Obesity

A Health Economics paper by Timothy K. M. Beatty finds that “households who make more frequent, smaller food purchases buy healthier foods than households who make fewer, larger purchases. These households are more likely to purchase foods with a lower share of total calories from fats, saturated fats and a larger share of calories from fruits and vegetables.”

However, I am not exactly sure what this proves. If you want to eat healthy food (fruits and vegetables), you need to shop more frequently since these “healthy” foods tend to spoil more easily than fatty, non-perishable foods (frozen burritos). Further, invidiuduals who live in denser, urban environoments likely 1) live closer to grocery stores and 2) have a social network that values healthy eating. Beatty even admits that “The exact causal relationship between dietary quality and expenditure dispersion is ambiguous.”

It seems more sensible that the desire to eat healthy foods determines shopping habits rather than the converse.

• Timothy K. M. Beatty (2008) “Expenditure dispersion and dietary quality: evidence from Canada” Health Economics, Volume 17, Issue 9 (p 1001-1014)

The New York Times writes that its “Better to Be Fat and Fit Than Skinny and Unfit.”

The BBC recently reported that a Durham University professor David Hunter is claiming that obesity is such a problem that its “…threat to our future health is just as significant as the current security threat.” What is Dr. Hunter’s solution?

He said that bigger warning labels, changes in the taxation of “unhealthy” foods, and even the use of compulsory regulations to force manufacturers to cut levels of salt, sugar and fat in their foods could be employed.

I am not sure where you weigh in (pun intended) on this debate, but I think that this is pure hyperbole. Obesity is a health problem, but is one where rational individuals are able to trade-off buying inexpensive, tasty, high calorie meals against the health risks of due to increased obesity. Further, the benefits of eating high calorie, low cost meals are never mentioned. As the cost per calorie decreases, individuals in society are able to afford to purchase more goods (e.g., education, housing).

On the other hand, individuals who experience a terrorist attack are not able to choose their own fate.

If the price of health insurance was risk adjusted so that obese individuals–who are more at risk for diseases such as diabetes–would pay more for health insurance, this would give individuals an incentive to lose weight. In theory this makes sense, but sometimes individuals gain weight when they are sick (since they cannot exercise) and thus risk adjusting health insurance premiums for obesity may be problematic. Nevertheless, claiming that obesity is a bigger problem then terrorism is going too far.

Pierre Dubois of VoxEU has a suggestion to reduce obesity rates: a junk food tax. Dubois claims that a junk food tax of 5% would reduce junk food consumption by 15% and thus reduce obesity.

While junk food is not healthy, it offers the most calories per dollar. Thus, a junk food tax would fall disproportionally on the poor. Dubois states that “poor consumers [affected by the junk food tax] could then find cheap calories in less-dense food items, like starchy foods which are less apt to be overeaten.”

From a philosophical point of view, I generally do not like government officials making rules about what type of food you can eat. If you want to have a banana split every day that is your choice.

Some “experts” argue that in countries with public health care systems, however, the public does end up paying for the additional health costs of obesity. Yet it not been conclusively showed that obesity leads to higher health care costs. While obese individuals generally have higher health care costs each year, those who are extremely overweight also have lower life expectancy. According to a PLoS study, obese individuals actually cost the NHS less money due to their lower life expectancy.

Further, as a practical matter, it is difficult to determine which food are junk foods. Most people would claim that Pringles are junk food. In the UK, food is exempt from their 17.5% sales tax with the exception of potato chips. According to the L.A. Times, a British court has ruled that Pringles are not potato chips and thus are exempt from the tax.

If Pringles don’t count as junk food, then what does?

The WSJ Real Time Economics blog reviews a paper by Michael Lechner which finds that “sports-playing adults saw a boost in income of about 1,200 euros per year over 16 years when compared to their less active peers. That translates into a 5-10% rate of return on sports activities, roughly equal to the benefit of an extra year’s worth of education.” How can playing sports increase income?

The simplest mechanism is that playing sports increases one’s health level. Healthier people are less likely to get sick and more likely to be able to work to earn income. This health difference, however, only explains a portion of the income differential. Dr. Lechner claims that playing sports builds a social network which helps to increase pay (e.g., your friends are the ones who recommend you for jobs). In fact, Lechner finds that sports-playing men display a higher level of “social functioning” than did the less active men.

