The Lancet. Healthy Longevity (Oct 2021)

Age-related disparities in diabetes risk attributable to modifiable risk factor profiles in Chinese adults: a nationwide, population-based, cohort study

  • Tiange Wang, ProfPhD,
  • Zhiyun Zhao, PhD,
  • Guixia Wang, ProfMD,
  • Qiang Li, ProfMD,
  • Yu Xu, ProfPhD,
  • Mian Li, PhD,
  • Ruying Hu, ProfPhD,
  • Gang Chen, ProfMD,
  • Qing Su, ProfMD,
  • Yiming Mu, ProfMD,
  • Xulei Tang, ProfMD,
  • Li Yan, ProfMD,
  • Guijun Qin, ProfMD,
  • Qin Wan, ProfMD,
  • Zhengnan Gao, ProfMD,
  • Xuefeng Yu, ProfMD,
  • Feixia Shen, ProfMD,
  • Zuojie Luo, ProfMD,
  • Yingfen Qin, ProfMD,
  • Li Chen, ProfMD,
  • Yanan Huo, ProfMD,
  • Tianshu Zeng, ProfMD,
  • Lulu Chen, ProfMD,
  • Zhen Ye, ProfPhD,
  • Yinfei Zhang, ProfMD,
  • Chao Liu, ProfMD,
  • Youmin Wang, ProfMD,
  • Shengli Wu, ProfMD,
  • Tao Yang, ProfMD,
  • Huacong Deng, ProfMD,
  • Jiajun Zhao, ProfMD,
  • Lixin Shi, ProfMD,
  • Yiping Xu, ProfMS,
  • Min Xu, ProfPhD,
  • Yuhong Chen, ProfMD,
  • Shuangyuan Wang, PhD,
  • Jieli Lu, ProfMD,
  • Yufang Bi, ProfMD,
  • Guang Ning, ProfMD,
  • Weiqing Wang, ProfMD

Journal volume & issue
Vol. 2, no. 10
pp. e618 – e628

Abstract

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Summary: Background: National investigations of age-specific modifiable risk profiles for diabetes are crucial to promote personalised strategies for the prevention and control of diabetes, particularly in countries such as China, which is experiencing both a diabetes epidemic and a rapidly ageing population. We aimed to examine the associations of 12 potentially modifiable socioeconomic, lifestyle, and metabolic risk factors with diabetes in a nationwide prospective cohort of Chinese adults across four age groups. Methods: We analysed data from the China Cardiometabolic Disease and Cancer Cohort Study, a nationwide, population-based, cohort study done between Jan 1, 2011, and Dec 31, 2016. Among 93 781 participants without diabetes at baseline and with complete information available about risk factors and diabetes incidence, we examined the hazard ratios (HRs) and population-attributable risk percentages (PAR%s) of incident diabetes associated with 12 potentially modifiable risk factors: two socioeconomic risk factors (less education and intermediate or low grade occupation), five lifestyle risk factors (unhealthy diet, physical inactivity, current alcohol consumption, current smoking, and unhealthy sleep), and five metabolic risk factors (general or central obesity, insulin resistance, prediabetes, hypertension, and dyslipidaemia) across four age groups (40 to <55 years, 55 to <65 years, 65 to <75 years, and ≥75 years). Findings: With 337 932 person-years' follow-up, 6171 participants developed diabetes. Although diabetes risk attributable to metabolic risk factors decreased slightly with age, metabolic risk factors accounted for most incident diabetes cases across all age groups (from a PAR% of 73·8% in participants aged 40 to <55 years to 65·5% in those aged ≥75 years), with prediabetes (ranging from a PAR% of 56·6% to 47·4%, with increasing age) and hypertension (PAR% of 16·8% to 28·6% with increasing age) being the leading risk factors across all age groups. By contrast, diabetes risk attributable to lifestyle risk factors increased substantially with age (with a PAR% of 9·9% in adults aged 40 to <55 years increasing to 29·7% in adults aged ≥75 years), and was especially evident in participants aged 75 years or older, in whom unhealthy sleep was the largest lifestyle factor, accounting for a PAR% of 17·0%. The impact of socioeconomic risk factors on diabetes was mainly driven by less education, which contributed to a PAR% of 7·1% to 12·4% in participants younger than 75 years but conferred no excess risk in participants aged 75 years or older. The risk of diabetes associated with unhealthy sleep significantly increased with age group (HR 1·04 [95% CI 0·95–1·13] among participants aged 40 to <55 years vs 1·36 [1·01–1·85] among participants aged ≥75 years; pinteraction=0·0054), but there was an age-related decrease in the risk of diabetes associated with obesity (1·35 [1·23–1·48] vs 0·99 [0·72–1·36]; pinteraction=0·0003), prediabetes (3·00 [2·67–3·37] vs 2·18 [1·41–3·37]; pinteraction=0·0014), and dyslipidaemia (1·23 [1·13–1·34] vs 0·90 [0·66–1·21]; pinteraction=0·016). Interpretation: These findings provide novel insights into age-related modifiable risk factor profiles for diabetes in Chinese adults, highlighting the importance of prioritising risk factors according to age groups for effective prevention and management of diabetes. Funding: National Natural Science Foundation of China. Translation: For the Chinese translation of the abstract see Supplementary Materials section.