Global, regional, and national prevalence for type 2 diabetes among women of childbearing age,1992-2021: an age-period-cohort analysis based on the Global Burden of Disease Study 2021

Objectives Analyze the trends and inequalities in type 2 diabetes mellitus (T2DM) prevalence among women of childbearing age (WCBA) from 1992 to 2021. Design: Population-based analysis. Setting: T2DM prevalence data were obtained from GBD2021. Population: Participants in GBD2021. Methods T2DM prevalence data from GBD 2021 database were analyzed using Age-Period-Cohort (APC). Inequalities across SDI levels were also assessed, and decomposition analysis identified burden drivers. Bayesian APC (BAPC) model provided future projections (2022-2030). Main outcome measures Prevalence number (million), age-standardized rate (ASR, per million), net drift (%). Results In 2021, the global T2DM prevalence among WCBA reached 73.86 (95% UI: 63.43-85.32) million. From 1992 to 2021, the prevalence burden rose in 195 countries, declined in eight, and remained stable in one. Greenland exhibited the largest rise with a net drift of 11.32% (95% UI: 8.33-14.39%). The highest burden worsened over time and ASR peak occurred in the 45-49 age group. Population and epidemiological factors was the main driver relatively in low and high SDI regions. T2DM-related visual impairment was more severe in low and medium SDI regions. Projections suggest significant increases both on global and country level. Conclusions T2DM prevalence among WCBA has risen steadily since 1992, with worsening inequalities. Projections to 2030 underscore the urgent need for targeted prevention and treatment strategies. Global, regional, and national prevalence for type 2 diabetes among women of childbearing age,1992-2021: an age-period-cohort analysis based on the Global Burden of Disease Study 2021 Zhongyan Xu 1#, Mengting Liu 3#, Miaoran Chen 4, Xinying Shen 3, Xinying Hao 3, Quan Yun 3, Yunzhou Zheng 1, Yan Cui 1, Jun Qiao 2* and Fukun Wang 1* 1 Clinical Laboratory, Bethune International Peace Hospital, 398 Zhongshan Road, Shijiazhuang, Hebei 050082, China 2 Department of Pharmacology, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China. 3 Department of Breast Surgery, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China 4 Department of Nephrology, Shanxi Kidney Disease Institute, Second Hospital of Shanxi Medical University, Taiyuan, Shanxi 030001, China. # These authors contributed equally to this work. * Corresponding author Email: [email protected] (F.W.) and [email protected] (J.Q.)

Analyze the trends and inequalities in type 2 diabetes mellitus (T2DM) prevalence among women of childbearing age (WCBA) from 1992 to 2021. Design: Population-based analysis. Setting: T2DM prevalence data were obtained from GBD2021. Population: Participants in GBD2021.

T2DM prevalence data from GBD 2021 database were analyzed using Age-Period-Cohort (APC). Inequalities across SDI levels were also assessed, and decomposition analysis identified burden drivers. Bayesian APC (BAPC) model provided future projections (2022-2030). Main outcome measures Prevalence number (million), age-standardized rate (ASR, per million), net drift (%).

In 2021, the global T2DM prevalence among WCBA reached 73.86 (95% UI: 63.43-85.32) million. From 1992 to 2021, the prevalence burden rose in 195 countries, declined in eight, and remained stable in one. Greenland exhibited the largest rise with a net drift of 11.32% (95% UI: 8.33-14.39%). The highest burden worsened over time and ASR peak occurred in the 45-49 age group. Population and epidemiological factors was the main driver relatively in low and high SDI regions. T2DM-related visual impairment was more severe in low and medium SDI regions. Projections suggest significant increases both on global and country level.

T2DM prevalence among WCBA has risen steadily since 1992, with worsening inequalities. Projections to 2030 underscore the urgent need for targeted prevention and treatment strategies. Funding Key Research and Development Program of Hebei Health Commission (No. 20231340) and Medical Science Research Project of Hebei Health Commission (No.20240368).