One worry of this study is that of reverse causation. If someone is very sick, they are not able to play sports. Further, if you are sick, you are probably less likely to engage in social activities. Thus, health–and not sports playing–may be a hidden, unobserved feature which may be driving these results.

• Hat tip to The Sports Economist
• The full paper is available here.

There is much evidence that has shown that over time for most developed countries, people have been getting fatter. Obesity rates are especially high in the U.S., but a trend towards increased obesity is similar in most developed countries. Are obesity rates “too high?”

In a recent NBER working paper, Philipson and Posner argue that obesity rates may be too high if one’s goal is to maximize health. However, the authors wisely note that:

“From an economic standpoint, the proper maximand is of course not health but utility, in which good health is only one argument. Rational persons constantly trade off health for competing goods, such as pleasure, income, time, and alternative consumption possibilities. Intervention that considers such tradeoffs unworthy of consideration is paternalistic. This is recognized in such areas as highway safety—no one proposes to shut down highways in order to reduce traffic deaths, or to force automobile manufacturers to equip their cars with engines that limit top speed to 25 miles per hour—but the principle that legitimizes trade-offs involving life and health is equally applicable to obesity.”

One argument in favor of trying to reduce obesity is that obese individuals have higher annual medical expenses. With the public–through Medicare and Medicaid–footing much of this bill, maybe the government should enact policies to reduce these “insurance externalities.” Philipson and Posner respond by stating that these insurance externalities

“…are an argument for experience-rating health insurance, so that groups with above-average expected medical expenses pay higher insurance premiums…There is no reason to single out obesity as a basis for higher insurance costs, since there are other, equally or more, risky “life style” choices that increase expected medical costs.”

• Thomas Philipson and Richard Posner (2008) “Is the Obesity Epidemic a Public Health Problem? A Decade of Research on the Economics of Obesity” NBER WP #14010.

Living in an urban, pedestrian friendly area may compel individuals to walk more, and thus reduce the likelihood one is obese. Living in a suburban, car-dependent area makes walking less attractive and thus could increase obesity. Some studies have shown that individuals who live in the suburbs weigh more than individuals living in urban areas. Does living in the suburbs cause obesity?

The Vox EU website cites a paper (”Fat City“) that claims that urban sprawl is not to blame for increasing waistlines. The authors examine six years worth of data on 6000 people, 79% of whom changed addresses. They find that people who are more likely to be obese are more likely to move to sprawling neighbourhoods. However, those who moved from urban to suburban areas showed no additional weight change compared to individuals who moved from suburban to urban areas. It looks like a case of correlation not being the same as causation.

• HT: Free exchange.

To find out how “walkable” your neighborhood is, check out Walk Score.

Increasing obesity rates have significant costs to society. An article in MSN Money (”What if no one were fat?“) claims that if, on average, each American was to lose 20 pounds, we would save $487 billion. Where is this number coming from?

• Savings on fuel for cars and airlines due to their lighter loads would top $5 billion.
• Plus-sized clothing costs 10% to 15% more, so shoppers would save $10 billion on shirts, pants and dresses.
• Reduced food consumption would translate into a savings of $81 billion.
• The medical costs of obesity-related problems such as diabetes, stroke and heart disease run near $140 billion.
• Productivity in the workplace would jump from fewer sick days and better health: This would lead to a savings of $257 billion.
• The weight loss industry might become obsolete, resulting in a savings of $55 billion.

Are these figures credible? The savings on flights and car trips likely are true. Reduced material cost from plus-sized clothing may save costs, but any way to standardize the body shape would save costs. There would be significant cost savings as well if individuals were the same height. Cynthia Istook, an associate professor in textile apparel at North Carolina State University, says clothing makers could then afford to offer more variety in hip and bust sizes, rather than asking every woman to squeeze into an hourglass shape. Thus, costs likely would not decrease, but customization would increase.

Would reduced food consumption reduce obesity? The problem is not that food is too expensive; it is that it is too cheap. Eating a high calorie diet for a low cost is easy (just grab some fast food or buy processed food at the grocery store). Buying fresh fruit and vegetables is more expensive (in terms of calories per dollar) than eating processed food. Thus, moving people to a healthier diet will likely decrease obesity, but increase food costs.

