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International Journal of Women's Health logoLink to International Journal of Women's Health
. 2026 Aug 20;18:620765. doi: 10.2147/IJWH.S620765

Trends in Burden of Female Infertility During 1990–2021: An Analysis of Data from the Global Burden of Disease Study 2021

Jingfang Zheng 1,✉, Xiang Chen 1, Aijuan Yuan 1, Liying Ying 1
PMCID: PMC13502221  PMID: 42639142

Abstract

Purpose

This study aimed to analyze the global trends in the disease burden of Female Infertility (FI) from 1990 to 2021.

Material and Methods

Data were sourced from the GBD2021 database, which aggregates information from disease registries, cause-of-death statistics, and medical records across numerous countries and regions worldwide. The primary metrics analyzed were the age-standardized Disability-Adjusted Life Years (DALYs) and DALY rates for FI. The estimated annual percentage change (EAPC) was calculated to quantify temporal trends. Regions were also categorized according to their socio-demographic index (SDI) to evaluate the association between development levels and the FI disease burden.

Results

Globally, the age-standardized DALY rate for FI increased from 12.32 per 100,000 in 1990 to 15.12 per 100,000 in 2021, with an EAPC of 0.71, indicating a significant upward trend. Geographically, East Asia, Eastern Europe, and South Asia had the highest age-standardized DALY rates in 2021. The most notable increases in the burden of FI were observed in Andean Latin America (EAPC: 8.11), High-income North America (EAPC: 2.91), and South Asia (EAPC: 1.85). In contrast, regions such as Oceania and Eastern Sub-Saharan Africa experienced a decrease in the FI burden. When analyzed by SDI, regions with high-middle and middle SDI carried the highest overall disease burden. Meanwhile, high-SDI countries, despite having a relatively lower burden, showed the highest rate of increase. Age-specific analysis revealed that the DALY rate peaked among women aged 40–44 years, followed by a sharp decline in the 45–49 age group. Notably, contrary to the conventional developmental gradient expectation, SDI exhibited nearly no meaningful correlation with female infertility burden across all continents, with R2 values close to zero throughout the study period.

Conclusion

The findings from the GBD Study indicate a rising global trend in the disease burden of female infertility from 1990 to 2021. The increasing burden, particularly in high-SDI regions and among women in their late reproductive years (40–44), highlights a growing public health challenge that requires targeted interventions and resource allocation.

Keywords: female infertility, DALY, EAPC, GBD, SDI

Introduction

Per the World Health Organization’s unified definition, female infertility (FI) is a disease of the reproductive system characterized by the inability to achieve a clinical pregnancy following 12 months or more of regular unprotected sexual intercourse.1 The causes of FI are varied and complex,2 making treatment challenging. Moreover, FI treatment can be costly, leading to significant financial strain on patients and their families, and requiring substantial healthcare and professional resources. This places a heavy burden on both healthcare systems and economies. Globally, an estimated 12% of married women experience FI,3 impacting physical and mental health and having broader societal and national consequences. This estimate only covers married women of reproductive age, as the underlying population surveys excluded unmarried individuals from the calculation denominator. The substantial burden of FI can impede population growth, decrease labor supply, contribute to population decline and aging, shortages in the workforce, increased pressure on social security systems, and hindered economic progress.4 Despite these serious implications, FI has not received adequate attention, and comprehensive studies analyzing the global distribution and trends of FI burden are limited. Previous studies utilizing GBD data have provided insights into infertility prevalence and trends worldwide. For example, Sun et al investigated the prevalence and disability-adjusted life years (DALYs) associated with infertility across 195 countries and regions from 1990 to 2017,5 revealing significant regional differences and temporal patterns. Similarly, Borumandnia et al analyzed the trends in infertility rates across 198 countries and regions, highlighting variations based on socioeconomic and geographic factors.3 Bhattacharjee et al conducted an extensive demographic analysis of global fertility trends in 204 countries and territories from 1950 to 2021,4 with projections up to 2100, illustrating the complex interaction of demographic factors influencing fertility and infertility rates.

