childhood obesity in the uk: is fast food a factor? peter dolton (royal holloway college, university...

Childhood Obesity in the UK: Is Fast Food a Factor?

Peter Dolton

(Royal Holloway College, University of London and

Centre for Economic Performance, London School of Economics)

MOTIVATION

Source: Brunello et al Economic Policy (2008)

•Annual Reviews

Motivation• Obesity is 2nd biggest cause of death in the UK

(after smoking).• 23% of men obese and 24% of women [2008]• Wanless report obesity costs - £3.6 billion a

year.[2007]• Obesity rates have risen by 65% for boys and

51% for girls in the last 10 years. [up to 2005]• 10% of kids obese by the time of starting primary

school (17% in deprived areas) [2008]• Fat kids make fat adults.

KEY QUESTIONS

Main Research Questions:

• Can we explain what causes childhood obesity (and why it is rising)?

Main Research Questions:

• Can we explain what causes childhood obesity (and why it is rising)?

• Does Fast Food have a causal impact on childhood obesity (which can be identified)?

Main Research Questions:

• Can we explain what causes childhood obesity (and why it is rising)?

• Does Fast Food have a causal impact on childhood obesity (which can be identified)?

• Does Fast Food Outlet Proximity have a causal impact on Childhood Obesity?

ANSWER

• The answer is NO!!!!! – There is no causal link between fast food proximity and obesity

• Note – this does not mean that I am saying FF if you eat enough of it does not make you fat.

• It merely says that having a FF outlet near does not cause you to be fat.

How Do We Answer the Question?

• To answer this question properly we would need a controlled experiment – with some children exposed randomly to FF and others not.

• We would also need to know exactly what else the children ate to control for variations in eating patterns and calorie intake.

• Such data does not exist.

Currie, Della Vigna, Moretti and Pathania AEJ(P),NBER 2009

• ‘Taken together, the weight of the evidence is consistent with a causal effect of fast-food restaurants on obesity rates among 9th graders…’

• “We find that among 9th grade children, a fast food restaurant within one tenth of a mile from a school is associated with at least a 5.2% increase in obesity rates”.

WRONG!!

• US is ‘full saturated’ with FF and so no control group.

• They only find their effects at .1 of a mile – in the school playground!!!

• Hence I will look at the nearest thing we have to an experiment.

UK Cohort Data

• 1946 NSHD Cohort

On food rationing up to age of 8.

• 1958 NCSD Cohort

“Control cohort”

• 1970 BCS Cohort

“Fast Food Cohort”

0.0

5.1

.15

.2D

ensi

ty

10 15 20 25 30 35Male BMI at 16

NSHD NCDS BCS

Male BMI at age 16 by Cohort

0.0

5.1

.15

Den

sity

10 15 20 25 30 35Female BMI at 16

NSHD NCDS BCS

Female BMI at age 16 by Cohort

Fraction Obese by Cohort at Age 15/16.

Girls Boys

NSHD - 1961 0.06 0.04

NCDS- 1974 0.06 0.05

BCS- 1986 0.09 0.09

WHAT MY RESEARCH DOES

• Takes a cohort of children born in 1970 (BCS 1970) and follows them through to adulthood.

• Merges all their data with information on WHERE and WHEN ALL fast food outlets opened in Britain.

• Estimates the effect of fast food outlet proximity on children’s BMI.

BCS70 DATA

BCS70 Follow-upsBCS70 Follow-ups and sources of information 1970-2000

BBS

(1970) Birth

CHES (1975)

5

CHES (1980)

10 Youthscan

(1986) 16

BCS70 (1996)

26

BCS70 (2000)

30

Mother — Parents — Parents — Parents

School — School

Tests — Tests — Tests

Medical — Medical — Medical — Medical

Subject — Subject — Subject — Subject

16,135a 13,135 14,875 11,628 9,003 11,261

Note: a Achieved Sample – when at least one survey instrument partially completed.