Lower obesity rates likely would decrease disease rates. But just because there is a correlation between obesity and disease rates, doesn’t mean that obesity is the causal factor. It could be that individuals who are obese are also more disease-prone and this would be the case even if they lose weight. Still, on an annual basis, healthier living of course does decrease medical costs. Over a lifetime, however, healthier lifestyles and reduced obesity may actually increase medical costs (see 12 Feb 2008 post).

Sick days may decrease when obesity rates drop, but individuals may have less time to work if they go to the gym everyday. Also, it is highly unlikely the weight loss industry would disappear. Individuals are always unsatisfied with their bodies. Money saved on weight loss programs might now go towards plastic surgery or gym memberships.

Further, these figures do not take into account the utility loss people will incur not eating the foods they choose.

What would we do with all the money we saved from reduced obesity? Maybe we could celebrate with some bananas foster or Extraordinary Desserts.

Gruber (1994) shows that the costs of employer-provided health insurance benefits are passed on to employees through lower wages. But do employees with higher expected medical expenses have their wages reduced by a higher amount to reflect the additional medical costs to employers? This may not be the case if employers can not observe the health of employees when they hire them. On the other hand, for obese individuals, the fact that they are obese is easily observable. Papers such as Finkelstein, Fiebelkorn and Wang (2003) show that annual medical expenditures for obese individuals are $732 more than those of normal weight. Is this additional cost passed on to obese employees through lower wages?

This is what an NBER working paper by Bhattacharya and Bundorf (2005) aims to investigate. The authors compare the wages of obese and non-obese individuals in companies without health insurance. Then they compare the differences in wages of obese and non-obese employees in companies with health insurance. Since no health insurance costs will be passed on employees if no insurance is offered, the difference between the two wage gaps may be able to identify if higher health insurance premiums are passed on to employees through lower wages. If there are differences in wages between obese and non-obese workers (i.e.: due to discrimination, lower productivity, etc.) these differences are likely constant across firms with and without health insurance.

The authors find that “the incidence of obesity on wages for workers insured through their employers is -$1.68.” After controlling for a variety of covariates, this estimate lowers to -$1.44. This difference is mostly due to the fact that wages of obese workers with health insurance grew slower than thinner workers with health insurance. This may be due to the increasing price of medical care, the increasing severity of obesity–the BMI of individuals at the 95th body weight percentile has increased over time–or the aging of the population in the panel.

As a falsification test, the authors use a similar difference-in-difference estimation strategy comparing the obese vs. non-obese wage gap between employers with and without other fringe benefits (e.g.: life insurance, dental insurance, retirement benefits, child care, maternity leave, etc.). If obesity does not affect the cost of these fringe benefits, than we should see no difference in the obese/non-obese wage gap between employers who do and do not offer these benefits. The authors find that this difference-in-difference estimator is not statistically different from zero.

There are a few problems with this analysis. First the authors admit that “those with relatively low productivity due to health consequences of obesity may consume more medical care and, as a result, self select into firms offering health insurance.” Also, the data the authors have only reveals whether or not the individual has health insurance, and does not give the insurance premium paid by either the employer or the employee. Thus, these estimates are likely to be very imprecise.

Nevertheless, if this study’s results are true, then it would imply the following:

“If there are no externalities in these decisions, then “twinkie” taxes will only distort already optimal decisions. But if employer-provided insurance pools the health risk of the obese and non-obese, it will create an externality that reduces incentives to maintain a normal weight. Our evidence on the incidence of the obesity wage premium suggests that pooling of the obese and non-obese does not occur in the employer-sponsored insurance market; hence the externalities caused by health insurance on decisions about body weight are small.

• Jay Bhattacharya and M. Kate Bundorf (2005) “The Incidence of Healthcare Costs of Obesity,” NBER WP #11303.
• Finkelstein, Fiebelkorn and Wang (2003) “National Medical Spending Attributable To Overweight And Obesity: How Much, And Who’s Paying?,” Health Affairs, Web Exclusive, May 14, 2003.

Freakonomics by Steven Levitt and Stephen J. Dubner is an extremely popular book that has made economics a (somewhat) sexy topic of discussion. Levitt’s research makes economics exciting and his quirky, controversial studies make interesting reading.

