TY - JOUR
T1 - Adiposity and risk of death
T2 - A prospective cohort study of 463,002 adults
AU - Yu, Tsung
AU - Bo, Yacong
AU - Chang, Ly yun
AU - Liu, Xudong
AU - Tam, Tony
AU - Lao, Xiang Qian
N1 - Funding Information:
We thank MJ Health Research Foundation for authorizing us to use the MJ health data (Authorization code: MJHR2019006A). Any interpretation or conclusion described in this paper does not represent the views of MJ Health Research Foundation. We also thank the Health and Welfare Data Science Center, Ministry of Health and Welfare in Taiwan for the help of mortality data linkage. Figure 1 was generated using the SAS macro % RCS_Reg developed by Prof. Loic Desquilbet and his colleagues. This study is in part supported by Environmental Health Research Fund of the Chinese University of Hong Kong ( 7104946 ), China. Yacong Bo is supported by the PhD Studentship of the Chinese University of Hong Kong , China.
Funding Information:
We thank MJ Health Research Foundation for authorizing us to use the MJ health data (Authorization code: MJHR2019006A). Any interpretation or conclusion described in this paper does not represent the views of MJ Health Research Foundation. We also thank the Health and Welfare Data Science Center, Ministry of Health and Welfare in Taiwan for the help of mortality data linkage. Figure 1 was generated using the SAS macro % RCS_Reg developed by Prof. Loic Desquilbet and his colleagues. This study is in part supported by Environmental Health Research Fund of the Chinese University of Hong Kong (7104946), China. Yacong Bo is supported by the PhD Studentship of the Chinese University of Hong Kong, China.
Publisher Copyright:
© 2020 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism
PY - 2021/4
Y1 - 2021/4
N2 - Background: It is crucial to have simple and appropriate measures to identify people with adiposity-related risk. We compared the associations of mortality with body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and body fat percentage (BF%) in a prospective cohort. Methods: A total of 463,002 adults were recruited between 1996 and 2017. Vital data were obtained from the National Death Registry System in Taiwan. Cox proportional hazards model was used to assess the associations of BMI, WC, WHtR, and BF% with mortality. Result: Clear U-shape relationships were observed for all four parameters. In both men and women, the lowest risk of mortality was observed in the BMI category of 23.5–24.9 kg/m2. Regarding WC, men in the third quintile (79.0–82.9 cm) and women in the fourth quintile (70.0–74.9 cm) had the lowest risk of mortality. For WHtR, men in the third quintile (0.46–0.49) and women in the fourth quintile (0.45–0.48) had the lowest risk of mortality. For BF%, both men and women in the fourth quintile (24.0–27.2% and 28.7–32.8%, respectively) had the lowest risk of mortality. The WC, WHtR, and BF% exhibited slightly associations with the risk of mortality across the three BMI categories [low (10.8–20.9 kg/m2), normal (21.0–27.4 kg/m2) and high (27.5–51.7 kg/m2)]. C-statistics of the four parameters ranged from 0.51 to 0.69. Conclusion: Our results suggest that BMI should remain the primary marker for screening excessive adiposity. However, our findings also support the use of the WC, WHtR, and/or BF%, in addition to BMI when assessing the risk of mortality.
AB - Background: It is crucial to have simple and appropriate measures to identify people with adiposity-related risk. We compared the associations of mortality with body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and body fat percentage (BF%) in a prospective cohort. Methods: A total of 463,002 adults were recruited between 1996 and 2017. Vital data were obtained from the National Death Registry System in Taiwan. Cox proportional hazards model was used to assess the associations of BMI, WC, WHtR, and BF% with mortality. Result: Clear U-shape relationships were observed for all four parameters. In both men and women, the lowest risk of mortality was observed in the BMI category of 23.5–24.9 kg/m2. Regarding WC, men in the third quintile (79.0–82.9 cm) and women in the fourth quintile (70.0–74.9 cm) had the lowest risk of mortality. For WHtR, men in the third quintile (0.46–0.49) and women in the fourth quintile (0.45–0.48) had the lowest risk of mortality. For BF%, both men and women in the fourth quintile (24.0–27.2% and 28.7–32.8%, respectively) had the lowest risk of mortality. The WC, WHtR, and BF% exhibited slightly associations with the risk of mortality across the three BMI categories [low (10.8–20.9 kg/m2), normal (21.0–27.4 kg/m2) and high (27.5–51.7 kg/m2)]. C-statistics of the four parameters ranged from 0.51 to 0.69. Conclusion: Our results suggest that BMI should remain the primary marker for screening excessive adiposity. However, our findings also support the use of the WC, WHtR, and/or BF%, in addition to BMI when assessing the risk of mortality.
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U2 - 10.1016/j.clnu.2020.09.008
DO - 10.1016/j.clnu.2020.09.008
M3 - Article
C2 - 32988652
AN - SCOPUS:85091612467
SN - 0261-5614
VL - 40
SP - 1932
EP - 1941
JO - Clinical Nutrition
JF - Clinical Nutrition
IS - 4
ER -