Female infertility is attributed to multiple epidemiological risk factors worldwide, covering sociocultural determinants (early marriage, delayed childbearing), reproductive and sexually transmitted infections, as well as exposure to environmental toxicants. The uneven geographic distribution of these risk factors leads to marked disparities in the global burden of female infertility. To interpret such heterogeneity, we conducted stratified analyses by Socio-demographic Index (SDI) and age groups. Analyzing the correlation between socioeconomic development and infertility burden facilitates rational allocation of reproductive health resources, while age-specific trends can supply differentiated evidence for population-level reproductive health policy formulation. Monitoring long-term temporal changes in infertility burden allows policymakers to screen regions with increasing or decreasing disease load and implement tailored reproductive health interventions within constrained public health budgets.

Expanding on prior research, our study delves into the topic of female infertility, examining patterns from 1990 to 2021 using the latest data from the Global Burden of Disease Study 2021 (GBD2021). The GBD2021 database serves as a comprehensive resource for gathering, organizing, and analyzing epidemiological data on various diseases worldwide, facilitating the evaluation and measurement of their impact on global health. This research seeks to present a thorough examination of the global burden and trends in female infertility burden over the period of 1990 to 2021, offering valuable insights for the global management of FI.

Materials and Methods

Data Sources

The study sourced data from the GBD 2021 database, which aggregates disease-related information from various sources such as disease registries, cause-of-death statistics, and medical records worldwide. The database includes health status data categorized by age group and gender for all countries and regions, facilitating a comprehensive assessment of the global burden of diseases and allowing for comparisons of health statuses across different regions and countries.6,7 This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by University of Washington. This study employed publicly available data that did not include confidential or personally identifiable patient information. Data were extracted from the GBD 2021 database for female infertility, including DALYs and DALY rates from 1990 to 2021. The extracted dataset included female populations aged 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, and 45–49 years, with both number and rate metrics retrieved for all available countries and territories. In addition to national-level burden estimates, the GBD 2021 database provides independent modelled disease burden outputs for subnational administrative units within Pakistan, including Islamabad Capital Territory and Gilgit-Baltistan. All accessible subnational DALY modelled estimates were fully retained during data extraction. To visualize intra-country heterogeneity of female infertility burden, both national aggregate data and subnational regional data of Pakistan were displayed together in the Results section.

Definitions

Infertility is clinically defined as the inability to achieve pregnancy after 1 year of regular, unprotected intercourse, or after 6 months for women over 35 years old. It is classified as primary if no pregnancy has ever occurred, and secondary if at least one previous pregnancy has been achieved. Diseases related to infertility are coded using the International Classification of Diseases, 11th edition (ICD-11) codes for FI (GA31.0, GA31.1, and GA31.Z).

Methods of Analysis

This study utilized DALYs and DALY rates for FI sourced from the GBD 2021 database as key indicators for each region and country spanning from 1990 to 2021. DALYs represent a comprehensive measure capturing the overall health impact of a disease, calculated by summing the years of life lost (YLL) due to premature death and the years lived with disability (YLD): DALYs=YLL+YLD. DALYs offer valuable insights into the quantity of healthy years compromised by an individual or population due to a specific disease or injury within a specified timeframe. They play a pivotal role in assessing the general health status of diverse populations, regions, or countries. The DALY rate, on the other hand, is derived by dividing the total DALYs by the population size or a particular demographic group, typically denoted as the disease burden per 1,000 individuals in a specific region, year, or group. A higher DALY rate signifies a more substantial disease burden for that particular area or demographic group.

When comparing regions with different population structures or analyzing disease indicators within the same region over different years, the age-standardized rate (ASR) per 100,000 population is commonly employed. Age standardization was performed using the GBD 2021 global standard population. This rate is calculated as follows:

graphic file with name Tex001.gif

where denotes a particular disease burden indicator for the ith age group, eg, the DALY rate, and denotes the corresponding standardized population weight.8

In this study, the data was standardized by age and age-standardized DALY rates were used for different countries and regions from 1990 to 2021. The estimated annual percentage change (EAPC) and its 95% confidence intervals (CIs) were also utilized to detect notable trends in the overall burden of FI between 1990 and 2021.9 The EAPC is a widely employed method for assessing trends in disease burden indicators over time, calculated through a specific formula.

