Development of the obesity epidemic in England

David Boniface

Health Behaviour Research Centre

Epidemiology and Public HealthUniversity College London

e-mail: d.boniface@ucl.ac.uk

Talk Programme

• Description of the obesity epidemic.

• Effects of environment, lifestyle and ageing.

• Extrapolating current obesity trends.

• Issues and limitations.

Obesity Epidemic References• Development of the epidemic:

– Breslow L. Public health aspects of weight control. Am J Public Health 1952;42: 1116-20.

– Rosenbaum S. 100 years of heights and weights. J R Statist Soc A 1988;151: 276-309.

– Harlan WR et al. Secular Trends in body mass in the United States, 1960-1980. Am J Epidemiol 1988;128: 1065-74.

– Flegal KM, et al. Prevalence and trends in obesity among US adults, 1999-2000. JAMA. 2002; 288:1723-7.

Data Sources (cross-sectional)

• National Heights and Weights Survey, 1980

• Health and Lifestyle Survey, 1984/85

• Diet and Nutritional Survey of British Adults, 1987

• Health Survey for England 1991-2006 (annual)

Heights & Weights

Health & Lifestyle

DNSBA

Health Survey for England

Health Survey for England

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ple

size

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1980 1984 1988 1992 1996 2000 2004 2008year

Surveys in England: sample sizes for BMI, ages 18-64

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20 30 40 50 60age at interview

Distribution of age over 19 surveys

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1980 1985 1990 1995 2000 2005survey year

adjusted unadjusted

- adjusted and unadjustedMen (18-64): mean age by survey year

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%

1980 1985 1990 1995 2000 2005year

obesity_rate_raw obesity_rate_adj

Men: obesity rates, raw and age-adjusted

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25

ob

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%

1980 1985 1990 1995 2000 2005year

obesity_rate_raw obesity_rate_adj

Women: obesity rates, raw and age-adjusted

Change of shape of the BMI distribution

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10 20 30 40 50 10 20 30 40 50

1980 2006

perc

ents

BMI

Distributions of BMI (males 18-64)

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10 20 30 40 50 10 20 30 40 50

1980 2006

perc

ents

BMI

Distributions of BMI (females 18-64)

Changes in percentiles (Tukey mean-difference plot)

• Differences between the 1980 and 2006 values of each percentile are plotted against the mean of the 1980 and 2006 values

• Graph shows these percentiles:

2.5 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 95 97.5.

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15 20 25 30 35 40means of centiles (2.5%, 5%, 10%, 20%, ...)

95% Upper L diffs95% Lower L

Women, 25-34yMean-difference plot 1980-2006, BMI centiles

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20 25 30 35means of percentiles (5%, 10%, 20% ...)

18-24 25-3435-44 45-5455-64

Men: BMI mean-difference plot 1980-2006, by age

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tile

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20 25 30 35means of percentiles (5%, 10%, 20% ...)

18-24 25-3435-44 45-5455-64

Women: BMI mean-difference plot 1980-2006, by age

Interpretation of Tukey mean-difference plots

• Greater increases in BMI for higher vs lower percentiles

• Females: greater increases than males in the higher percentiles, especially in younger age groups

• Males: increases in lower percentiles for older men.

Obesity epidemic - contributions of environment, lifestyle and ageing

Pseudo-cohorts

• take a sequence of cross sectional surveys some years apart.

• in each survey identify participants whose ages match those of a hypothetical cohort repeatedly observed as it ages.

Compare real- with pseudo-cohorts

• A real longitudinal cohort study provides rich information about growth patterns

• A pseudo-longitudinal study can draw repeatedly on the same range of ages.

• A group of parallel pseudo-cohorts can help separate ageing and environmental effects.

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1980 1984-87 1991-92 1993-97 1998-2002 2003-06Cohort Age in 2005

43-45 46-48

49-51 52-5455-57 58-6061-64

Males 18-64: mean BMI: parallel pseudo-cohorts.

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16-24 25-34 35-44 45-54 55-64Survey groups

1980 1984-871991-92 1993-971998-2002 2003-06

Males 18-64: BMI age trends.

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1980 1984-87 1991-92 1993-97 1998-2002 2003-06Age groups

18-24 25-3435-44 45-5455-64

Males 18-64: BMI environmental or secular trends.

Linear annual increases in BMIMALES COEFFICIENT 95% C.I. Due to

age (adj) 0.079 (0.076 to 0.081) ageing

survey year(adj) 0.108 (0.103 to 0.113) environ.

survey year

(adj for cohort)

0.177

(expct. 0.187)

(0.170 to 0.184) cohort

FEMALES

age (adj) 0.088 (0.085 to 0.091) ageing

survey year(adj) 0.114 (0.108 to 0.120) environ.

survey year

(adj for cohort)

0.199

(expct. 0.202)

(0.191 to 0.208) cohort

Obesity epidemic - contributions of environment, lifestyle and ageing

• Pseudo-cohorts can reproduce the development of adiposity throughout lifetimes

• Ageing and environmental effects are confounded within but not between cohorts.

