An economic analysis of adult obesity: results from the Behavioral Risk Factor Surveillance System

Chou, Shin‐Yi; Grossman, Michael; Saffer, Henry

doi:10.1016/j.jhealeco.2003.10.003

Cited by 853 publications

(552 citation statements)

References 28 publications

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“…Speculatively, the bias usually found in self-reported measurements might have been reduced in the NHANES due to knowledge about the upcoming physical exam. It also suggests that adjusting self-reports in other datasets using the difference between self-reports and measured height and weight in the NHANES is not valid (performed, for instance, in [39,40]). More generally, exploring differences in self-reported and measured BMI by race/ethnicity and SES would be an interesting topic for future research.…”

Section: Discussionmentioning

confidence: 99%

BMI Trends, Socioeconomic Status, and the Choice of Dataset

Grabner

2012

Obes Facts

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Objective:This study is a descriptive investigation of trends in BMI in the USA over time, across race/ethnicity, gender, and socioeconomic status (SES) groups, and across different datasets. Methods: The study analyzes micro-level data from three widely used cross-sectional US health datasets: the National Health and Nutrition Examination Survey (NHANES), the National Health Interview Survey (NHIS), and the Behavioral Risk Factor Surveillance System (BRFSS), from the 1970s to 2008. Consistent race/ethnicity and SES groups are constructed for all datasets. SES is measured by education and income. Focusing on adults aged 20–74 years, the study estimates BMI time trends, distributional shifts, and incremental associations (gradients) with SES. Results: SES-BMI gradients are consistently larger for women than for men, differ across race/ethnicity groups, and are similar across datasets. Trends in mean BMI are comparable across White, Black and Hispanic males, while Hispanic females range between White and Black females. Self-reported BMI in the NHANES differs markedly from self-reports in the NHIS and BRFSS. Conclusion: The NHANES, NHIS, and BRFSS provide similar evidence regarding BMI trends over time and across race/ethnicity, gender, and SES groups. Racial disparities in BMI remain after adjusting for SES and should be studied further.

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Section: Discussionmentioning

confidence: 99%

BMI Trends, Socioeconomic Status, and the Choice of Dataset

Grabner

2012

Obes Facts

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“…Another reason might be having less time available for food preparation and consequently eating ''fast food.' ' Chou et al (2004) examined the relationship between relative price levels and BMI. They investigated the effects of the price of a meal in fast food restaurants, the price of food consumed at home, and the price of cigarettes on BMI.…”

Section: Literature Reviewmentioning

confidence: 99%

A Research Note on the Relationship Between Long Working Hours and Weight Gain for Older Workers in the United States

Mercan

2013

Res Aging

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Working long hours may be related to obesity in older adults. No studies have focused on older workers and long work hours, although the risk of obesity is high among this population group. This study is the first attempt to investigate the relationship between obesity and the older workforce. Panel data from the Health and Retirement Study are examined using Cox regression techniques. We found that older workers who work more than 59 hr a week are more likely to gain weight than older workers who work less than 59 hr per week.

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“…That is, technological change has contributed to the rise in obesity either by lowering the cost of consuming calories and/or by raising the cost of expending them (Philipson and Posner 2003). In addition, the prevalence of fast-food restaurants, higher prices of alcohol and cigarettes (Chou et al 2004), lower time costs of food preparation resulting from technological changes in mass food preparation (Cutler et al 2003) and even the rise of sprawl patterns in land development (Plantinga and Bernell 2007;Ewing et al 2003) have been linked to rising obesity. In a cross-country comparison among OECD countries, Loureiro and Nayga (2005) showed that the percentage of female labor force participation positively affects obesity rates.…”

Section: Literature Reviewmentioning

confidence: 99%

Food away from home expenditures and obesity among older Europeans: are there gender differences?

2011

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Older people (i.e., at least 50 years of age) are becoming one of the most important demographic groups in the world. We explore the effect of food away from home expenditures on obesity among the older population in Europe using instrumental variable methods. Several statistical tests were conducted to assess endogeneity of selected variables, the exogeneity, relevance, and validity of instruments used. Our results generally suggest that food-away-from-home expenditure has no statistically significant effect on body mass index (BMI) of older males but is negatively related to BMI of older females.

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An economic analysis of adult obesity: results from the Behavioral Risk Factor Surveillance System

Cited by 853 publications

References 28 publications

BMI Trends, Socioeconomic Status, and the Choice of Dataset

BMI Trends, Socioeconomic Status, and the Choice of Dataset

A Research Note on the Relationship Between Long Working Hours and Weight Gain for Older Workers in the United States

Food away from home expenditures and obesity among older Europeans: are there gender differences?

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