Fast Food Data

• Collected data on all the fast food outlets over 1968-1986 and their year of opening and their exact location.

• Includes:– McDonalds– Wimpy– Burger King– Kentucky Fried Chicken

What counts as Fast Food??

• Use Counter service• Kids can buy it – served at source to eat

immediately, at any time of the day, and take away.

• Fish and Chips was everywhere – so is assume to be a constant background effect – (as is changing supermarket food – like microwave meals)

• Fish and Chips only available at ‘frying times’.

When did they open?0

.1.2

.3D

en

sity

1968 1970 1972 1974 1976 1978 1980 1982 1984 1986Year of Opening of Fast Food Outlet

Source: Author's Calculations

Opening of UK Fast Food Outlets 1968-1986

How can we measure Fast Food Treatment?

• Distance to nearest outlet.

• Number of outlets

• Currie et al (2009) use dummy if there is a FF outlet with .1 of a mile. (Also measure obesity as fraction in class x year who are obese.)

• I use Distance x Years of opening – to give intensity of treatment.

Key Explanatory Variables

• Psychological Problems – ‘Any evidence of any emotional or behavioural problem since 10’ as reported by doctor.

• Physical Handicap – ‘Any evidence of significant illness, developmental problem, defect or handicap’ as reported by doctor.

• Exercise – Participation in any sport 3 times a week or more – self reported.

• High Calorie Diet – Consumes any of: hamburger/beef burger, pudding, butter, chocolate, sweets, ice cream, cake or buns, biscuits, chips, takeaway, white bread more than three times a week – reported by mother.

• Eating Problems – Parental reported eating or appetite problems.

• Screen Hours – Total of TV time, DVD time and computer time in a day.

• Teen Eats Takeaway – Teen eats Takeaway meal as reported by the mother.

Table 4 Determinants of Age 16 BMI for Girls in BCS70. (1) (2) (3) (4) (5) Fast Food Treatment 0.003 -0.005 -0.004 -0.001 -0.005 Intensity (0.005) (0.003) (0.003) (0.004) (0.007) BMI at 10 0.818 0.818 0.824 0.673 (0.028)*** (0.028)*** (0.030)*** (0.050)*** Mother's BMI 0.062 0.063 0.051 0.112 (0.016)*** (0.016)*** (0.017)*** (0.032)*** Asian 0.352 0.315 1.258 (0.736) (0.841) (1.625) European 0.375 0.169 0.861 (0.636) (0.727) (1.518) Psychological -0.251 -0.238 -0.052 Problems (0.335) (0.384) (0.661) Physical Handicap -0.168 -0.177 -0.192 (0.192) (0.209) (0.355) Eating Problems 0.005 0.071 0.113 (0.132) (0.142) (0.247) High Calorie Diet 0.168 0.010 (0.185) (0.320) Exercise 0.341 0.027 (0.323) (0.590) Smoker 0.842 -0.154 (0.928) (1.493) Mother Works -0.118 -0.241 (0.116) (0.198) Inner London -1.173 (0.788) Screen Hours 0.093 (0.046)** Constant 21.539 5.777 5.400 5.770 5.919 (0.071)*** (0.538)*** (0.831)*** (0.932)*** (1.772)*** Observations 2668 2111 2070 1798 694 R-squared 0.00 0.32 0.32 0.31 0.25

