane et al. (2008a)

reported that 51% of boys and 49% of girls had systolic BP in hypertensive range (> 95th

percentilefor age, sex and height). Results also showed a clear and continuous increase in systolic BP

with increasing BMI, particularly in boys. This is of significance, since 93% of this sample (aged 2-18

years) was obese. Finucane et al. (2008b) reported significant associations between degree of

obesity, insulin sensitivity and markers of liver steatosis among a sample of obese children and

adolescents (mean age 15.5 years). Carolan et al. (2013) reported that obese children showed

changes in immune cell frequency, inflammatory environment, and regulation of metabolic gene

expression compared to children of healthy weight. These changes have been causally linked to

adult onset of metabolic disease and suggest a future trajectory for the development of type 2

diabetes and premature cardiovascular disease.

Three further papers examined associations between overweight/obesity and musculo-

skeletal/motor function (O’Malley et al., 2012, 2015a, 2015b). For example, in a sample of obese

children and adolescents (mean age 12.2 years), O’Malley et al. (2012) reported moderate negative

correlations were found between body composition and range of motion, flexibility, and strength.

Genu valgum deformity was moderately positively correlated to body mass index.

One source from Ireland examined psychological/emotional impacts. On the basis of a

representative sample of 9 year-olds, Layte & McCrory (2011) reported that self-perceptions relating

to popularity and physical appearance were significantly negatively related to self-perceptions of

weight. The perception of overweight was also significantly associated higher levels of emotional

and behavioural problems.

5.2.5 Inequalities

Nine studies from Ireland that examined inequalities in prevalence were retrieved. One (Williams et

al., 2013) confirmed the presence of a socio-economic gradient at age 3 years, while another study

examining weight gain from birth to three years showed that lower SES was associated with lower

birth weights and highest gains in weight; higher gains in weight were associated with higher

maternal weight gain during pregnancy and no breastfeeding (Layte & Biesma-Blanco, 2014).

Multivariate analyses of children’s BMI at age 9 (Layte & McCrory, 2011; Keane et al., 2012; Perry et

al., 2015) indicated higher prevalence of overweight and obesity among girls, one parent families,


lower occupational class, lower parental education, lower rates of physical activity, poorer dietary

quality, and, in particular, among children with overweight or obese parents. Walsh and Cullinan

(2015) conducted an analysis of the relative contributions of a range of child and parent

characteristics to the socio-economic gradient at age 9 and found that parental characteristics

accounted for a large majority of this gradient, while child-related measures were not statistically

significant. Other studies confirmed an association between socio-economic deprivation and child

overweight/obesity (Heinen et al., 2014; O’Shea et al., 2014). One study (Fahey et al., 2005) did not

find a significant association between SES and rates of overweight or obesity among adolescents.

However, Fahey et al.’s (2005) analysis was bivariate and used a rather broad measure of SES

(parental occupation, split into 9 groups by sector).



20171130 Phase 1 (Ireland) Data Calculations.xlsx

20171130 Phase 1 (Ireland) Data Calculations (2).xlsx

20171130 Phase 1 (Ireland) Data Collation Workbook.xlsx

20171130 Phase 1 (Ireland) Data Sources.xlsx


20171130 Phase 2 (Ireland) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Ireland) Data Documentation (Part 2).docx


20171130 Phase 5 (Ireland) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Ireland) Model Outputs Workbook - UNDISC.xlsm

5.3.1 Irish Disease Data Quality Scores

1 2 3 4 5 6

No acceptable

data

Must be

estimated

from other

data1

International

proxy

"Approximate"

data only2

Not

applicable

(non-fatal

disease)

Acceptable

data




ICD code mismatch


Self-reported BMI


Adult diseases

DISEASE INCIDENCE PREVALENCE SURVIVAL

MORTALITY

Oesophageal Cancer NCRI NCRI NCRI CSO

Colorectal Cancer NCRI request NCRI request NCRI request CSO

Liver Cancer NCRI request NCRI request NCRI request

CSO

Gallbladder Cancer NCRI NCRI

not available CSO

Pancreatic cancer NCRI NCRI NCRI CSO

Cancer-Breast, post-menopausal (females only aged 50+) NCRI - aged 50+ NCRI request NCRI request

CSO - aged 50+

Endometrial cancer NCRI NCRI NCRI request CSO

Ovarian Cancer NCRI NCRI NCRI request CSO

Prostate cancer (males only) NCRI NCRI NCRI CSO

Kidney Cancer NCRI NCRI NCRI request CSO

Urothelial Cancer (males only) NCRI NCRI NCRI CSO

Thyroid cancer NCRI NCRI NCRI CSO

Type 2 Diabetes

Calculate incidence from

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4748605/


Not required


prevalence for the model


not available not available not available CSO

Adult obesity


Multiple Sclerosis

UK proxy http://jnnp.bmj.com/content/early/2013/09/19/jnnp-2013-305450.full.pdf

UK proxy http://jnnp.bmj.com/content/early/2013/09/19/jnnp-2013-305450.full.pdf

not available

CSO

Stroke

hospital discharges North Dublin population; first ever stroke

CSO Quarterly National Household Survey Q3 2010 - doc dx IPH estimates - based on self-report from SLAN

Irish Heart Foundation/HSE National Stroke Audit 2015 http://www.irishheart.ie/media/pub/advocacy/research/ihf_national_stroke_audit_2015_web.pdf CSO

Hypertension

Calculate incidence from prevalence TILDA Wave 1 - age 50+

Health Survey for Eng 2014 - UK proxy - age up to 54




Calculate incidence from prevalence

I20; I21; I50 - mixture TILDA and UK data (http://heart.bmj.com/content/early/2015/05/06/heartjnl-2015-307516.full.pdf+html)

calculated from mortality and prevalence CSO

Deep Vein Thrombosis UK proxy UK proxy

not available CSO

Asthma


CSO Quarterly National Household Survey Q3 2010 QOF - NI zero deaths

CSO


not available not available

zero deaths

CSO

Gallbladder Disease HIPE data HIPE data (same as incidence) zero deaths

CSO


Psoriasis

Global Epidemiology of Psoriasis: A Systematic Review of Incidence and Prevalence; http://www.jidonline.org/article/S0022-202X(15)36098-X/pdf Have incidence

not available

CSO

Gout UK proxy UK proxy zero deaths CSO



UK proxy zero deaths

CSO

Chronic Back Pain


CSO Quarterly National Household Survey Q3 2010 zero deaths

CSO



Pulmonary Embolus UK proxy UK proxy

not available CSO

Childhood diseases

DISEASE INCIDENCE PREVALENCE SURVIVAL

MORTALITY

Wheezing disorders

not available not available not available not available

Metabolic syndrome


Hyperlipidemia


Depression Calculate incidence from prevalence

hospital attendance not available CSO



PRIME-C study not available CSO




proxy https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3004499/#B8

not available CSO

High blood pressure


Wales proxy Not required for the model


Type 2 diabetes


England Proxy Not required for the model


Asthma Calculate incidence from prevalence

PCRS data as a proxy zero deaths

J45 to J46 EUROSTAT



http://bmcpediatr.biomedcentral.com/articles/10.1186/1471-2431-13-40

zero deaths CSO

5.4 DATA


20171130 Phase 1 (Republic of Ireland) Data Collation Workbook.xlsx




20171130 Phase 3&4 (Republic of Ireland) Initial Model Output Workbook.xlsx


20171130 Phase 5 (Republic of Ireland) Initial Resturctured Model Output Workbook.xlsx

20171130 Phase 5 (Republic of Ireland) Initial Core tables and Graphs Workbook.xlsx

Phase 6: Reporting

20171130 (Republic of Ireland) Final Restructured Model Output Workbook.xlsx

20171130 (Republic of Ireland) Final Combined Model Outputs SAS Dataset.ssd

20171130 (Republic of Ireland) Final Combined Model Outputs Worksheet.xlsx

20171130 (Republic of Ireland) Final Core Tables and Graphs Workbook.xlsx



As a result of the feedback loops include in the workflow; the software was sometimes rerun with

corrected inputs (this occurred for the Republice of Irealnd). Only the final model outputs from the

simulation software are listed.

Table is a profile of children, age 0-17, living in the Republic of Ireland in 2015. Most (76.5%)

children are healthy weight with 23.5% either obese or overweight. Percent who are

obese/overweight increases with age. In the 0-5 age group, slightly higher percent of males are

obese/overweight than females. However, this changes in 6-11 year old group and persists in the

12-17 year old group with relatively more obese/overweight females than males.

Table. Phase 5: Profile of Republic of Ireland children (2015)

IRELAND

AGE SEX BMI AT AGE 18 NUMBER PERCENTAGE

0-17 YEARS PERSONS OBESE/OVERWEIGHT 281,751 23.5%

HEALTHY WEIGHT 917,569 76.5%

ALL 1,199,320 100.0%

FEMALES OBESE/OVERWEIGHT 144,292 24.6%


ALL 586,526 100.0%

MALES OBESE/OVERWEIGHT 137,459 22.4%


ALL 612,794 100.0%



ALL 431,592 100.0%



ALL 211,159 100.0%



ALL 220,433 100.0%



ALL 408,206 100.0%



ALL 200,426 100.0%




ALL 207,780 100.0%



ALL 359,522 100.0%



ALL 174,941 100.0%



ALL 184,581 100.0%

REPUBLIC OF IRELAND AND NORTHERN IRELAND REFERENCES

Carolan, E., Hogan, A.E., Corrigan, M., Gaotswe, G., O'Connell, J., Foley, N., O'Neill, L.A., Cody, D., & O'Shea, D.

(2013). "The impact of childhood obesity on inflammation, innate immune cell frequency, and metabolic

microRNA expression." The Journal of Clinical Endocrinology & Metabolism 99(3): E474-E478.

Fahey, T., Delaney, L., & Gannon, B. (2005). School children and sport in Ireland. Dublin: ESRI.

Finucane, F., Pittock, S., Fallon, M., Hatunic, M., Ong, K., Burns, N., Costigan, C., Murphy, N., & Nolan, J. (2008a). "Elevated blood pressure in overweight and obese Irish children." Irish Journal of Medical Science 177(4): 379-381. Finucane, F., Teong, L., Pittock, S., Fallon, M., Hatunic, M., Costigan, C., Murphy, N., Crowley, V., & Nolan, J.

(2008b). "Adverse metabolic profiles in a cohort of obese Irish children." Annals of Clinical Biochemistry 45(2):

206-209.

Heinen, M., Murrin, C. Daly, L., O’Brien, J., Heavey, P., Kilroe, J., O’Brien, M., Scully, H., Mulhern, L.M., Lynam,

A., Hayes, C., O’Dwyer, U., Eldin, N., & Kelleher, C. (2014). The Childhood Obesity Surveillance Initiative (COSI)

in the Republic of Ireland: Findings from 2008, 2010 and 2012. Dublin: Health Service Executive and

Department of Health.

Keane, E., Layte, R., Harrington, J., Kearney, P.M., & Perry, I.J. (2012). "Measured parental weight status and

familial socio-economic status correlates with childhood overweight and obesity at age 9." PloS One 7(8):

e43503.

Layte, R., & Biesma-Blanco, R. (2014). “Social class differences in weight gain from birth to three years.” Paper

presented at the Growing Up in Ireland Research Conference 2014: Dublin, November.

Layte, R. & McCrory, C. (2011). Growing Up in Ireland-National Longitudinal Study of Children: Overweight and

Obesity Among 9-Year-Olds. Dublin: Department of Children and Youth Affairs.

McCarthy, L., Keane, E., Geaney, F., O’Sullivan, M., & Perry, I.J. (2016a). Trends and prevalence of overweight

and obesity in primary school aged children in Ireland from 2002-2015: An update on the existing literature.

Report commissioned by safefood Ireland. Cork: safefood.


Mangan, L., & Zgaga, L. (2014). “Exploring the association between sleep duration and overweight and obesity

in infants.” Paper presented at the Growing Up in Ireland Research Conference 2014: Dublin, November.

O'Malley, G., Hussey, J., & Roche, E. (2012). "A pilot study to profile the lower limb musculoskeletal health in children with obesity." Pediatric Physical Therapy 24(3): 292-298. O’Malley, G., Elmes, M., Keating, R., Killeen, S., Doyle, S., Murphy, S., & Lennon, O. (2015a). “Exploring the prevalence of musculoskeletal impairments in children and adolescents attending an obesity management service.” Appetite 89: 309. O’Malley, G., Keating, R., Elmes, M., Killeen, Sheridan, N., Murphy, S., & Brinkley, A. (2015b). “Standing balance

and health-related quality of life in children who are obese.” Appetite 89: 309.

O’Shea, B., Ladewig, E.L., Kelly, A., Reulbach, U., & O’Dowd, T. (2014). “Weighing children; parents agree, but

GPs conflicted.” Archives of Disease in Childhood 99: 543-545.

Perry, C., Keane, E., Fitzgerald, A.P., Layte, R., Perry, I.J., & Harrington, J.A. (2015). “The use of a Dietary Quality

Score as a predictor of childhood overweight and obesity.” BMC Public Health 15: 581.

Walsh, B., & Cullinan, J. (2015). “Decomposing socioeconomic inequalities in childhood obesity: Evidence from

Ireland.” Economic & Human Biology 16: 60-72.


6. ITALY

6.1 LOCAL CONTEXT

The Italian National Health Service was set up in 1978, with universal coverage, solidarity, human

dignity, and health needs as its guiding principles. It is regionally based and organized at the

national, regional, and local levels. Under the Italian constitution, the central government controls

the distribution of tax revenue for publicly financed health care and defines a national statutory

benefits package to be offered to all residents in every region—the “essential levels of care” (livelli

essenziali di assistenza, or LEA). The 19 regions and two autonomous provinces have the

responsibility to organize and deliver health services through local health units. Regions have

significant autonomy in determining the macro structure of their health systems. Local health units

are managed by a general manager appointed by the governor of the region, and deliver primary

care, hospital care, outpatient specialist care, public health care, and health care related to social

care.

