does financial insecurity make people obese?

Biology of FatteningNLSY & ESI studiesConcluding Remarks

Does Financial Insecurity Make People Obese?

Trenton G. Smith

University of Otago, New ZealandDepartment of Economics

15 October 2014Newcastle University

Trent Smith Obesity & Economic Insecurity 1 / 35


Introduction: Obesity and Material Constraints

Economic analysis of obesity typically emphasises:price (of calories, of fat, of physical exercise...) andincome effects (poverty, wealth), perhaps conditioned oninformation (nutrition education, food labels, marketing...).One dimension typically left out is the role of stochasticnature of economic environments.I’ve argued that the extent to which income ormaterial well-being is uncertain or at risk may well bemore important than conventional explanations.

Motivation is from behavioural biology:body fat as hedge against food shortage.Good news: clear theoretical predictions;opens door to sources of empirical evidencepreviously ignored in economicsBad news: higher moments difficult to measure;endogeneity (still) a hurdle



LeptinSeasonalitySociality & Serotonin

Which of these two mice is starving?




Endocrinology of Obesity: Leptin

It has long been known that the obese-type mouse carries a recessivegene that causes it, under free-feeding conditions, to gain weight rapidlyfrom birth while exhibiting the clinical symptoms of starvation:

hyperphagia

decreased body temperature

lethargy

diminished immune function

infertility

Since 1994 we’ve known that the ob/ob mouse lacks the gene that codes forleptin, a peptide hormone secreted by fat cells.

In normal mice, leptin circulates in the bloodstream in proportion tothe amount of body fat, sending a signal to the brain about availabilityof energy stores.




Endocrinology of Obesity: Leptin, Cont’d

The human homologue of the normal genefor leptin (Ob) and for the leptin receptorwere quickly identified.

The mutant (ob) allele is exceedingly rarebut has been medically documented.

Parents of these children say that frombirth they were “...constantly hungry,demanding food continuously and eatingconsiderably more than their siblings.”

Initial optimism about leptin-based weightloss drugs has not panned out.

Intriguing implications:

ob effects suggest adaptive (evolutionary)function for body fat

subjective beliefs encoded in our genes?




Seasonal Fattening: Siberian Hamsters

Many foraging animals(e.g., the Siberian hamster)fatten seasonally.

The key environmental triggerappears to be photoperiod.

In humans, seasonal affective disordercharacterized by depression,hypersomnia, hyperphagia, andweight gain.

Most commonly prescribed treatment:exposure to artificial light.

Conversely, summer depression inhumans causes insomnia,decreased appetite, and weight loss.




Social Rank and Obesity: Willow Tits

In natural settings, willow tits fall intostable binary dominance hierarchies thatdetermine access to food supply.

In spite of restricted access to foodsupply, subordinate tits typically fatterthan their dominant counterparts.

Theoretical explanation: fattening isan optimal response to increased riskof starvation.

Interesting corollary: if food becomesscarce enough, direction of thegradient reverses.

Similar pattern observed in humans?




SSRIs

The molecular basis for the link between(indicators of) starvation risk and body weightare not well understood.

There is suggestive evidence however that theserotinergic system in the brain is involved.

Serotonin injected directly into (pigeon) brainsuppresses appetite.

SSRIs, widely used as antidepressants, can causeweight loss (and are sometimes even marketedas weight loss drugs).

SSRIs (selective serotonin reuptake inhibitors) arethought to work by increasing levels of serotonin(“5-HT”) at neural synapses in the brain.




Ecstasy as a Weight Loss Drug?

3,4-methylenedioxymethamphetamine(MDMA or “ecstasy”) developed by Merckin 1912 as a weight loss drug

Acts via nicotinic receptor and serotonergicsystem

MDMA induces weight loss via hyperthermia,loss of appetite, peripheral hyperactivity

Never marketed because of adverse side effects:Feelings of “euphoria and empathy,” “extremecomfort, belonging, and closeness to others,”which can result in “inappropriate and/orunintended emotional bonding.”

Specificity of these effects suggests psychologicalstate conducive to weight loss?




Tobacco

Nicotine from tobacco is known to activatenicotinic receptors in the brain, which in turnactivate the serotinergic system.