graphic file with name Tex002.gif
graphic file with name Tex003.gif

The Socio-Demographic Index (SDI) is a comprehensive measure that combines economic, educational, and reproductive data to assess levels of social development.9 SDI values typically range from 0 to 1, with higher scores indicating regions with more advanced socioeconomic and demographic development. Global regions were categorized into five groups based on their SDI levels: high, medium-high, medium, medium-low, and low. Stratification cut-points followed standard GBD 2021 criteria: high SDI (≥0.80), high-middle SDI (0.70–0.79), medium SDI (0.60–0.69), low-middle SDI (0.40–0.59), and low SDI (<0.40). To elaborate our analytical framework, we conducted pairwise comparisons of FI burden in 1990 and 2021 to enable straightforward cross-regional horizontal contrasts. Meanwhile, the EAPC model incorporated all annual estimates spanning 1990–2021 to capture sustained long-term temporal trends. A temporal trend was deemed statistically significant if its corresponding 95% CI excluded zero. Linear regression analysis was performed to quantify the linear association between continental SDI and age-standardized DALY rates of FI in 1990 and 2021. The coefficient of determination R2 and corresponding P-values were reported to reflect the strength and statistical significance of correlations across each continent.

Statistical analyses were conducted using the Kruskal–Wallis test to compare age-standardized DALY rates across continents. The Kruskal–Wallis test is a non-parametric method that assesses whether there are statistically significant differences in medians among three or more independent groups. This test was selected for its ability to handle non-normally distributed data effectively. For post-hoc pairwise comparisons across continents, Dunn’s test with Bonferroni multiplicity correction was applied to control type I error inflation. All annual continental modelled DALY estimates of female infertility derived from GBD were treated as independent analytical units for intercontinental comparisons. A p-value below 0.05 was deemed statistically significant. It should be noted that the Kruskal–Wallis and Dunn’s tests in this study were performed based on point estimates of age-standardized DALY rates from GBD 2021, without incorporating the accompanying 95% uncertainty intervals of modelled outputs into intergroup comparison tests. This separate handling of point values and uncertainty ranges may underestimate the overall statistical uncertainty of intercontinental comparisons, which we have acknowledged as a limitation of the present study in the Discussion section.

Statistical analysis and data visualization in this study were conducted using R software (version 4.3.1). Data management was conducted using the dplyr package, and data visualization was performed using the ggplot2 package.

Results

Age-Standardized DALY Rates and Changes in FI in Different Global Regions During 1990–2021

The age-standardized DALY rate for FI globally was 15.12 per 100,000 (95% UI: 5.35, 36.88) in 2021, indicating an increase from the rate of 12.32 per 100,000 (95% UI: 4.39, 30.93) in 1990. There was a noticeable upward trend in the global DALYs for FI from 1990 to 2021, with an EAPC of 0.71 (95% CI: 0.5907, 0.8271) (Table 1).

Table 1.

Global Burden of Age-Standardized DALY Rate of Female Infertility in 1990, 2021 and EAPC in Different Regions of the World

location ASR in 1990 (Per 100,000),
value (95% CI)
ASR in 2021 (Per 100,000),
value (95% CI)
EAPC (95% CI), %
Global 12.32 (4.39, 30.93) 15.12 (5.35, 36.88) 0.71 (0.5907, 0.8271)
Sociodemographic index – – –
High SDI 5.85 (1.77, 15.46) 7.83 (2.20, 21.41) 1.41 (1.3006, 1.5167)
High-middle SDI 15.51 (5.41, 40.19) 17.04 (5.87, 41.71) 0.27 (0.2504, 0.2814)
Middle SDI 14.30 (4.94, 35.35) 16.47 (5.84, 39.99) 0.62 (0.5388, 0.7020)
Low-middle SDI 11.45 (4.01, 27.23) 16.34 (5.70, 39.57) 1.19 (0.8111, 1.5605)
Low SDI 12.12 (4.52, 27.60) 12.80 (4.73, 31.10) 0.11 (−0.1590, 0.3783)
Region - - -
Andean Latin America 0.38 (0.12, 0.98) 2.71 (0.23, 9.58) 8.11 (7.0755, 9.1596)
Australasia 0.75 (0.12, 3.24) 0.87 (0.14, 3.67) 0.83 (0.7300, 0.9232)
Caribbean 13.22 (5.08, 32.55) 13.19 (4.88, 33.64) −0.13 (−0.2368, −0.0183)
Central Asia 8.03 (2.65, 20.02) 8.44 (2.67, 20.74) 0.83 (0.6616, 0.9984)
Central Europe 11.18 (3.56, 28.09) 13.60 (4.29, 34.98) 0.84 (0.7525, 0.9362)
Central Latin America 4.49 (1.13, 12.67) 8.71 (2.50, 23.20) 1.17 (0.9015, 1.4353)
Central Sub-Saharan Africa 14.13 (4.47, 33.38) 15.23 (4.70, 35.74) −0.13 (−0.5451, 0.2910)
East Asia 20.52 (6.83, 53.23) 21.55 (7.40, 54.10) 0.02 (−0.0150, 0.0532)
Eastern Europe 18.69 (6.52, 47.12) 20.11 (7.05, 51.09) 0.58 (0.4910, 0.6629)
Eastern Sub-Saharan Africa 13.32 (5.22, 29.97) 10.57 (3.79, 25.04) −1.23 (−1.4079, −1.0494)
High-income Asia Pacific 3.51 (0.24, 14.01) 3.24 (0.24, 12.55) −0.40 (−0.5697, −0.2227)
High-income North America 3.06 (0.24, 9.60) 4.90 (0.58, 15.30) 2.91 (1.9326, 3.8936)
North Africa and Middle East 7.54 (2.85, 16.38) 10.93 (3.36, 27.16) 1.09 (0.9168, 1.2642)
Oceania 9.09 (2.66, 23.39) 5.90 (2.05, 14.25) −1.53 (−1.7150, −1.3445)
South Asia 12.56 (3.93, 30.53) 19.74 (7.09, 46.79) 1.85 (1.4414, 2.2562)
Southeast Asia 12.11 (4.20, 30.16) 16.11 (5.57, 40.33) 1.66 (1.4285, 1.8834)