MAIN POLICIES

Policy and planning frameworks are the responsibility of the national government through the

Ministry of Health, with an increasingly important role played by the Standing Conference on

Relations between the State, Regions and Autonomous Provinces through agreements knownas

“Pacts for Health” (Patti per la Salute), which are adopted every three years. Every year, the

Standing Conference on Relations between the State, Regions and Autonomous Provinces (with the

presidents of the regions and representatives from central government as its members) sets the

criteria (usually population size and age distribution) to allocate funding to Regions and set the

priorities. Local health units are funded mainly through capitated budgets.

The Conference on Relations between the State, Regions, and Autonomous Provinces, signed the 14

of April 2016 (Rep. 65/CSR), identified the projectual national priorities for 2016 and established a

new approach towards the projectual lines according to the new “Pact for Health” of 2014-2016. It is

emphasized the need for the joint commitment of the Government and the Regions in implementing

important and concrete measures of planning and reorganization of the health system, aiming to

increase its efficiency and to identify strategies for overcoming the differences between territorial

areas (health results, accessibility and quality of services).

STRATEGIES

An important goal in the recent history of Italian public health was achieved with the “Guadagnare

salute” (“Gaining health”) action plan, approved through a decree of the Prime Minister on 4 May

2007. “Gaining health: encouraging healthy choices” is an action plan whose main objectives are to

prevent and change unhealthy behavior and lifestyles; these are the main risk factors for major non-

communicable diseases, which have the highest epidemiological relevance and strongest impact on

public health: cardiovascular diseases, cancer, diabetes mellitus, obesity, chronic respiratory

pathologies, disorders of the muscle-skeletal and gastro-intestinal system, mental health problems.

This initiative, therefore, should be assessed both as a long-term investment to reduce the incidence

of chronic diseases on the national health system and on society, but also as regards its short-term

advantage of attempting to improve the citizens‘ lifestyle by immediately promoting healthy choices


and correct lifestyles (stop smoking, follow a correct diet, limit the alcohol intake and exercise

regularly). With this new culture of prevention, all individuals become protagonists and accountable

for the quality of their life.

The strategy of “Guadagnare salute” (a transversal government programme) is based on the four

changeable risk factors and major determining factors for the most frequent chronic diseases, by

identifying four subject areas (or specific programmes):

• promoting healthy eating patterns (as regards the risk factor “inappropriate diet”)

• counteracting smoking (as regards the “smoking” risk factor)

• counteracting alcohol abuse (as regards the “alcohol” risk factor)

• promoting physical activity (as regards the “sedentary lifestyle” risk factor).

“Gaining health” indicates strategies across the board, based on actions which involve several social

sectors and institutions, with specific actions to counteract smoking and alcohol abuse as well as to

promote physical activity and a healthy diet, through close cooperation among all institutions and

social organisations involved. Such an approach results from the awareness that most of the

effective actions to prevent risk factors and promote healthy lifestyles are implemented outside the

national health system. In order to act appropriately on the environment-related elements and

socio-economic causes of chronic diseases it is necessary to join forces, working together in

coordinated way.

With the ministerial decree of 26 April 2007 the former Ministry of Health established the “National

Platform on diet, physical activity and smoking” with the task of making suggestions and

implementing actions, in line with the "Gaining health" plan. The Platform is a three-year project

supervised by the Ministry of Health, involving representatives of the central authorities involved, of

the independent regional and provincial governments of Trento and Bolzano and of the associations

which signed the protocols of agreement.

The Platform involved:

• Ministry of Health

• Department for Family Policies of the Council of Ministers‘ Presidency

• Department for Rights and Equal Opportunities of the Council of Ministers‘ Presidency

• Department for Youth Policies and Sports of the Council of Ministers‘ Presidency

• Ministry for Agricultural, Food and Forestry Policies

• Ministry of Education

• Ministry for Economic Development

• Ministry for Economics and Finance

• Ministry of Transport


• Ministry for the Environment and Protection of Land and Sea

• Conference for Relations between State, independent Regional and Provincial Governments

of Trento and Bolzano

• National Association of Italian Municipalities (Anci )

• Advanced Health Institute (Iss )

• Advanced Institute for Prevention and Safety on the Workplace (Ispesl )

• National Research Institute on Food and Nutrition (Inran )

• Independent Regional and Provincial Government of Trento and Bolzano

• Trade associations in the food sector

• Consumers‘ associations

• The most representative national trade unions, which have signed specific protocols of

agreement with the Ministry of Health

• Associations of independently-chosen General Practitioners and Paediatricians.

FOOD-BASED DIETARY GUIDELINES - ITALY

The Italian National Research Institute on Food and Nutrition (INRAN, Istituto Nazionale di Ricerca

per gli Alimenti e la Nutrizione), now called CRA-NUT, is the institution leading the development and

revisions of the ‘Guidelines for healthy Italian food habits’ as one of its institutional tasks. The Italian

dietary guidelines are based on the Italian recommended dietary allowances (RDAs). The last version

of the RDAs was published in 2014 and the dietary guidelines were revised accordingly in 2017 by

experts from a wide variety of Italian institutions, including universities, research institutes and

scientific societies.

6.2 LOCAL EVIDENCE


Estimates from Italy were retrieved from 16 sources. Six are described here. The most important

source of information is the national surveillance system on childhood obesity, OKkio alla SALUTE,

which started in 2007 and has collected data on a sample of more than 45,000 children aged 8-9

years every 2 years (Binkin et al 2010; Spinelli et al 2012; 2015; Nardone et al., 2015). OKkio alla

SALUTE is part of the WHO/Europe Childhood Obesity Surveillance Initiative (COSI) and in 2016

showed a prevalence of 21.3% of overweight children aged 8 and 9 (not including obesity) and 9.3%

of obesity (using the IOTF cutoffs). Gender differences were not very high: 8.8% of girls and 9.7% of

boys were obese. Data show a large regional variation, as confirmed also in Turchetta et al.’s (2012)

systematic review of prevalence of overweight and obesity among children in Italy (aged 6-11,

studies published since 2000). The highest prevalence is found in the South and the lowest in the

North of Italy.


There are no nationally representative estimates of overweight and obesity among preschool

children. However, a study of two regions of children aged 2 to 6 from Northeast and Southern Italy

(Verona and Messina, surveyed in 2002), overweight and obesity prevalence was estimated at about

23% in boys and 28% in girls (Maffeis et al., 2006).

Trends

Information on trends in prevalence of overweight and obesity in children comes from two sources:

OKkio alla SALUTE (which informs COSI), where prevalence among 8 and 9 year-olds in 2008, 2010,

2012 and 2014 have been compared (Spinelli et al., 2015), and a study examining trends in

overweight and obesity among children and adolescents in Tuscany (Lazzeri et al., 2015).

Spinelli et al. (2015) reported small but statistically significant decreases between 2008 and 2014 in

the prevalence of both overweight (from 23.2% to 20.9%) and obesity (from 12.0% to 9.8%) among 8

and 9 year-olds in the nationally representative OKkio alla SALUTE study (IOTF criteria). In the study

of children and adolescents in Tuscany (2002-2006), results were mixed, depending on the age-

group considered. Prevalence of overweight and obesity decreased only among 11 year-olds. Small

increases were recorded in children aged 9 (from 31.7% to 33.4%) and 13 (from 16.8% to 17.9%),

with the largest increases found among 15 year-olds (from 13.3% to 19.7%) (IOTF cut-offs).

In summary, there is evidence in Italy for a small decrease in the prevalence of both overweight and

obesity rates among children since 2008. Evidence for trends in adolescent overweight and obesity

are limited and provide mixed results.


Most of the sources from Italy – 14 of 15 – examined aspects of cardio-metabolic risk factors. Eight

of these looked at the metabolic syndrome (DiBonito et al., 2015; Capizzi et al., 2011; Caserta et al.,

2010; Valerio et al., 2013; Invitti et al., 2005; Calcaterra et al., 2008; Invitti et al., 2003; Ianuzzi et al.,

2004). For example, in a sample of children aged 0-14 years, Calcaterra et al. (2008) found that the

prevalence of metabolic syndrome (i.e. three or more of BMI > 97th percentile, triglyceride levels >

95th percentile, high density lipoprotein (HDL) cholesterol level < 5th percentile, systolic or diastolic

Blood pressure > 95th percentile, and impaired glucose tolerance) was 0% in normal and overweight

children, 12.0% in moderately obese and 31.1% in severely obese children. Ianuzzi et al. (2004)

reported that, among children/adolescents aged 6-14 years, obese children had significantly higher

BP and plasma concentrations of tryglycerides, cholesterol, glucose, insulin, HOMA and C-reactive

protein than healthy weight children. Carotid intima-media thickness (CIMT) was also significantly

higher in obese children.


A further four papers examined blood pressure (Turconi et al., 2006, 2007; Barba et al., 2006;

Genovesi et al., 2005). For example, Barba et al. (2006) reported that BMI and waist circumference

were independently associated with systolic BP, after adjusting for parental education and children's

levels of physical activity (sample aged 6-11 years).

Bruno et al. (2010) examined trends in type 1 diabetes among children aged 0-14 years from 1990-

2003 and found that the incidence rate was 12.26 per 100,000 person years and significantly higher

in boys (13.13) than in girls (11.35). Incidence rates increased linearly by 15, 27, 35, and 40% across

four successive birth cohorts studied. Note that this trend is not empirically linked with trends in

prevalence of overweight or obesity in the article. In a sample of obese children and adolescents

aged 3-18 years, Brufani et al. (2010) found that glucose metabolism abnormalities were present in

12.4%. Impaired glucose tolerance (IGT) was the most frequent alteration (11.2%), with a higher

prevalence in adolescents than in children (14.8 vs. 4.1%).

The final source from Italy considered here examined pulmonary/aerobic function. Eight per cent of

all children (aged 6-7 years) reported current wheezing and 6.7% reported current asthma. Elevated

BMI (comparing highest quintile to others) was significantly associated with both current wheeze

(adjusted odds ratio=1.47) and current asthma (adjusted odds ratio=1.61) (Corbo et al., 2008).

6.2.5 Inequalities

Nine studies from Italy examined inequalities. There is strong and consistent evidence for regional

variation in the prevalence of overweight and obesity. Prevalence in the south is much higher than in

the north. Generally, prevalence tends to be highest in Campania and lowest in Bolzano (e.g. Spinelli

et al., 2014). Binkin et al. (2008) reported that this regional variation is not accounted for by

differences in levels of maternal education or employment, nor have any variations by urban/rural

location been reported (Spinelli et al., 2009, 2012). There is some evidence of higher prevalence of

overweight and obesity among boys, though this is not entirely consistent (Spinelli et al. 2009, 2012;

Lombardo et al., 2014). Research from Italy also confirms associations between parental education

and parental BMI and child prevalence of overweight and obesity (as well as rates of weight gain in

children over time: Lombardo et al., 2014; Nardone et al., 2015; Lazzeri et al., 2014; Valerio et al.,

2013). Prevalence is also higher among Italian-born than foreign-born children (Spinelli et al., 2012).



20171130 Phase 1 (Italy) Data Calculations (1).xlsx

20171130 Phase 1 (Italy) Data Calculations (2).xlsx


20171130 Phase 1 (Italy) Data Collation Workbook.xlsx

20171130 Phase 1 (Italy) Data Sources.xlsx


20171130 Phase 2 (Italy) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Italy) Data Documentation (Part 2).docx


20171130 Phase 5 (Italy) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Italy) Model Outputs Workbook - UNDISC.xlsm

Table. Phase 1: Italian Disease Data Quality Scores (Initial model under review)

1 2 3 4 5 6

No acceptable

data

Must be

estimated

from other

data1

International

proxy

"Approximate"

data only2

Not

applicable

(non-fatal

disease)

Acceptable

data



ICD code mismatch


Self-reported BMI


Adult diseases


Disease Mortality Incidence Survival Prevalence

Oesophageal Cancer

EUROSTAT Globocan Eurocare 5 Database

Globocan

Colorectal Cancer

C18 to C21 EUROSTAT

C18 to C21 Globocan

Eurocare 5 Database

C18 to C21 Globocan

Liver Cancer

C22 EUROSTAT

C22 Globocan

Eurocare 5 Database

C22 Globocan

Gallbladder Cancer

C23 to C24 Globocan

C23 to C24 Globocan

Eurocare 5 Database

Globocan

Pancreatic cancer


Globocan



Globocan

Endometrial cancer

EUROSTAT C54 Globocan

Eurocare 5 Database

C54 Globocan

Ovarian Cancer


Globocan



Globocan


Kidney Cancer

EUROSTAT C64 to C66 Globocan

Eurocare 5 Database

Globocan



Globocan

Thyroid cancer


Globocan

Asthma

J45 to J46 EUROSTAT

Drug Proxy

calculated from prevalence and mortality

EHIS

Chronic Back Pain

ISTAT Calculate incidence from prevalence

EHIS - lower back pain


ISTAT EU/UK Proxy Zero deaths Calculated from GP cost data

Gallbladder Disease

ISTAT Hospital Discharge Data

Hospital Discharge Data

Gout

M10 WHO Global Health Estimates

Use hospital admissions data??

