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. 2024 Jan 8:11:1297203.
doi: 10.3389/fpubh.2023.1297203. eCollection 2023.

Association between sociodemographic status and the T2DM-related risks in China: implication for reducing T2DM disease burden

Xin Huang  1 , Yinhui He  1 , Haiyan Xu  1 , Yuyan Shen  2 , Xiaowen Pan  2 , Junyun Wu  2 , Kai Chen  1
Affiliations

Association between sociodemographic status and the T2DM-related risks in China: implication for reducing T2DM disease burden

Xin Huang et al. Front Public Health. .

Abstract

Objective: Analyzing the association between sociodemographic status and the type 2 diabetes mellitus (T2DM)-related risks in China to reduce the disease burden of T2DM.

Methods: We downloaded data from the Global Burden of Disease Study 2019 to estimate the disease burden of T2DM in China. Secondary analyses were performed by year, age, gender, summary exposure value (SEV), and sociodemographic index (SDI).

Results: In China, it is estimated that 3.74 (3.44-4.10) million incidence, 90.0 (82.3-98.5) million prevalence, 168.4 (143.2-194.0) thousand deaths, and 9.6 (7.6-11.9) million DALYs occurred in 2019, showing an increase of 96.8, 156.7, 162.8, and 145.4% compared to 1990. An inverse U-shaped curve was observed for the correlations between T2DM-related burden and SDI. A heavier burden was found in males. The top four risk factors were high body mass index (HBMI), dietary risks, air pollution and tobacco. HBMI, as the key risk, accounted for half of the disease burden of T2DM in China. Lower degree of SEV and higher level of attributable T2DM-related burden could be found in main risks, meaning their critical role of them in the development and progression of T2DM. An inverse U-shaped curve could be found in the association between age-standardized incidence, mortality, DALYs rate, and SDI.

Conclusion: The disease burden of T2DM has rapidly increased in China. Gender disparities, different age distributions and inconsistent socioeconomic levels all played an important role in it. The key risk was HBMI. With the improvement of socioeconomic level, the main risk factors for T2DM have changed from environmental factors to lifestyle factors. Targeted control and preventative strategies to address adjustable risk factors could put an end to this soaring burden.

Keywords: China; ambient particulate matter pollution; disability-adjusted life years; high body mass index; sociodemographic index; type 2 diabetes mellitus.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The burden of T2DM from 1990 to 2019 in China. (A) Trends in all-ages numbers and age-standardized rates of T2DM-related incidence in China, 1990–2019; (B) trends in all-ages numbers and age-standardized rates of T2DM-related incidence in China by age in 2019; (C) trends in all-ages numbers and age-standardized rates of T2DM-related prevalence in China, 1990–2019; (D) trends in all-ages numbers and age-standardized rates of T2DM-related prevalence in China by age in 2019; (E) trends in all-ages numbers and age-standardized rates of T2DM-related death in China, 1990–2019; (F) trends in all-ages numbers and age-standardized rates of T2DM-related death in China by age in 2019; (G) trends in all-ages numbers and age-standardized rates of T2DM-related DALYs in China, 1990–2019; and (H) trends in all-ages numbers and age-standardized rates of T2DM-related DALYs in China by age in 2019. Error bars indicate the 95% uncertainty interval (UI) for numbers. Shading indicates the 95% UI for rates.
Figure 2
Figure 2
The most-detailed risk factors attributable to T2DM-related burden in China, 1990–2019. (A) All-ages number of deaths and DALYs; (B) age-standardized rate of deaths and DALYs.
Figure 3
Figure 3
The most-detailed risk factors attributable to T2DM-related burden in China in 1990, 2005, and 2019, with percentage changes in the all-ages numbers and age-standardized rates. (A) Number and rate of deaths and (B) number and rate of DALYs. Solid lines indicate increases and dashed lines indicate decreases in rank between periods. The darker part in each column represents the proportion of corresponding causes. The red part is metabolic risk factors, the blue part is behavioral risk factors, and the yellow part is environmental risk factors. Red indicates that the rate of change is positive, while green is negative, and the depth of color indicates the degree of change.
Figure 4
Figure 4
The proportion of the T2DM-related burden attributable to 15 risk factors in 2019 by different age groups. (A) Deaths and (B) DALYs.
Figure 5
Figure 5
The correlation between the burden of T2DM and SDI in China. (A) Prevalence; (B) incidence; and (C) death; (D) DALYs. Shading indicates the 95% UI.
Figure 6
Figure 6
The main findings of the study.
See this image and copyright information in PMC

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