Table 5 Determinants of Age 16 BMI for Boys BCS70 (1) (2) (3) (4) (5) Fast Food Treatment 0.003 -0.003 -0.002 -0.004 -0.002 Intensity (0.005) (0.004) (0.004) (0.004) (0.006) BMI at 10 0.812 0.804 0.794 0.754 (0.026)*** (0.027)*** (0.027)*** (0.041)*** Mother's BMI 0.106 0.100 0.108 0.091 (0.015)*** (0.015)*** (0.015)*** (0.023)*** Asian -0.441 -0.750 0.636 (0.720) (0.821) (1.417) European -0.395 -0.860 0.616 (0.586) (0.697) (1.282) Psychological 0.897 1.330 1.698 Problems (0.384)** (0.406)*** (0.760)** Physical Handicap -0.014 0.072 -0.050 (0.216) (0.222) (0.316) Eating Problems 0.016 -0.009 -0.242 (0.136) (0.139) (0.207) High Calorie Diet -0.115 -0.441 (0.201) (0.306) Exercise 0.636 1.173 (0.501) (0.738) Smoker 0.240 -1.906 (1.753) (2.502) Mother Works 0.237 0.176 (0.114)** (0.166) Inner London 3.307 (1.447)** Screen Hours 0.082 (0.046)* Constant 21.539 5.339 5.946 6.227 5.572 (0.071)*** (0.510)*** (0.789)*** (0.881)*** (1.550)*** Observations 2668 2273 2221 1907 914 R-squared 0.00 0.34 0.33 0.36 0.32

Summary of BCS70 Findings @ 16

• NO FAST FOOD EFFECT• Think of average kid with BMI of 20 then 1 unit of

BMI = 5% extra body mass.• Both

– Own BMI at age 10 (1.25 units of BMI @ 10= 1 unit of BMI)

– Mothers BMI (10 units of Mothers BMI = 1 unit of BMI)

– Screen Time (approx 10 hrs per day= 1 unit BMI)

• For Boys only: – Psychological Problems (extra .8-1.6 units of BMI)

– Inner London (up to 3 units of BMI)

– Mother Works (2.5 unit of BMI)

Extra Findings

• Number of Takeaways per week does not correlate with BMI.

• Fizzy drinks alone is significant for boys – 5 drinks a day = 1 BMI

• Urban/Rural location is not significant.

• No Fast food effect at 26.

MAIN Conclusions

• In the UK Fast Food Proximity does not have an impact on childhood BMI/Obesity.

• In so far as it is identifiable – the effect of eating FF is not clear on BMI – we just don’t observe EXACTLY what an individual eats.

• Proximity of FF outlets does have an effect on FF consumption.

Other Findings

• Main factors in BMI at 16 are own BMI at 10, Mothers BMI.

• Exercise has no impact on BMI.• Fizzy drinks do impact on BMI.• Screen Time does impact on BMI.• For boys emotional /behavioural problems are a factor.• Increased FF consumption reduces consumption of Vit C

and fibre and increases consumption of crisps, fizzy drinks and fatty food.

• FF outlet location is not related to where fat people live.

Tentative Implications

• Blaming Fast food outlets may be wrong.• A huge fraction of overweight risk is from your

genes and your family environment.• Onus must be on mothers to control kids diet

(and their own diet) when young.• Fast food outlets don’t have information to locate

where fat people are – but they do cite where poor people in work and ethnic minorities are.

EXTRA SLIDES

Outline of Talk

• Motivation• Literature • Identification and Causality?• Measuring Childhood Obesity• BCS Cohort Data and Fast Food Data &

Fast Food Treatment.• BCS 1970 Results• Conclusions and Policy Implications

David Cameron 2008

“We talk about people being at risk of obesity instead of talking about people who eat too much and take too little exercise – its as if obesity is a purely external event like a plague or bad weather”

Source: Anderson et al NBER paper (2007)

The Literature - Effect

Chou et al (2004) (J of H Econ)– state wide US data find an effect.

Dunn (2008) (mimeo) IV of interstate exits – 10%increase in FF density – gives .33 of BMI

Davis and Carpenter (2009) (Am J of Pub Health) Uses US data from CHKS over the 2002-2005 period.

Currie et al (2009) (AEJ(P), NBER) Use US data from 1999-2007 for Californian kids.

The Literature – No effect

Burdette et al (2004) (Preventive Med) 7,000 Ohio kids.

Simmons et al (2005) (Int J of Obesity) find no relationship in Australia.

