portion size and weight control: insights from new

Portion size and weight control:Insights from new research and implications for policy and practice

Professor Susan Jebb

Nuffield Department of Primary Care Health Sciences

University of Oxford

Increases in portion sizes in US and UK

Changing tableware

Systematic review: methods

• Randomised controlled trials comparing effects on energy intake of selection and consumption of different sizes of:

- portions - packages

- items of tableware used

Hollands et al. Cochrane Database of Systematic Reviews 2015

Methods: Searches

• 11 electronic databases plus citation searching, trials registers and key websites

• Dual screening of 51,288 unique title and abstract records then 182 full-text reports. 72 studies met eligibility criteria and were included in analysis (with a further 11 identified in updated searches but awaiting full integration)

• Study data extracted and risk of potential bias systematically assessed

Results

• IF sustained reductions in exposure to large sizes could be achieved across the whole diet, this could reduce average daily energy consumed from food by up to 16% among UK adults (equivalent of 279 kcals per day) or up to 29% among US adults (527 kcals per day)

• No evidence that size of effect varied substantively between men and women, BMI or tendency to control eating behaviour.

Intervention Outcome Comparisons Effect

Larger size vs

smaller size

Consumption 92 from 61

studies (6711 participants)

Small to moderate increase

SMD: 0.37 (95% CI: 0.29 to 0.45) –

Moderate quality evidence

x% increase in size equates to x% increase in energy intake

Portion size effect is maintained over 2 days …

Rolls et al. (2006) JADA, 106(4): 543-549

… and onto 11 days

Rolls et al. (2007)Obesity, 15(6), 1535-1543

Portion size and energy intake

• Larger packets encourage selection of greater quantities of food (Wansink, J Marketing; 1996:60, 1-14)

• Larger portion sizes increase energy intake of that food (Rolls et al. JADA; 2006: 106, 543-549)

• Additional food does not increase sense of fullness (Rolls et al AJCN; 2002: 76, 1207-1213)

• Energy compensation at the next course, or subsequent meal is incomplete (Rolls et al. Appetite, 2004: 42, 63-69)

• Portion size effect is maintained, even if taste is poor (Wansink and Kim J Nutr Educ Behav, 2005: 37, 242-245)

Smaller and larger sizes both ≥ 100% reference portion size: 81% (n=34).

Smaller size < 100% reference portion size and larger size > 100% reference portion size: 14% (n=6).

Smaller size < 100% reference portion size and Larger size = 100% reference portion size: 5% (n=2).

Reference portion size (100%)

Most studies have addressed the effects of larger (than reference) portion size

What happens to eating habits when portion sizes shrink?

?

Immediate calorie savings

Grande filter coffee with semi skimmed milk = 188 kcals

Short filter coffee with semi skimmed milk = 95 kcals

Saving = 93 kcals

MacDonald BigMac burger = 540 kcals

MacDonald cheese burger = 300 kcals

Saving = 240 kcals

Large Jamie Oliver carbonara penne = 930 kcals

Small Jamie Oliver carbonara penne = 465 kcals

Saving = 465 kcals

.Prentice and Jebb

Nutr Rev. 2004 Jul;62(7 Pt 2):S98-104

Energy excess

Energy Balance

Energy deficit

Weaksatiety signals

Energy-dense dietsInactivity

Efficienthunger signals

Low-energy diets Exercise

Asymmetry of appetite control

A covert, randomised crossover study to test impact of smaller portions

Day prior to study day: overnight fast from 9pm

B – Portion size reduced by 20%

A – Regular portion size

Minutes 0

C – Portion size reduced by 40%

60 120 240 300 360

Food intake– Lunch and snack – ad libitum eating occasions– Intake over rest of day – weighed diet diaries

Biochemical Measures (n = 20)– PYY, GLP-1 and insulin

Perceived appetite using VAS questionnaires– Appetite and mood ratings taken before and after consumption of meals and at half hourly time points

0 minutes- BreakfastEat in entirety

240 minutes– LunchAd libitum

360 minutes- SnackAd libitum

90 150 21018030

Lewis et al (2015). Obesity 23 (7): 1362-70

Study design

• Participants: 33 overweight and obese men (n = 15) and women (n = 18), mean BMI 29 kg/m2, mean age 43 years

• Differences in energy intakes were compared using mixed models (fixed effect = condition, random effect = person)