John DiNardo, however, thinks that even Freakonomics is “interesting” and “entertaining,” it may not be revealing truths. Dr. DiNardo has written three critical reviews of the book. DiNardo’s criticisms call into doubt the meaning of some of the conclusions derived from Levitt’s research. For instance, DiNardo discusses the logical meaning the causal effect of obesity on health.

Nonetheless, I would argue that it is unlikely that anyone will devise a severe test of the proposition that obesity causes an increase in all-cause mortality. Simply put, the effect of obesity (or of ideal weight) is inextricably implementation specific. That is, it is not helpful to think about the “effect” of obesity for the same reason it is not helpful to debate the “causal effect of race on income”(Granger 1986). Many of us suspect, for example, that encouraging obese individuals to “starve themselves” for short periods of time might help one lose weight, but wouldn’t necessarily promote longevity (although it might, who knows? ).

Similarly, we might expect weight loss that results from increased physical activity to be more protective than
weight loss that results from increased life stress. The experience in the U.S. with the drugs fenfluramine and dexfenfluramine (Redux) is a case in point. Despite good evidence that the causal effect of taking Redux was weight loss, the drugs were pulled from the market because a “side effect” of the medication was an increase in potentially serious heart problems (Food and [Drug] Administration 1997) . Indeed, it would appear that the presumption that obesity is a cause of ill health made it virtually impossible to debate whether non–obesity was the cause of the increased heart problems. Rather, the consensus seems to be that the heart problems were not caused by non–obesity, but rather by Redux’s “side effects.”

My point is simple: when each way of “assigning” obesity that we can imagine would be expected to produce a different effect on all–cause mortality or other outcome, it is not at all clear that it is helpful to debate the “effect of obesity.” It seems more intelligible (and more policy relevant) to discuss the effect of Redux or exercise than it is to talk about the “effect” of obesity.

One study that DiNardo does hold up as an example of fine research is Cullen, Jacob and Levitt (Econometrica 2006). This paper was written by Levitt as well as my dissertation advisor Julie Cullen.

• John Dinardo (2007). “Interesting Questions in Freakonomics .” Journal of Economic Literature, Volume 45, Number 4, pp. 973-1000(28)
• Julie Berry Cullen, Brian A Jacob, Steven Levitt (2006) “The Effect of School Choice on Participants: Evidence from Randomized Lotteries.” Econometrica 74 (5) , 1191–1230 doi:10.1111/j.1468-0262.2006.00702.x

Are you friends members of the Marathon Runner’s of America club or the Bratwurst and Philly Cheesesteak club? If the answer is the later, you are much more likely to be obese than the former.

This is the finding of a 2007 NEJM paper by Christakis and Fowler. Obese individuals are more likely to be friends, relatives, or spouses with other obese people (and vice versa). The authors contend that there are 3 explanations for why this could be the case empirically.

1. Homophily. This means that individuals choose to associate with people who look like them. In this case, social networks would not cause obesity, it is just that obese individuals choose to hang out with other obese individuals.
2. Counfounding factors. Siblings have the same genes. Obesity social norms within a particular geographic area may affect friends and family in a similar manner. These unobserved, confounding variables may also be the true cause of why
3. Induction. Social influence and peer effects may effect the obesity level of each person in a group. The authors hypothesize that this explanation to be the major avenue by which social networks affect obesity.

The paper tracks a database of 12,067 individuals over 32 years. The regressions use a lagged dependent variable to eliminate problems of serial correlation.

Results

Let us define the ‘ego‘ the person as the person whose behavior is being analyze and the ‘alter’ as a person connected to the ego by a social network. When the ego’s alter is a friend and becomes obesity, there is a 57% chance that the ego will become obese. This impact is larger for same sex friendships (71% probability of become obese if the alter becomes obese) than opposite sex friendships (effect not different from zero).

How does the obesity of one’s spouse affect the ego’s obesity? According to the authors, “[a]mong married couples, when an alter became obese, the spouse was 37% more likely (95% CI, 7 to 73) to become obese. Husbands and wives appeared to affect each other similarly (44% and 37%, respectively).”