Powell (2009) (J of H Econ)– uses US data from NLSY data over teenagers from 1997-2003

Anderson and Matsa (2009) (mimeo) Use adjacent highways as IV and find no effect.

What this paper does that is new:

• (To my knowledge) First study in the UK• Set at a time when fast food outlets were growing

exponentially.• Use distance from home not school.• Know all - not just the closest restaurants.• Know the timing of the opening of the fast food

restaurants - hence can work out a measure of ‘duration intensity of fast food treatment'.

• Uses medically measured height and weight (not self reported)

• Other detailed data – Mothers BMI, Screen time, mothers work etc.

• New identification clarity.

Identification and Causality?

Base ModelCurrie et al (2009), Chou et al (2004), Burdette et al (2004), Powell

(2009)

• BMI – is a measure of obesity

• R is a measure of (EXOG) FF treatment

• X is observable controls

• X* unobservables

*2 2 2 2 (1)BMI R X X

How are R & BMI measured?

• Chou et al (2004), Powell (2009) measure R by number of restaurants at the state level.

• Currie et al (2009) measure R as the proximity of the FF outlets from school and BMI as the % of kids in a class who are ‘fit’.

IV ModelAnderson and Mata (2009) & Dunn(2008)

• Assumption here is that R is endogenous and we need to find IVs, Z for it. Anderson & Matsa use interstate highways and Dunn uses exits.

*1 1 1 1

*2 2 2 2

(2.1)

(2.2)

R X X Z

BMI R X X

Full Model

Here we make a distinction between consumption of FF and Proximity of FF outlets.

T is a measure of Take-away consumption. May be endog – in which case could use FF outlet proximity, R as an IV.

*1 1 1 1

3 1 3

*2 2 2 2

(3.1)

(3.2)

(3.3)

R X X Z

T X R

BMI T X X

Measuring Childhood Obesity

How do we measure BMI?

• BMI – Quetelet Index

2

( )

( )

Weight kBMI

Height m

BMI Classification for Adults

BMI Score Category

< 18.5 Underweight

18.5 - 24.9 Normal Weight

25 - 29.9 Overweight

30 - 39.9 Obese

40 Morbidly Obese

BMI for kids

• Use the LMS tables generated by Pan and Cole for the MRC

• Gives Obese BMIs as:

Age Boys Girls

10 20.27 21.35

16 24.9 25.85

Fraction Obese by Cohort at Age 15/16.

Girls Boys

NSHD - 1961 0.067 0.044

NCDS- 1974 0.064 0.054

BCS- 1986 0.087 0.086

Local Examples

• Norwich– 1978 Wimpy opened (Ipswich had one in 1977!!!)– 1981 McDonalds opened– 8 Fast food outlets by 1981

• Lancaster• 1977 Wimpy opened• 1980 McDonalds opened• 4 Fast food outlets by 1980

Duration Intensity Treatment of Fast Food

• Where Y is years since outlet k opened, and d is distance from individual i. This measures DITFF for less than 5 miles.

5: 5

k

kk d

YDITFF

d

8 year @ 1 mile ==2(1 year @ 4 miles)

Example: Duration Intensity of Fast Food TreatmentAdditive Measure

0.0

2.0

4.0

6.0

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sity

0 20 40 60 80 100Fast Food Intensity

Kernal Density of Total Fast Food Treatment Intensity

Reasons why it is interesting to look at location of kids home and fast food

outlets:

• 1. At least 50% of the days in a year kids dont go to school if we count weekends and holidays and absence. They are only there for 6 hours and all but 1 are in lessons. So only around 2-3% of time can get FF at school.

• 2. Only 2.2% of primary kids age 10 in 1980 ate their midday meal outside school but not in the family home.

• 3. Only 15% of secondary kids age 16 in 1986 ate their midday meal outside school but not in the family home.

Table 6 Determinants of Age 16 BMI for Girls BCS70: Currie et al Specification.