Global Burden of Disease, Type 2 Diabetes Mellitus, Women of Childbearing Age, Age-Period-Cohort Analysis. Funding This work was supported by grants from the Key Research and Development Program of Hebei Health Commission (No. 20231340) and the Medical Science Research Project of Hebei Health Commission (No.20240368).

Diabetes is the seventh most prevalent non-communicable disease worldwide, 1 with Type 2 diabetes mellitus (T2DM) comprising about 90% of cases. 2 Women, particularly those of childbearing age, are more susceptible to T2DM than men due to socioeconomic disparities, patterns of adipose tissue distribution, and hormonal fluctuations, especially estrogen, during menopause. 3 The United Nations’ Sustainable Development Goal to lower the global maternal mortality ratio to under 70 per 100,000 live births by 2030 aligns with the World Health Organization’s focus on improving maternal health outcomes. 4 However, T2DM among women of childbearing age (WCBA) presents severe reproductive health risks, including delayed puberty and menarche, irregular menstrual cycles, decreased fertility, adverse pregnancy outcomes, and potentially premature menopause. 5 These complications can impair female fertility and elevate maternal morbidity and mortality. T2DM not only poses serious health risks to WCBA but also its disease burden in WCBA cannot be ignored. A systematic review and meta-analysis in the Middle East and North Africa found a 7.5% prevalence of T2DM (95% CI: 6.1% to 9.0%) among WCBA. 6 Despite the significant implications of these findings, a global analysis of T2DM prevalence among WCBA is still lacking. An in-depth investigation into the age, period, and birth cohort effects is essential to better understand T2DM prevalence among WCBA. Each of these factors offers unique insights into the risk profile of T2DM. First, considering age, T2DM risk varies significantly across women’s life stages. 7 For example, pregnancy elevates the risk of T2DM due to metabolic stress, and menopause introduces factors such as upper-body fat accumulation and insulin resistance, which further increase susceptibility. 8 Second, T2DM prevalence trends are influenced by period effects as socio-economic development and health policies over time impact factors like neonatal birth weight—a recognized predictor of T2DM risk in later life. 9 Finally, birth cohort effects may also shape T2DM trends in WCBA populations. Shifting external conditions, lifestyle changes, and unique generational experiences contribute to variations in T2DM prevalence across cohorts. 10 While these associations offer a basis for understanding T2DM risk in WCBA, further analysis is needed to accurately quantify the combined impact of age, period, and cohort effects on the disease’s prevalence in these populations. Despite existing studies on T2DM prevalence among WCBA in specific regions, a comprehensive global analysis of the T2DM burden still needs to be developed. Moreover, it is essential to conduct cross-national comparisons across different income levels and investigate the contributions of age, period, and birth cohort effects to this burden. To address these gaps, we utilized data from the Global Burden of Disease, Injury, and Risk Factors Study (GBD) 2021. We analyzed T2DM prevalence data from the GBD 2021 database using Age-Period-Cohort (APC) and Bayesian APC (BAPC) models to examine trends, assess SDI-related inequalities, and project future patterns from 2022 to 2030. Through decomposition analysis, we identified key contributing factors and evaluated the impact on women of childbearing age across various SDI levels.