Tobacco causes weight loss(or prevents weight gain).

Smoking associated with unemployment,financial problems, reduced social contacts, lackof social support, and antidepressant use(indeed antidepressants are sometimes marketedas aids to smoking cessation).

Coincidence of psychological correlates ofeconomic security with weight loss (via tobacco)suggestive of a link between the two.




The Insecurity Hypothesis

Given apparent adaptive function of body fat, andmany parallels between animal and human fattening,a natural question arises:

Might variation in material risk drive incidence of obesity inthe modern world?



Identification in NLSYThe Economic Security IndexTwo Sources of Data

A Weighty Problem

The identification problem in obesity research is difficult.

individual choices (food, exercise, career choice...) affect BMIunobserved heterogeneity always a concernidentification strategy needed for causal inferenceex: Smith et al. 2009 (FHEP) used local job market conditionsto isolate effect of economic insecurity on body weight

Moreover, economic insecurity is difficult to measure.(In 2009 study we relied on detailed employment histories toestimate income-loss risk...leaving us with cross-section only).

Without an appropriate measure of economic insecurity, it isnot possible to address the “big” question of its role in theoverall trend in obesity.

A new measure has recently become available for the US:the Economic Security Index (ESI).




The Economic Security Index

ESI developed by researchers at Yale’sInstitution for Social and Policy Studies.

Uses US Current Population Survey (CPS),household incomes linked year-to-year by residence.

ESI is defined as the probability of > 25% drop in annualhousehold income. (Adjusted for household size,out-of-pocket medical expenses, household debt service,buffering effect of wealth, but excluding retirement events).

ESI is available by gender, race/ethnicity, age, householdstructure, geographic (state) location, and year (currentlyback to 1986).




Empirical Strategy

Our strategy: focus on exogenous demographiccharacteristics: age, gender, race/ethnicity.

Obesity data come from US National Health and NutritionExamination Surveys (NHANES), which provide nationallyrepresentative repeated cross-sections with measuredheight and weight for the civilian population.

NHANES surveys cover 2-3 year periods:1990 NHANES III (phase 1), 1988–19911993 NHANES III (phase 2), 1992–19941999 NHANES 1999–20002001 NHANES 2001–20022003 NHANES 2003–20042005 NHANES 2005–20062007 NHANES 2007–20082009 NHANES 2009–20102011 NHANES 2011–2012




2020

30

40

50

Per

cent

Obe

se

19901990 1993 1996 1999 2002 2005 2008year

White NH MenBlack NH MenHispanic MenWhite NH WomenBlack NH WomenHispanic Women

Source: NHANES

NHANESUS Obesity Rates, 18+




01020304050607080

01020304050607080

01020304050607080

.1.1 .15 .2 .25 .3 .35 .1.1 .15 .2 .25 .3 .35 .1.1 .15 .2 .25 .3 .35 .1.1 .15 .2 .25 .3 .35

Age 20-24 Age 25-29 Age 30-34 Age 35-39

Age 40-44 Age 45-49 Age 50-54 Age 55-59

Age 60-64 Age 65-69 Age 70-74 Age 75+

White NH Men Black NH Men Hispanic Men

White NH Women Black NH Women Hispanic Women

Per

cent

Obe

se

Economic Security Index (ESI)




Empirical Specification

BMIij = ESIjα + Xijβ + σij

where

BMIij is individual i ’s obesity status (body mass index≥ 30),

ESIj is individual i ’s economic security index, as determinedby year and exogenous demographic characteristics,

Xij is a vector of i ’s personal characteristics and exogenousdemographic indicators (possibly including year of survey), and

σij is a disturbance term.

Linear probability model.

