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RESEARCH PAPER
The effects of smoking on obesity: evidence from Indonesian panel data
1
Department of Economics, Konkuk University, Gwangjin-gu, South Korea
Submission date: 2015-04-15
Acceptance date: 2015-11-16
Publication date: 2015-11-26
Corresponding author
Kitae Sohn
Department of Economics, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, South Korea
Department of Economics, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, South Korea
Tobacco Induced Diseases 2015;13(November):39
KEYWORDS
ABSTRACT
Background:
It has been known that smoking is negatively related to weight-related outcomes. However, it has been difficult to determine whether the relationship is causal, and if so, how strong it is. We attempted to estimate the approximately causal effects of smoking on weight, body mass index (BMI), and obesity.
Methods:
The Indonesian Family Life Survey provided a sample of over 9000 men aged 15–55 years—each of them was observed in 1993, 1997, 2000 and 2007. The preferred method was a fixed effects model; that is, we related changes in smoking status or smoking intensity to changes in weight-related outcomes, while controlling for time-varying covariates. We also compared these results to those estimated by ordinary least squares and assessed the importance of controlling for time invariant individual heterogeneity.
Results:
Although the effects of smoking were precisely estimated in a statistical sense, their size was minuscule: a quitter would gain weight by at most 1 kg, or a smoker would lose weight by the same amount. The results were similar for BMI and obesity. When we did not control for time invariant individual heterogeneity, the size of the relationship was overestimated at least three times.
Conclusions:
Smoking exerted little influence on weight, and it was important to control for bias stemming from time invariant individual heterogeneity.
It has been known that smoking is negatively related to weight-related outcomes. However, it has been difficult to determine whether the relationship is causal, and if so, how strong it is. We attempted to estimate the approximately causal effects of smoking on weight, body mass index (BMI), and obesity.
Methods:
The Indonesian Family Life Survey provided a sample of over 9000 men aged 15–55 years—each of them was observed in 1993, 1997, 2000 and 2007. The preferred method was a fixed effects model; that is, we related changes in smoking status or smoking intensity to changes in weight-related outcomes, while controlling for time-varying covariates. We also compared these results to those estimated by ordinary least squares and assessed the importance of controlling for time invariant individual heterogeneity.
Results:
Although the effects of smoking were precisely estimated in a statistical sense, their size was minuscule: a quitter would gain weight by at most 1 kg, or a smoker would lose weight by the same amount. The results were similar for BMI and obesity. When we did not control for time invariant individual heterogeneity, the size of the relationship was overestimated at least three times.
Conclusions:
Smoking exerted little influence on weight, and it was important to control for bias stemming from time invariant individual heterogeneity.
REFERENCES (36)
1.
Chiolero A, Faeh D, Paccaud F, Cornuz J. Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr. 2008;87(4):801–9.
2.
Klesges RC, Meyers AW, Klesges LM, LaVasque ME. Smoking, body weight, and their effects on smoking behavior: a comprehensive review of the literature. Psychol Bull. 1989;106(2):204–30.
3.
US Department of Health and Human Service. The health benefits of smoking cessation: a report of the surgeon general. Rockville: Office on Smoking and Health; 1990.
4.
Chou S-Y, Grossman M, Saffer H. An economic analysis of adult obesity: results from the behavioral risk factor surveillance system. J Health Econ. 2004;23(3):565–87. doi:10.1016/j.jhealeco.2003.10.003.
5.
Chou S-Y, Grossman M, Saffer H. Reply to jonathan gruber and michael frakes. J Health Econ. 2006;25(2):389–93. doi:10.1016/j.jhealeco.2005.12.004.
6.
Gruber J, Frakes M. Does falling smoking lead to rising obesity? J Health Econ. 2006;25(2):183–97. doi:10.1016/j.jhealeco.2005.07.005.
7.
Nonnemaker J, Finkelstein E, Engelen M, Hoerger T, Farrelly M. Have efforts to reduce smoking really contributed to the obesity epidemic? Econ Inq. 2009;47(2):366–76. doi:10.1111/j.1465-7295.2008.00147.x.
8.
Baum CL. The effects of cigarette costs on bmi and obesity. Health Econ. 2009;18(1):3–19. doi:10.1002/hec.1340.
9.
Fang H, Ali MM, Rizzo JA. Does smoking affect body weight and obesity in china? Econ Hum Biol. 2009;7(3):334–50. doi:10.1016/j.ehb.2009.07.003.
10.
Ng M, Freeman MK, Fleming TD, Robinson M, Dwyer-Lindgren L, Thomson B, et al. Smoking prevalence and cigarette consumption in 187 countries, 1980–2012. JAMA. 2014;311(2):183–92.
11.
Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med. 2006;3(11):e442.
12.
World Health Organization. Obesity: prevention and managing the global epidemic: report of a who consultation. Who technical report series. Geneva: World Health Organization; 2000.
13.
Popkin BM, Adair LS, Ng SW. Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev. 2012;70(1):3–21. doi:10.1111/j.1753-4887.2011.00456.x.