Data Sources and Disease Definition This study utilized GBD 2021 data from the Institute for Health Metrics and Evaluation (IHME), encompassing 371 diseases, 88 risk factors, and data from 204 countries and territories. 1112, T2DM, classified as a fourth-level non-communicable disease (ICD-10: E11), is distinguished by subtracting type 1 diabetes cases from total diabetes prevalence. GBD integrates data from 22,236 sources using advanced methods like MR-BRT with Bayesian priors and DisMod-MR 2.1, ensuring standardized, age-adjusted comparisons. Prevalence estimates, including 95% uncertainty intervals (UIs), were sourced from the Global Health Data Exchange (https://vizhub.healthdata.org/gbd-results/), offering robust measures of variability. Countries are categorized by the Socio-demographic Index (SDI) into five groups, reflecting development levels and enabling standardized health outcome comparisons 11 . Study Population The study focused on WCBA, defined by the WHO as women aged 15 to 49 who have reproductive capabilities and undergo cyclical hormonal changes. Notably, the study included women aged 15 to 19, a phase of adolescence, to address the disease burden specific to younger women. Examination of temporal trends in T2DM prevalence among WCBA The study evaluated the prevalence of T2DM in WCBA from 1992 to 2021, utilizing case numbers and age-standardized prevalence rates (ASR) per 100,000 population, with 95% confidence intervals (CIs). Age differences were addressed by age-standardizing crude rates through the direct method, assuming rates are a weighted sum of independent Poisson random variables. Age-period-cohort (APC) analysis of T2DM prevalence in WCBA The APC model addresses linear dependency (cohort = period - age) through techniques like maximum likelihood estimation and Bayesian methods, mitigating collinearity for robust parameter estimation. Widely applied in epidemiology, it disentangles biological aging, period-specific events, and cohort exposures, offering insights into health and socioeconomic trends. 413, Using GBD 2021 data, T2DM prevalence in WCBA from 1992 to 2021 was analyzed across seven age groups (15-49 years), six 5-year periods, and twelve 10-year birth cohorts (1942-2021), enabling the separation of age, period, and cohort effects. Log-linear regression assessed rates, while logistic regression evaluated binary outcomes. Net drift quantified overall trends, and local drift captured age-specific changes. Age-specific rates reflected age effects, while period and cohort effects indicated relative prevalence risks, unaffected by reference group selection. Cross-country inequality analysis To quantify SDI-related inequalities in T2DM prevalence among WCBA, we used the Slope of Inequality Index (SII) for absolute inequality and the Concentration Index for relative inequality. Positive values indicate higher burden in high-SDI countries, while negative values reflect greater burden in low-SDI countries. Larger absolute values denote greater disparities. 1415, Decomposition and impairment analysis To analyze drivers of T2DM prevalence changes (1992-2021), decomposition analyses examined population growth, aging, and epidemiologic changes. 16 From GBD 2021’s impairment hierarchy, T2DM-attributable blindness and vision loss data were extracted, categorized as first- and second-level impairments, and modeled to estimate prevalence proportions among WCBA across SDI levels. Bayesian Projections The Bayesian Age-Period-Cohort (BAPC) model, an enhancement of the traditional APC method, was used to project T2DM prevalence trends (2022-2030). By incorporating Bayesian inference, it offers robust, probabilistic parameter estimation, with nested Laplace approximations ensuring computational efficiency and precision. 17 Ethical Considerations This study relied solely on publicly available data, which did not necessitate ethical approval, as no personal or confidential information was involved. All methods adhered to the GATHER guidelines, ensuring consistency and transparency. 18 Statistics

were expressed as age-standardized prevalence rates per 100,000 population, with 95% uncertainty intervals (UIs). A two-tailed P-value of less than 0.05 was used to establish statistical significance. All analyses were conducted in R Studio (version 4.2.1), with specialized R packages, including BAPC, INLA, and ggplot2, used for implementing the APC and BAPC models. The Wald χ² test was used to assess the significance of annual percentage change trends from the APC model. 1219,