Calculated from GP cost data


Hypertension




ISTAT


ISTAT

Use hospital admissions data - this has not been calculated

Zero deaths Calculated from GP cost data


Excludes I46 & I50 EUROSTAT



EHIS

Multiple Sclerosis

WHO Global Health Estimates

Atlas of MS


Atlas of MS


ISTAT





ISTAT

Use hospital admissions data- this has not been calculated



ISTAT



Psoriasis

ISTAT



Pulmonary Embolus

ISTAT EU/UK/Spain Proxy


Stroke

I60 to I69 EUROSTAT



EHIS

Type 2 Diabetes




ISTAT PASSI - age 18 to 69


Childhood diseases

Diseases Mortality Incidence Survival Prevalence

Wheezing disorders

not available not available not available Preschool asthma in Italy

Metabolic syndrome


Hyperlipidemia not available not available not available not available

Depression Use drugs data Use drugs data



Prevalence of Obstructive Sleep Apnoea Syndrome in a Cohort of 1,207 Children of Southern Italy https://www.ncbi.nlm.nih.gov/pubmed/11742924


High blood pressure



ISTAT



ISTAT


Asthma J45 to J46 EUROSTAT

Anti-asthma medication prescribing to children in the Lombardy Region of Italy: chronic versus new users http://bmcpulmmed.biomedcentral.com/articles/10.1186/1471-2466-11-48

Anti-asthma medication prescribing to children in the Lombardy Region of Italy: chronic versus new users http://bmcpulmmed.biomedcentral.com/articles/10.1186/1471-2466-11-48 Preschool asthma in Italy: Prevalence, risk factors and health resource utilization http://www.resmedjournal.com/article/S0954-6111(08)00257-6/abstract


ISTAT

Use hospital admissions data- this has not been calculated

Global Proxy





6.4 DATA


20171130 Phase 1 (Italy) Data Collation Workbook.xlsx




20171130 Phase 3&4 (Italy) Initial Model Output Workbook.xlsx


20171130 Phase 5 (Italy) Initial Resturctured Model Output Workbook.xlsx

20171130 Phase 5 (Italy) Initial Core tables and Graphs Workbook.xlsx

Phase 6: Reporting

20171130 (Italy) Final Restructured Model Output Workbook.xlsx

20171130 (Italy) Final Combined Model Outputs SAS Dataset.ssd

20171130 (Italy) Final Combined Model Outputs Worksheet.xlsx

20171130 (Italy) Final Core Tables and Graphs Workbook.xlsx




ITALIAN REFERENCES

Barba, G., Troiano, E., Russo, P., Strazzullo, P., Siani, A., on behalf of the ARCA Project study group (2006). “Body mass, fat distribution and blood pressure in Southern Italian children: Results of the ARCA project.” Nutrition, Metabolism & Cardiovascular Diseases 16: 239-248.

Binkin, N., Fontana, G., Lamberti, A., Cattaneo, C., Baglio, G., Perra, A., & Spinelli, A. (2010). “A national survey


of the prevalence of childhood overweight and obesity in Italy.” Obesity Reviews 11: 2-10.

Brufani, C., Ciampalini, P., Grossi, A., Fiori, R., Fintini, D., Tozzi, A., Cappa, M., & Barbetti F. (2010). “Glucose tolerance status in 510 children and adolescents attending an obesity clinic in Central Italy.” Pediatric Diabetes 11: 47–54.

Bruno, G., Maule, M., Merletti, F., Novelli, G., Falorni, A., Ianilli, A., Iughetti, L., Altobelli, E., d’Annunzio, G., Piffer, S., Pozzilli, P., Iafusco, D., Songini, M., Roncarolo, F., Toni, S., Carle, F., Cherubini, V., & the RIDI Study Group (2010). “Age-Period-Cohort Analysis of 1990–2003 Incidence Time Trends of Childhood Diabetes in Italy: The RIDI Study.” Diabetes 59: 2281-2287.

Calcaterra, V., Klersy, C., Muratori, T., Telli, S., Caramagna, C., Scaglia, F., Cisternino, M., & Larizza, D. (2008). “Prevalence of metabolic syndrome (MS) in children and adolescents with varying degrees of obesity.” Clinical Endocrinology 68: 868-872.

Capizzi, M., Leto, G., Petroni, A., Zampetti, S., Papa, R.E., Osimani, M., Spoletini, M., Lenzi, A., Osborn, J., Mastantuono, M., Vania, A., & Buzzetti, R. (2011). “Wrist Circumference Is a Clinical Marker of Insulin Resistance in Overweight and Obese Children and Adolescents.” Circulation 128: 1757-1762.

Caserta, C.A., Pendino, G.M., Alicante, S., Amante, A., Amato, F., Fiorillo, M., Mesisneo, A., Polito, I., Surace, M., Surace, P., Vacalebre, C., Zuin, M., Cotichini, R., Marcucci, F., Rosmini, F., & Mele, A. (2010). “Body mass index, cardiovascular risk factors, and carotid intima-media thickness in a pediatric population in Southern Italy.” Journal of Pediatric Gastroenterology & Nutrition 51(2): 216-220.

Cattaneo A1, Monasta L, Stamatakis E, Lioret S, Castetbon K, Frenken F, Manios Y, Moschonis G, Savva S, Zaborskis A, Rito AI, Nanu M, Vignerová J, Caroli M, Ludvigsson J, Koch FS, Serra-Majem L, Szponar L, van Lenthe F, Brug J (2010). Overweight and obesity in infants and pre-school children in the European Union: a review of existing data. Obesity Review 11(5):389-98.

Corbo, G.M., Forastiere, F., de Sario, M., Brunetti, L., Bonci, E., Bugiani, M., Chellini, E., la Grutta, S., Migliore, E., Pistelli, R., Rusconi, F, Russo, A., Simoni, M., Talassi, F., Galassi, C., & the Sidria-2 Collaborative Group (2008). “Wheeze and Asthma in Children: Associations With Body Mass Index, Sports, Television Viewing, and Diet.” Epidemiology 19(5): 747-755.

Di Bonito, P., Valerio, G., Grugni, G., Licenziati, M.R., Maffeis, C., Manco, M., Miraglia del Giudice, E., Pacifico, L., Pellegrin, M.C., Tomat, M., & Baroni, M.G. for the CARITALY Study Group (2015). “Comparison of non-HDL-cholesterol versus triglycerides-to-HDL-cholesterol ratio in relation to cardiometabolic risk factors and preclinical organ damage in overweight/obese children: The CARITALY Study.” Nutrition, Metabolism and Cardiovascular Diseases 25: 489-494.

Genovesi, S., Giussani, M., Federico, P., Vigorita, F., Arcovio, C., Cavuto, S., & Stella, A. (2005). “Results of blood pressure screening in a population of school-aged children in the province of Milan: role of overweight.” Journal of Hypertension 23(3): 493-497.

Ianuzzi, A., Romano, M.L., Licenziati, M.R., Panico, S., Acampora, C., Rubba, P., Salvatore, V., Trevisan, M., & Auriemma, L. (2004). “Increased carotid intima-media thickness and stiffness in obese children.” Diabetes Care 27(10): 2506-2508.

Invitti, C., Morabito, F., Guzzaloni, G., Veberti, G., & Gilardini, L. (2003). “Prevalence and Concomitants of Glucose Intolerance in European Obese Children and Adolescents.” Diabetes Care 26(1): 118-124.

Invitti, C., Gilardinia, L., Pontiggia, G., Morabito, F., Mazzilli, G., & Viberti, G., (2005). “Period prevalence of abnormal glucose tolerance and cardiovascular risk factors among obese children attending an obesity centre in Italy.” Nutrition, Metabolism & Cardiovascular Diseases 16: 256-262.

Lazzeri, G., Giacchi, M.V., Spinelli, A., Pammoli, A., Dalmasso, P., Nardone, P. Lamberti, A., & Cavallo, F. (2014). “Overweight among students aged 11-15 years and its relationship with breakfast, area of residence, and parents’ education: Results from the Italian HBSC 2010 cross-sectional study.” Nutrition Journal 13: 69.

Lazzeri, G., Panatto, D., Pammolli, A., Azzolini, E., Simi, R., Meoni, V., Giacchi, M.V., Amicizia, D., & Gasparini, G. (2015). "Trends in overweight and obesity prevalence in Tuscan schoolchildren (2002-2012)." Public Health Nutrition 18(17): 3078-3085.

Lombardo, F.L., Spinelli, A., Lazzeri, G., Lamberti, A., Mazzarella, G., Nardone, P. Pilato, V., Buoncristiano, M., & Caroli, M. for the OKkio alla SALUTE Group 2010 (2014). “Severe obesity prevalence in 8- to 9-year-old Italian children: a large population-based study.” European Journal of Clinical Nutrition 1-6.

Maffeis, C., Consolaro, A., Cavarzere, P., Chini, L., Banzato, C., Grezzani, C., Silvagni, D., Salzano, D., de Luca, F., & Tató, L. (2006). “Prevalence of overweight and obesity in 2- to 6-year-old Italian children.” Obesity 14 765-769.

Nardone, P., Spinelli, A., Lauria, L., Buoncristiano, M., Bucciarelli, M., Galeone, D. & Gruppo OKkio alla SALUTE


(2015). “[Sociodemographic variation in childhood overweight and obesity in Italy in 2014]”. Epidemiologia e Prevenzione 39(1):64.

Spinelli, A., Lamberti, A., Baglio, G., Andreozzi, S., & Galeone, D. (2009). OKkio alla SALUTE: sistema di sorveglianza su alimentazione e attività fisica nei bambini della scuola primaria. Risultati 2008. Roma: Istituto Superiore di Sanità. (Rapporti ISTISAN 09/24).

Spinelli, A., Lamberti, A., Nardone, P., Andreozzi, S., & Galeone, D. (2012). Sistema di sorveglianza OKkio alla SALUTE: Risultati 2010. Roma: Istituto Superiore di Sanità. (Rapporti ISTISAN 12/14).

Spinelli, A., Nardone, P., Buoncristiano, M., Lauria, L., Andreozzi, S., & Galeone, D. (2014). Sistema di sorveglianza OKkio alla SALUTE: dai risultati 2012 alle azioni. Roma: Istituto Superiore di Sanità. (Rapporti ISTISAN 14/11).

Spinelli, A., Nardone, P., Buoncristiano, M., Lauria, L., Andreozzi, S., Galeone, D. & Gruppo OKkio alla SALUTE (2015). [Italy 2014: childhood obesity is decreasing]. Epidemiologia e Prevenzione 39(1):63.

Turchetta, F., Gatto, G., Romano, F., Boccia, A., & La Torre, G. (2012). "Systematic review and meta-analysis of the prevalence of overweight and obesity among school-age children in Italy." Epidemiologia e Prevenzione 36(3-4): 188-195.

Turconi, G., Guarcello, M., Maccarini, L., Bazzano, R., Zaccardo, A., & Roggi, C. (2006). “BMI values and other anthropometric and functional measurements as predictors of obesity in a selected group of adolescents.” European Journal of Nutrition 45: 136-143.

Turconi, G., Maccarini, L., Bazzano, R., & Roggi, C. (2007). “Overweight and blood pressure: results from the examination of a selected group of adolescents in northern Italy.” Public Health Nutrition 11(9): 905-913.

Valerio, G., Maffeis, C., Balsamo, A., Miraglia Del Giudice, E., Brufani, C., Grugni, G., Licenziati, M.R., Brambilla, P., & Manco, M., on the behalf of the Childhood Obesity Group of the Italian Society of Pediatric Endocrinology and Diabetology (2013). “Severe Obesity and Cardiometabolic Risk in Children: Comparison from Two International Classification Systems.” PLoS One 8(12): e83793.


7. NORTHERN IRELAND

See Chapter 5 for other Northern Ireland context and evidence.