Hypothesis of interest: HA : α > 0




Table 2: Effect of Economic Insecurity on Obesity: Role of Demographic FE(1) (2) (3) (4) (5) (6) (7)

ESI 0.851*** 0.609*** 1.282*** 0.882*** 1.059*** -0.388*** 0.526***1993 0.0318*** 0.0307*** 0.0285** 0.0367**1999 0.0981*** 0.0995*** 0.0984*** 0.0970***2001 0.0922*** 0.0910*** 0.0888*** 0.102***2003 0.110*** 0.107*** 0.103*** 0.126***2005 0.128*** 0.124*** 0.119*** 0.149***2007 0.119*** 0.113*** 0.106*** 0.147***20091 0.135*** 0.127*** 0.117*** 0.171***Female 0.0235*** 0.00934 0.0155** 0.0441***White NH 0.125*** 0.133*** 0.132*** 0.105***Black NH 0.208*** 0.180*** 0.200*** 0.238***Hispanic 0.140*** 0.119*** 0.132*** 0.160***Age 25-29 0.0449*** 0.0504*** 0.0473*** 0.0492***Age 30-34 0.0799*** 0.0871*** 0.0839*** 0.0884***Age 35-39 0.113*** 0.128*** 0.119*** 0.122***Age 40-441 0.136*** 0.155*** 0.143*** 0.149***Age 50-541 0.161*** 0.182*** 0.166*** 0.170***Age 60-64 0.180*** 0.198*** 0.186*** 0.189***Age 65-69 0.153*** 0.163*** 0.156*** 0.160***Age 70-74 0.116*** 0.113*** 0.115*** 0.114***Age 75+ 0.00928 -0.00154 0.00444 0.00121

Yr*Grp FE No No No No No No YesTrent Smith Obesity & Economic Insecurity 19 / 35



Table 3: Unemployment & Other Measures of Income

(1) (2) (3) (4) (5) (6) (7)

ESI 0.526*** 0.534*** 0.496*** 0.541*** 0.499*** 0.516***(0.139) (0.141) (0.154) (0.140) (0.154) (0.153)

Mean PIR 0.00884(0.0101)

Unempl. Rate -0.236 -0.296 -0.107 -0.152(0.187) (0.190) (0.209) (0.207)

Employed -0.0251*** -0.0229***(0.00788) (0.00789)

Unemployed -0.0125 -0.0107(0.0177) (0.0177)

Married 0.0115*(0.00664)

High School 0.0174**(0.00861)

Some College 0.0171*(0.00913)

College -0.0699***(0.0110)

Household Size 0.00544**(0.00219)

Year*Group FE? Yes Yes Yes Yes Yes Yes YesTrent Smith Obesity & Economic Insecurity 20 / 35



Table 4: Effect of Economic Insecurity by Demographic Characteristics

, Cont’d

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

ESI 0.526***ESI*1990 0.513*ESI*1993 0.400ESI*1999 0.760ESI*2001 0.649*ESI*2003 -0.383ESI*2005 0.357ESI*2007 0.527ESI*2009 0.893**ESI*2011 0.869*

ESI*Male -0.323**ESI*Female 0.945***ESI*Black NH 1.018***ESI*White NH -0.475**ESI*Hispanic 0.618***ESI*Other NH 0.176ESI*Age 20-24 0.268ESI*Age 25-29 0.552*ESI*Age 30-34 1.106***ESI*Age 35-39 0.719***ESI*Age 40-44 0.312ESI*Age 45-49 0.936***ESI*Age 50-54 0.245ESI*Age 55-59 0.603*ESI*Age 60-64 0.216ESI*Age 65-69 0.171ESI*Age 70-74 -0.00465ESI*Age 75+ 0.709*




Table 4: Effect of Economic Insecurity by Demographic Characteristics, Cont’d

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

ESI 0.526***ESI*Male -0.323**ESI*Female 0.945***ESI*Black NH 1.018***ESI*White NH -0.475**ESI*Hispanic 0.618***ESI*Other NH 0.176ESI*Age 20-24 0.268ESI*Age 25-29 0.552*ESI*Age 30-34 1.106***ESI*Age 35-39 0.719***ESI*Age 40-44 0.312ESI*Age 45-49 0.936***ESI*Age 50-54 0.245ESI*Age 55-59 0.603*ESI*Age 60-64 0.216ESI*Age 65-69 0.171ESI*Age 70-74 -0.00465ESI*Age 75+ 0.709*

ESI*1990 0.513*ESI*1993 0.400ESI*1999 0.760ESI*2001 0.649*ESI*2003 -0.383ESI*2005 0.357ESI*2007 0.527ESI*2009 0.893**ESI*2011 0.869*