What explains this phenomenon that the alter’s obesity will affect the ego’s obesity. It is possible that the social network as a whole experiences similar life events which affect obesity. However, even when alter’s live geographically far from the ego–and thus likely have different life experience over time–this does not change the effect the alter’s obesity has on the ego. Christakis and Fowler claim that this supports their perception that social norms heavily influence obesity. Also, the spread of smoking behavior does not affect the spread of obesity. One would guess that social networks would have a similar effect on smoking and obesity. The authors claim that this finding, “…suggests that the psychosocial mechanisms of the spread of obesity may rely less on behavioral imitation than on a change in an ego’s general perception of the social norms regarding the acceptability of obesity.”

• Christakis NA, Fowler JH. 2007. “The spread of obesity in a large social network over 32 years.” New England Journal of Medicine. 357(4): 370-379.

Why do people want to lose weight? While this seems like an obvious question, it does merit answering. There are two major reasons: health concerns and appearance. Being obese increases the risk of suffering from many diseases (e.g.: diabetes). On the appearance side, individuals may experience social pressure to lose (or possibly gain) weight. Further, individuals may want to maintain a healthy body appearance to attract a mate.

Jeffery Sobal is an expert in obesity studies. According to his 2003 study, activities which directly affect weight are caloric intake, physical activity and smoking.

One of the more interesting questions is how an individual’s marriage status affects obesity. It is generally found that–even controlling for age and other covariates–married individuals are more likely to be overweight than non-married individuals. Why is this the case. Sobal cites some studies which attempt to explain this.

• Entering into marriage results in higher food intake. Craig & Truswell (1988).
• Marriage may change the physical activity level of the individuals. Some studies find that married individuals are more active (King, Kiernan, Ahn, & Wilcox 1998) other that they are less active (Myers, Weigel, & Holliday 1989, Verhoef, Love & Rose 1992), and still others find no relationship between marriage and physical activity (Hirvensalo, Lintunen & Rantanen 2000, Umberson 1992, Van den Hombergh, Schouten, Van Staveren, van Amelsvoort, & Kok 1995.).
• Smoking has been found to be correlated with lower body weights. Two studies (Venters et al. 1989, Waldron & Lye 1989) have found that married individuals are less likely to smoke than single, divorced, or widowed individuals. Two other sutides found that people who enter marriage are more likely to stop smoking (Waldron & Lye 1989, Wee, Rigotti, Davis & Phillips 2001).
• Umberson 1992 found that after 3 years, Americans who exited marriage had lower weights than those who remained married. In a six year study, Finnish individuals who got married gained weight and those who were widowed lost weight (Rissanen, Heliovaara, Knekt, Reunanen & Aromaa, 1991). Three studies by Kahn and Williamson use a 10 year panel of U.S. residents and find individuals gained weight upon entering marriage and lose weight upon exiting marriage (Kahn & Williamson 1990, Kahn & Williamson 1991, and Kahn, Williamson and Stevens 1991). These findings hold for both men and women in these two studies.
• While most studies do find that married individuals weight more than nonmarried, there are some subtleties to this statement. A paper by French et al. 1993 using 2-year data on US men and women found that women gained weight after they married, but men did not.

After citing all this evidence, Sobal and co-authors state 4 hyptotheses to test:

1. Marital trajectories that are stable are related to stable body weights,
2. marital trajectories entering marriage are related to weight gain,
3. marital trajectories dissolving marriage are related to weight loss,
4. marital trajectories involving the death of a spouse are related to weight loss.

Sobal uses data from from the National Health and Nutritional Examination Survey (NHANES I). A 10 year follow up survey of the participants is collected in the National Health and Nutrition Epidemiological Followup Survey (NHEFS). The authors use an OLS specification with a lagged dependent variable (i.e., lagged BMI) in order to estimate the impact of marital status on weight. Sobal, Rauschenbach and Frongillo conclude the following:

1. Stable marital trajectories were not associated with significant weight changes, except for weight loss among men who remained separated/divorced.
   
2. Marital trajectories involving entry into marriage were associated with weight gain among women, but not among men.
   
3. Marital trajectories involving dissolving marriages were associated with weight loss among men, but not women.
   
4. Marital trajectories involving death of a spouse were associated with weight loss among men, but not women.
   
5. Marital and other demographic characteristics were better predictors of weight loss than weight gain.

• Sobal J, Rauschenbach B, Frongillo EA., 2003. “Marital status changes and body weight changes: a US longitudinal analysis.” Social Science and Medicine, 56(7): 1543-55.

