TY - JOUR
T1 - The impact of BMI on mental health
T2 - Further evidence from genetic markers
AU - Amin, Vikesh
AU - Flores, Carlos A.
AU - Flores-Lagunes, Alfonso
N1 - Funding Information:
We gratefully acknowledge the comments from three anonymous referees and Associate Editor Ásgeirsdóttir that considerably improved the paper. The authors acknowledge research funding from NIH grant number 1R01HD094011-01 and thank the research assistance of Giuseppe Germinario. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due to Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis. The Health and Retirement Study (HRS accession number 0925-0670) is sponsored by the National Institute on Aging (grant numbers NIA U01AG009740, RC2AG036495, and RC4AG039029) and is conducted by the University of Michigan. Additional funding support for genotyping and analysis were provided by NIH/NICHDR01 HD060726.
Funding Information:
We gratefully acknowledge the comments from three anonymous referees and Associate Editor Ásgeirsdóttir that considerably improved the paper. The authors acknowledge research funding from NIH grant number 1R01HD094011-01 and thank the research assistance of Giuseppe Germinario. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development , with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due to Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website ( http://www.cpc.unc.edu/addhealth ). No direct support was received from grant P01-HD31921 for this analysis. The Health and Retirement Study (HRS accession number 0925-0670) is sponsored by the National Institute on Aging (grant numbers NIA U01AG009740 , RC2AG036495 , and RC4AG039029 ) and is conducted by the University of Michigan. Additional funding support for genotyping and analysis were provided by NIH/NICHD R01 HD060726 .
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/8
Y1 - 2020/8
N2 - We estimate the effect of BMI on mental health for young adults and elderly individuals using data from the National Longitudinal Study of Adolescent Health and the Health & Retirement Study. To tackle confounding due to unobserved factors, we exploit variation in a polygenic score (PGS) for BMI within two related econometric methods that differ in the assumptions they employ. First, we use the BMI PGS as an IV and adjust for PGSs for other factors (depression and educational attainment) that may invalidate this IV. We find a large statistically significant effect of BMI on mental health for the elderly: a 5 kg/m2 increase in BMI (a difference equivalent to moving from overweight to obese) increases the probability of depression by 29 %. In contrast, for young adults the IV estimates are statistically and economically insignificant. We show that IV estimates likely have to be interpreted as identifying a weighted average of effects of BMI on mental health mostly for compliers on the upper quantiles of the BMI distribution. Second, we use the BMI PGS as an “imperfect” IV and estimate an upper bound on the average treatment effect for the population. The estimated upper bounds are consistent with the conclusions from the IV estimates.
AB - We estimate the effect of BMI on mental health for young adults and elderly individuals using data from the National Longitudinal Study of Adolescent Health and the Health & Retirement Study. To tackle confounding due to unobserved factors, we exploit variation in a polygenic score (PGS) for BMI within two related econometric methods that differ in the assumptions they employ. First, we use the BMI PGS as an IV and adjust for PGSs for other factors (depression and educational attainment) that may invalidate this IV. We find a large statistically significant effect of BMI on mental health for the elderly: a 5 kg/m2 increase in BMI (a difference equivalent to moving from overweight to obese) increases the probability of depression by 29 %. In contrast, for young adults the IV estimates are statistically and economically insignificant. We show that IV estimates likely have to be interpreted as identifying a weighted average of effects of BMI on mental health mostly for compliers on the upper quantiles of the BMI distribution. Second, we use the BMI PGS as an “imperfect” IV and estimate an upper bound on the average treatment effect for the population. The estimated upper bounds are consistent with the conclusions from the IV estimates.
KW - BMI
KW - Depression
KW - Genetics
KW - Instrumental variables
UR - http://www.scopus.com/inward/record.url?scp=85086914453&partnerID=8YFLogxK
U2 - 10.1016/j.ehb.2020.100895
DO - 10.1016/j.ehb.2020.100895
M3 - Article
C2 - 32603998
AN - SCOPUS:85086914453
SN - 1570-677X
VL - 38
JO - Economics and Human Biology
JF - Economics and Human Biology
M1 - 100895
ER -