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Smoking and body weight: Evidence using genetic instruments

Author Info

  • Wehby, George L.
  • Murray, Jeffrey C.
  • Wilcox, Allen
  • Lie, Rolv T.
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    Abstract

    Several studies have evaluated whether the high and rising obesity rates over the past three decades may be due to the declining smoking rates. There is mixed evidence across studies – some find negative smoking effects and positive cigarette cost effects on body weight, while others find opposite effects. This study applies a unique approach to identify the smoking effects on body weight and to evaluate the heterogeneity in these effects across the body mass index (BMI) distribution by utilizing genetic instruments for smoking. Using a data sample of 1057 mothers from Norway, the study finds heterogeneous effects of cigarette smoking on BMI – smoking increases BMI at low/moderate BMI levels and decreases BMI at high BMI levels. The study highlights the potential advantages and challenges of employing genetic instrumental variables to identify behavior effects including the importance of qualifying the instruments and the need for large samples.

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    File URL: http://www.sciencedirect.com/science/article/pii/S1570677X11000931
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    Article provided by Elsevier in its journal Economics & Human Biology.

    Volume (Year): 10 (2012)
    Issue (Month): 2 ()
    Pages: 113-126

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    Handle: RePEc:eee:ehbiol:v:10:y:2012:i:2:p:113-126
    Contact details of provider: Web page: http://www.elsevier.com/locate/inca/622964

    Keywords: Smoking; Obesity; Body mass index; Genetic instrumental variables; Quantile regression; Mendelian randomization;

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    Cited by:

    1. Taylor, Amy E. & Davies, Neil M. & Ware, Jennifer J. & VanderWeele, Tyler & Smith, George Davey & Munafò, Marcus R., 2014. "Mendelian randomization in health research: Using appropriate genetic variants and avoiding biased estimates," Economics & Human Biology, Elsevier, vol. 13(C), pages 99-106.
    2. George Wehby & Allen Wilcox & Rolv Lie, 2013. "The impact of cigarette quitting during pregnancy on other prenatal health behaviors," Review of Economics of the Household, Springer, vol. 11(2), pages 211-233, June.
    3. Dodd, Mark C., 2014. "Intertemporal discounting as a risk factor for high BMI: Evidence from Australia, 2008," Economics & Human Biology, Elsevier, vol. 12(C), pages 83-97.
    4. Srinivasan, C.S., 2013. "Can adherence to dietary guidelines address excess caloric intake? An empirical assessment for the UK," Economics & Human Biology, Elsevier, vol. 11(4), pages 574-591.

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