In 2021, East Asia had the highest age-standardized DALY rate for FI at 21.55 per 100,000 (95% UI: 7.40, 54.10), followed by Eastern Europe and South Asia. These regions showed a significant burden of FI, with the highest rates worldwide.

The regions with the most significant increases in FI burden, as measured by the EAPC, were Andean Latin America, which had the highest EAPC of 8.11 (95% CI: 7.0755, 9.1596), indicating a significant rise in FI burden over the study period. High-income North America also exhibited a notable increase with an EAPC of 2.91, followed by South Asia with an EAPC of 1.85 (refer to Tables 1, S3 and Figures 1, 2).

Figure 1.

Two bar graphs comparing age-standardized disability adjusted life year rates by region in 1990 and 2021. Two bar graphs illustrate age-standardized disability-adjusted life year rates across global regions. Each region has four bars representing rate groupings of 5, 10, 15 and 20, with error bars. The Y-axis shows ASRs from 0 to 50 in image A and 0 to 60 in image B. The X-axis lists regions like Global, High income, Low SDI and others. In 1990 (image A), most regions have values between 5 and 25, with Oceania and South Asia higher, near 35 to 40. In 2021 (image B), South Asia peaks at about 60, with Low SDI and High income North America also notable. Low income and Low SDI regions generally have higher rates than high income regions. Rates in South Asia and Andean Latin America increase from 1990 to 2021, while high income regions remain lower across both years.

Global burden of female infertility from 1990 to 2021, by locations. (A) Age-standardized DALY rate in 1990; (B) Age-standardized DALY rate in 2021.

Abbreviation: DALY, disability adjusted life-year.

Figure 2.

A bar graph showing EAPCs for DALYs by region in 1990 to 2021. A bar graph titled ′DALYs (Disability Adjusted Life Years) by Region, 1990-2021′ illustrates EAPCs for various regions. The X-axis includes regions like Global, High SDI, Middle SDI, Low SDI and specific areas such as Andean Latin America, Australasia, Caribbean, Central Asia and more. The Y-axis displays EAPCs from approximately -2.5 to 9.0. Notable data points are: Andean Latin America (~8.1), High income North America (~2.9), South Asia (~1.9), High SDI (~1.4), Low middle SDI (~1.2), Central Latin America (~1.1), Southeast Asia (~1.7), Tropical Latin America (~1.6), Oceania (~-1.6), Eastern Sub Saharan Africa (~-1.3), Southern Sub Saharan Africa (~-0.8) and High income Asia Pacific (~-0.5). The legend marks EAPCs at intervals of 0, 2, 4, 6 and 8.

Global burden trend of age-standardized DALY rate of female infertility from 1990 to 2021, by SDI regions.

Abbreviation: DALY, disability adjusted life-year.

Conversely, Australasia reported the lowest age-standardized DALY rate in 2021 at 0.87 per 100,000, followed by Andean Latin America and High-income Asia Pacific.