20171130 Phase 1 (Northern Ireland) Data Calculations.xlsx

20171130 Phase 1 (Northern Ireland) Data Calculations (2).xlsx

20171130 Phase 1 (Northern Ireland) Data Collation Workbook.xlsx

20171130 Phase 1 (Northern Ireland) Data Sources.xlsx


20171130 Phase 2 (Northern Ireland) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Northern Ireland) Data Documentation (Part 2).docx


20171130 Phase 5 (Northern Ireland) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Northern Ireland) Model Outputs Workbook - UNDISC.xlsm

Table. Phase 1: Northern Ireland Disease Data Quality Scores

1 2 3 4 5 6

No acceptable

data

Must be

estimated

from other

data1

International

proxy

"Approximate"

data only2

Not

applicable

(non-fatal

disease)

Acceptable

data



ICD code mismatch



Self-reported BMI


Adult diseases


Oesophageal Cancer NISRA NICR NICR NICR

Colorectal Cancer NISRA NICR NICR NICR

Liver Cancer

NISRA

NICR C22.0 not available from NICR - adjusted C22 using cancer data from RoI NICR NICR

Gallbladder Cancer NISRA NICR NICR NICR

Pancreatic cancer NISRA NICR NICR NICR

Cancer-Breast, post-menopausal NISRA NICR NICR NICR

Endometrial cancer NISRA NICR NICR NICR

Ovarian Cancer NISRA NICR NICR NICR

Prostate cancer (males only) NISRA NICR NICR NICR

Kidney Cancer NISRA NICR NICR

NI QOF - Chronic kidney disease

Urothelial Cancer (males only) NISRA NICR NICR NICR

Thyroid cancer NISRA NICR NICR data request to NICR

Type 2 Diabetes




RoI Proxy

Polycystic Ovarian Syndrome NISRA

not available not available not available

Multiple Sclerosis NISRA

UK Proxy not available UK Proxy


Stroke NISRA

NI hosp data - G45, I61, I62, I63, I64

compute from prevalence and mortality

NI QOF - stroke or TIA

Hypertension




NI QOF


NISRA Calculate incidence from prevalence

compute from prevalence and mortality

NI QOF - CHD, heart failure, Peripheral Arterial Disease, Atrial Fibrillation

Deep Vein Thrombosis NISRA

UK Proxy not available UK Proxy (compute from incidence)

Asthma NISRA


not available NI QOF - asthma, COPD

Non-alcoholic fatty liver disease (NAFLD) NISRA

not available not available not available

Gallbladder Disease NISRA

NI hosp data not available NI hosp data

Psoriasis NISRA

UK Proxy not available UK Proxy (compute from incidence)

Gout NISRA UK Proxy not available UK Proxy

Osteoarthritis – Gonarthrosis Knee Pain NISRA


not available

NI QOF -Rheumatoid arthritis

Chronic Back Pain NISRA


not available NIHSWB - self-reported




Pulmonary Embolus

NISRA UK Proxy not available UK Proxy (compute from incidence)

Childhood diseases


Wheezing disorders


Metabolic syndrome


Hyperlipidemia


Depression NISRA Calculate incidence from prevalence

not available RoI proxy - hospital attendance



not available RoI proxy - PRIME-C study

Obstructive NISRA Calculate incidence not available RoI proxy


sleep apnoea

from prevalence

High blood pressure




Wales proxy

Type 2 diabetes




England Proxy

Asthma J45 to J46 EUROSTAT


not available PCRS data as a proxy



not available http://bmcpediatr.biomedcentral.com/articles/10.1186/1471-2431-13-40

7.2 DATA


20171130 Phase 1 (Northern Ireland) Data Collation Workbook.xlsx




20171130 Phase 3&4 (Northern Ireland) Initial Model Output Workbook.xlsx


20171130 Phase 5 (Northern Ireland) Initial Resturctured Model Output Workbook.xlsx

20171130 Phase 5 (Northern Ireland) Initial Core tables and Graphs Workbook.xlsx

Phase 6: Reporting

20171130 (Northern Ireland) Final Restructured Model Output Workbook.xlsx

20171130 (Northern Ireland) Final Combined Model Outputs SAS Dataset.ssd

20171130 (Northern Ireland) Final Combined Model Outputs Worksheet.xlsx

20171130 (Northern Ireland) Final Core Tables and Graphs Workbook.xlsx



As a result of the feedback loops include in the workflow; the software was sometimes rerun (this

occourred infor Northern Ireland) with corrected inputs. Only the final model outputs from the

simulation software are listed.

Table is a profile of children, age 0-17, living in Northern Ireland in 2015. Most of the children are

healthy weight (74.2%), with 25.8% overweight or obese (ow/ob). A trend toward increasing ow/ob

with increasing age begins with the 0-5 age group and continues throughout adulthood, also

beginning with the 0-5 age group, increasing proportions of ow/ob females compared to males that

continues throughout adulthood.

Table. Phase 5: Profile of Northern Ireland children

IRELAND

AGE SEX BMI AT AGE 18 NUMBER PERCENTAGE

(0-17 YEARS) PERSONS OBESE/OVERWEIGHT 111,875 25.8%


TOTAL 432,791 100.0%



TOTAL 210,716 100.0%



TOTAL 222,075 100.0%



TOTAL 150,187 100.0%



TOTAL 73,429 100.0%



TOTAL 76,758 100.0%



TOTAL 142,145 100.0%



TOTAL 69,071 100.0%



TOTAL 73,074 100.0%




TOTAL 140,459 100.0%



TOTAL 68,217 100.0%



TOTAL 72,243 100.0%


8. PORTUGAL

8.1 LOCAL CONTEXT

In Portugal, the Ministry of Health (MoH) is responsible for the development of health policies and their evaluation. Among the institutions administrated by the MoH, the Directorate General of Health (DGH) plans, regulates, coordinates and supervises all health promotion and disease prevention activities and define technical conditions for proper provision of health care. DGH is also responsible for public health programmes, quality and epidemiological surveillance, health statistics reports and studies and the design and implementation of the National Health Plan.

The main function of the MoH is the regulation, planning and management of the National Health Service (NHS). The NHS is a structure through which the Portuguese State assures the constitutional right to health to all citizens of Portugal. It integrates all health care, from health promotion and surveillance to disease prevention, diagnosis, treatment and medical and social rehabilitation. Regional Health Administrations (RHAs) are responsible for the implementation of national health policies and the management of the NHS at regional level. Under RHAs authority and administration are the health care units: Hospitals and Groups of Health Centres, a set of functional units that ensure the provision of primary health care to a population of a geographical area.

Beyond the National Health Plan, General-Directorate of Health (DGH) is also responsible for the

design and implementation of the National Priority Programmes, among which we highlight the

following examples, that are somehow related to nutrition and obesity:

National Programme for the Promotion of Healthy Eating1,2

National Programme for the Promotion of Physical Activity

National Programme for Diabetes

National Programme for Cerebrum and Cardiovascular Diseases

National Programme for Oncological Diseases

National Programme for Respiratory Diseases

National Programme for Mental Health

The National Health Institute Doctor Ricardo Jorge (INSA) is a public organization of the Ministry of Health endowed with scientific, technical, administrative, financial and property of its own. INSA has operating units at its headquarters in Lisbon, two centers in Porto (Centre for Public Health Dr. Gonçalves Ferreira and Medical Center of Genetics Jacinto Magalhães) and Águas de Moura (Centre for Vectors and Infectious Diseases Dr. Francisco Cambournac). INSA is organized in technical and scientific terms in six major departments: • Food and Nutrition Department • Infectious Diseases Department • Epidemiology Department • Human Genetics Department • Health Promotion and non-Communicable Disease Prevention • Environmental Health Department All operative units composing the departments develop multidisciplinary programmes in Public Heath areas, namely performing R&D, health monitoring, training, laboratory external quality assessment and general health services. INSA is responsible for National Health Plan evaluation.


Other programmes designed and implemented by DGH are closely related to the nutritional status of

children and childhood obesity:

National Programme for Child and Youth’s Health

National Programme for Oral Health

National Programme of School Health

Other institutions out of the health sector also contribute for health promotion and other activities

of the health system, namely in the nutrition and obesity field (e.g. Nutritionists Councils;

Municipalities; Portuguese Association of Nutritionists, Private Social Solidarity Institutions;

Portuguese Association Against Childhood Obesity; Association Of Obese And Ex-Obese Patients In

Portugal; Universities.

MAPICO (Mapping and Dissemination of Good Practices in Community Intervention Projects in the Area of Preventing Obesity and Reducing Prevalence of Pre-Obesity and Infant Obesity in Portugal) is a project developed in the scope of the National Programme for the Promotion of Healthy Eating. The main objective of this project is to carry out a "mapping" of community intervention programs aiming to prevent obesity at the level of primary health care services and also in Portugal schools. In the course of this project, it has been developed a national registry of these interventions, with the aim of disseminating good practices and establishing a national benchmark. (Table 1)

The National Programme for the Promotion of Healthy Eating (PNPAS) was approved in 2012, and has five main goals: (i) to increase knowledge about the food intake of the Portuguese population and about its determinants and consequences; (ii) to modify the availability of certain foods (high in sugar, salt and fat), in schools, workplaces and public spaces; (iii) to inform and empower the population for the purchase, preparation and storage of healthy food, especially the most vulnerable groups; (iv) to identify and promote cross- sectoral actions that encourage the consumption of foods of good nutritional quality in an articulate and integrated way with other sectors, namely agriculture, sport, environment, education, social security and local authorities; and (v) to improve the qualifications and conduct of the different professionals who, owing to their roles, may influence nutritional knowledge, attitudes and behaviours

1.

“The design of PNPAS followed the latest strategic lines suggested by World Health Organization and the European Commission, proposing a cross- sectoral mix of interventions to ensure physical and economic access to healthy eating by creating healthy environments and empowering individuals and communities

1.”


Table National registry of community intervention programs aiming to prevent obesity (MAPICO)


8.2 LOCAL EVIDENCE

8.2.1 Overweight / Obesity

Estimates for pre-obesity and obesity prevalence from Portugal were retrieved from 17 sources and

data are described and analysed here.

Adult

The oldest pre-obesity and obesity prevalence data available for population resident in Portugal

come from a study that dates to 1998/99. It is the National Health Survey 1998/99 that was carried

out in the mainland of Portugal with a representative sample of the adult population aged 18 or

over. Weight and height data were self-reported and pre-obesity and obesity prevalence were,

respectively, 20.3% and 12.9% for men and 16.2% and 14.6% for women 3,4.

In the following National Health Survey, carried out in 2005/06, the prevalence of pre-obesity and

obesity among adult population were, respectively, 20.8% and 16% for men and 16.6% and 17% for

women. This survey included population resident in Portugal (mainland and archipelagos of Madeira

and Azores) and weight and height data were equally self-reported 5.

The last National Health Survey was carried out in 2015 with a representative sample of adult

population from 25 to 74 years old living in Portugal (mainland and islands). Weight and height were

measured and results show that pre-obesity and obesity prevalence more than doubled compared

with previous surveys, being, respectively, 45.5% and 25% for men and 33.2 and 32% for women 6.

Despite this important increase in the prevalence of pre-obesity and obesity in the adult population

resident in Portugal shoed by National Health Surveys, it is important to consider the methodological

differences of these studies.

The other three epidemiological studies considered in the model presented the following results,

respectively for pre-obesity and obesity prevalence of adult population (18+) in Portugal: 45.2% and

15% for men and 34.4% and 13.4% for women (2003/05)7; 53.3% and 11,2% for men and 27.8% and

10.4% (2009)8; 41.8% and 19.7% for men and 31% and 23.7% for women (2015/16)9. All the studies

used measured data for the calculation of BMI. The first one considered just the population of the

mainland and the others all the population resident in Portugal (mainland and islands).

Regardless of some discrepancies, all studies show high prevalence of pre-obesity and obesity in the

adult population living in Portugal, with pre-obesity being more prevalent among men and obesity

more prevalent among women.

It is also evident that obesity prevalence increase with age and is higher in the population groups

with lower levels of education6,9.

Children

The collection and analysis of prevalence data on pre-obesity and obesity during childhood has been

more systematic in Portugal for the 6 to 8 and 11 to 16 age groups due to the international studies


Childhood Obesity Surveillance Initiative (COSI) and Health Behaviour in School-aged Children

(HBSC)10.

Regarding COSI, weight and height data of children from 6 to 8 years old living in Portugal (mainland

and islands) were measured in school settings. Although some numbers appear to show a trend

towards a reduction in the prevalence of pre-obesity and obesity, these trends were not statistically

confirmed. Table below presents the results of COSI in all the years in which it were carried out11–13.

Contrary to what happens with adults, pre-obesity is more prevalent in girls and obesity in boys.

Table Pre-obesity and obesity prevalence for boys and girls (6-8 years old) in Portugal according

International Obesity Taskforce (IOTF) criteria.

Study Year

COSI

2008 2010 2013

Boys Pre-obesity 20.2% 16.5% 16.5%

Obesity 9.7% 10.1% 8.6%

Girls Pre-obesity 18.1% 17.5% 17.9%

Obesity 8.1% 8.4% 7.7%

Source: Childhood Obesity Surveillance Initiative Portugal, 2008, 2010 and 101311–13.

Regarding HBSC, weight and height data of adolescents from 11 to 16 years old living in Portugal

(mainland) were self-reported and data were analysed according IOTF criteria. The first study was

conducted in 199814, the second in 200215, the third in 200616, the fourth in 201017 and the most

recent in 201418. In the last round, it was observed that, in this age group, girls present more

frequently a normal body mass index (14.4% of girls were pre-obese and 2.3% were obese) and boys

have higher rates of obesity (16% of boys were pre-obese and 3.8% were obese). Older adolescents

present most often a normal body mass index, that is, the older the adolescents in this age group,

the lower the prevalence of obesity18. Table below presents the evolution of the prevalence of pre-

obesity and obesity in adolescents aged 11 to 16 years in Portugal (mainland) during the years of

HBSC study, using IOTF criteria. It is possible to verify that there was no significant change in the

prevalence of adolescent pre-obesity and obesity during these years in Portugal18.

Table Evolution of the prevalence of pre-obesity and obesity in adolescents of both sexes aged 11 to

16 years in Portugal (mainland) during the years of HBSC study.

Study Year

HBSC

1998 2002 2006 2010 2014

Adolescents (both sexes)

Pre-obesity

13.3% 15% 15% 15% 15%

Obesity

2.3% 3.2% 2.9% 3.4% 3%

Source: M. Matos, C. Simões, I. Camacho, et. al., 201518.

Other study conducted in 2007/08 for a PhD thesis presented results slightly higher in the

prevalence of pre-obesity and obesity in adolescents using the same criteria (IOTF): respectively,


22.9% and 8.8% for boys and 22.4% and 6.9% for girls. In any case, adolescent boys continue to have

higher rates of obesity then girls19.

Regarding infants and pre-school children, three studies were considered for the model with the

following prevalence of pre-obesity and obesity per age group data:

a PhD study, conducted in 2001 with a sub-national sample of Coimbra municipality, using

IOTF criteria – 13.6% and 6.5% for boys and 20.4% and 6.9% for girls of 3 to 5 years old20;

EPACI study, conducted in 2012 with a national (mainland and islands) representative

sample, using World Health Organization criteria – 6.3% and 0.6% for boys and 5.6% and

0.4% for girls of 2 to 3 years old21;

IAN AF study, conducted in 2015/16 with a national (mainland and islands) representative

sample, using World Health Organization criteria – 3.3% and 1.1% for boys and 8.6% and

1.4% for girls of 0 to 4 year old9.