Table 6: Effect of Economic Insecurity: Alternative BMI Measures

Dependent Variable

BMI≥30 BMI BMI≥20 BMI≥25 BMI≥35 10yr wtchange

(1) (2) (3) (4) (5) (6)

ESI 0.526*** 9.892*** 0.268*** 0.847*** 0.138 35.69***(0.139) (2.192) (0.0779) (0.173) (0.0945) (11.18)




Table 4C: Effect of Economic Insecurity on Child BMI z-scores

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

ESI 0.631***ESI*1990 0.593ESI*1993 1.435**ESI*1999 0.748*ESI*2001 -0.118ESI*2003 0.891ESI*2005 1.086**ESI*2007 -0.0730ESI*2009 -0.0507ESI*Male 0.174ESI*Female 1.150***ESI*Black NH -0.331*ESI*White NH 2.138***ESI*Hispanic 0.108ESI*Other NH 0.770***ESI*Age 0-4 -0.355ESI*Age 5-9 0.218ESI*Age 10-14 1.319**ESI*Age 15-19 0.997***



Insecurity and Economic PolicyConclusion

Whitehall Study Stumbles upon a Natural Experiment

Michael Marmot’s Whitehall Study has followed more than 10,000British civil servants for many years, conducting periodic interviewsand medical exams to better understand the interaction ofsocioeconomic and employment experience with health outcomes.

In the early 1990s one of the 19 departments covered by Whitehall(the Property Services Administration) was privatised.

Because privatisation threatened the job security of PSA employees,Marmot’s group had the opportunity to study the effects of thethreat of insecurity, and then the effects of actual privatisation.

Two effects in particular were noted (any guesses?).

1 An increase in body weight (0.5 kg for men, 1 kg for women).2 An increase in the odds of sleeping > 9 hours per night.

Q: When do you suppose these effects were observed?(A: On the rumour. The uncertainty, not the change itself,seems to have triggered the response).




1980 1985 1990 1995 2000 2005Year0

5

10

15

20

25

30

35% Obese

United StatesSwitzerlandSwedenSpainNew ZealandNetherlandsJapanItalyIcelandFranceFinlandEnglandDenmarkCzech RepublicCanadaAustriaAustralia




Economic Policy and Household-Level Risk

Why has the obesity epidemic been more severe in some countries(US, Iceland, New Zealand, Australia, England, Spain...)than in others (France, Switzerland, Austria, Japan...)?

Public policy can affect the extent to which households aresubject to financial risks. In particular, over the past 35 yearsmany countries have pursued “neoliberal” economic policies,characterized by:

expanded international tradeprivatisation of state-owned assetsfloating exchange ratemonetary policy emphasising price stabilityrather than full employmentweakening of social safety netelimination of labour protectionsdiminished antitrust enforcement

Could obesity epidemic be an unintended side effect?




Australia

Finland

Netherlands

Japan

United States

Spain

Denmark

New Zealand

Sweden

France

Iceland

England

Austria

Switzerland

Italy

Canada

Annual

Growth

in

Obesity

(%)

Revenue from Sales of State-Owned Enterprises (% of 1985 GDP)

0 5 10 15 20 25

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Privatization and Obesity in the OECD, 1985-1999




America’s “Great Risk Shift”

ESI suggests economic insecurity has risen in the U.S. sincethe 1980s. Why?

Some likely culprits:

1974-present Health insurance subscriptions down (Hacker 2006)

1979-present Rising income instability(Gottschalk and Moffitt 2009)

1980-present “Creative destruction”stemming from decline in antitrust enforcement(Lynn 2010)

1981-present Pensions: from pooled to individual risk1994-present NAFTA and outsourcing1996-present Welfare reform1999-present Financial deregulation




Obesity and Welfare Regimes




Summary & Reflections

Obesity and Insecurity

The “insecurity hypothesis” is broadly consistent with theincidence of obesity in human populations.

Open questions: particular cues? proximate mechanisms?

Larger issue: does economic liberalisation(or, more generally, do economic incentives) always imply atrade-off between efficiency & insecurity?(...with opportunity to succeed comes threat of failure...)




Worries go down better with soup than without.–Jewish proverb


does financial insecurity make people obese?

Education