According to the Daily Mail (…obesity epidemic…) the NHS could give “vouchers to the overweight to spend on healthy food in supermarkets” or cash prizes to those who manage to lose weight. The UK could also mandate cooking classes in school and more time for physical education classes.

The UK report on obesity states: “We need to rework the incentives for individuals and public bodies to encourage actions now, thereby avoiding much larger costs in later years.”

But will decreasing obesity save the government money? Not according to a recent paper in the PLoS Medicine titled “Lifetime Medical Costs of Obesity: Prevention No Cure for Increasing Health Expenditure.” The paper finds that healthy people have more lifetime medical costs that either obese individuals or smokers. How can this be the case? It is true, that each year an obese individual lives they will incur more medical costs than a healthy person. In particular, spending on heart disease, diabetes, and musculoskeletal diseases. Since a healthy person lives longer, however, the healthy person has more years of medical expenditures which will accumulate compared to an obese individual. Similarly, smokers have higher medical costs per year but since they have a shorter life expectancy, smokers actually incur fewer medical costs over their lifetime than healthy individuals.

It seems that giving prizes to obese individuals for losing weight will not only be costly in terms of the tax revenue needed to fund the project, but will also increase medical expenditures if people do in fact lose weight. The Healthcare Economist is proposing a revolutionary concept: let each individual choose their own weight make their own lifestyle choices without any government interference.

• van Baal PHM, Polder JJ, de Wit GA, Hoogenveen RT, Feenstra TL, et al. (2008) Lifetime medical costs of obesity: Prevention no cure for increasing health expenditure. PLoS Med 5(2): e29. doi:10.1371/journal.pmed.0050029

How do we measure the financial burden of elderly obesity? At first this seems like an easy question to answer. Find the average medical spending of the obese elderly and compare that to the spending of an elderly individual of healthy weight.

Yet causation is difficult to show.

True, it is possible that the obese may be more likely to get sick and thus incur higher costs, but it is also possible that sick people can gain weight–since it is difficult to exercise when sick–which can cause more obesity. Thus, the original sickness and not the obesity may be the true cause of the additional medical expenses.

A 2007 Health Services Research paper by Yang and Hall try to examine this question. They use panel data from the Medicare Current Beneficiary Survey (MCBS). The authors use a maximum likelihood estimation strategy, modeling current BMI as a function of last year’s BMI and Acute Medical Events. Acute Medical Events are also a function of BMI in a separate estimating equation. Health care expenditure is a function of BMI, BMI-squared, functional status, chronic and acute disease and demographics.

To identify this system of questions, the authors uses the following exogenous variables: average food prices, density of fast food restaurants and air quality. Using these instruments, the authors find that “elderly men who were overweight or obese at age 65 had 6–13 percent more lifetime health care expenditures than the same age cohort within normal weight range at age 65. Elderly women who were overweight or obese at age 65 spent 11–17 percent more than those in a normal weight range.”

• Yang Z, Hall AG, (2007) “The Financial Burden of Overweight and Obesity among Elderly Americans: The Dynamics of Weight, Longevity, and Health Care Cost” HSR, Early Online Edition

Do state physical education (PE) requirement help to decrease the percentage of children and teens who are overweight?

This is the question Cawley, Meyerhoefer and Newhouse investigate in their 2007 Health Economics paper.

One would certainly not be surprised if PE requirements decrease the prevalence of obesity, but this may not be correct.  PE requirements may have no effect if schools do not comply with the state mandates, or increased PE exercise may lead to decreased exercise outside of school (substitution).  Further, it is possible that PE classes may do little to promote exercise.  For instance, 12 states allow students to earn PE credit online.

To find the truth, the authors use Youth Risk Behavior Surveillance System data from the 1999, 2001, and 2003.  The authors attempt to find the local average treatment effect (LATE) by using state PE requirements as an instrument for whether or not a given student has taken a PE class.

Cawley and co-authors conclude that “high school students with a binding PE requirement report an average of 31 additional minutes per week spent physically active in PE class. Our results also indicate that additional PE time raises the number of days per week that girls report having exercised vigorously or having engaged in strength-building activity. We find no evidence that PE lowers BMI or the probability that a student is overweight.”