Despite the undoubted importance of studies on the prevalence of overweight and obesity in this

age group from 0 to 5 years old, the methodological differences of these three studies make it

impossible to compare their results.


Seven sources on health and other impacts of child overweight and obesity in childhood were

retrieved for Portugal. Two of these examined the metabolic syndrome in children (aged 7-9 years;

Pedrosa et al., 2010) and adolescents (mean age 13.2 years; Teixera et al., 2001). Pedrosa et al.

(2010) reported that presence of metabolic syndrome (MS), i.e. three or more of abdominal obesity,

high fasting triglycerides, low HDL, high BP, and high fasting glucose, was significantly associated

with higher BMI, while Teixera et al. found that both direct and indirect measures of adiposity were

associated with serum cardiovascular risk factors in boys and girls. Leite et al. (2012) reported that,

among a sample of children/adolescents (mean aged 12.9 years), CIMT was positively associated

with higher BMI, even in moderately overweight ranges, independent of age, gender, systolic blood

pressure and plasma lipid concentrations. Ribeiro et al. (2003) found that systolic and diastolic blood

pressure were significantly and positively related to BMI among a sample of 8-16 year-olds (all at risk

of obesity).

Lopes et al. (2011) found that motor co-ordination was inversely associated with BMI: the strength

of the association increased during childhood but decreased into early adolescence; however at all

ages, overweight and obese children had significantly lower motor co-ordination than healthy

weight children.

Two sources from Portugal examined psychological/emotional impacts (Ferreira Felgueiras, 2011;

Moreira et al., 2013). The study by Moreira et al. is of note since it allows comparisons of healthy

children and adolescents with children/adolescents with various conditions including obesity.

Participants in their study were classified as healthy, with diabetes, asthma, epilepsy, or obesity.

Children with obesity and epilepsy reported the lowest quality of life and highest levels of

psychological problems, and parents of obese children reported the lowest quality of life.


8.2.5 Inequalities

Thirteen studies from Portugal described inequalities in prevalence. Some regional variations in the

prevalence of overweight and obesity have been reported for Portugal, but these are not as

dramatic as in Italy. Nazareth (2013) reported the highest levels of overweight and obesity among

infants in the North, with lowest rates in the Algarve in the South. Recent COSI results indicate that

prevalence of overweight is higher in Lisbon, the Tagus Valley and the Azores, while rates of obesity

were higher in central regions and Madeira (Rito et al., 2012b, Rito & Graça, 2015). Differences by

urban-rural location were not evident in the COSI results (Rito et al., 2012a). Research by Nogueira

et al. (2013) and Ferrao et al. (2013) suggest that inequalities in prevalence may be related to

specific aspects of children’s local communities, such as poorer built environments and less safe

neighbourhoods. Other studies from Portugal confirm associations between parental BMI, parental

education and children’s overweight and obesity (Bingham et al., 2013, Ramos et al., 2007; Padez et

al., 2005, 2009; Ferreira & Marques-Vidal, 2008), as well as among children who were first-born,

with fewer siblings, and whose mothers gained more weight during pregnancy (Moreira et al., 2007).



20171130 Phase 1 (Portugal) Data Calculations.xlsx

20171130 Phase 1 (Portugal) Data Calculations (2).xlsx

20171130 Phase 1 (Portugal) Data Collation Workbook.xlsx

20171130 Phase 1 (Portugal) Data Sources.xlsx


20171130 Phase 2 (Portugal) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Portugal) Data Documentation (Part 2).docx


20171130 Phase 5 (Portugal) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Portugal) Model Outputs Workbook - UNDISC.xlsm

8.4 DATA


20171130 Phase 1 (Portugal) Data Collation Workbook.xlsx





20171130 Phase 3&4 (Portugal) Initial Model Output Workbook.xlsx


20171130 Phase 5 (Portugal) Initial Resturctured Model Output Workbook.xlsx

20171130 Phase 5 (Portugal) Initial Core tables and Graphs Workbook.xlsx

Phase 6: Reporting

20171130 (Portugal) Final Restructured Model Output Workbook.xlsx

20171130 (Portugal) Final Combined Model Outputs SAS Dataset.ssd

20171130 (Portugal) Final Combined Model Outputs Worksheet.xlsx

20171130 (Portugal) Final Core Tables and Graphs Workbook.xlsx




PORTUGUESE REFERENCES

Graça P, Gregório MJ, Sousa SM De, Carriço J, Correia A, Salvador C. The Portuguese National Programme for the Promotion of Healthy Eating : 2012 – 2015. Public Heal Panor. 2016;2(2):184-209.

Graça P, Gregório MJ, Mendes de Sousa S, Camolas J. Food policy in Portugal: historical context, opportunities, and threats. Food Sci. 2016:1-10. doi:http://dx.doi.org/10.1016/B978-0-08-100596-5.21166-9 Reference.

Portugal. Ministério da Saúde. INSA. Inquérito Nacional de Saúde 1998/1999 : Dados Gerais. Lisboa; 2001.

Portugal. Ministério da Saúde. INSA. Inquérito Nacional de Saúde 1998/1999 : Informação Síntese. Lisboa; 2001.

Portugal. Ministério da Saúde. INSA. Inquérito Nacional de Saúde 2005/2006 : Dados Gerais. Lisboa; 2007.


Instituto Nacional de Saúde Doutor Ricardo Jorge. 1o Inquérito Nacional de Saúde Com Exame Físico (INSEF 2015). Lisboa; 2016.

Carmo I, Santos O, Camolas J, et al. Overweight and obesity in Portugal: national prevalence in 2003-2005. Obes Rev. 2008;9(1):11-19. doi:10.1111/j.1467-789X.2007.00422.x.

Poínhos R, Franchini B, Afonso C, et al. Alimentação e estilos de vida da população portuguesa : metodologia e resultados. Aliment Humana. 2009;15(3):43-60.

Faculdade de Medicina da Universidade do Porto/Instituto de Saúde Publica da Universidade do Porto (Carla Lopes, Milton Severo, Andreia Oliveira, Elisabete Ramos SV, Faculdade de Ciências da Nutrição e Alimentação da Universidade do Porto (Duarte Torres SR, Instituto Nacional de Saúde Doutor Ricardo Jorge (Sofia Guiomar LO, et al. Inquérito Alimentar Nacional E de Atividade Física. IAN-AF 2015-2016. Lisboa; 2017.

World Health Organization. Adolescent Obesity and Related Behaviours : Trends and Inequalities in the WHO European Region, 2002-2014. Copenhagen; 2017.

Portugal. Ministério da Saúde. Instituto Nacional de Saúde Doutor Ricardo Jorge. Childhood Obesity Surveillance Initiative - Portugal. Vol INSA, I.P. Lisboa; 2011. doi:10.1111/j.2047-6310.2012.00068.x.

Portugal. Ministério da Saúde. Instituto Nacional de Saúde Doutor Ricardo Jorge. Childhood Obesity Surveillance Initiative: COSI Portugal 2010. Lisboa: INSA, I.P.; 2012.

Portugal. Ministério da Saúde. Instituto Nacional de Saúde Doutor Ricardo Jorge. Childhood Obesity Surveillance Initiative: COSI Portugal 2013. Lisboa; 2013.

Matos MG de, Simões C, Carvalhosa S, Reis C. A Saúde Dos Adolescentes Portugueses. Estudo Nacional Da Rede Europeia HBSC /OMS (1998). Lisboa; 1998.

Matos MG de, Equipa do projeto Aventura Social e Saúde. A Saúde Dos Adolescentes Portugueses (Quatro Anos Depois). Relatório Português Do Estudo HBSC 2002. Lisboa; 2002.

Matos MG de, Simões C, Tomé G, et al. A Saúde Dos Adolescentes Portugueses Hoje E Em 8 Anos. Relatório Preliminar Do Estudo HBSC 2006. Lisboa; 2006. doi:ISSN: 2183-5888.

Matos MG de, Diniz JA, Simões C, Equipa do projeto Aventura Social. Health Behaviour in School-Aged Children: Dados Nacionais 2010 - Abril 2011. Problemas Emergentes E Contextos Sociais. Lisboa; 2011.

Matos MG, Simões C, Camacho I, Reis M, Equipa do projeto Aventura Social. Relatório Do Estudo HBSC 2014: A Saúde Dos Adolescentes Portugueses Em Tempos de Recessão - Dados Nacionais 2014. Lisboa; 2015. doi:978-989-98346-1-3.

Ferreira J. Prevalência de obesidade infanto-juvenil. Associação com hábitos alimentares, actividade física e comportamentos sedentários dos adolescentes escolarizados de Portugal Continental. 2010.

Rito A. Estado nutricional de crianças e oferta alimentar do pré-escolar do município de Coimbra, POrtugal, 2001. 2004.

EPACI Portugal 2012. Alimentação e crescimento nos primeiros anos de vida: a propósito do EPACI Portugal 2012. 2013.


9. ROMANIA

9.1 LOCAL CONTEXT

In recent years, the Romanian Government has developed through its health and social protection

policies measures designed to reduce the burden of disease in the population by reducing existing

inequalities in health, optimizing resources use and improving administrative and management

capacity at all levels of the health system.

Taking into account the health profile of the population, the Romanian Government has developed

and approved in 2014 the National Health Strategy for 2014-2020. The strategy is the expression of

the recognition of the role of population’s health as a key determinant and as engine of sustainable

development of the society.

Priority areas in the strategy aim early prevention and combat early and high-frequency disease in

adult populations such as circulatory diseases, cancers, or digestive diseases.

Women's and child's health is one of the priority areas of intervention taking in account the deficit

of health care during the prenatal period fact linked with a large number of premature and / or low

birth weight babies. Nutrition of under 2 years old children also raise problems regarding low rates

of exclusive breastfeeding or early diversification. Strengthening primary care by increasing its

capacity to detect early major illnesses with a major impact on the burden of non-communicable

diseases is another priority area. Prioritizing this area is essential for early prevention of overweight

and obesity, taking in account the fact that the foundation of health is often set during the prenatal

period and early childhood.

The strategy is accompanied by a concrete action plan with institutional responsibilities and financial

allocations so that all strategic targets can be monitored and achieved by 2020.

In the past 5 years in Romania there have been accomplished following achievements in the area of

nutrition and physical activity:

New Low and regulations

the National Health Programs 2017 provide and support interventions to adopt a healthy

lifestyle through healthy eating and physical activity

There are changes of existing legislation on food labelling according to the Regulation (EU)

No 1169/

The Ethical Code for Food Product Advertising Targeting Children promote rules for all

institutions involved in marketing food products to children.

Elaboration of the Code on marketing of food and non-alcoholic beverages to children

A New Law frame for development of community care services

Elaboration of educational materials

A new version of the booklet for pregnant women with focus on nutrition in pregnancy and

breastfeeding ,

the Guidelines for a Healthy Diet Food was developped which bring information for a

healthy diet in the form of food pyramid divided into 7 foodgroups

The guide on physical development standards of children and youth as a tool to be used

to assess the physical development of children in school setting was elaborate


IEC activities

national and local information campaigns for disadvantaged populations were implemented

broadcasting of advisory messages, such as “For a healthy lifestyle, avoid excess salt, sugar

and fat” and “For a healthy lifestyle, exercise for at least 30 minutes every day”,

Brestfeeding is best

Studies

In order to reduce health inequalities, the Ministry of Health funded several studies to assess the use

of preventive and curative medical services, the quality and accessibility of these services for

pregnant women and children including the evaluation of the nutritional status. The aim of these

studies is to collect data to support interventions to improve these services in the benefit of the

entire population.

The assessment of the nutritional status of children in the primary school was performed in the

frame of the COSI project - WHO initiative.

Assessment of the nutritional status of children in the primary school through participation in the

COSI project - WHO initiative.. The impact of these actions on the health profile of the population is

positive in some areas such as infant and maternal mortality, life expectancy, but with the mention

that these actions are not the only factor of influence. For other areas, such as diseases with a high-

risk for disability, non-communicable or chronic (specific to the Romanian population) diseases, the

impact is still not (cannot be) measured in results that reflects significant short term improvement in

the prevalence of these diseases.

Strengthening policies to reduce social inequalities in all areas and implicitly in health can reduce

with time the burden of disease in the population.

9.2 LOCAL EVIDENCE

This section should be read in conjunction with the international context outlined in Section 1.2.


Data on prevalence were available from 14 studies identified in Romania. Seven are described here.

Note that reference standards to classify overweight and obese varies across studies.

In 2010, Romania’s national nutrition programme collected data from a representative sample of

infants aged 0-24 months. Nanu et al. (2011) reported that 5.4% of the infants assessed had high

weight for height (WHO growth standards). The results of a survey conducted in 2010-2012 in 14

counties of Romania indicated that 20% of children aged 6-7 years were overweight or obese, and

that 18% of children aged 13-14 were overweight or obese (WHO cut-points; Ardeleanu et al., 2015).


The results for the third round of COSI for Romania have been published in a national report

(Nicolescu et al., 2013) and discussed at the eighth international meeting for COSI (World Health

Organisation Regional Office for Europe, 2016). Among the 8-9 year-olds surveyed, prevalence of

overweight and obesity was higher among boys than girls: 14.8% of boys were classified as

overweight, and 15.0% obese, compared with 15.7% and 8.0% among girls, respectively

The other four Romanian studies were conducted using regional samples. Mocanu (2013) reported

the results of a study carried out in Northeast Romania among children aged 6 to 10. Across all

children, about 25% of boys and 23% of girls were overweight or obese (IOTF cut-points). No

significant gender differences were found for any age, and prevalence was highest at age 9 in both

sexes. Valean et al. (2009) surveyed children in Northwest Romania and estimated, using the US-CDC

cut-points, that 25% of boys and 17% of girls aged 6-18 were overweight or obese. At all age groups,

there were significantly more overweight and obese boys than girls. There was a large decline in

prevalence with increasing age. For example, 34% of boys in grades 1-4, compared to 16% of boys in

grades 9-12, were overweight or obese. Chirita-Emandi et al. (2012) estimated that, in West

Romania, 30% of boys and 22% of girls aged 6-17 were overweight or obese (IOTF cut-points).