Trends in T2DM prevalence in WCBA, 1992-2021 Global prevalence numbers, age-standardized prevalence rates in 1992 and 2021 and net drift from 1990 to 2021, as well as in 5 SDI regions, were demonstrated in Figure 1 and Table 1. Over this period, the global and regional prevalence of T2DM in this population increased by approximately 2.28%, reaching 73.86 million (95% UI: 63.43 to 85.32) in 2021. The percentage change in T2DM prevalence increased across all SDI regions. In 2021, the global age-standardized prevalence rate of T2DM among WCBA was 3,678.6 per 100,000 population (95% UI: 3,154.7 to 4,254.5), representing a 1.08% increase since 1992. The age-standardized prevalence rate increased across all SDI regions: high, high-middle, middle, low-middle, and low. The Age-Period-Cohort (APC) model estimated a global net drift in T2DM prevalence among WCBA at 2.53% annually (95% CI: 2.49% to 2.57%), with regional variations from 2.01% annually (95% CI: 1.94% to 2.08%) in middle SDI regions to 3.78% annually (95% CI: 3.69% to 3.98%) in high SDI regions. The national prevalence and age-standardized prevalence rate in 2021, as well as the net drift of prevalence of T2DM among WCBA from 1992 to 2021 were shown in Figure 2, Supplemental Table 1. In 2021, among 204 countries and territories, 8 countries reported over 1 million prevalent number: Mexico (2,458,313; 95% UI: 2,076,437 to 2,866,945), China (17,450,317; 95% UI: 14,840,016 to 20,383,999), the United States (3,020,792; 95% UI: 2,623,444 to 3,451,048), Bangladesh (2,418,066; 95% UI: 2,052,168 to 2,851,355), India (14,500,694; 95% UI: 12,036,671 to 17,150,827), Pakistan (2,525,387; 95% UI: 2,075,252 to 3,021,205), Indonesia (1,685,287; 95% UI: 1,367,900 to 2,031,338), and Brazil (1,505,795; 95% UI: 1,215,481 to 1,826,271).China, India, and the United States reported the most cases. The global average age-standardized prevalence rate was 4,209.69, with 74 countries exceeding this global average. Six countries, including American Samoa, Cook Islands, Marshall Islands, Niue, Palau, and Samoa, had prevalence rates exceeding three times the global average; notably, all are Pacific island nations with varying SDI levels. Between 1992 and 2021, Greenland saw the largest rise in age-standardized prevalence rate at 7.93%, with an annual net drift in prevalence of 11.32% (95% UI: 8.33% to 14.39%). Age-standardized prevalence rates increased in all countries and territories, with the APC model estimating increasing trends in net drift for 195 of the 204 countries and territories. However, several countries demonstrated a reduction in T2DM burden, with a net drift less than 0: North Macedonia (-0.94%; 95% UI: -3.37% to 1.54%), Montenegro (-1.04%; 95% UI: -3.52% to 1.50%), Czechia (-0.53%; 95% UI: -1.47% to 0.42%), Croatia (-1.7%; 95% UI: -3.19% to -0.18%), Hungary (-0.6%; 95% UI: -1.22% to 0.03%), Romania (-0.37%; 95% UI: -0.93% to 0.2%), Indonesia (-0.68%; 95% UI: -0.89% to -0.47%), and Serbia (-1.81%; 95% UI: -3.71% to 0.13%). Only Albania displayed relatively stable trends, with a net drift of 0% (95% UI: -0.35% to 0.35%). Overall, these findings indicate that the global burden of T2DM among WCBA is generally on the rise. Temporal trends in T2DM prevalence in WCBA across different age groups The local drift in the prevalence of T2DM among WCBA across SDI quintiles from 1992 to 2021 for seven age groups was presented in Figure 3, Supplemental table 3. The prevalence of T2DM among WCBA has been rising globally across all age groups. The trend increased with age in the 15-19 years group and stabilized from the 20-24 years group (2.71%, 95% UI 2.63% to 2.79%) to the 25-29 years group (2.71%, 95% UI 2.64% to 2.77%). After age 29, the rate of increase gradually declined with age, reaching its lowest level in the 45-49 years group (2.11%, 95% UI: 2.04% to 2.17%). In all SDI regions, T2DM prevalence among WCBA rose across age groups, with a declining trend as age increased. Low-SDI regions showed a steady decline with age, while low-middle SDI regions peaked at 15-19 years. Middle and high-middle SDI regions peaked at 25-29 and 20-24 years, respectively, before declining. High-SDI regions showed a consistent age-related decline. Overall, T2DM prevalence is rising, but the rate slows with age. Supplemental Table 4 details local drifts on country level. Analysis of age, period, and birth cohort influences on T2DM prevalence among WCBA Figure 4, and Supplemental Tables 5 to 7 illustrate the age, period, and birth cohort effects on T2DM prevalence among WCBA as determined by the APC model, with the test of results significance presented in Supplementary Table 2. Age-related effects showed consistent patterns across SDI regions, with the lowest risk in adolescents (15-19 years) and increasing risk with advancing age. High SDI regions consistently exhibited a lower prevalence across all age groups