objectives · 2016. 9. 27. · objectives 1 prevalence of household & individual...

Objectives

1

Prevalence of household & individual non-communicable disease (NCD) risk factors and outcomes in rural populations

Feasibility of community-based interviews, point-of-care diagnostics and electronic data capture

Evaluate clustering of NCD’s in households, effects of NCD’s on expenditures, HH members & health care decision-making

Matlab (n=1143) Carambolim (n=1212) Sirudhavur (n=940)

Men Women Men Women Men Women

Age, yrs (SD)

30.5 (22.0)

30.0 (19.2)

29.0 (18.4)

33.6(19.0)

28.2 (17.1)

30.5 (18.1)

EducationIlliterate 48 47 17 34 20 35Primary school 23 18 38 35 18 18Secondary school 30 35 34 28 15 41

OccupationAt home, unemployed, student

46.4 96.9 50.4 71.5 41.4 61.0

Unskilled manual, farming

16.7 1.2 28.2 21 39.3 32.8

Skilled manual 16.7 0.3 8.5 1.3 6.3 2.3

Semi-/Professional 19.6 1.4 12.2 5.6 6.7 2.3

Cigarettes/Beedi 46 0 15 6 33 0.3Tobacco 13 31 14 11 28 28Alcohol n/a n/a 30 0.2 75 1.4

Results

Matlab (n=1143) Carambolim (n=1212) Sirudhavur (n=940)

Men Women Men Women Men Women

High fasting glucose(Glucose > 126 mg/dl) - - 10.0 8.0 7.0 4.9

Hypertension(SBP>140 or DBP>90 mmHg or BP meds)

9.5 10.4 23.6 18.3 15.2 8.8

Body Mass Index23+ kg/m2 21 33 27 40 27 3225+ kg/m2 10 18 15 25 16 21

DepressionAny (PHQ>5) 11 20 9 22 37 61

Disability (WHO-DAS II> 5) 9 29 6 19 35 64

Airflow obstruction(Obs. Vs.pred < 0.7) 6.4 2.7 5.1 3.7 10.1 12.3

Results

Lung function data

◊ Spirometry –5 blows (FEV1, FVC, Predicted)

◊ Exclusion criteria:- Surgeries in past 3 months (eg, eye, heart)- Heart attack in past 3 mos, suffers from heart ailment- Pulse > 120 beats/min- Blood pressure greater than 180 (SBP)/ 100 (DBP)- Epilepsy, Pregnant, breast feeding

◊ Re-schedule if:- Respiratory infection, bronchodilators, smoking

◊ Comments – position, unable to complete, unable to understand, refused to cooperate, etc.

Spirometry

“A method for assessing lung function by measuring the volume of air a patient can expel from the lungs after a maximal inspiration”

It is then compared with predicted normal values based on age, height, ethnicity, gender to gauge airway obstruction

◊ Uses of Spirometry:- Gold standard (other clinical-based measures)- Variations in technical abilities, interpretations- Used to distinguish asthma vs. COPD- Management of respiratory disease- Epilepsy, Pregnant, breast feeding

Airway obstruction◊ Spirometry data:

– FVC : Forced Vital Capacity – total volume of air patient can forcibly exhale in one breath (litres)

- FEV1: Forced Expiratory Volume in 1 second- volume of air patient can exhale in the 1st second of exhalation (litres)

- FEV1/FVC: Ratio expressed as a fraction

◊ Interpreting the data:- Normal FEV1/FVC: 0.7-0.8- Airway obstruction < 0.7 (COPD post-bronchodilator)- Caution with 70+ years (overdx; 0.65 threshold OK)- Flow-volume measurement: traces flow rate against

rate of air exhaled to produce a flow-volume curve

Spirometry curve

* GOLD: 3 blows that are consistent and within 5% of each other is ideal•Normal: Volume-time curve rises rapidly & smoothly & plateaus within 3-4 seconds

Flow-vol curves

Concluding points

◊ Comparison with national/other data- Similarities: tobacco use, hypertension, depression- Differences: alcohol abuse- First time: physical activity, disability

◊ Gender differences- Health awareness- Tobacco & alcohol use- Depression

◊ Potential –Intra-/inter-household NCD pathways & effects

◊ Challenges – Recruitment to clinics, male migrants, blood donation, spirometry in women

Report from working group #3

13

Multi-centre Household Chronic Disease Risk Factor (CDRF) Study

Preet Dhillon, Dilip JhaDewan Alam, Amit Dias, Joseph Williams

Shah Ebrahim

Project period: Jan. 2011-Jan. 2013

Funded by the Wellcome Trust, UK

Methods

14

◊ Design: Cross-sectional, community-based

◊ Sample size:250 households x 3 partner sites 3000 total

◊ Study population: AdultsChildren 2+ years

◊ Locations: Matlab, BangladeshCarambolim, GoaSirudhavur, Chennai

Data collection

◊ Household-level data- Cooking fuel exposure- Salt, sugar, oil- Household expenditures, insurance

◊ Individual-level data

Questionnaires:- Tobacco, alcohol, physical activity, diet, medicine- Disabilities, pain, falls, urinary- Mental health, neighbourhood, networks

Physical Measurements:- Anthropometrics, body fat- Lung function, visual acuity, grip strength- Blood pressure, fasting glucose, 24-hr urine

Scientific questions

• What is the effect of indoor exposure to biomass fuel on respiratory (e.g. lung function) and on cognitive outcomes (e.g. depression score)? (exposure-response)

• What is the causal effect of installing electricity and natural gas as both primary and secondary sources of fuel on health outcomes? (causal effect of an intervention)

