Race, obesity, and the puzzle of gender specificity

1. Race, obesity, and the puzzle of gender specificity Mary A. Burke Federal Reserve Bank of Boston Frank Heiland Florida State University North Atlantic Summer Meeting of the Econometric Society Carnegie Mellon University June 19, 2008

2. Introduction • Puzzles • gaps in body mass index (BMI) and obesity rates between white and African-American women • no black-white BMI/obesity gap for men • Gap may contribute to disparities in morbidity and mortality • diabetes (type II) • heart disease & hypertension • life expectancy • Policy implications depend on source of gap • socioeconomic status and economic incentives • biological factors • sociocultural factors

5. Potential explanations of obesity puzzle • Education (health knowledge) • Economic incentives and constraints • income • food prices • built environment • occupation • Biological factors (health-related incentives) • health consequences of high BMI • body fat, visceral fat for given BMI • metabolism • Sociocultural factors/incentives • ideal/desired physique/weight • stigmatization of overweight • cultural roles and identity

6. Data sources • NHANES (National Health and Nutrition Examination Survey) • focus on 1988-94 (III), 1999-2004 • BMI values based on in-person examinations • sample: 25-74 year olds with examined weight and height • BRFSS (Behavioral Risk Factor Surveillance System) • 1989-2002 • BMI values based on phone reports of height &weight, corrected for bias

7. Multivariate models of BMI (NHANES) • (Also: Poisson regressions with obesity as dep. var.) • Race: non-Hisp White, non-Hisp Black, Mexican-Am., other Hisp (NHANES III: all Hisp), other race • Location: 4 census regions (ref=northeast), MSA indicator (ref=metro) • Education: <less than high school>, <high school>, <some college*> • Income: “poverty income ratio” <less than 1>, <1-3.5>, <3.5 or higher> • Occupation: blue collar, unskilled white collar, skilled white collar, unemployed • Behavior: activity level relative to peers (ref=similarly active), smoking (ref=smoked in past), diet (ref=% carbohydrates; not available in NHANES ’03-’04) • Included alternately in additional regressions • race*educ, race*income • marital status, live births (not sig.) • HIV status, drug use variables

8. Fraction Obese: Women 25 – 74, NHANES 1999 - 2004 Education Income Age Blacks Whites Marital Status Occupation

9. Fraction Obese: Men 25 – 74, NHANES 1999 - 2004 Education Income Age Marital Status Occupation

10. Black Race Fixed Effects Across Models, Age 25 - 74 Notes: See text for an explanation of the other variables included. † Statistically significant at the .10 level; * at the .05 level; ** at the .01 level.

11. Black Race Fixed Effects Across Models, Age 25+ Notes: See text for an explanation of the other variables included. † Statistically significant at the .10 level; * at the .05 level; ** at the .01 level.

12. Competing Explanations • Health incentive hypothesis -> variation in fixed physiological factors results in gender-specific differences between blacks and whites in health incentives relating to BMI • Social incentive hypothesis -> variation in sociocultural norms governing body size and physique result in gender-specific differences between blacks and whites in social incentives relating to BMI

13. Predicted Disease Risk, NHANES 1999 – 2004, Age 25 - 74 Women Men Hypertension Hypertension* Blacks Whites Diabetes Diabetes* Notes: Predictions based on poisson regressions with diabetes or hypertension as dependent variables. See text for explanation of variables in estimation. * BMI x Race is not significant at 10% level.

14. Diabetes Notes: See text for an explanation of the other variables included. † Statistically significant at the .10 level; * at the .05 level; ** at the .01 level.

15. Hypertension Notes: See text for an explanation of the other variables included. † Statistically significant at the .10 level; * at the .05 level; ** at the .01 level.

17. Weight Perception, by Race

18. Weight Perception, by Race

19. BMI Dissatisfaction (actual – desired), BRFSS Age 25 - 74 Notes: † Statistically significant at the .10 level; * at the .05 level; ** at the .01 level.

20. Prior evidence of Black-White and male-female differences in body ideals and stigma • Black women • identify larger “social norm for ideal size” • Racial disidentification, positive image of size and strength • experience weaker effects of obesity on self-esteem • stigmatize obesity in others less strongly than all other groups • irrespective of own obesity status • incur smaller wage, spousal income, and marriage penalties for obesity • expected to be strong, selfless caretakers, at expense of own health • problem of overeating ignored in black community • Black men • select larger “desired size” for female partners • hypermasculine ideal: exaggerates white male ideal • Men in general • weaker/non-existent wage and marriage penalties for obesity • weight concerns less salient, less likely to diet