compared to other regions. Period effects indicated a rising prevalence risk across SDI regions, with the low SDI region showing generally lower period risks throughout the study period, whereas other regions exhibited more unfavorable period risks over time. The relative period risk in 2017-2021, compared to the 1992-1996 reference period, varied from 1.73 (95% UI: 1.69-1.76) in the middle SDI region to 2.58 (95% UI: 2.52-2.64) in the high SDI region. Successive birth cohorts in all SDI regions showed a rising prevalence risk. High SDI regions exhibited a marked increase in prevalence across birth cohorts. The relative cohort risk for individuals born between 1997 and 2006, compared to those born in the 1942-1951 reference cohort, varied from 2.24 (95% UI:2.08 to 2.41) in the middle SDI region to 5.38 (95% UI:4.89 to 5.92) in the high SDI region. The online supplemental tables 8-10 present the age, period, and birth cohort effects on T2DM prevalence among WCBA for each country. The APC results for country level were represented in Supplementary Table 8 to 10. And several representative countries, with relatively favorable and unfavorable age, period, and cohort effects, are provided in Supplementary Figure 1 to offer a clearer understanding of the temporal trends at the country level. Health inequalities in T2DM burden among WCBA across SDI levels Over the past three decades, the prevalence of T2DM among WCBA has significantly increased globally, accompanied by a substantial rise in health inequality. During this period, the SII increased from 2416.15 (95% UI: 1922.3 to 2910) in 1992 to 6108.72 (95% UI: 4765.48 to 7451.96) in 2021, as shown in Supplementary Figure 2A, with an estimated annual percentage change (EAPC) of 15.19% (95% UI: 10.41 to 20.17). This indicates a worsening absolute gap in health inequality, with the disease burden remaining disproportionately concentrated in high SDI countries. Additionally, the concentration index increased from 0.14 (95% UI: 0.12 to 0.16) in 1992 to 0.18 (95% UI: 0.16 to 0.21) in 2021, with an EAPC of 0.14% (95% UI: 0.11 to 0.18), reflecting both an increasing disease burden and a growing inequity in its distribution worldwide (Supplementary Figure 2B). Key drivers of the T2DM health burden in WCBA across Global and SDI levels The decomposition of changes in the T2DM prevalence increase in WCBA globally and across SDI countries is presented in Supplementary Figure 3 and Supplemental Table 11. Globally, epidemiological changes are the primary drivers of the increased prevalence of T2DM in WCBA, followed by population growth, while the contribution of aging is relatively minor. In high and high-middle SDI countries, epidemiological changes are the dominant contributors, whereas, in middle and low-middle SDI countries, both epidemiological changes and population growth significantly influence the prevalence increase. In low SDI countries, population growth is the main driver of the increasing T2DM prevalence among WCBA. Global and SDI-based distribution of T2DM-related visual impairment in WCBA The epidemiological distribution of T2DM-related visual impairment in WCBA globally and across SDI quintiles in 2021 is shown in Supplementary Figure 4 and Supplemental Table 12. The prevalence of moderate vision loss is relatively uniform across all SDI countries, ranging from 5% to 10%, while severe vision loss is consistently low (<5%). However, the total prevalence of blindness and visual loss combined exceeds 15% in moderate and low SDI countries, significantly higher than in high SDI and low SDI regions. This highlights that moderate and low SDI countries bear the highest burden of T2DM-induced visual impairment, emphasizing the need for targeted interventions in these areas. Projected trends for T2DM prevalence among WCBA To capture global T2DM trends among WCBA, projections of ASR and prevalence number from 2022 to 2030 were analyzed using BAPC model. The analysis predicts a continued rise in T2DM prevalence among WCBA, both in terms of ASR and total case numbers. By 2030, the global ASR is projected to reach 3820.72 (95% UI: 3716.4 to 3925.04) per million population, with the total number of prevalent cases expected to peak at 76903117.41 (95% UI: 73944936.2 to 79861298.63) million, both are higher than the historical peaks, as illustrated in Supplementary Figure 5. Consistent with the global trend, Figure 5 showed the BAPC results for several representative countries mentioned in the age-period-cohort (APC) analysis, also show a clear upward trajectory in both ASR and total case numbers. This suggests an expanding global burden of the disease. Detailed information was presented in Supplementary Table 13 to 15.