Significant reductions in FI burden were observed in various regions. Oceania saw the most substantial decrease with an EAPC of −1.53. Eastern Sub-Saharan Africa also experienced a notable decline, with an EAPC of −1.23, while Southern Sub-Saharan Africa showed a reduction in FI burden with an EAPC of −0.80.

The disease burden increased significantly in both high-SDI and low-middle-SDI countries. Although high-SDI countries had a lower age-standardized DALY rate compared to countries at other SDI levels, the EAPC for DALYs in high-SDI countries during the study period was 1.57 (95% CI: 1.30, 1.83), the highest among all regions (Table 1 and Figure 2). Furthermore, the age-standardized DALY rate in low-middle SDI countries rose from 11.45 in 1990 to 16.34 in 2021, with an EAPC of 1.19 over the same period (Figure S2).

Age-Standardized DALY Rates and Changes in FI in Different Countries During 1990–2021

In 2021, the countries with the highest age-standardized DALY rates for female infertility were Islamabad Capital Territory (45.57 per 100,000; 95% UI: 10.92, 115.53), Central African Republic (31.40 per 100,000; 95% UI: 11.58, 71.65), and Gilgit-Baltistan (28.98 per 100,000; 95% UI: 5.50, 83.83). These regions exhibited a significant burden of female infertility, underscoring the substantial health impacts resulting from this condition.

In 2021, Australia had a low age-standardized DALY rate of 0.71 per 100,000 (95% UI: 0.12, 3.04), followed by Colombia with 1.26 per 100,000 (95% UI: 0.23, 3.38), and New Zealand with 1.72 per 100,000 (95% UI: 0.18, 7.33). These figures suggest that these countries experienced relatively lower burdens of FI.

When analyzing changes in the FI burden from 1990 to 2021, Ecuador exhibited the most significant increase with an EAPC of 9.15 (95% CI: 7.1341, 11.1983), followed by Peru with an EAPC of 7.08 (95% CI: 5.5385, 8.6525), and Bolivia (Plurinational State of) with an EAPC of 6.65 (95% CI: 3.8837, 9.4953). These countries witnessed the most substantial rises in FI burden over the study period.

Conversely, countries that experienced the most substantial reductions in female infertility burden were Malawi, showing an EAPC of −6.18 (95% CI: −6.6207, −5.7290), Pakistan with an EAPC of −5.46 (95% CI: −9.9167, −0.7835), and Uganda with an EAPC of −5.02 (95% CI: −5.3870, −4.6503). These regions have made significant progress in addressing the burden of female infertility over the past three decades, as shown in Tables S1, S2, S4 and Figures 1, S1.

Age-Specific Trends in DALY Rates for Female Infertility

The study found that DALY rates were lower in younger age groups and increased with age, reaching a peak in the 40–44 years age group. Notably, the highest DALY rate was observed in individuals aged 40–44 years, with a significant decrease in those aged 45–49 years who showed lower DALY rates compared to most other age groups.

The incidence of DALY was relatively low among individuals aged 20–24 years, gradually increasing in the 25–29 and 30–34 age groups. The rates peaked in the 40–44 age group, followed by a significant decrease in the 45–49 age group. DALY rates for FI decreased notably beyond 50 years of age, with minimal rates observed in older age groups (50 years and above) (Table S2 and Figure S3).

SDI and DALY Rates in Different Global Regions During 1990 and 2021

In 1990 (Figure 3A), the scatter plot illustrates a weak correlation between SDI and DALY rates across all continents. Africa exhibited an R2 value of 0.003 (p=0.6943), indicating a minimal correlation. Similarly, America, Asia, Europe, and Oceania had R2 values of 0.044 (p=0.2336), 0.078 (p=0.0704), 0.145 (p=0.0185), and 0.08 (p=0.2415), respectively. These findings suggest that a higher SDI is not strongly associated with lower DALY rates in the year 1990.

Figure 3.