• John Cawley, Chad Meyerhoefer, and David Newhouse (2007) “The impact of state physical education requirements on youth physical activity and overweight.” Health Economics.Volume 16, Issue 12 , Pages 1287 - 1301

On Wednesday, I reviewed a paper by John Cawley and Feng Liu about the mechanisms by which maternal employment can affect childhood obesity. It turns out that Cawley and Liu aren’t the only ones interested in this issue. A recent working paper by Fertig, Glomm and Tchernis investigates the same question.

The authors use time diaries from the Child Development Supplement to the PSID. They use two regressions to test their hypothesis. First, they regress BMI on the amount of time spent in various activities (e.g.: eating, watching TV, playing video games). The second regression measures how maternal employment impacts each one of these activities. In general, these regressions are estimated using OLS, but some activities are count variables (e.g.: number of meals in an average day) and the authors use a Poisson regression in these cases.

For the Poisson regression to be accurate, one must assume the mean and variance of the distribution must be the same. I would have preferred for the authors to use a negative binomial regression to increase flexibility, but I do not know whether this methodological alteration would change the results.

Some of the results of the paper are not surprising. For instance, maternal employment leads to more TV watching for the children and more TV watching leads to more childhood obesity.

Yet other results are interesting. Cawley and Liu found that working mothers cook fewer meals at home and that lead to more childhood obesity. Fertig and co-authors also found that working mothers cook fewer meals at home, but that the percentage of meals eaten at home did not affect childhood obesity in a statistically significant manner.

One of the major determinants of childhood obesity is the number of meals they eat. Missing breakfast and eating fewer meals, according to the authors, “may lead to higher concentrations of 24 hour insulin, which, in turn, can lead to increased fat deposition and higher body weight.” Children of working mothers eat fewer meals and having fewer meals significantly increases obesity.

Maybe breakfast is the most important meal of the day.

• Fertig A, Glomm G, Tchernis R, 2006. “The Connection between Maternal Employment and Childhood Obesity: Inspecting the Mechanisms” CAEPR Working Paper #2006-020.

Thanks to Scott Cunningham for sending me this working paper.

A general result in the obesity literature, is that higher female labor participation rates lead to higher obesity rates in children. For instance, the 1996 Welfare Reform act (PRWORA) increased work requirements for low-income mothers and thus increased labor participation and likely childhood obesity. One question which has not been resolved yet thorough which mechanisms does the mother’s employment increase childhood obesity.

One of the first attempts to answer this question is by John Cawley and Feng Liu (NBER 2007). They use 2003-2006 data from the American Time Use Survey to analyze how employment affects various household activities. The authors estimate a two-part model (probit for whether or not any time was spent in the activity and OLS estimating how employment affects the amount of time spent in each activity). The authors also use the state unemployment rate as an instrument in the first stage for female labor participation.

The authors find that female employment leads to fewer meals prepared at home. This is seem through a 5 percentage point lower probability of grocery shopping, 13 percentage point lower probability of doing any cooking, 10 percentage point lower probability of eating with the children. Working mothers who engage in these activities on average still spend fewer minutes preforming these tasks.

Often, when mothers spend less time with children, this results in more sedentary activity–primarily watching television. The authors found that working mothers engage in less time playing with the child, less time engaged in child care and child supervision as well.

The authors find some evidence that working women who have a husband or partner in the household reduce time spent with their children to a greater extent than single mothers since the husband spend some time with the child.

This research may lead one to believe that the Welfare-to-Work legislation may have helped reduce reliance on welfare and the number of single mothers who are unemployed, but may have also increased childhood obesity rates throughout the country.

• Cawley, John; Liu, Feng (2007) “Maternal Employment and Childhood Obesity: A Search for Mechanisms in Time Use Data” NBER Working Paper #13600.

Are married people more likely to be obese than single individuals? More to the point, does being married cause obesity? Married individuals are generally older than never-married individuals and since age is correlated with obesity, there could be a spurious relationship between marriage and obesity.