22. Discussion • Race patterns highly robust to long list of controls - residual may reflect different motivation to achieve a given BMI • Health-related incentives - marginal impact of BMI/obesity on health risks may be lower for blacks, difference in risks may be greater for women - results may be spurious: greater risk among low-BMI blacks may drive findings - aware of marginal health differences? health recommendations not race-specific • Sociocultural incentives - Blacks’ size ideals larger than whites’, lower “size dissatisfaction” - strong evidence that differences greater for women (gender-specificity) - consistent prior evidence - body ideals determined by realized values? Ideal and realized weight moved opposite for white women, obesity rates similar for white men and women but white women’s ideals much lower

23. Policy implications • Importance of “culturally sensitive” public policy campaigns: imposing (extreme) white standards may do more harm than good • Higher morbidity/mortality among blacks not accounted for by obesity: health policy should focus on identifying the common factors among blacks that lead to their having worse health outcomes • Public policy on obesity may have focused too narrowly on BMI and not on more fundamental risk factors such as body fat (distribution), nutrition, and physical activity

27. Diverse images: thin Black model and “plus-size” white models

28. BRFSS data • Differences from NHANES • Larger sample (telephone interviews) • Individual MSAs observed • Food prices by MSA can be linked in some years (’98-’02) • Year fixed effects • Finer income categories (8 vs. 3) • Exercise measure: any phys activity (running, walking, golf, etc.) past month • No occupations: use employment and labor-force status • Weight and height self-reported • Correct for bias based on NHANES data • “Desired weight” observed intermittently—used in separate analysis

29. Why do physical ideals differ? • Past and ongoing experience with poverty • Thinness associated with poverty, starvation, ill health • Poorer countries today have more positive valuation of larger body sizes • Late-19th century U.S. dominant female ideal larger than today • “Cultural lag” in updating of valuations • Very poor today still less obese than “near-poor” • Disidentification • Black women rejected white beauty standards as oppressive (Black power movement of ’70s) • Re-valorization of stereotypes: size and nurturance part of pos. identity • Rejection of dominant ideal as protection against sexual harassment • Racist constructions of Black womanhood • reappropriation of “mammy” stereotype from slavery and Jim Crow era • Obese, desexualized, nurturing, happy • Inaccurate portrayal, obscured sexual abuse of female slaves

30. Model of BMI Quasi-reduced form: • Pf = relative food price • Y = income • a = age • ε = idiosyncratic biological endowments • δ = individual preferences (e.g., food, exercise, shape) • β = health beliefs • g = gender • θT = technology (work, medicine) • θS = social norms (e.g., body ideal, punishments) • θC = built environment

32. Interaction Effects on Obesity, NHANES 1999 – 2004 Women 25 - 74 Notes: Standard errors are reported in parentheses. See text for an explanation of the other variables included. † Statistically significant at the .10 level; * at the .05 level; ** at the .01 level.

33. Predicted Body Fat, Age 25 - 74 NHANES III NHANES 1999 – 2004 Notes: Predictions based on linear regressions with estimated body fat as dependent variables. See text for explanation of variables in estimation.

34. Results discussion • Results consistent between NHANES and BRFSS • Relative risks similar in Poisson models of obesity • Robust to measurement differences in control variables • Residual race effects still large and significant for women, modest for men • SES (education and income) contributes somewhat to race gap among women • Some indication that gaps increased between NHANES III and ’99-’04 • Gender-gap smaller in controlled models • Lack of gap for Black men partly explained by differences in behavior (smoking and exercise; what motivates behavior?) • Interactions models indicate high SES blacks of both sexes more likely to be obese than whites with high SES • May reflect race differences in education and income within top categories • Including HIV-status and drug-use indicators increases male gap • Some portion of gender specificity may be explained by differences in these factors • Suspect true effect greater; NHANES undersamples HIV-positive individuals

35. Weight Perception, by Sex

36. Reverse causality? • Hypothesis • ideals and/or punishments for deviation determined by realized values • Objections • White (female) obesity and ideal physique have moved in opposite directions during second half of 20th century • Evidence from Miss America and Playboy • Obesity patterns similar between white women and white men, but white women’s desired BMI significantly lower than white men’s • Our view • Ideals and punishments *are* endogenous, but • Depend on factors other than (in addition to) realized outcomes in ref. group • Move with lag; can be considered exogenous to individual • Represent real incentives separate from health incentives

37. Competing explanations, part II: sociocultural incentives • Support for social incentives hypothesis • Differences in self-perception of weight status in NHANES and inferred “ideal BMI” (gender-specific) • Differences in “size dissatisfaction” in BRFSS (gender-specific) • Differences in media images/messages (women) • Prior evidence of differences in ideals, obesity stigma • Male ideal emphasizes muscularity/masculinity • Higher ideal BMI, but obesity still stigmatized • Arguments against social incentives hypothesis • Causal links hard to prove; reverse causality possible • Role of ideals vs. role of stigma and punishments? • why aren’t men more obese than women?