(1) (2) (3) (4) (5) _16BMI _16BMI _16BMI _16BMI _16BMI FF distance <.1 mile -4.630 -0.508 -0.427 -0.231 -0.927 (1.683)*** (1.591) (1.617) (2.000) (3.009) FF distance <.25 mile 1.551 -0.901 -1.033 -1.463 -1.637 (1.002) (0.860) (0.903) (1.084) (1.616) FF distance <.5 mile 0.271 -0.003 0.072 0.175 -0.104 (0.529) (0.449) (0.455) (0.483) (0.729) FF distance <1 mile -0.109 -0.011 -0.049 -0.009 -0.464 (0.259) (0.216) (0.220) (0.235) (0.390) BMI at 10 0.808 0.807 0.810 0.661 (0.027)*** (0.027)*** (0.029)*** (0.049)*** Mother's BMI 0.060 0.062 0.051 0.119 (0.015)*** (0.015)*** (0.017)*** (0.032)*** Asian 0.603 0.808 1.620 (0.703) (0.834) (1.625) European 0.509 0.447 0.738 (0.598) (0.720) (1.508) Psychological -0.100 -0.101 0.137 Problems (0.323) (0.374) (0.637) Physical Handicap -0.103 -0.111 -0.075 (0.189) (0.206) (0.350) Eating Problems 0.010 0.063 0.130 (0.130) (0.140) (0.243) High Calorie Diet 0.217 0.050 (0.181) (0.318) Exercise 0.344 0.009 (0.321) (0.572) Smoker 0.847 -0.193 (0.924) (1.482) Mother Works -0.061 -0.127 (0.114) (0.195) Screen Hours 0.077 (0.045)* Constant 20.945 5.962 5.446 5.675 6.074 (0.066)*** (0.523)*** (0.792)*** (0.913)*** (1.758)*** 2598 2172 2130 1852 710 R-squared 0.00 0.31 0.32 0.31 0.26

Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

Table 7 Determinants of Age 16 BMI for Boys BCS70: Currie et al Specification.

(1) (2) (3) (4) (5) _16BMI _16BMI _16BMI _16BMI _16BMI FF distance <.1 mile 2.087 0.496 0.508 -0.452 0.000 (1.809) (1.643) (1.629) (1.847) (0.000) FF distance <.25 mile -0.522 -0.414 -0.407 -0.296 -0.199 (0.874) (0.731) (0.725) (0.710) (0.991) FF distance <.5 mile -0.426 -0.550 -0.610 -0.116 -0.549 (0.532) (0.462) (0.460) (0.458) (0.669) FF distance <1 mile 0.394 0.183 0.282 -0.112 0.277 (0.263) (0.225) (0.228) (0.227) (0.333) BMI at 10 0.804 0.794 0.787 0.769 (0.026)*** (0.026)*** (0.027)*** (0.040)*** Mother's BMI 0.108 0.104 0.111 0.093 (0.015)*** (0.015)*** (0.015)*** (0.023)*** Asian -0.444 -0.716 0.569 (0.717) (0.821) (1.423) European -0.353 -0.774 0.609 (0.577) (0.691) (1.274) Psychological 0.696 1.013 1.501 Problems (0.368)* (0.386)*** (0.723)** Physical Handicap 0.007 0.089 -0.085 (0.209) (0.216) (0.312) Eating Problems 0.020 -0.020 -0.275 (0.133) (0.137) (0.202) High Calorie Diet -0.098 -0.561 (0.197) (0.298)* Exercise 0.656 1.200 (0.510) (0.734) Smoker 0.204 -1.986 (1.751) (2.484) Mother Works 0.233 0.145 (0.112)** (0.163) Screen Hours 0.082 (0.045)* Constant 21.549 5.423 5.977 6.192 5.308 (0.066)*** (0.499)*** (0.772)*** (0.868)*** (1.531)*** 2752 2353 2299 1978 936 R-squared 0.00 0.34 0.33 0.36 0.34

Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

Full Model

Here we make a distinction between consumption of FF and Proximity of FF outlets.