14.
Sohn K. A note on the effects of education on youth smoking in a developing country. J Asia Pac Econ. 2013;19(1):66–73. doi:10.1080/13547860.2013.803845.
15.
Grilo CM, Pogue-Geile MF. The nature of environmental influences on weight and obesity: a behavior genetic analysis. Psychol Bull. 1991;110(3):520–37.
16.
Keskitalo K, Silventoinen K, Tuorila H, Perola M, Pietiläinen KH, Rissanen A, et al. Genetic and environmental contributions to food use patterns of young adult twins. Physiol Behav. 2008;93(1–2):235–42.
17.
Rowe DC. The limits of family influence: genes, experience, and behavior. New York: Guilford Press; 1994.
18.
Cawley J, Markowitz S, Tauras J. Lighting up and slimming down: the effects of body weight and cigarette prices on adolescent smoking initiation. J Health Econ. 2004;23(2):293–311. doi:10.1016/j.jhealeco.2003.12.003.
19.
Rees DI, Sabia JJ. Body weight and smoking initiation: evidence from add health. J Health Econ. 2010;29(5):774–7. doi:10.1016/j.jhealeco.2010.07.002.
20.
Sohn K. Sufficiently good measures of obesity: the case of a developing country. J Biosoc Sci. 2014;46(6):797–817. doi:10.1017/S0021932013000692.
21.
World Health Organization. The asia-pacific perspective: redefining obesity and its treatment. Geneva: World Health Organization; 2000.
22.
Sohn K. Age and size at maturity in indonesian women: a norm of reaction? Am J Hum Biol. 2014;26(5):713–5. doi:10.1002/ajhb.22571.
23.
Sohn K. The height premium in indonesia. Econ Hum Biol. 2015;16:1–15. doi:10.1016/j.ehb.2013.12.011.
24.
Sohn K. The value of male height in the marriage market. Econ Hum Biol. 2015;18:110–24.
25.
Sohn K. Height and happiness in a developing country. J Happiness Stud. forthcoming. doi:10.1007/s10902-014-9566-8.
26.
Sohn K. Is leg length a biomarker of early life conditions? Evidence from a historically short population. Am J Hum Biol. 2015;27(4):538–45. doi:10.1002/ajhb.22682.
27.
Sohn K. Job strenuousness and obesity: the case of a developing country. J Dev Stud. 2014;50(9):1289–301. doi:10.1080/00220388.2014.925543.
28.
Sohn K. Does a taller husband make his wife happier? Pers Indiv Differ. forthcoming.
29.
Sohn K. The influence of birth season on height: Evidence from Indonesia. Am J Phys Anthropol. 2015;157:659–65.
30.
Sohn K. The role of spousal income in the wife’s happiness. Soc Indic Res. forthcoming.
31.
Sohn K. Gender discrimination in earnings in Indonesia: a fuller picture. B Indones Econ Stud. 2015;51:95–121.
32.
Sohn K. Monetary and nonmonetary returns to education in Indonesia. Dev Econ. 2013;51:34–59.
33.
Sohn K. Forthcoming. Is age at menarche a good predictor of future body fat? the case of a developing country. Health Care Women In. forthcoming.
34.
Gonçalves RB, Coletta RD, Silvério KG, Benevides L, Casati MZ, Da Silva JS, et al. Impact of smoking on inflammation: overview of molecular mechanisms. Inflamm Res. 2011;60(5):409–24.
35.
Hotamisligil GS. Inflammation and metabolic disorders. Nature. 2006;444(7121):860–7.
36.
Lakdawalla D, Philipson T. The growth of obesity and technological change. Econ Hum Biol. 2009;7(3):283–93. doi:10.1016/j.ehb.2009.08.001.
CITATIONS (6):
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Risk Incomprehension and Its Economic Consequences
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The Journal of Development Studies
3.
Insights into the association between smoking and obesity: the 2014 Indonesian Family Life Survey
Yusuf Nawawi, Afsheen Hasan, Liza Salawati, Husnah, Widiastuti
Medical Journal of Indonesia
Yusuf Nawawi, Afsheen Hasan, Liza Salawati, Husnah, Widiastuti
Medical Journal of Indonesia
4.
Better Dietary Knowledge and Socioeconomic Status (SES), Better Body Mass Index? Evidence from China—An Unconditional Quantile Regression Approach
Jie Yu, Xiao Han, Hongxing Wen, Jinzheng Ren, Lihong Qi
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Nutrients
5.
Underweight, overweight, and tobacco use among adolescents
aged 12–15 years: Evidence from 23 low-income and middle-income
countries
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Tobacco Induced Diseases
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6.
What makes Indonesian government officials believe in and implement evidence-based policy: The mediating role of religion-science compatibility beliefs
Andries Lionardo, Faisal Nomaini, Oemar Madri Bafadhal, Anang Dwi Santoso, Alfitri
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Andries Lionardo, Faisal Nomaini, Oemar Madri Bafadhal, Anang Dwi Santoso, Alfitri
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