Scatter plots of DALY against SDI by continent for 1990 and 2021, labeled A and B. The image A showing a scatter plot titled, Scatter plot of 1990 vs SDI by continent. The horizontal axis label is SDI with tick labels 0.25, 0.50, 0.75. The vertical axis label is DALY with tick labels 0, 10, 20. A legend lists Africa, America, Asia, Europe, Oceania, with distinct point markers and matching fitted trend lines for each continent. The fitted line for Africa is nearly flat with a slight downward slope. The fitted line for America slopes upward. The fitted line for Asia slopes downward. The fitted line for Europe slopes downward more steeply than Asia. The fitted line for Oceania slopes downward. Point distribution shows many points concentrated around SDI near 0.60 to 0.80 and DALY near 8 to 14, with fewer points at SDI near 0.25 to 0.40. Several higher DALY points appear above 20, mainly at SDI below about 0.60. The printed statistics are: Africa R2: 0.003 p: 0.6943; America R2: 0.044 p: 0.2336; Asia R2: 0.078 p: 0.0704; Europe R2: 0.145 p: 0.0185; Oceania R2: 0.08 p: 0.2415. The image B showing a scatter plot titled, Scatter plot of 2021 vs SDI by continent. The horizontal axis label is SDI with tick labels 0.25, 0.50, 0.75. The vertical axis label is DALY with tick labels 0, 10, 20. A legend lists Africa, America, Asia, Europe, Oceania, with distinct point markers and matching fitted trend lines for each continent. The fitted line for Africa is nearly flat with a slight upward slope. The fitted line for America slopes upward. The fitted line for Asia slopes downward. The fitted line for Europe slopes downward. The fitted line for Oceania slopes downward. Point distribution shows many points concentrated around SDI near 0.60 to 0.85 and DALY near 6 to 12, with fewer points at SDI below about 0.40. Several higher DALY points appear above 20, mainly at SDI below about 0.60. The printed statistics are: Africa R2: 0 p: 0.890; America R2: 0.032 p: 0.314; Asia R2: 0.036 p: 0.223; Europe R2: 0.07 p: 0.110; Oceania R2: 0.047 p: 0.375.

Scatter plots showing the correlation between the age-standardized DALY rates of female infertility burden and SDI levels across regions; Panel (A) corresponds to 1990 data, and Panel (B) corresponds to 2021 data.

Abbreviation: DALY, disability adjusted life-year.

The scatter plot for 2021 (Figure 3B) continues to demonstrate a weak correlation between SDI and DALY rates. Africa’s R2 value remained insignificant at 0 (p=0.890), while America, Asia, Europe, and Oceania showed R2 values of 0.032 (p=0.314), 0.036 (p=0.223), 0.07 (p=0.110), and 0.047 (p=0.375), respectively. Across 1990 and 2021, SDI served as a weak, non-significant predictor of FI burden across continents. These results suggest that as of 2021, SDI was not a significant predictor of DALY rates for FI across various continents.

Significant differences were observed between continents, particularly between Asia and Africa (p=0.012). However, no significant differences were noted between America and Africa (p=0.72), Asia and Oceania (p=0.099), Europe and Oceania (p=0.094), Africa and Europe (p=0.27), America and Asia (p=0.2), America and Oceania (p=0.6), Asia and Europe (p=0.4), Europe and Asia (p=0.33), and Europe and America (p=0.55) (Figure 4).

Figure 4.

A box plot showing age standardized disability adjusted life year rate for female infertility by continent. A box plot with overlaid points comparing age standardized disability adjusted life year rate for female infertility across continents. The x axis label is, Continent, with categories America, Asia, Europe, Oceania and Africa. The y axis label is, Value, ranging from 0 to 60 with labeled ticks at 0, 20, 40 and 60. Each continent shows a box with a median line and whiskers, plus individual data points. Bracketed p values above groups read 0.6, 0.2, 0.55, 0.4, 0.33, 0.27, 0.094, 0.099, 0.012 and 0.72. America points span roughly 1 to 21 with the box roughly 6 to 16 and median near 12. Asia points span roughly 2 to 24 with the box roughly 7 to 12 and median near 10. Europe points span roughly 2 to 19 with the box roughly 6 to 11 and median near 10. Oceania points cluster near 11 to 12 with a few low points near 1 to 4 and one higher point near 18. Africa points span roughly 2 to 31 with the box roughly 7 to 17 and median near 11.

Comparison with box plots of age-standardized DALY rate for the global burden of female infertility in 2021. DALY = disability adjusted life-year. (The box extends from the 25th percentile to the 75th percentile, with the center line indicating the median; the bottom whisker line indicates the minimum value, and the top whisker line indicates the 75th percentile plus 1.5 times the interquartile distance (the distance between the 25th and 75th percentiles). The p-values from the Kruskal–Wallis test are labeled in the figure. Statistical significance is indicated by p < 0.05.).