Estimates from South Romania (Bucharest) in children aged 7-19 are similar to those for the West

(IOTF cut-points), with prevalence of overweight and obesity around 29% among boys and 21%

among girls (Barbu et al., 2015).

Trends

There are two sources of information on trends in overweight and obesity among infants and

children from Romania. Nanu et al. (2011) reported a slight increase in the prevalence of increased

weight for height in children 0-24 months old in 2010 compared with 2004 (5.4% compared with

4.2%).

In contrast to other JANPA participants, this research has also highlighted the relatively high

prevalence of underweight children, noting relatively stable trends in underweight over time. For

example, Nanu, Stativa Moldovanu (2006) reported a median birth weight of 3,200g in Romania in

2005, which is below that of other European countries (3,400g). This study also reported that 4.4%

of children under 5 had low weight for height, and about 5% of children aged 6-7 had low weight for

height.

With regard to the evolution of the overweight in the 6-year-olds, there was a rise in the prevalence

of obesity within 10 years. Thus, the indicator WHZ> +2 DS in 2005 had a weight of 3.3% for boys and

4.4 % in girls. In 2016 the BMI weight > +2 DS vs. average is 5.61% boys and 5.44% in girls. Evolution

to overweight is more pronounced in boys than girls (Nanu M, Moldovanu F, 2016 unpublished data)


Four sources on this topic were located for Romania. Unlike other JANPA countries, a positive

association between SES (income) and prevalence of overweight/obesity has been reported in

Romania, after adjusting for aspects of children’s diets and physical and sedentary activity levels

(Mocanu, 2013). The COSI round 3 results for Romania (World Health Organization Regional Office

for Europe, 2016; Nicolescu et al., 2013) indicate quite large regional variations in the prevalence of


overweight and obesity among children in rural (21.6% overweight/obese), semi-urban (25.0%) and

urban (31.6%) areas. Cosoveanu (2011) reported higher rates of overweight and obesity among

children with higher parental BMI, who were not breastfed and introduced early to solid foods, and

with less healthy diets and less active lifestyles. Morea and Miu (2013) found a positive association

between childhood overweight and obesity and parental BMI (measured as pre-pregnancy maternal

overweight or obesity).

9.2.3 Adult Impacts

Prevalence of overweight in adult population is 31.2% and for obesity is 16, 7% (Bunescu at. Al,

2009)

Similar results were found in another study published in 2015 (Roman et al.,), which shows that

prevalence of overweight and obesity is 52%. The highest prevalence is in Moldavia 57,2% and the

lowest in Banat, Crisana&Transylvania 46%. This regional structure confirms that overweight and

obesity affects mostly the less developed regions (which for Romania is Moldavia), implicitly with

poor populaton and probably the ones with limited access to health care services.

9.2.5 Inequalities

The highest mean BMI is in children from NW, W and SW regions. Below the country mean values

are the children from centre, NE and E region. Bucharest is below country mean value. Mean BMI is

higher in children from urban area than in rural and in boys than in girls.

The mean BMI of 6 years old children is higher in most developed counties compared with the

poorest region of Romania . This diffrences could be explained either trough the decrease of

nutrional deficiencies or un increase of overweight among children in the most developed counties

Mean BMI decreases by number of children in family, being below country mean for families with 3

and more than 3 children. The highest value of BMI and over country mean is in families with higher

educational level and in mother aged over 45 years. (Nanu M, Moldovanu F., 2016 unpublished data)



20171130 Phase 1 (Romania) Data Calculations (1).xlsx

20171130 Phase 1 (Romania) Data Calculations (2).xlsx

20171130 Phase 1 (Romania) Data Collation Workbook.xlsx


20171130 Phase 1 (Romania) Data Sources.xlsx


20171130 Phase 2 (Romania) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Romania) Data Documentation (Part 2).docx


20171130 Phase 5 (Romania) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Romania) Model Outputs Workbook - UNDISC.xlsm

Table. Phase 1: .Romanian Disease Data Quality Scores

1 2 3 4 5 6

No acceptable

data

Must be

estimated

from other

data1

International

proxy

"Approximate"

data only2

Not

applicable

(non-fatal

disease)

Acceptable

data



ICD code mismatch


Self-reported BMI


Adult diseases


Oesophageal Cancer

INS (National Institute of Statistics)

morbidity at family doctor's office

calculate from prevalence and mortality

Globocan

Colorectal Cancer




C18 to C21 Globocan

Liver Cancer

have C22 only morbidity at family doctor's office


C22 Globocan


have C22 only

Gallbladder Cancer




Globocan

Pancreatic cancer




Globocan




calculate from incidence and mortality

have incidence

Endometrial cancer




C54 Globocan

Ovarian Cancer




Globocan





Globocan

Kidney Cancer




Globocan





Globocan

Thyroid cancer




Globocan

Type 2 Diabetes




Coronary heart disease and cardiovascular risk factors among people aged 25–65 years, as seen in Romanian primary healthcare http://www.tandfonline.com/doi/full/10.1080/13814780802343141 European Health Interview Survey (EHIS)


have E28 only

morbidity at family doctor's office have E28 only


have incidence

Multiple Sclerosis

INS (National Institute of


calculate from prevalence and

National Institute of Public Health - total


Statistics) mortality cases only

Stroke




European Health Interview Survey (EHIS)

Hypertension




SEPHAR II http://www.romanianjournalcardiology.ro/wp-content/uploads/2016/01/RRC_art_4-4-22.pdf Coronary heart disease and cardiovascular risk factors among people aged 25–65 years, as seen in Romanian primary healthcare http://www.tandfonline.com/doi/full/10.1080/13814780802343141 European Health Interview Survey (EHIS)





Coronary heart disease and cardiovascular risk factors among people aged 25–65 years, as seen in Romanian primary healthcare http://www.tandfonline.com/doi/full/10.1080/13814780802343141


have I80 only

morbidity at family doctor's office have I80 only


have incidence

Asthma

have J45 and J46 combined only

morbidity at family doctor's office have J45 and J46 combined only




have K76 only

morbidity at family doctor's office have K76 only


have incidence

Gallbladder Disease

have K80, K81, K85 combined only

morbidity at family doctor's office have K80, K81, K85 combined only


have incidence

Psoriasis






Gout Have M10 only

morbidity at family doctor's office Have M10 only


have incidence


have M17 only

morbidity at family doctor's office have M17 only


have incidence

Chronic Back Pain

have M54 only

morbidity at family doctor's office have M54 only







have incidence

Pulmonary Embolus




have incidence

Childhood diseases


Wheezing disorders

no deaths Calculate incidence from prevalence

Prob survival = 1 (no deaths)

Prev wheezing ever/last 12 months Paraschiva CHERECHES-PANTA Epidemiological Survey 6 Years Apart: Increased Prevalence of Asthma and Other Allergic Diseases in Schoolchildren Aged 13-14 Years in Cluj-Napoca, Romania https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3150021/pdf/maed-06-10.pdf also have hospital discharges by age - 0 to 4; 5 to 14

Metabolic syndrome

no deaths hospital discharges 0 to 17


hospital discharges 0 to 17

Hyperlipidaemia

no deaths Calculate incidence from prevalence


hospital discharges 0 to 4; 5 to 14


Depression no deaths

0 to 4; 5 to 9; 10 to 14; National Institute for Public Health - new cases


have incidence


no deaths

0 to 4; 5 to 9; 10 to 14; G47 National Institute for Public Health - new cases


hospital discharges 0 to 4; 5 to 14 - G47.3

High blood pressure


0 to 4; 5 to 9; 10 to 14; 15 to 19 morbidity at family doctor's office have J45 and J46 combined only


have incidence

Type 2 diabetes



15 to 24 have incidence

Asthma 0 to 4; 5 to 9; 10 to 14; 15 to 19



prevalence 'asthma ever' in kids age 13 to 14


0 to 4; 5 to 9; 10 to 14; 15 to 19 - K76 only

0 to 4; 5 to 9; 10 to 14; 15 to 19 - K76 only morbidity at family doctor's office have J45 and J46 combined only


have incidence


have M17 only

have M17 only 0 to 4; 5 to 9; 10 to 14; 15 to 19 morbidity at family doctor's office


have incidence


9.4 DATA


20171130 Phase 1 (Romania) Data Collation Workbook.xlsx




20171130 Phase 3&4 (Romania) Initial Model Output Workbook.xlsx


20171130 Phase 5 (Romania) Initial Resturctured Model Output Workbook.xlsx

20171130 Phase 5 (Romania) Initial Core tables and Graphs Workbook.xlsx

Phase 6: Reporting

20171130 (Romania) Final Restructured Model Output Workbook.xlsx

20171130 (Romania) Final Combined Model Outputs SAS Dataset.ssd

20171130 (Romania) Final Combined Model Outputs Worksheet.xlsx

20171130 (Romania) Final Core Tables and Graphs Workbook.xlsx


As a result of the feedback loops include in the workflow; the software was sometimes rerun(this

occurred for Romania) with corrected inputs. Only the final model outputs from the simulation

software are listed.

Table. Phase 5: Profile of Romanian children ((from Initial model which is under review)

)

Age Sex BMI at age 18 Number Percentage

Total Persons Obese/Overweight 846,573 22.1


(0-17)

Healthy weight 2,986,481 77.9

Total 3,833,054 100.0

Females Obese/Overweight 354,157 19.0


Total 1,860,048 100.0

Males Obese/Overweight 492,416 25.0


Total 1,973,006 100.0

0-5 Persons Obese/Overweight 185,527 15.8

Healthy weight 990,548 84.2

Total 1,176,076 100.0



Total 571,372 47.6



Total 604,704 50.4



Total 1,288,496 100.0



Total 626,700 100.0



Total 661,797 100.0



Total 1,368,482 100.0



Total 661,977 100.0



Total 706,505 100.0

9.5 COMMENTS

There are a few collaboration among different professionals acting in the health system in the area of nutrition and related diseases


There is a gap in the collaboration between services addressed to children and adults fact which act negatively on the follow up evaluation of nutritional disturbances starting in childhood

Evidence

The following points apply to the Romanian modelling.

There is little collaboration among research institutions in design, implementation and

evaluation of studies regarding obesity

In Romania there are few nutritional studies performed on national representative samples of children

Taking in account all diseases in Romania few impact and cost related studies were performed in the area of obesity in general and children obesity Romania researcher published only few materials in international newspaper.

Data

Limited access different data basis In Romania, data that is recorded at different health care level, is not available for research. This data is recorded using software only serving the needs of the National Health Insurance House and this data cannot be summarised.

Romania was involved only in the last years in international studies regarding childhood obesity ( Cosy study)

There are national registries only for a few diseases and on local basis ( cancer registry ) Regarding the accuracy of primary data, this is not collected by a unitary criteria

Central institutes, such as Health Ministry, Ministry of labour receive processed data and not primary data from the different counties and therefore it is difficult to explore in the existing data in a secondary manner

The following recommendations arose out of the Romanian modelling

Childhood obesity

There is a lack of primary data regarding costs for drugs, treatment, and care for specific

diseases. Currently the available data is available only in processed/aggregated form,

depending on the needs of the National Health Insurance Fund. Availability of primary data

would facilitate analyses which have other goals, as in our case the cost of all diabetes

related to obesity, It is important to inform the policy makers in order to manage the basic

information.

Use of proxy data doesn’t make us sure that this data is necessarily relevant for Romanian

population. We don’t have the possibility to check if they match our specific.

Gaps in the evidence and data

Inequalities in childhood obesity in Romania

Building capacity


Currently, there is not an institution that centralises costing data such as: drugs costs,

especially at primary care level

ROMANIAN REFERENCES

Ardeleanu, I.S., Nanu, M., Moldovanu, F., Bacalearos, C., & Moculescu, C. (2015). “OVERWEIGHT AND OBESITY

SCREENING OF 6-7 YEARS OLD AND 13-14 YEARSOLD CHILDREN IN 14 COUNTIES FROM ROMANIA”. Paper

presented at IOMC days, December, Bucharest.

Barbu, C. G., Teleman, M. D., Albu, A. I., Sirbu, A. E., Martin, S. C., Bancescu, A., & Fica, S. V. (2015). Obesity and

eating behaviors in school children and adolescents–data from a cross sectional study from Bucharest,

Romania. BMC public health, 15(1), 206.

Bunescu, D. M., Stoffers, H. E., van den Akker, M., & Jan Dinant, G. (2008). Coronary heart disease and

cardiovascular risk factors among people aged 25–65 years, as seen in Romanian primary healthcare. The

European journal of general practice, 14(2), 56-64.

Chereches-Panta P, et al (2011)– Epidemiological survey 6 years apart: increased prevalence of asthma and

other allergic diseases in schoolchildren aged 13-14 years in Cluj-Napoca, Romania (based on Isaac

questionnaire) Maedica. ;6:10–16.)

Chirita-Emandi, A., Puiu, M., Gafecnu, M., & Pienar, C. (2012). “GROWTH REFERENCES FOR SCHOOL AGED

CHILDREN IN WESTERN ROMANIA.” Acta Endocrinologica (Buc)VIII: 133-152.