• BMI increase can be decomposed into ageing and environmental contributions.

Concluding remarks on historical development of the BMI distribution 1. Significant environment based increases

in BMI started after 1987.

2. Male ageing effect mainly in 18-44y but females show increases 18-64y.

3. Environment effect > ageing effect.

4. Pseudo-cohorts BMI increase, total rate = environment + ageing.

Obesity rates and the future

Attention is on future of obesity rates as BMI 30+ is the threshold for clinical consequences.

Overweight and Obesity Prevalence (ages 18-64)

BMI 25 to 29 = overweight: BMI 30+ = obese:

Base n % overwt % obese

1980 men

women

3,683

4,007

36.5

25.4

6.4

9.2

1993 men

women

5,772

6,176

44.4

30.3

13.6

16.3

2006 men

women

4,151

4,958

43.7

31.1

23.5

23.1

[age standardised to 2001]

Alternative models for growth in obesity rates

• The government’s Foresight project predicted very high obesity rates for England for 2050 using a tanh model and HSE data from 1993-2004.

• How does this compare with using 1980-2006 data and different models?

“tanh - A simple and convenient set of slowly varying, monotonic functions that are asymptotic to 0 and 1 are provided by the set:”

)tanh(1)( 21 btatp

Foresight (McPherson K. et al (2007))

Probability of males aged 21–60 belonging to a specific BMI group in a given year [95% C.I.]

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-.5 -.3 -.1 .1 .3 .5 .7 .9 1.1 1.3x

0.5*(1 + tanh(x)) section used in Foresight - obese % males

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0.5*(1 + tanh(x)) between -2 and +2

Probability of females aged 21–60 belonging to a specific BMI group in a given year [95% C.I.]

NatCen PredictionZaninotto P, Wardle H, Stamatakis E. et al. 2006.

Forecasting Obesity to 2010. Report prepared for UK Department of Health. www.dh.gov.uk/en/

This report was by NatCen – who carry out the Health Survey for England. It used HSE 1993-2003.

Predictions for obesity rates 2003 2010 were:

Men (16-74) 21.3% 29.4%

Women (16-74) 21.7% 26.3%

Zaninotto et al, 2006

• “Two curves, …. power and exponential, were selected as being plausible models for the data that would allow for either acceleration or slowing down in changes in prevalence of obesity”

• “The choice between the two curves was made on the basis of the curve that ‘best fits’ the data”

• Power curve: Y = b0*(t**b1)• Logistic curve: Y = 1/{(1/u) + (b0*(b1**t))}

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y3

0 .5 1 1.5 2x

power curve 1*(x**0.09) between -2 and +2

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logistic Gompertzgeneralised logistic

Compare Three Logistic Curves

Prediction using Gompertz curve and 1980-2006 data

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1980 1985 1990 1995 2000 2005 2010year

pred_obese_1 (mean) obeseupper

obesity rates (Gompertz curve) - males 18-64

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1980 1985 1990 1995 2000 2005 2010year

pred_obese_1 (mean) obeseupper

obesity rates (Gompertz curve) - females 18-64

Predictions to 2010

model

Data used

Male

Obese % 2010

95% C.I.

tanh (Foresight)

(2 parameters)

1993-03

(21-60y)

31.3 (30.0 – 32.7)

NATCEN 1993-03

(16-74y)

29.4

Gompertz 1980-06

(18-64y)

25.5 (24.3 – 26.8)

Predictions to 2050

model

Data used

Male

Obese % 2050

95% C.I.

tanh (Foresight)

(2 parameters)

1993-03

(21-60y)

60.0 (55.0 – 65.0)

tanh

(3 parameters)

1980-05

(21-60y)

31.5 (19.7 – 43.3)

Gompertz 1980-05

(18-64y)

33.0 (23.1 – 43.3)

Modelling Issues

Obtaining a predicted distribution of BMI rather than just a mean or % obese

Taking account of predicted changes in population age distribution

Choice of shape of fitted curve

Conclusions

Conclusions (pseudo-cohorts)

A group of parallel pseudo-cohorts is advantageous in separating ageing and environmental effects.

Conclusions (BMI trends)

• Pseudo-cohorts showed BMI in men and women increasing as they aged by around 0.20 BMI points p.a.

• Environment-based change was the largest contributor at around 0.11 p.a.

• Ageing added around 0.08 p.a.

Conclusions (start of the epidemic)

• The main environment-based increases appear after 1987

Conclusions (BMI distribution shape change)

There has been a marked change in the BMI distribution:

– Higher percentiles have increased more than lower percentiles.

– Especially true in women, where younger women have shown the largest increases.

– Suggests faster than expected increase in prevalence of very obese (BMI 40+)

Conclusions (predicting the future)

Predicting the future is important and there should be a debate about the methods.