Discussion

The analysis of age-standardized DALY rates for female infertility from 1990 to 2021 reveals significant regional disparities and temporal trends. The global increase in burden, particularly in regions like East Asia, Eastern Europe, and South Asia, highlights the widespread impact of this public health issue. The noticeable rise in burden in Andean Latin America, High-income North America, and South Asia, supported by significant EAPC values, indicates a complex interplay of contributing factors. The increase in high-SDI countries, despite lower absolute DALY rates, suggests underlying issues such as delayed childbearing, lifestyle-related health issues, and potentially improved diagnostic capabilities for identifying infertility problems more effectively.

Numerous studies in various regions have highlighted exposure to toxic and chemical substances, human immunodeficiency virus (HIV) infection, reproductive tract infections, early age at first birth, inadequate care after unsafe abortions, and post-partum infections as significant risk factors for FI.10–12 Countries in East Asia, Eastern Europe, and South Asia are predominantly agrarian with inadequate health and hygiene standards, which heightens women’s exposure to harmful substances and consequently increases the risk of FI.10 The high prevalence of HIV, particularly in Africa, not only directly impacts fertility but also contributes to other reproductive tract infections.11 Sociocultural factors such as early marriage, young age at first birth, and inadequate post-abortion care further compound the risk of FI.12 These sociocultural influences play a significant role in reproductive decisions and health behaviors, exacerbated by a general lack of knowledge and awareness about FI, its causes, treatment, and the importance of seeking medical assistance.13 In South Asia, the interplay of socio-economic and cultural factors is notably intricate. The prevalence of early marriages and childbearing, along with insufficient maternal healthcare, can result in higher rates of reproductive tract infections and complications, ultimately increasing the burden of FI. Additionally, widespread poverty and limited healthcare access exacerbate the issue, as many women do not receive timely and adequate treatment for conditions that may lead to infertility.

The higher age-standardized DALY rate of FI in Andean Latin America is largely influenced by socio-economic disparities and restricted access to reproductive health services, which collectively contribute to the burden of FI. Unsafe abortions and insufficient post-abortion care only serve to worsen this problem. Moreover, exposure to environmental toxins resulting from agricultural practices and mining activities likely plays a role in the elevated rates of FI in the region. Meanwhile, high EAPC values were observed for Andean Latin America and Ecuador in this study. According to the general output patterns of the GBD modelling framework, regions lacking long-term historical health surveillance data and with low baseline DALY burdens in 1990 tend to produce inflated estimates of annual percentage change. Therefore, the dramatic rising trends detected in these regions cannot fully reflect the real changes in the prevalence of female infertility; such extreme values may arise jointly from the extremely low baseline disease burden in 1990 and insufficient local epidemiological surveillance data. High-income North America poses unique challenges in the field of fertility issues. The trend of delayed parenthood, influenced by career and educational goals, has led to a rise in age-related infertility. Additionally, lifestyle factors like obesity, stress, and dietary habits are further exacerbating the burden of fertility issues in this region. The higher EAPC values observed here indicate enhanced diagnostic technologies and increased awareness, resulting in more cases being recognized and documented.

In South Asia, socio-cultural practices, such as consanguineous marriages, may contribute to genetic factors that increase infertility rates. Furthermore, the high prevalence of untreated sexually transmitted infections (STIs) and reproductive tract infections, due to inadequate healthcare infrastructure, also plays a significant role.13,14 The stigma associated with infertility often deters women from seeking timely medical intervention, thereby exacerbating the issue.

The limited availability of healthcare resources, such as essential diagnostic and treatment technologies and specialized personnel,15–17 poses a significant challenge to accessing effective healthcare services for FI in less developed regions. This disparity exacerbates the burden of the disease, emphasizing the need for region-specific interventions to address FI. The global burden of FI has varied based on SDI levels from 1990 to 2021. High-middle-SDI and Middle-SDI regions have experienced the highest disease burden, while high-SDI countries have shown a lower overall burden but the highest rate of increase. Differences in FI burden across countries with varying SDI levels can be attributed to factors such as higher education levels and increased participation of women in occupational and educational activities in high-SDI countries, leading to delays in childbearing and subsequently increasing the risk of FI.17 Despite having a relatively low overall burden, the prevalence of delayed childbearing in high-SDI countries has contributed to a rise in FI burden.