Diabetes is the world’s seventh-largest non-communicable disease, posing a severe threat to human health. 1 T2DM constitutes about 90% of diabetes cases, 2 imposing a considerable societal burden and significant health risks for WCBA. 20 T2DM patients face elevated risks of microvascular and macrovascular complications, 21 non-alcoholic fatty liver disease, 22 and increased mortality from Alzheimer’s disease and related dementias, particularly in postmenopausal women. 23 Women aged 15 to 49 with T2DM face numerous health challenges, including blood sugar control, cardiovascular risk, neuropathy, kidney disease, retinopathy, self-management difficulties, and reproductive health concerns. 24 A comprehensive understanding of T2DM prevalence trends among WCBA is essential to assess the impact of T2DM in this population. A comprehensive analysis of T2DM prevalence in WCBA is currently unavailable. This study analyzed data from the GBD 2021 using an APC model to investigate prevalence trends and disease risks of T2DM among WCBA in 204 countries and regions from 1992 to 2021. The GBD 2019 study reported a global rise in metabolic disease incidence (2000-2019), particularly in high-SDI countries, with unchanged T2DM mortality. 25 In low-middle SDI regions, T2DM showed the largest increases in incidence, prevalence, mortality, and DALYs. 26 GBD 2021 data revealed rising age-standardized prevalence and percentage change of T2DM in WCBA across all SDI regions (1992-2021). By 2021, 8 countries exceeded 1 million T2DM cases, with China, India, and the U.S. ranking highest. Despite advanced healthcare, the U.S. exhibited disproportionately high prevalence. Dietary risks (e.g., low fruit intake, high red/processed meat consumption) contributed to 26.07% of T2DM mortality and 27.08% of DALYs in 2019, correlating positively with SDI levels. 27 The global average T2DM prevalence in WCBA in 2021 was 4,209.69 per 100,000, with 74 countries exceeding this level. Six Pacific island nations reported prevalence rates over three times the global average, suggesting geographic and unique local factors beyond SDI models require further exploration. Using the APC model, the study demonstrated the influence of age, period, and cohort effects on T2DM prevalence in WCBA. Age-related patterns showed adolescents (15-19 years) had the lowest risk, with prevalence rising significantly with age, even among individuals with normal BMI. 28 Period effects revealed increasing T2DM risks across SDI regions, with low-SDI regions experiencing consistently lower risks compared to higher-SDI regions. Cohort effects indicated rising prevalence across successive birth cohorts, with high-SDI regions showing the greatest increase. For those born in 1997-2006, relative cohort risk compared to the 1942-1951 cohort ranged from 2.24 (95% UI: 2.08-2.41) in middle-SDI regions to 5.38 (95% UI: 4.89-5.92) in high-SDI regions. The rising period and cohort risks in high-SDI countries may reflect lifestyle and dietary factors. This study analyzed future T2DM trends among WCBA across SDI levels using representative countries. In high-SDI countries, Canada exhibits annual net and local drift rates above 0%, with rising prevalence driven by worsening age and period effects, projecting significant future growth. Conversely, the Czech Republic, with a net drift below 0%, shows moderate projected incidence. Middle-SDI countries like China and India display similar age, period, and cohort effects, with prevalence expected to continue rising. In low-SDI countries, Afghanistan shows the highest net drift, while Rwanda shows the lowest; however, T2DM risk among WCBA is projected to gradually increase in both nations. This study highlights a significant global increase in the prevalence of T2DM among WCBA during 1992-2021, accompanied by a substantial rise in health inequality. The SII more than doubled from 1992 to 2021, with an annual increase of 15.19 %, reflecting a widening absolute disparity, particularly concentrated in high SDI countries. Similarly, the CI increased, indicating both a growing disease burden and increasing inequity in distribution. The disproportionate burden in high SDI countries may be driven by higher rates of obesity, unhealthy lifestyles, and improved diagnostics. 