Chirita-Emandi, A., Puiu, M., Gafencu, M., & Pienar, C. (2013). Arterial hypertension in school-aged children in

western Romania. Cardiology in the Young, 23(2), 189-196.

Cosoveanu, C.S. (2011). Primary obesity in children: Etiopathogenic, clinical and prophylactic aspects.

Unpublished Doctoral Thesis, Faculty of Medicine, University of Medicine and Pharmacy, Craiova

Coşoveanu, S.; Bulucea, D. (2010) Study on the Relationship Between Lifestyle and Obesity in Kindergarden

and Primary School Children, Acta Medica Marisiensis Vol. 56 Issue 4, p322-324

Dumbrava, L.M. Metabolic syndrome and risk factors screening in overweight and obese children and

adolescents, Unpublished Doctoral Thesis available on www.uoradea.ro, Faculty of Medicine, University of

Medicine and Pharmacy, Oradea

Glavce, C. , Milici, N. Roville-Sausse, F., (2011), Mondialisation du comportement alimentaire et l`obesite, 24-

25, Ciuhuta, M., Baciu, A., Luca, E., chapter "L'accomplissement corporel chez les enfants de III e- IV e classes

de l'ecole no.178 de Bucarest", Spineni, D., Glavce, C., David-Rus R., Manuc, D.,Roville-Sausse, F. chapter

"Understanding obesity in romanian children and adolescents: steps to an anthropological perspective":, ISBN:

973-27-2133-9

Kozma,A., Glavce,C., Balaceanu Stolnici, C., (2012), Anthropology and culture, Glavce, C., Radu, E. Sima, A.

Milici, N., Ionescu-Targoviste, C., Iancu, E., Kozma, A., chapter: Anthropological aspects of obesity among adult

population in Romania: 190, ISBN 978-973-748-674-5

Ministry of Health, Romania, Institute for Mother and Child Care Alfred Rusescu, Bucharest, Romania, Center

for Disease Control, Georgia, USA, UNICEF Romania National Nutrition Study of Chidlren under 5 years old -

Final report 1993,

http://www.uoradea.ro/

https://www.librariaeminescu.ro/ro/autori/Cristiana-Susana-Glavce.html

https://www.librariaeminescu.ro/ro/autori/Nicoleta-Milici.html

https://www.librariaeminescu.ro/ro/autori/Francoise-Roville-Sausse.html


Mihalache, L. (2010) “Obesity in a rural community from Iasi county” Unpublished Doctoral Thesis available on

www.umfiasi.ro , Faculty of Medicine, University of Medicine and Pharmacy, Iasi

Mocanu, V. (2013). “Prevalence of Overweight and Obesity in Urban Elementary School Children in

Northeastern Romania: Its Relationship with Socioeconomic Status and Associated Dietary and Lifestyle

Factors.” Hindawi Publishing Corporation BioMed Research International, ArticleID537451,

http://dx.doi.org/10.1155/2013/537451.

Morea, M., & Miu, N. (2013). “Metabolic syndrome in children.” Human & Veterinary Medicine5(3): 103-108.

Morea, M., Miu, N., Morea, V. F., & Cornean, R. (2013). Maternal obesity-a risk factor for metabolic syndrome

in children. Clujul Medical, 86(3), 259.

Nanu, M.I., Stativă, E., Moldovanu, F., Stoicescu, S., & Novak, C. (2011). “Chapter 4: Growth and

Development.” Evaluation of interventions’ efficiency of the national programs regarding nutrition of children

under 2 years. Translated version provided by first author.

Neagu, A. (2015). Body image dimensions among romanian adolescents. 52. 41-57.

Nicolescu, R., Cucu, A., Branduse, L., Dumitrache, C., Standescu, C.T., Kassai, V., Drost, M. (2013). Nutritional

status assessment in children from primary school by participation in the European Childhood Obesity

Surveillance Initiative (COSI). Bucharest: Romania National Institute of Public Health.

Olaya, B., Moneta, M. V., Pez, O., Bitfoi, A., Carta, M. G., Eke, C., ... & Mihova, Z. (2015). Country-level and

individual correlates of overweight and obesity among primary school children: a cross-sectional study in

seven European countries. BMC Public Health, 15(1), 475.

Preda, M.P. (2011) “Metabolic syndrome in childhood obesity”, Unpublished Doctoral Thesis available on

www.umfiasi.ro , Faculty of Medicine, University of Medicine and Pharmacy, Iasi

Radu E, Ciotaru L.O, Macovei A. (2007). Retrospection upon anthropological research of obesity in Romania.

Proc Roman Acad Series B1 9:45–50

Roman, G., Bala, C., Creteanu, G., Graur, M., Morosanu, M., Amorin, P., ... & Cadariu, A. A. (2015). Obesity and

health-related lifestyle factors in the general population in Romania: a cross sectional study. Acta

Endocrinologica (1841-0987), 11(1).

SEPHAR II results reported: http://www.romanianjournalcardiology.ro/wp-

content/uploads/2016/01/RRC_art_4-4-22.pdf

Stanescu, A. (coord.), authors: Nanu, R. , Palicari, G., Chauliac, M., Soaita, Constantin, M., National Nutrition

Surveillance Program, Institute of Mother and Child Care "Alfred Rusescu" and UNICEF, 1993-2000,

Stanescu, A., Stativa, E. (coord.), Nanu, M. (coord), authors: Nanu, R., Palicari G., Stativa, E., Vitcu, A. (2006),

Nutritional status of children under 5 years old, ISBN: 973-8411-45-9

Valean, C., Tatar, S., Nanulescu, M., Leucuta, A., & Ichim, G. (2009). Prevalence of obesity and overweight

among school children in Cluj-Napoca. Acta Endo (Buc), 5(2), 213-219.

https://www.saebo.com/stroke-statistics/ (accesed on 08.05.2017)

https://www.hindawi.com/journals/srt/2012/731570/ (accesed on 08.05.2017)

http://chartsbin.com/view/2438 (accesed on 08.05.2017)

https://www.saebo.com/stroke-statistics/

https://www.hindawi.com/journals/srt/2012/731570/

http://chartsbin.com/view/2438


http://actamedicamarisiensis.ro/category/amm-2011-vol-57-no-4/page/2/ (accesed on 08.05.2017)

http://www.insse.ro/cms/en (accesed on July 2016)

http://www.insp.gov.ro (accesed on October 2016)

http://cnsisp.insp.gov.ro (accesed on October 2016)

http://www.cnas.ro (accesed on April 2017)

http://www.ms.ro/ (accesed on October 2016)

http://www.mmuncii.ro

www.bnr.ro

http://www.snmf.ro

http://actamedicamarisiensis.ro/category/amm-2011-vol-57-no-4/page/2/

http://www.insse.ro/cms/en

http://www.insp.gov.ro/

http://cnsisp.insp.gov.ro/

http://www.cnas.ro/

http://www.ms.ro/

http://www.mmuncii.ro/

http://www.bnr.ro/

http://www.snmf.ro/


10. SLOVENIA

10.1 LOCAL CONTEXT

Ministry of Health of the Republic of Slovenia is the responsible authority for nutrition and health

enhancing physical activity policies, according to the Act Regulating the Sanitary Suitability of

Foodstuff, Products and Materials Coming into Contact with Foodstuffs (Slovene Official Gazete No.

52/00, 42/02 in 47/04)7. Nutrition council is defined by the law as the main advisory body for the

Minister of Health. New national strategy on Nutrition and health enhancing physical activity was

adopted for the period 2015 – 25 (“Dober tek, Slovenia”)8, based on the extensive evaluation

recommendations of the previous action plan9.

National health care plan 2016-25 “Together for healthy society” (Resolucija o nacionalnem planu

zdravstvenega varstva 2016–2025 »Skupaj za družbo zdravja« (ReNPZV16–25)10 was adopted based

on Health care and health insurance act in 2016 (currently under revision). Plan is defining Health in

all policies approach as the strategic aproach for work with other sectors. In the preparation and

implementation phasess of the national strategy on Nutrition and health enhancing physical activity

was adopted for the period 2015 – 25 number of different sectors were actively involved, such as

agriculture, forestry and food, education, science and sport, infrastructure and transport, labour,

family, social affairs and equal opportunities, economy, defence, finances. Number of other

stakeholders were also involved, including private sector, such as Chamber of Commerce and

Industry in Slovenia11, Chamber of Craft and Small Businesses in Slovenia12 and Slovene Chamber of

Commerce13, and non governmental organizations, such as Slovene Consumers organization,

Slovene Health Association14 and many others.

National Institute of Public Health as the governmental agency15 supports actions in nutrition and

health enhancing physical activity, with translation arguments and setting priorities participatory

and engaging to the policy level while intensively networking with a number of relevant stakeholders

at the national, regional, local and also international level.

On 22nd May 2017 the EU Semerster recommendations were published, for Slovenia you could find

them at the https://ec.europa.eu/info/sites/info/files/2017-european-semester-country-specific-

recommendations-commission-recommendations_-_slovenia.pdf - highlighting majority of the

7 http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO1381 8http://www.mz.gov.si/fileadmin/mz.gov.si/pageuploads/javno_zdravje_2015/resolucija_preh_gib/DTS_brosura__zgibanka_slo_in_angl/brosura_DTS_angl_A4_za_print.pdf 9 http://www.euro.who.int/__data/assets/pdf_file/0012/320520/FNAP-Slovenia-upgraded-2016.pdf?ua=1 10 https://www.uradni-list.si/glasilo-uradni-list-rs/vsebina/2016-01-0999?sop=2016-01-0999 11 https://eng.gzs.si/ 12 http://www.ozs.si/ozseng/Aboutus.aspx 13 http://www.tzslo.si/pic/pdf/broshure_tzslo_en.pdf 14 http://zasrce.si/ 15 http://www.nijz.si/

http://www.uradni-list.si/1/objava.jsp?sop=2000-01-2452



https://ec.europa.eu/info/sites/info/files/2017-european-semester-country-specific-recommendations-commission-recommendations_-_slovenia.pdf

https://ec.europa.eu/info/sites/info/files/2017-european-semester-country-specific-recommendations-commission-recommendations_-_slovenia.pdf

http://www.pisrs.si/Pis.web/pregledPredpisa?id=ZAKO1381

http://www.mz.gov.si/fileadmin/mz.gov.si/pageuploads/javno_zdravje_2015/resolucija_preh_gib/DTS_brosura__zgibanka_slo_in_angl/brosura_DTS_angl_A4_za_print.pdf

http://www.mz.gov.si/fileadmin/mz.gov.si/pageuploads/javno_zdravje_2015/resolucija_preh_gib/DTS_brosura__zgibanka_slo_in_angl/brosura_DTS_angl_A4_za_print.pdf

http://www.euro.who.int/__data/assets/pdf_file/0012/320520/FNAP-Slovenia-upgraded-2016.pdf?ua=1

http://www.euro.who.int/__data/assets/pdf_file/0012/320520/FNAP-Slovenia-upgraded-2016.pdf?ua=1

https://www.uradni-list.si/glasilo-uradni-list-rs/vsebina/2016-01-0999?sop=2016-01-0999

http://www.nijz.si/


above mentioned issues, including the financial stability where lowering of the societal costs of

obesity is also important.

10.2 LOCAL EVIDENCE


Fourteen sources on the prevalence of child overweight and obesity were retrieved for Slovenia.

Three are described here. Slovenia is noteworthy in that it has a national monitoring and

surveillance system, SLOfit (http://en.slofit.org/) which has collected data on children’s measured

BMI, triceps skinfold, and a battery of eight motor tests annually since 1987. It covers all of the

population aged 6 to 19 years with sample sizes ranging from about 180,000-190,000 in recent

years. Participation rates are generally a little over 90% of the population. Based on SLOfit data from

201416 (SLOfit database 1989-2015, Laboratory for the Analysis of Somatic and Motor Development,

Faculty of Sport, University of Ljubljana), 26.4% of boys and 22.2% of girls aged 7 to 18 were

classified as overweight or obese. Gender differences became apparent at around age 11 onwards

(with higher prevalence among boys). Prevalence of overweight and obesity peaked among girls at

ages 9-10 (with 26-27% overweight or obese), and among boys at ages 11-12 (with about 30%

overweight or obese), generally decreasing thereafter. Prevalence estimates from Kovac et al.

(2012), also based on SLOfit data from 2011, show similar results to those for 2014.

Among younger children in Slovenia, Sedej et al. (2014) estimated, on the basis of a representative

sample of 5 year-olds, that 17% of boys and a little over 21% of girls were overweight or obese.

Round 2 of the COSI study indicated that overweight and obesity combined ranged from 17% to 26%

in boys aged 6 to 9, and from 18% to 29% in boys aged 6 to 9, with prevalence increasing with age

(Wijnhoven et al., 2014a). The increase of prevalence with age in COSI is consistent with the SLOfit

results. Results for Slovenia for the third round of COSI are not yet published.

Trends

Slovenia’s national monitoring and surveillance system, SLOfit, provides annual data on the BMI of

children aged 7-18 years since 1987. Several papers have been published examining trends on the

basis of the SLOfit data (Kovac et al., 2008, 2012, 2014; Leskosek et al., 2010). For example, Kovac et

al. (2012) examined trends from 1991-2011 on the basis of these data. They found that the

percentage of overweight (IOTF cut-points) increased substantially from 1991 to 2011, from 13.3%

to 19.9% in boys and from 12.0% to 17.2% in girls. Prevalence of obesity also rose even more

dramatically, from 2.7% to 7.5% in boys and from 2.1% to 5.5% in girls. Based on SLOfit data from

2010-201517 (SLOfit database 1989-2015, Laboratory for the Analysis of Somatic and Motor

Development, Faculty of Sport, University of Ljubljana), rates of overweight and obesity (IOTF

criteria) have remained quite stable in recent years with some evidence of a decline in overweight

16 With thanks to Dr Gregor Starc for providing the data.

http://en.slofit.org/


and obesity since around 2010. During these years, between 19.0% and 20.4% of boys aged 7 to 18

were overweight, and between 6.9% and 7.5% were obese. Among girls aged 7 to 18 during these

years, between 16.6% and 17.8% were overweight, and 6.1% to 6.6% were obese.