T is a measure of Take-away consumption. May be endog – in which case could use FF outlet proximity, R as an IV.

*1 1 1 1

3 1 3

*2 2 2 2

(3.1)

(3.2)

(3.3)

R X X Z

T X R

BMI T X X

Eqn (3.2) First Stage IV

Total Girls Boys FF distance <.25 mile 0.070 0.074 0.063 (0.034)** (0.046) (0.053) Fast Food Treatment 0.000 0.000 0.000 (0.000)** (0.000)* (0.000)* Constant 0.067 0.067 0.068 (0.003)*** (0.004)*** (0.004)*** Observations 10324 5145 5179 R-squared 0.02 0.02 0.02

Table 11 Marginal Effects Estimates for Different Fast Food Treatment Intensity Measures. Boys in the BCS70 at 16.

Fast Food Treatment Measure

(1) (2) (3) (4) (5)

Intensity 0.003 -0.003 -0.002 -0.004 -0.002 (0.005) (0.004) (0.004) (0.004) (0.006) Nearest 0.004 -0.009 -0.007 -0.011 -0.019 (0.009) (0.008) (0.008) (0.008) (0.008) School Area 0.002 -0.005 -0.005 -0.009 -0.019 (0.006) (0.006) (0.006) (0.006) (0.010)* Teen Eats Takeaways IV 0.991 -3.359 -2.506 -2.734 -0.104 (4.332) (3.348) (3.156) (2.917) (9.203)

Table 12 Marginal Effects Estimates for Different Fast Food Treatment Intensity Measures. Girls in the BCS70 at 16.

Fast Food Treatment Measure

(1) (2) (3) (4) (5)

Intensity 0.003 -0.005 -0.004 -0.001 -0.005 (0.005) (0.003) (0.003) (0.004) (0.007) Nearest 0.004 -0.008 -0.008 -0.008 -0.028 (0.009) (0.006) (0.006) (0.009) (0.015)* School Area -0.003 -0.006 -0.006 -0.001 0.000 (0.006) (0.005) (0.005) (0.006) (0.011) Teen Eats Takeaways IV -2.193 -3.540 -3.744 -11.471 19.038 (3.026) (2.536) (2.724) (18.914) (31.354)

Identification Issue

Does living near Fast Food outlet ‘cause’ you to be fat?

OR

Do Fast Food outlets cite near people who are fat and/or do people who have a propensity to be fat choose to live near FF outlets?

Full Model

Here we make a distinction between consumption of FF and Proximity of FF outlets.

T is a measure of Take-away consumption. May be endog – in which case could use FF outlet proximity, R as an IV.

*1 1 1 1

3 1 3

*2 2 2 2

(3.1)

(3.2)

(3.3)

R X X Z

T X R

BMI T X X

Trying to establish Causality?!

• Took all the Youth Cohort Surveys 1-7 over the whole period of the 1983-1992 to characteristics of the LEAs:

Table 13 Explanation of Fast Food Duration Intensity by LEA Characteristics. Duration Intensity Fast

Food Duration Intensity Fast Food

Mean Overweight 16.667 21.596 (22.489) (16.853) % Non Manual Fathers -52.185 -21.448 (36.267) (27.412) % Owner Occupiers 23.958 -16.182 (25.440) (19.655) Average Education Score 2.553 1.859 (0.955)*** (0.720)** % Youth Unemployment -565.945 -282.110 (82.830)*** (70.809)*** % Truancy 161.684 40.614 (51.942)*** (41.538) % Dads in Work -100.999 -16.345 (36.099)*** (28.890) % One Parent Families 112.402 55.262 (59.109)* (44.799) % Non-White 96.066 (11.556)*** Constant 65.339 16.240 (39.660) (30.284) Observations 96 96 R-squared 0.55 0.75

Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

Source from Cummins et al (2005) Int J of Behavioral Nutrition and Physical Activity.

