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The Genome-Wide Influence on Human BMI Depends on Physical Activity, Life Course, and Historical Period

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  • Guang Guo
  • Hexuan Liu
  • Ling Wang
  • Haipeng Shen
  • Wen Hu

Abstract

In this analysis, guided by an evolutionary framework, we investigate how the human genome as a whole interacts with historical period, age, and physical activity to influence body mass index (BMI). The genomic influence is estimated by (1) heritability or the proportion of variance in BMI explained by genome-wide genotype data, and (2) the random effects or the best linear unbiased predictors (BLUPs) of genome-wide association studies (GWAS) data on BMI. Data were used from the Framingham Heart Study (FHS) in the United States. The study was initiated in 1948, and the obesity data were collected repeatedly over the subsequent decades. The analyses draw analysis samples from a pool of >8,000 individuals in the FHS. The hypothesis testing based on Pitman test, permutation Pitman test, F test, and permutation F test produces three sets of significant findings. First, the genomic influence on BMI is substantially larger after the mid-1980s than in the few decades before the mid-1980s within each age group of 21–40, 41–50, 51–60, and >60. Second, the genomic influence on BMI weakens as one ages across the life course, or the genomic influence on BMI tends to be more important during reproductive ages than after reproductive ages within each of the two historical periods. Third, within the age group of 21–50 and not in the age group of >50, the genomic influence on BMI among physically active individuals is substantially smaller than the influence on those who are not physically active. In summary, this study provides evidence that the influence of human genome as a whole on obesity depends on historical period, age, and level of physical activity. Copyright Population Association of America 2015

Suggested Citation

  • Guang Guo & Hexuan Liu & Ling Wang & Haipeng Shen & Wen Hu, 2015. "The Genome-Wide Influence on Human BMI Depends on Physical Activity, Life Course, and Historical Period," Demography, Springer;Population Association of America (PAA), vol. 52(5), pages 1651-1670, October.
    • Handle: RePEc:spr:demogr:v:52:y:2015:i:5:p:1651-1670
    DOI: 10.1007/s13524-015-0421-2
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    References listed on IDEAS

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    1. Jason Boardman & Benjamin Domingue & Casey Blalock & Brett Haberstick & Kathleen Harris & Matthew McQueen, 2014. "Is the Gene-Environment Interaction Paradigm Relevant to Genome-Wide Studies? The Case of Education and Body Mass Index," Demography, Springer;Population Association of America (PAA), vol. 51(1), pages 119-139, February.
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    Cited by:

    1. John Cawley & Euna Han & Jiyoon Kim & Edward C. Norton, 2019. "Testing for family influences on obesity: The role of genetic nurture," Health Economics, John Wiley & Sons, Ltd., vol. 28(7), pages 937-952, July.
    2. Davidson, Trent & Vinneau-Palarino, Justin & Goode, Joshua A. & Boardman, Jason D., 2021. "Utilizing genome wide data to highlight the social behavioral pathways to health: The case of obesity and cardiovascular health among older adults," Social Science & Medicine, Elsevier, vol. 273(C).
    3. Augustine Denteh & Daniel L. Millimet & Rusty Tchernis, 2019. "The origins of early childhood anthropometric persistence," Empirical Economics, Springer, vol. 56(6), pages 2185-2224, June.
    4. Pereira, Rita & Biroli, Pietro & von hinke, stephanie & Van Kippersluis, Hans & Galama, Titus & Rietveld, Niels & Thom, Kevin, 2022. "Gene-Environment Interplay in the Social Sciences," OSF Preprints d96z3, Center for Open Science.
    5. Lauren L. Schmitz & Dalton Conley, 2016. "The Impact of Late-Career Job Loss and Genotype on Body Mass Index," NBER Working Papers 22348, National Bureau of Economic Research, Inc.

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