• Hormone and perceived appetite profiles were compared using mixed effects model (fixed effects = interaction between condition and time, random effects = person and time)

A

B

C

Lewis, Solis-Trapala and Jebb Obesity Facts, 6(suppl. 1), 139

Lewis et al (2015). Obesity 23 (7): 1362-70

Greater hunger and reduced fullness after smaller breakfast

Mean ± SEMLetter indicates the condition where the mean is

significantly different at that time

Lewis et al (2015). Obesity 23 (7): 1362-70

Reduced postprandial GLP-1 and GIP after smaller breakfast

Mean ± SEMLetter indicates the condition where the mean is

significantly different at that time

GLP-1 GIP

Lewis et al (2015). Obesity 23 (7): 1362-70

No significant differences in ad libitum energy intake at lunch…

Mean ± SEM

Lewis et al (2015). Obesity 23 (7): 1362-70

…or over the remainder of the day

Mean ± SEM

Lewis et al (2015). Obesity 23 (7): 1362-70

AUC as predictor Pre-lunch measure as predictor

Predictor of

lunch EI

Regression

coefficient (SE)

P value Regression

coefficient (SE)

P value

Biochemical measure

GLP-1 0.019 (0.071) 0.790 15.95 (11.17) 0.154

GIP 2.666 (4.446) 0.549 39.08 (33.06) 0.237

Glucose -0.916 (0.710) 0.197 -365.5 (245.8) 0.137

Insulin -197.0 (259.8) 0.448 -157.0 (168.7) 0.352

Do biochemical measures predict energy intake at lunch (fixed effects models)?

Lewis et al (2015). Obesity 23 (7): 1362-70

AUC as predictor Pre-lunch measure as predictor

Predictor of lunch EI Regression coefficient

(SE)

P value Regression coefficient

(SE)

P value

Appetite rating

Hunger 0.091 (0.022) <0.001 11.96 (3.934) 0.002

Fullness -0.029 (0.017) 0.085 -10.43 (3.389) 0.002

Desire to eat 0.087 (0.018) <0.001 8.788 (3.783) 0.020

Prospective

consumption

0.100 (0.022) <0.001 19.21 (4.384) <0.001

Predictor of whole

day EI

Regression coefficient

(SE)

P value

AUC appetite rating

Hunger 0.057 (0.025) 0.026

Fullness -0.016 (0.021) 0.469

Desire to eat 0.057 (0.023) 0.013

Prospective

consumption

0.068 (0.025) 0.007

Do appetite ratings predict energy intake at lunch and over the whole day (apart from breakfast); fixed effects models

Lewis et al (2015). Obesity 23 (7): 1362-70

Mean (± SEM) energy intake over the whole day according to condition. Dark shading: energy intake at breakfast, medium shading = lunch, light shading + remainder of day

0

2000

4000

6000

8000

10000

12000

A B C

Ener

gy in

take

(kJ

)

Condition

Reducing portions at breakfast leads to day-long reduction in energy intake

Implications for public health strategies

• Covert portion size reduction of 40% was largely unnoticed

• Biological responses were evident in attenuated gastrointestinal hormone and perceived appetite profile.

• Subsequent energy intake was not significantly affected

• Consistency of later intake implies importance of habitual behaviour, at least in a highly controlled laboratory setting

Portion size messages for consumers

Portion size recommendations:

• No specific guidance

• Often include generic statements, such as “choose smaller portions”

• Specific portion sizes often inconsistent

• Lack credibility with consumers

• Perceived as only relevant to “dieters and diabetics”

“watch your portions”

November 11, 2015

Educating families: Me-size meals

What is an appropriate portion?

0

100

200

300

400

500

600

700

800

900

Min

i

Par

ty

Sna

ck

Sta

ndar

dKin

g

Gia

nt

kcal

20%female GDA

Using labelling to indicate appropriate portion size

Lack of consistency in suggested portion sizes

Muesli

• Varied from 45g to 105g

Meat

• Industry = 100g

• NGOs/HCPs = 74g

Fat spreads

• Industry = 10g

• NGOs/HCPs = 5g

Ice cream

• Industry = 2 scoops

• NGOs/HCPs = 1 scoop

Lewis, Ahern and Jebb (2012). Public Health Nutr. 15(11):2110-7.

What do we consider as ‘normal’?

Lewis, et al (2015) Int J Obes 39 (8): 1319-24.