Exposure to biomass fuel◊ Household-level questionnaire

2.1 Does the house have electricity? 1=No, 2=Yes

2.2 Fuel for cooking

1=Kerosene 5=Wood 9=Animal Dung/cake 2=Charcoal 6=Agriculture/crop 10=Shrub/Grass 3=Coal 7=Gobar Gas/bio gas 11=Other 4=Gas 8=Electricity 12=None

Primary Fuel

Secondary Fuel

2.3 Where is the cooking for the household done?

1=Inside the house 2=Inside the house in a separate kitchen 3=Outside the house 4=Both inside and outside

2.4 Does the inside cooking area have the following? 1=No 2=Yes, 3=Not Applicable

Window Chimney Exhaust

2.5 On average, how many months per year do you cook inside? (0-12 months, 99=unknown)

Primary Fuel

Secondary Fuel

2.6 On average, how many months per year do you cook outside?

(0-12 months, 99=unknown)

Primary Fuel

Secondary Fuel

Overview

• How do we define exposure to biomass fuel from the questionnaire ?

1. Howard and Lindsay exposure index

2. Ashis and Neeraj exposure index

• Visualizing exposure (Hemangi)

• Considerations about the pulmonary outcomes (Roopa and Kapil)

• Estimating the association between exposure index and health outcomes using a regression model (Lindsay and Howard)

• Estimating the causal effects of using clean sources of fuel for indoor cooking on health outcomes (Francesca)

Almost 20% households do not have access to electricity

Hemangi(graphical representation of the exposure distribution)

Type of cooking fuel

Wood is used by more than 50% households for primary and nearly 20% households for secondary

cooking.

More than 80% households do their cooking inside the house either totally or

partially.

Kitchen Facilities

More than 20%

households do

not have any

ventilation facility.

Less than 10%

households have

sophisticated

facilities like

Chimney and

Exhaust fan.

Inside cooking

More than 35% households do theirprimary cooking and more than 15%households do their secondary cookinginside the house through out the year.

Outside cooking

Type of fuel Vs BP

Ashis and Neeraj Exposure Index

Exposure Indices•Separately for Adult M/F and Child M/F with corresponding weights / discounting factors relative to Adult Female

•Indoor Exposure = [{# months per year (py) cooking}*{# months py primary unclean cooking(A)} + {# months py secondary unclean cooking(B)}*] *(#years cooking)

•* Discount factor for windows*Discount factor for outdoor cooking with unclean fuel

•(A) and (B) to be obtained thru weights computed from time spent within a month for the corresponding activity.

Outcome analysis (Roopa and Kapil)

• Depression

• Lung function

Lung function (N=1459)

• Forced vital capacity in liters

• Forced expiratory volume (1st second) in liters

Up to five

measures

FVC (Liters) FEV1/FVC ( %)

Mean (SD)

Range Mean (SD)

Range

Children(n=301)

2.0 (0.9) 0.6 -7.2

88.83 ( 9.4)

48.5-125.4

Adult –men (n=554)

3.6 (1.3) 0.8-8.9 84.5 (10.6)

38.2 -149.3

Adult-women (n= 604)

2.3 (0.8) 0.7-8.1 85.6 (9.8) 39.0 –108.8

Depression (N=2772, only adults)

• Patient Health Questionnaire -9 data 0

.1.2

.3

Den

sity

0 10 20 30 40 50phqsumm

Depression and gender

Depression Men Women Total

NO 81.8 68.7 74.6Mild 13.6 21.8 18.2

Moderate 3.5 6.5 5.2

Severe 1.1 2.9 2.1

Howard and LindsayExposure Score: Conceptualization

Primary Fuel Score

x2

Secondary Fuel Score

Total Fuel

Score

Exposure Index: Some Issues

• Missing data on number of months spent cooking outside or inside for primary and secondary fuel sources – for 1/3 site

– Could not calculate proportion of time spent cooking inside for those participants that cook inside

• Measures are at the household level

– Assumptions required to assign exposure to individuals (women, men, and children)

Primary Fuel ScoreScore

Fuel Source

Location of Cooking Ventilation: window,chimney, or exhaust

Total Count

0 Clean N/A N/A 1413

1 Unclean Outside N/A 706

2 Unclean Sometimes outside or inside butin separate room

2 or 3 25


1 590


None 345

5 Unclean Inside 2 or 3 33

6 Unclean Inside 1 515

7 Unclean Inside None 69

NA 24

Primary Fuel Score

Secondary & Total Fuel ScoreSecondary Total

Francesca• This is a cross sectional study of approx 3000 households in 3

locations in rural areas of India (slides with her description of the data sets are attached)

• The exposure (indoor exposure to biomass) is at the household level (and categorical), but the individual level outcomes and risk factors more than 100) are at the individual level

• The key slide is #9 where are summarized the key questions regarding the exposure to biomass. From this slide we need to define the “intervention variable” as “clean" versus "non clean" cooking.

Francesca• We define “clean" cooking if a household uses "gas

or electricity" as a primary AND as secondary OR "gas and electricity" as a primary and non secondary source. We define “no clean” cooking all the other options.

• We could estimate the causal effect of the intervention of “clean" cooking on several outcomes, some are continuous (pulmonary functions) and some are categorial (depression score). We could do a matched analyses, propensity scores, or anything else you like!

Saanvi1.She is 492.She lives in Sangath3.She is cooking indoor4.High intake of sugar5.Her husband smoke6.No physical activity7.3 children8.She has hypertension (outcome)9.She does only indoor cooking with woods (exposure)

Question: what would have been Saanvi’s health outcome, if she had a gas stove? (counterfactual)

•Obviously we would never know, but we can estimate the counterfactual by taking the outcome for the women that are as similar as possible to Saanvi in terms of all the measured confounders but that they use ONLY clean sources of indoor cooking (indoor and gas)

objectives · 2016. 9. 27. · objectives 1 prevalence of household & individual...

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