One may think that married individuals are not on the “single’s market” and thus may not have a strong incentive to maintain an athletic physical appearance to attract mates. As stated in Sobal (1984), “We may hypothesize that as a marital relationship becomes solidified the partners may feel less need to maintain external appearances important in attracting a mate.” On the other hand, a paper by Rand, Kuldau and Robbins (JAMA 1982) found that individuals who had jejunoileal bypass surgery to decrease obesity had improved marriage relationships. Thus, those who value their marriage may wish to avoid being overweight to make the marriage experience more pleasurable.

If healthier individuals can more easily attract a mate, than it would be the case that married individuals will be less overweight than single individuals. Averett and Korenman (Int J Obesity 1999) found that obesity is associated with a lower probability of marriage. Gortmaker et al. (NEJM 1993) use the NLSY to conclude that individuals who where overweight in their adolescent years are 20% less likely to be married seven years later than a healthy-weighted individual. Cawley, Joyner and Sobal (Rationality and Society 2006) confirm that for adolescents “dating is less likely among heavier girls and boys and among shorter girls and boys.”

Sobal, Rauschenbach and Frongillo (Soc Sci Med 1992) categorizes the relationship between obesity as marriage through two distinct mechanisms: “marital selection” and “marital causation.” Non-overweight people are more likely to attract a mate, and thus “select” into marriage. However, if marriage “causes” weight gain–due to a more sedentary lifestyle, lower mate attraction incentive, childbirth, etc.–than a researcher may find that married individuals are more overweight on average.

The best way to control for these two conflicting effects is to use a panel data set. Cawley (JHR 2004) employs the 1979 NLSY, using lagged BMI as an instrument for current BMI and individual fixed effects to control for time-invariant individual characteristics. Other studies have used sibling weight (Avarett and Kroenman (JHR 1996), or spousal weight as an instrument for current BMI. Using data from the National Survey of Personal Health practices and consequences, the Sobal, Rauschenbach and Frongillo paper finds that “it appears that there is a relationship between fatness and marital status for men, with married men fatter and more obese.”

Nevertheless, more research is needed to refine the exact manner in which marriage affects obesity.

• Averett S and Korenman S. 1996. “The Economic Reality of the Beauty Myth.” J Human Resources. 31(2): 304-330.
• Averett S and Korenman S. 1999. “Black-white differences in social and economic consequences of obesity.” International Journal of Obesity. vol 23, pp. 166-173.
• Cawley J. 2004. “The Impact of Obesity on Wages” J Human Resources. 39(2): 451-474.
• Cawley J, Koyner K, Sobal J. 2006. ”Size Matters: The influence of adolescents’ weight and height on dating and sex.” Rationality and Society. Vol. 18, No. 1, 67-94.
• Gortmaker SL, Must A, Perrin JM, Sobol AM, Dietz WH. 1993. “Social and Economic Consequences of Overweight in Adolescence and Young Adulthood.” NEJM. 329(14): 1008-1012.
• Rand CS, Kuldau JM, Robbins L. 1982. “Surgery for Obesity and Marriage Quality.” 247(10): 1419-1422.
• Sobal J. 1984. “Marriage, Obesity and Dieting.” Marriage and Family Review. 7:115-139.
• Sobal J, Rauscehnbach BS, Frongillo EA. 1992. “Marital Status, Fatness and Obesity.” Social Science and Medicine. 35(7): 915-923.

The incapacity benefit system in the UK is intended to provide an income support for those unable to work.  Like any government program, many of the beneficiaries are in dire need of the money and are truly unable to work, but many other individuals who are able–but not inclined–to work have taken advantage of government largesse.  Liberals will highlight the fact that these programs help the needy while conservatives will generally retort with numerous examples of how individuals are able to take advantage of ‘the system.’

Last week, The Times of London reported (’Too fat to work‘) that “Almost two thousand people who are too fat to work have been paid a total of £4.4 million in benefit.”  Should obese individuals receive a disability benefit?  If obesity is truly a disease, than one may say yes.  On the other hand, there is a seemingly simple cure for obesity–eat less and exercise more.  For those who are obese, however, accomplishing this physiological feat is not as simple as it sounds.  It is possible that the incapacity benefit may actually make the obese worse off.  Allowing the obese to collect an incapacity benefit may reduce an overweight individual’s incentive to lose weight in order to be able to work.

Any input on this subject would be greatly appreciated.

Thanks to my colleague Mike Ewens for the referral to the Times article.