Determining the portion size ‘norm’

Participants

Lean group (n = 30)

BMI = 22.7 (IQR: 21.7-24.3)

Age = 27 (IQR: 24-36)

Obese group (n = 30)

BMI = 32.1 (IQR: 31.2-33.4)

Age = 26 (IQR: 21-33)

0.5

0.7

0.9

1.1

1.3

1.5

1.7

Personal norm Social norm

Po

rtio

n s

ize

ind

ex

Lean

Obese

Obese have larger personal norms than lean

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

Personal norm Social norm

Po

rtio

n s

ize

ind

ex

Low restraint

High restraint

Those with lower restraint had larger personal norms

0.5

0.7

0.9

1.1

1.3

1.5

1.7

Personal norm Social norm

Port

ion

siz

e in

dex

Low liking

High liking

Those with greater liking, had larger personal norms

Lewis, et al (2015) Int J Obes 39 (8): 1319-24.

Norms are larger than suggested portion sizes

Lewis, et al (2015) Int J Obes 39 (8): 1319-24.

Norms are larger than reported portion sizes

Lewis, et al (2015) Int J Obes 39 (8): 1319-24.

Suggested potential actions

• Targeting physical environment:

– (Labelling) Define and indicate appropriate portion size

– (Design) Demarcate portions in packaging through wrapping; Introduce tableware shapes that reduce effects of size

– (Proximity) Place larger sizes less accessibly

– (Size) Make default serving sizes or tableware smaller

– (Availability) Reduce availability of larger size options

• Targeting economic environment:

– (Appeal) Restrict pricing practices whereby larger sizes cost less in relative terms than smaller sizes and so offer more value for money; Restrict promotions on larger-sized packages

Marteau, Hollands, Shemilt, Jebb. BMJ, under review

Fromeducation

To regulation

Through ‘Nudge’

Packaging has a powerful influence on norms

• 27 men (mean age 24.9 y; mean BMI 23.3 kg/m2)

• Portion size error greater when hungry than full (p<0.01)

• Trend towards greater error on larger serving sizes

63 g 427 g 140 g85 g150 g 80 g 520 g488 g

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5

Po

rtio

n e

sti

ma

ted

(fa

ste

d)

Portion served (based on FSA)

Ice-creamCrisps

Hot choc.

Muffin Cornflakes

Choc.bar

Cola

Banana

Brogden & Almiron-Roig (2011) Public Health Nutrition

Reductions in portion size of iconic brands

Need to build public acceptability for some interventions

Portion size negatively correlated with choosing more than one bag (p = 0.003)Portion size positively correlated with consumption per diner (P = 0.001)

Freedman et al. 2010. Obesity 2010 Sep;18(9):1864-6.

Portion size (g/bag) Number of diners choosing

french fries

Mean ± s.d.

Consumption per diner

Mean ± s.d.(g)

88 315 ± 88 74.3 ± 2.2

73 348 ± 62 71.4 ± 2.4

58 359 ± 144 53.0 ± 2.5

44 377 ± 74 52.2 ± 6.0

Smaller portions in a canteen setting decrease intake of French Fries

A 50% decrease in portion size led to a 35% decrease in intake

23,373

24,847

19,027

19,604

Total weight served (g)

How small can you go without triggering compensatory responses?

Portion size: from laboratory to policy

• Larger portions are associated with increased consumption and constitute a risk factor for weight gain

• Smaller portions may help limit overall energy intake

• Consumer awareness of appropriate portion sizes is poor and needs consistent messages to improve understanding, shape social norms and build acceptability of interventions

• Preliminary evidence that environmental changes to decrease portion size can reduce energy intake within a meal

• Pragmatic research studies needed to measure longer-term impact on eating behaviours and body weight in ‘real-world’ settings to inform policy options

With thanks to:

University of Oxford

• Paul Aveyard

• Nerys Astbury

• Jamie Hartmann-Boyce

• Sarah Morrish

• Carmen Piernas

• Sarah Tearne

University of Birmingham

• Amanda Daley

• Kate Jolly

• Claire Madigan ➡ Sydney

• Helen Parretti

MRC Human Nutrition Research, Cambridge

• Amy Ahern

• Eva Almiron-Roig

• Gina Ambrosini ➡ Perth

• David Johns

• Hannah Lewis

• Celia Walker

Other

• Theresa Marteau, Cambridge

• Eric Robinson, Liverpool

• Peter Rogers, Bristol

Thank you for listeningsusan.jebb@phc.ox.ac.uk