Possible explanations of why I dont find anything of a fast food effect:

1. Using home rather than school.2. Just too early - the data which finds an effect is for the US and in the 2000s.

Powell uses US data from NLSY data over teenagers from 1997-2003Davis (2009) Uses US data from CHKS over the 2002-2005 period.Currie et al (2009) Use US data from 1999-2007 for Californian kids.

3. Its just a US effect - At present there is no evidence from any other country that there is an effect.

Simmons et al (2005) find no relationship in Australia.4. Methodology or claimed causality on other papers is dubious. How can we be sure

that fast food restaurants do not locate where fat people (or people who have a propensity to consume more highly) live. i.e. fast food outlets locate where there are already fat people rather than the location of the fast food outlet causes people to become fat. All the papers purporting to find this effect do not satisfactorily tackle this question.

5. My measure of intensity of treatment is wrong.6. There simply is no causal effect for proximity of fast to children's whereabouts.7. Takeaways do not induce BMI gain as kids substitute calories when they take fast

food – we do not have good enough data to tell us about how FF substitutes for other food.

Table 14. Teen Version of What they Ate: Poisson Regression of Number of Times ate Takeaways this Week.

Regressors: Ate Yesterday Total portions of chips 0.260 (0.028)*** Total bags of crisps 0.173 (0.017)*** Total carbohydrate/starch score -0.016 (0.011) Total vitamin c score -0.014 (0.009) Total fibre score -0.051 (0.009)*** Total carbohydrate/sugar score 0.069 (0.009)*** Total fizzy drinks 0.052 (0.015)*** Constant -0.113 (0.046)** Observations 4652

Standard errors in parentheses * significant at 10%; ** significant at 5%; *** significant at 1%

Issues in Obesity Literature.

• Does maternal working play a role in childhood obesity? (Anderson et al 19 )

• Is SES related to obesity? (Baum and Ruhm )• Does mothers BMI impact on childs obseity (Parsons et

al )• Height is related to Earnings. (Case and Paxson)• BMI is negatively related to earnings for women.

Blanchflower and Sargent (1980) Morris• Childhood obesity is not linked to adult outcomes (Viner

and Cole)• Relation between screen viewing and obesity.

Other Geographical Studies

• Cummins & MacIntyre (2005) (Int J of Epidemiolgy)

• Cummins et al (2005) Int J of Behavioral Nutrition and Physical Activity.

• Morland & Evenson (2009) (Health and Place)

The Data

• 1946 NSHD Cohort

On food rationing since up to age of 8.

• 1958 NCSD Cohort

“Control cohort”

• 1970 BCS Cohort

“Fast Food Cohort”

NHSD Follow-ups

• Socially structured sample of 5362 singletons born in one week in March 1946.

• Followed at Birth

• 2,4 response 95%

• 6,7,8,9,10,11,13,15 response 85%

NCDS Follow-ups

NCDS Follow-ups and sources of information 1958-2000

PMS NCDS1 NCDS2 NCDS3 EXAMS NCDS4 NCDS5 NCDS6 (1958) (1965) (1969) (1974) (1978) (1981) (1991) (2000) Birth 7 11 16 20 23 33 42

17,733a 16,883 16,835 16,915 16,906 16,457 15,600 15,145

Mother — Parents — Parents — Parents

School — School — School — School

Tests — Tests — Tests

Medical — Medical — Medical — Medical

Subject — Subject — Subject — ———— — Subject — Subject — Subject

Census — ———— — Census

Spouse/ Partner

Motherc

Children

17,414b 15,568 15,503 14,761 14,370 12,537 11,407 11,419

Notes: a: Target Sample - immigrants with appropriate date of birth included for NCDS1-3.

b: Achieved Sample - at least one survey instrument partially completed. c: This could be the Cohort Member, their Spouse, or Partner.