Sedej et al. (2014) examined trends in prevalence among 5 year-olds in 2001, 2003-2005 and 2009

and found that rates of overweight and obesity were stable among both boys and girls during this

time period.

In summary, recent trends among both children and adolescents suggest a stabilisation in the

prevalence of overweight and obesity in Slovenia, along with some evidence of a slight decrease

since around 2010.


In Slovenia, three papers were retrieved. Two of these examined musculo-skeletal/motor

performance and pulmonary/aerobic function (Leskosek et al., 2007; Matejek et al., 2014). For

example, among 7-18 year-olds, Leskosek et al. (2007) reported that the performance in almost all

the fitness tests administered was substantially hindered (or at least had a negative correlation) with

obesity – regardless of the age or sex of the children. The greatest influence of obesity was found in

tests requiring movement of the whole body. The third study (Mocnik et al., 2015) reported an

association between less compliant arteries and childhood obesity and hypertension.



20171130 Phase 1 (Slovenia) Data Calculations (1).xlsx

20171130 Phase 1 (Slovenia) Data Calculations (2).xlsx

20171130 Phase 1 (Slovenia) Data Collation Workbook.xlsx

20171130 Phase 1 (Slovenia) Data Sources.xlsx


20171130 Phase 2 (Slovenia) Data Documentation (Part 1).xlsx

20171130 Phase 2 (Slovenia) Data Documentation (Part 2).docx


20171130 Phase 5 (Slovenia) Model Outputs Workbook - DISC.xlsm

20171130 Phase 5 (Slovenia) Model Outputs Workbook - UNDISC.xlsm


Table. Phase 1: Slovenia Disease Data Quality Scores

1 2 3 4 5 6

No acceptable

data

Must be

estimated

from other

data1

International

proxy

"Approximate"

data only2

Not

applicable

(non-fatal

disease)

Acceptable

data



ICD code mismatch


Self-reported BMI


Adult diseases


Oesophageal Cancer

Colorectal Cancer C18; C19-C21

Liver Cancer C22 C22 C22

Gallbladder Cancer C23 & C24

Pancreatic cancer


Endometrial cancer C54 C54 C54 C54

Ovarian Cancer


Kidney Cancer C64 & C65


Thyroid cancer

Type 2 Diabetes Not required for the model



calculated from mortality and prevalence


Multiple Sclerosis


Stroke


Hypertension Not required for the model






Calculate prevalence from incidence

Asthma




Gallbladder Disease


same as incidence

Psoriasis


Gout





Chronic Back Pain




same as incidence

Pulmonary Embolus



Childhood diseases


Wheezing disorders not available not available not available not available


Metabolic syndrome not available not available not available not available

Hyperlipidemia not available not available not available not available

Depression zero deaths Prob survival = 1 if zero deaths

Obstructive sleep apnoea zero deaths Prob survival = 1 if zero deaths


High blood pressure Not required for the model


age 15 to 19



age 15 to 19

Asthma age 15 to 19



Musculoskeletal pain age 0 to 19 - chronic back

pain


age 15 to 19 - chronic back pain

10.4 DATA


20171130 Phase 1 (Slovenia) Data Collation Workbook.xlsx




20171130 Phase 3&4 (Slovenia) Initial Model Output Workbook.xlsx


20171130 Phase 5 (Slovenia) Initial Resturctured Model Output Workbook.xlsx

20171130 Phase 5 (Slovenia) Initial Core tables and Graphs Workbook.xlsx

Phase 6: Reporting

20171130 (Slovenia) Final Restructured Model Output Workbook.xlsx

20171130 (Slovenia) Final Combined Model Outputs SAS Dataset.ssd

20171130 (Slovenia) Final Combined Model Outputs Worksheet.xlsx


20171130 (Slovenia) Final Core Tables and Graphs Workbook.xlsx


As a result of the feedback loops include in the workflow; the software was sometimes rerun (this

happened for Slovenia) with corrected inputs. Only the final model outputs from the simulation

software are listed.

Table. Phase 5: Profile of Slovenia children (Preliminary: from Initial model which is under review)

Age Sex BMI at age 18 Number Percentage

Total (0-17) Persons Obese/Overweight 100,562 27.8


Total 362,030 100.0



Total 175,687 100.0



Total 186,343 100.0



Total 129,453 100.0



Total 62,886 5.2



Total 66,567 5.6



Total 120,852 100.0



Total 58,690 100.0



Total 62,162 100.0




Total 111,725 100.0



Total 54,110 100.0



Total 57,614 100.0

SLOVENIAN REFERENCES

Kovac, M., Jurak, G., & Leskosek, B. (2012). "The prevalence of excess weight and obesity in Slovenian children and adolescents from 1991 to 2011." Anthropological Notebooks 18(1): 91-103.

Sedej, K., Kotnik, P., Avbelj Stefanija, M., Groselj, U., Sirca Campa, A., Lusa, L., Battelino, T., & Bratina, N. (2014). "Decreased prevalence of hypercholesterolaemia and stabilisation of obesity trends in 5-year-old children: possible effects of changed public health policies." European Journal of Endocrinology 170(2): 293-300.

Wijnhoven, T. M., van Raaij, J.M., Spinelli, A., Starc, G., Hassapidou, M., Spiroski, I., Rutter, H., Martos, E., Rito, A.I., Hovengen, R., Peréz-Farinós, N., Petrauskiene, A., Eldin, N., Braeckevelt, L., Pudule, I., Kunesova, M., & Breda, J. (2014a). "WHO European Childhood Obesity Surveillance Initiative: Body mass index and level of overweight among 6-9-year-old children from school year 2007/2008 to 2009/2010." BMC Public Health 14.

Leskosek, B., Strel, J., & Kovac, M. (2007). “Differences in physical fitness between normal-weight, overweight and obese children and adolescents.” Kinesiologia Slovenica 13(1): 21-30.

Matejek, C., Planincec, J., Fosnaric, S., & Pisot, R. (2014). “Relations of weight status and physical fitness of children in Slovenia.” Zdrav Var 53: 11-16.

Mocnik, M., Nikolic, S., & Varda, N.M. (2015). “Arterial Compliance Measurement in Overweight and Hypertensive Children.” Indian Journal of Pediatrics DOI 10.1007/s12098-015-1965-2.


11. CHALLENGES AND LESSONS, RECOMMENDATIONS AND

CONCLUSIONS

11.1 CHALLENGES AND LESSONS

JANPA WP4 was a very ambitious project with eight particpating countries and a relatively short

timetable. A more realistic and more structured longer term work programme would have been

useful.

It encountered a number of significance challenges, a number of which only emerged during the

project. These challenges concerned both scientific and organisational issues:

Conceptual challenges

Data demands

Software implementation

Documentation

Organisationally complex

Challenging communications

Inadequately resourced

We outline these in the table below:

Table 11 (a): Challenges encountered

CHALLENGE LESSONS

Conceptual challenges

Lifetime costing studies and closed cohort simulations are relatively new methodologies. They require solutions to conceptual challenges such as:

Summarising risk factor exposures (childhood obesity/overweight) that occur over long period of time

Modelling lifetime BMI trajectories using techniques that incorporate a longitudinal perspective using limited cross-sectional historical data

Data handling protocols that reflect their inherently longitudinal nature

Validation of the model and country findings

A range of statistical issues including the construction of meaningful uncertainty intervals around key metrics

Lesson: A wider properly supported network of researchers to undertake a systematic, longer term approach is needed


Data demands Micro-simulation models dealing with such complex issues as the impact and costs of childhood obesity/overweight require significant data and research inputs:

These challenges were exacerbated by the diversity in the information systems across the eight participating countries

This diversity resulted in significant data imputation and the associated methodological challenges

The challenges were exacerbated by the fact that the gathering and processing of the requisite data was spread across the organisations

Software implementation The JANPA costing model was implemented in a modification of existing UKHF (sub-contractor to IPH IRL) software because of its wide use.

The existing software has been used primarily for another type of model (what we have called “open cohort simulation models”). It is unclear if some of the fundamental components of the existing software can reflect the longitudinal nature of the JANPA costing model (a “closed cohort simulation model”) in countries whose obesity rates change too dramatically during childhood.

The modifications required were more complex than expected

The lead team at IPH IRL found it difficult to validate the modifications because the existing software and modifications were written in closed source proprietary software

Lesson: Implement model in software written in open source code available to other researchers

Documentation Transparency was one of the key Principles of JANPA WP4 and it was fully supported by CHAFEA and participating countries. This was challenging: :

The complex group of participants involved

The fragmentation of tasks across organisations with different cultures and responsibilities

Implementation of the model in closed source software

Lesson: Ensure systematic approach to project documentation with appropriate resources

Organisationally complex

JANPA WP4 involved a complex group of participants:

Seven teams spanning eight different countries

Software implementation sub-contracted to an independent organisation

Organisations operating in different sectors with different cultures and responsibilities

An eighth country (Northern Ireland) included in the Irish arm with additional funding from safefood (www.safefood.eu)

A diverse lead team in IPH IRL whose membership changed considerably during the project particularly during a period of severe staff cuts

Lesson: Greater support for the managing and co-ordinating these different participants

Challenging communications

Communicating across such a diverse group of participants was challenging:

Discussion of different types of simulation models requires appropriate technical language and terminology. The terms “open” and “closed” cohort simulation models were introduced to help resolve this issue.

Several tasks were challenging without the possibility for direct

http://www.safefood.eu/


communication with the sub-contractor’s software developers. These included:

o Modification of exiting software o Interpreting model outputs and identifying issues during the Post-

Simulation Review phase o Communicating to the sub-contractor the data and software

issues identified during those reviews o Negotiating changes to the implementation software to deal with

these issues These communication challenges were exacerbated when the lead team at IPH IRL experienced severe staff cuts Lesson: Avoid such fragmentation of the project tasks, pay closer attention to communication, and ensure clear communication between software developers and data analytical staff

Inadequately resourced

For such an ambitious project, human and financial resources and flexibility to adjust to changing circumstances and emerging challenges were always going to be critical.

In hindsight, the initial budgets for the lead team, participating countries and software sub-contract were inadequate

During the project, the scope of the sub-contract was significantly reduced to contain costs. To achieve this, the lead team at IPH IRL 1) took greater responsibility for data processing; 2) reduced the details that were provided in model outputs; and 3) took responsibility for reporting the results of simulations. These changes required protracted negotiation and significant unexpected work for the lead team at IPH IRL.

At a very critical stage of the project, the lead team in IPH IRL experienced severe staff cuts which meant work had to be done by a larger number of less experienced people unfamiliar with the project working on a short term basis

These resource issues, across the participants, led to inevitable delays. Lesson: A dedicated, more realistic budget managed within a larger well-resourced experienced modelling unit is needed

11.2 RECOMMENDATIONS

Recommendations about the modelling methodology and data and research requirements are

included in Deliverable D4.6.

With regard to the future development of the JANPA costing model we recommend sharing the

model with the OECD so that its managment and development can be incorporated in their ongoing

project to improve on the modelling capacity on the economics of prevention / public health.

This would include:


Conducting an independent scientific review of the JANPA costing model and how it was

developed

Developing stand-alone dedicated software, written in open source code, to fully implement

the model and making it available for use by all researchers

Conducting a detailed sensitivity audit and validation of the JANPA costing model once the

open source code is available

Deploying the JANPA costing model in all European countries for which good-quality data

are available for the next two years (2018-2019) with a dedicated European budget. This

would include the six countries for which data has already been collated (Croatia, Greece,

Italy, Portugal, Romania and Slovenia)

Organising a high-level European conference in 2020, for example at the European

Parliament, to draw comprehensive conclusions based on these estimates.

The JANPA costing model should be refined by incorporating research into the psychosocial

impacts of childhood obesity and their implications for human capital and the economy”.

Exploring the extension of the JANPA (childhood obesity/overweight) costing model to other

childhood risk factors that have significant short term and long term consequences that are,

in part, mediated through a similar adult risk factor. Early uptake of smoking and alcohol are

two examples.

11.3 CONCLUSIONS

JANPA WP4 was a very ambitious project. It is the first lifetime costing study of childhood

obesity/overweight that developed and applied standard modelling methodology in more than one

country. JANPA WP4 had eight participating countries.

JANPA WP4 encountered significant challenges but nevertheless established that reliable estimates

of the lifetime impacts and costs of childhood obesity/overweight could be obtained in more than

one country (see Deliverable D4.6). These estimates highlight the staggering human impact and

financial costs of childhood obesity/overweight and the substantial savings that could follow from a

modest change in mean childhood BMI.

The recommendations, incorporating the lessons learnt, plot a practical way of dealing with these

challenges. If implemented, then other valuable data that have been collated in all participating

countries during JANPA WP4 can be converted into reliable and meaningful estimates in those

countries as well as other EU countries.

Finally, the JANPA costing methodology is applicable to other childhood risk factors that,like

childhood obesity/overweight, have significant short term and long term consequences that are, in

part, mediated through a similar adult risk factor (like adult obesity/overweight). In particular,

the early uptake of alcohol consumption or smoking has several conceptual similarities with

childhood obesity.

the lifetime impacts and costs of childhood … d4.7_final.pdf · dr. benedetta contoli, dr. maria...

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