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. 2024 Aug 20;5(8):101656.
doi: 10.1016/j.xcrm.2024.101656. Epub 2024 Jul 26.

Association of social determinants, lifestyle, and metabolic factors with mortality in Chinese adults: A nationwide 10-year prospective cohort study

Jieli Lu  1 , Mian Li  1 , Jiang He  2 , Yu Xu  1 , Ruizhi Zheng  1 , Jie Zheng  1 , Guijun Qin  3 , Yingfen Qin  4 , Yuhong Chen  1 , Xulei Tang  5 , Zhen Ye  6 , Min Xu  1 , Tiange Wang  1 , Lixin Shi  7 , Qing Su  8 , Xuefeng Yu  9 , Li Yan  10 , Zhiyun Zhao  1 , Qin Wan  11 , Gang Chen  12 , Zhengnan Gao  13 , Guixia Wang  14 , Feixia Shen  15 , Xuejiang Gu  15 , Zuojie Luo  4 , Li Chen  16 , Xinguo Hou  16 , Yanan Huo  17 , Qiang Li  18 , Hong Qiao  18 , Yinfei Zhang  19 , Tianshu Zeng  20 , Chunyan Hu  1 , Qiuyu Cao  1 , Xiaojing Jia  1 , Chao Liu  21 , Youmin Wang  22 , Shengli Wu  23 , Tao Yang  24 , Huacong Deng  25 , Hongyan Qi  1 , Xueyan Wu  1 , Di Zhang  1 , Meng Dai  1 , Donghui Li  26 , Shenghan Lai  27 , Lulu Chen  20 , Jiajun Zhao  28 , Yiming Mu  29 , Weiguo Hu  30 , Guang Ning  1 , Ruying Hu  6 , Yufang Bi  31 , Weiqing Wang  32 ; 4C Study Group
Affiliations

Association of social determinants, lifestyle, and metabolic factors with mortality in Chinese adults: A nationwide 10-year prospective cohort study

Jieli Lu et al. Cell Rep Med. .

Abstract

Nationwide estimates of the impact of common modifiable risk factors on mortality remain crucial. We aim to assess the influence of social determinants, lifestyle, and metabolic factors on mortality in 174,004 adults aged ≥40 years from the China Cardiometabolic Disease and Cancer Cohort (4C) Study. We reveal that 17 modifiable factors are independently associated with mortality, accounting for 64.8% of all-cause mortality, 77.4% of cardiovascular mortality, and 44.8% of cancer mortality. Low education emerges as the leading factor for both all-cause and cancer mortality, while hypertension is predominant for cardiovascular mortality. Moreover, low gross domestic product per capita and high ambient particulate matter with a diameter of <2.5 μm (PM2.5) air pollution account for 7.8% and 4.3% for all-cause mortality, respectively, using a different method. Gender-specific analyses reveal distinct patterns, with women's mortality primarily associated with social determinants and men exhibiting stronger associations with lifestyle factors. Targeted health interventions are essential to mitigate mortality risks effectively in China.

Keywords: CVD mortality; all-cause mortality; cancer mortality; lifestyle; metabolic factors; social determinants.

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Conflict of interest statement

Declaration of interests The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Population-attributable fractions (PAFs) for all-cause mortality (A) PAFs associated with clusters of risk factors in the overall population, women, and men. (B–D) PAFs associated with individual risk factors in the overall population, women, and men. Models were adjusted for age, gender, and region, and individual risk factors were mutually adjusted. We showed the top ten most contributed risk factors based on population-attributable fractions of each mortality outcome. Gross domestic product per capita and ambient PM2.5 air pollution were not included in this figure since they were community-level risk factors and analyzed using separate model. The negative population-attributable fractions were truncated at a lower limit of 0 when calculating the cluster estimates. See also Table S3.
Figure 2
Figure 2
Population-attributable fractions (PAFs) for cardiovascular mortality (A–D) PAFs for cardiovascular mortality associated with clusters or individual risk factors in the overall population, women, and men. (E–H) PAFs for ischemic heart disease mortality associated with clusters or individual risk factors in the overall population, women, and men. (I–L) PAFs for stroke mortality associated with clusters or individual risk factors in the overall population, women, and men. Models were adjusted for age, gender, and region, and individual risk factors were mutually adjusted. We showed the top ten most contributed risk factors based on population-attributable fractions of each mortality outcome. Gross domestic product per capita and ambient PM2.5 air pollution were not included in this figure since they were community-level risk factors and analyzed using separate models. The negative population-attributable fractions were truncated at a lower limit of 0 when calculating the cluster estimates. See also Table S3.
Figure 3
Figure 3
Population-attributable fractions (PAFs) for cancer mortality (A) PAFs associated with clusters of risk factors in the overall population, women, and men. (B–D) PAFs associated with individual risk factors in the overall population, women, and men. Models were adjusted for age, gender, and region, and individual risk factors were mutually adjusted. We showed the top ten most contributed risk factors based on population-attributable fractions of each mortality outcome. Gross domestic product per capita and ambient PM2.5 air pollution were not included in this figure since they were community-level risk factors and analyzed using separate model. The negative population-attributable fractions were truncated at a lower limit of 0 when calculating the cluster estimates. See also Table S3.
See this image and copyright information in PMC

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