2930, This highlights the need for high SDI countries to increase focus on T2DM among WCBA by adjusting health policies and promoting healthier lifestyles. Disease burden drivers varied by SDI level: epidemiological changes dominated in high and high-middle SDI countries, while population growth also contributed significantly in middle and low-middle SDI regions. In low SDI countries, rapid population growth was the primary factor, exacerbating health inequalities due to limited resources. T2DM-related visual impairment was disproportionately higher in medium and low SDI countries, with severe vision loss and blindness emphasizing the need for early screening and intervention. Despite global improvements in relative health inequality for T2DM, absolute inequality is worsening, particularly in low SDI regions, underscoring the urgency of enhancing resource allocation and prevention strategies to reduce disparities. This study is the first to analyze T2DM prevalence trends among WCBA across 204 countries using GBD 2021 data and the APC model. Building on prior GBD 2019 analyses of metabolic diseases and T2DM mortality trends, 31 it provides a comprehensive examination of prevalence patterns across SDI regions and age groups. The APC model enabled detailed assessment of temporal trends by period and birth cohort, offering valuable insights for global T2DM epidemiology and health policy. However, the inherent time lag in GBD data should be acknowledged. In summary, this study indicates that the prevalence of T2DM among WCBA is increasing globally, with prevalence rates expected to continue rising in many countries and regions, and the disease burden will become increasingly concentrated in high SDI countries. The health of WCBA is closely tied to population growth and social development, highlighting an urgent need for increased investment in T2DM healthcare resources, expanded research on treatment strategies, and strengthened health policies. Conflict of Interest None declared. Contributors Z.X . and M.L. contributed equally to this work. M.C., Z.X., M.L., J.Q. designed the study and drafted the manuscript. M.L., X.S., Q.Y., and X.H. performed the statistical analysis. Y.Z., Y.C. and F.W. provided financial support. All authors contributed to the acquisition, analysis, or interpretation of data. All authors revised the report and approved the final version before submission. Details of ethics approval Not applicable. Acknowledgments We appreciate the works by the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 collaborators. We also thanks to Xiao Ming ([email protected]) for his help in our exploration of GBD database. Data availability statement We downloaded data from the Global Health Data Exchange (GHDx) query tool (https://vizhub. healthdata.org/gbd-results/).

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Figures and Tables Table1 Trends of T2DM prevalence in WCBA from 1990 to 2021 across SDI quintiles. | Location | Prevalence Number | |||| | (N, 95% UI) | Prevalence ASR | |||| | (per 100 000, 95% UI) | Prevalence Number | |||| | (N, 95% UI) | Prevalence ASR | |||| | (per 100 000, 95% UI) | Net Drift | |||| | (%/year) | ||||| | Global | 22,496,858 (18,563,996, 26,870,105) | 1,766.8 (1,467.1, 2,099.9) | 73,858,922 (63,433,476, 85,320,524) | 3,678.6 (3,154.7, 4,254.5) | 2.53 (2.49, 2.57) | | Low SDI | 1,624,940 (1,343,116, 1,933,787) | 1,631.4 (1,361.7, 1,923.7) | 7,485,015 (6,313,045, 8,782,708) | 3,154 (2679.1, 3677.5) | 2.33 (2.3, 2.36) | | Low-middle SDI | 4,710,595 (3,889,870, 5,596,286) | 1,906.3 (1,589, 2,246.1) | 18,565,820 (15,668,658, 21,735,513) | 3,857.2 (3,263.7, 4,504.8) | 2.48 (2.45, 