0.0

5.1

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10 15 20 25 30 35Male BMI at 16

NSHD NCDS BCS

Male BMI at age 16 by Cohort

0.0

5.1

.15

Den

sity

10 15 20 25 30 35Female BMI at 16

NSHD NCDS BCS

Female BMI at age 16 by Cohort

0.0

002

.00

04.0

006

.00

08D

ensi

ty

1000 2000 3000 4000 5000Birth Weight

NSHD NCDSBCS

Female Birth Weight by Cohort

0.0

002

.00

04.0

006

.00

08D

ensi

ty

1000 2000 3000 4000 5000Birth Weight

NSHD NCDSBCS

Male Birth Weight by Cohort

Additional features of the data:

• Have a 'rationed' and 'control' generation to examine the context of weight gain of teenagers over the period 1962-1986.

• Have repeated measure of BMI - i.e. longitudinal data and can model changes and identify changes in intensity of fast food treatment on weight gain.

• Know an extremely rich set of covariates including mothers and father own BMI - no other studies have access to such controlling data to provide a context of genetic and family environment factors.

Table 2 Determinants of Age 10/11 BMI by Cohort.

NSHD NCDS BCS Combined

Male 0.313 0.460 0.358 0.394 (0.076)*** (0.049)*** (0.039)*** (0.029)*** Medical Problems 0.396 0.157 0.077 0.188 (0.079)*** (0.088)* (0.056) (0.042)*** Birth Weight in gms 0.001 0.001 0.0004 0.001 (0.000)*** (0.000)*** (0.000)*** (0.000)*** Mother Works 0.391 0.120 0.156 0.169 (0.082)*** (0.050)** (0.039)*** (0.030)*** Social Class I 0.084 -0.050 -0.289 -0.165 (0.192) (0.131) (0.095)*** (0.074)** Social Class II -0.053 0.091 -0.123 -0.048 (0.136) (0.098) (0.068)* (0.054) Social Class III -0.189 0.125 -0.075 -0.029 (0.117) (0.086) (0.060) (0.047) Social Class IV -0.086 0.117 -0.080 -0.018 (0.137) (0.099) (0.080) (0.057) BCS Cohort -0.774 (0.032)*** NSHD Cohort -0.339 (0.046)*** Constant 14.838 14.995 15.431 15.566 (0.284)*** (0.181)*** (0.139)*** (0.107)*** Observations 3920 11567 11287 26774 R-squared 0.03 0.02 0.02 0.04

Table 3 Determinants of Age 15/16 BMI by Cohort NSHD NCDS BCS Combined

Male 0.824 0.483 0.617 0.580 (0.061)*** (0.044)*** (0.117)*** (0.035)*** Medical problems 0.019 0.035 0.046 0.047 (0.063) (0.080) (0.126) (0.048) BMI at 10/11 0.894 0.787 0.848 0.816 (0.013)*** (0.009)*** (0.028)*** (0.007)*** Mother Works 0.030 0.018 -0.022 0.015 (0.062) (0.047) (0.117) (0.036) Social Class I -0.185 -0.297 -0.100 -0.248 (0.147) (0.111)*** (0.284) (0.086)*** Social Class II 0.008 -0.147 0.184 -0.073 (0.102) (0.071)** (0.219) (0.057) Social Class III -0.024 0.031 0.133 0.013 (0.089) (0.059) (0.208) (0.049) Social Class IV 0.091 0.132 0.572 0.157 (0.106) (0.080)* (0.276)** (0.065)** BCS Cohort 1.219 (0.053)*** NSHD Cohort -0.334 (0.045)*** Constant 4.167 6.531 6.473 5.956 (0.237)*** (0.157)*** (0.521)*** (0.133)*** Observations 3319 8917 2067 14303 R-squared 0.61 0.50 0.31 0.50

Main Results of Cross Cohort Comparison

• At 10/11 mother works increases BMI

• At 10/11 social class effects

• At 10/11 Birth weight effects.

• At 15/16 still social class effects

• At 15/16 no mother works effect

• At 15/16 BMI @ 10/11 is main driver.