2.5) | | Middle SDI | 8,551,312 (7,052,551, 10,219,078) | 2,090.8 (1,739.2, 2,481.8) | 25,244,095 (21,763,766, 29,137,084) | 3,829.7 (3,292, 4,430.6) | 2.01 (1.94, 2.08) | | High-middle SDI | 4,479,853 (3,634,433, 5,421,055) | 1,635.7 (1,333.1, 1,973.5) | 12964107 (11,051,836, 15,112,952) | 3,720.3 (3,148.5, 4,364.6) | 2.89 (2.78, 3) | | High SDI | 3,107,365 (2,544,551, 3,703,944) | 1,272.6 (1,038.2,1,522) | 9536739 (8,251,796, 10,933,224) | 3,457.1 (2,971.8, 3,984.9) | 3.78 (3.69, 3.86) | Note: Parentheses for GBD estimates denote 95% uncertainty intervals and parentheses for net drift denote 95% CIs. Abbreviations: ASR, age-standardized prevalence rate; 95% UI, 95% uncertainty intervals; 95% CI, 95% Confidence Interval; APC, age period cohort; T2DM, type 2 diabetes mellitus; WCBA, women of childbearing age; SDI, sociodemographic index. Figure 1 The Prevalence numbers and ASR of T2DM in global and the five SDI regions among WCBA from 1992 to 2021. ASR, age-standardized prevalence rate; T2DM, type 2 diabetes mellitus; SDI, sociodemographic Index; WCBA, Women of childbearing age. Figure 2 World map of (A) ASR in 2021 and (B) Net drift of prevalence from 1992 to 2021 for T2DM in WCBA in 204 countries and territories. ASR, age-standardized prevalence rate; T2DM, type 2 diabetes mellitus; WCBA, women of childbearing age. Figure 3 Local drift of prevalence for T2DM in WCBA across SDI quintiles from 1992 to 2021 for seven age groups. The dots and shaded areas denote the local drift (ie, annual percentage change of age-specific prevalence, % per year) and their corresponding 95% CIs. 95% CI, 95% Confidence Interval; T2DM, type 2 diabetes mellitus; WCBA, women of child-bearing age; SDI, sociodemographic index. Figure 4 Age, period and birth cohort effects on T2DM prevalence in WCBA by APC models across SDI quintiles. The age effect are illustrated by the longitudinal rates specific to age, which are adjusted for variations across different birth cohorts, taking into account the period-specific deviations. (B) Period effects are shown through the relative risk of T2DM prevalence during different periods, calculated as the ratio of the age-specific rates from the period from 1992 - 1996 to 2017 - 2021, with the baseline period set as 1992 - 1996. (C) Birth cohort effects are demonstrated by the cohort relative risk of prevalence and calculated as the ratio of age-specific rates from 1942–1951 cohort to 1997–2006 cohort, with the reference cohort set at 1972–1981. The dots and shaded areas denote the prevalence rates or rate ratios and their corresponding 95% CIs. 95% CI, 95% Confidence Interval; T2DM, type 2 diabetes mellitus; WCBA, women of child-bearing age; APC, age period cohort; SDI, sociodemographic index. Figure 5 Projects the ASR and numbers of prevalence for T2DM in WCBA in exemplary countries from 2022 to 2030. ASR, age-standardized prevalence rate; T2DM, type 2 diabetes mellitus; WCBA, women of childbearing age. Information & Authors Information Version history Peer review timeline Published Journal of Diabetes Research Version of Record29 Jan 2026Published Copyright This work is licensed under a Non Exclusive No Reuse License.

Authors Metrics & Citations Metrics Article Usage 339views 145downloads Citations Download citation Zhongyan Xu, Mengting Liu, Miaoran Chen, et al. Global, regional, and national prevalence for type 2 diabetes among women of childbearing age,1992-2021: an age-period-cohort analysis based on the Global Burden of Disease Study 2021. Authorea. 21 February 2025. DOI: https://doi.org/10.22541/au.174012141.10106062/v1 DOI: https://doi.org/10.22541/au.174012141.10106062/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu. Cited by - Global, Regional, and National Prevalence for Type 2 Diabetes Among Women of Childbearing Age, 1992–2021: An Age–Period–Cohort Analysis Based on the Global Burden of Disease Study 2021, Journal of Diabetes Research, 2026, 1, (2026).https://doi.org/10.1155/jdr/2197672 Loading...