Disparities in the availability and quality of infertility care services between developed and less-developed countries are evident, with high-SDI countries having more advanced healthcare resources and technologies. Despite the long-standing presence of complementary treatment programs,18 access to these services remains challenging in less-developed countries due to limited public funding and other obstacles.19 This discrepancy contributes to variations in DALYs for infertility between countries with different SDI levels. High-SDI countries have access to superior diagnostic and treatment options for infertility, leading to more effective outcomes.20 In contrast, countries with lower SDI levels often face shortages in healthcare resources and services, such as a lack of specialized facilities for infertility diagnosis and treatment, outdated medical technologies, and inadequate medical personnel. These deficiencies present significant hurdles for infertility patients, hindering their access to proper medical care and treatment, thus increasing the disease burden. Notably, our cross-continental analysis revealed a novel and counterintuitive result: SDI exhibited nearly no linear correlation with female infertility burden across all continents between 1990 and 2021, with R2 values close to zero. This finding contradicts the typical developmental gradient of non-communicable diseases, whereby higher socioeconomic development is generally associated with lower disease burden. Such a weak correlation can be attributed to offsetting regional factors. In high-SDI regions, delayed childbearing and adverse lifestyle factors increase infertility risk, whereas well-developed reproductive healthcare systems reduce disease-related losses. In contrast, low- and medium-SDI regions face limited medical access, while traditional early childbearing practices decrease the risk of late-onset infertility. These opposing effects jointly weaken and eliminate the conventional socioeconomic gradient for female infertility burden.

Sociocultural factors, economic conditions, and the healthcare system have varying impacts on the burden of FI in different countries and regions. Further research and analysis are essential to gain a deeper insight into these variations, which can then be used to develop specific measures to alleviate the FI burden. The global distribution of DALY rates for FI in 2021 indicated a rise with age, peaking among individuals aged 40–44 years, followed by a sharp decline in those aged 45–49 years. In a study by Maheshwari et al,21 a diagnostic survey of 7,172 women highlighted a correlation between age and the causes of FI, showing that older women are more likely to experience unexplained infertility. A comprehensive investigation focusing on the fertility intentions and reproductive health of younger women, as well as the infertility risks and treatment requirements of middle-aged and older women, could lead to more targeted interventions aimed at reducing the burden of infertility across different age groups.

This study investigated the global distribution and changes in the burden of FI, focusing on DALYs and DALY rates across regions, countries, and age groups from 1990 to 2021. By comparing data over this period, the research aimed to quantify the global impact of FI, highlighting its scale and distribution while analyzing trends comprehensively. However, the study’s findings are limited by potential gaps or inaccuracies in data collection, particularly in certain regions, which could impact the reliability of estimates. Discrepancies in data collection methods across countries and regions may also introduce errors into the results. Although the analysis primarily contrasts data from 1990 and 2021, the availability of Global Burden of Disease data for intermediate years suggests the need to consider non-linear trends and variations between regions or SDI groups. Utilizing more detailed time series data could offer deeper insights into these non-linear trends and reveal variations that are not evident in a simple comparison of two time points.

As the global burden of FI continues to increase, there is an urgent need to intensify research efforts on FI, delve deeper into studying and evaluating the associated burden of disease, and establish a scientific foundation for designing more efficient intervention strategies. Future studies should explore the influences of diverse factors on the FI burden, such as sociocultural and economic factors, geographical disparities, education levels, and healthcare resources. By comprehensively examining the interplay of these factors, a more precise assessment and explanation of the formation and fluctuations in the FI burden can be achieved.

Conclusions

The Global Burden of Disease Study data on female infertility revealed a rising trend worldwide from 1990 to 2021, with notable variations across different regions. The most rapid growth of female infertility burden was observed in high-SDI regions, while low-middle SDI regions also presented a prominent upward trend from 1990 to 2021. The overall burden of female infertility shifted towards older age groups, particularly those between 40–44 years old. Despite marked subgroup gaps in burden growth and absolute DALY values across SDI tiers, there is no significant linear correlation between SDI and female infertility burden worldwide, owing to offsetting risk and protective factors in regions of different socioeconomic levels.

The rise in infertility-attributable DALYs has two underlying causes: first, a genuine increase in infertility risk driven by delayed childbearing and environmental factors; second, expanded access to reproductive healthcare that identifies more previously undiagnosed cases. Low- and middle-SDI regions carrying the highest absolute infertility burden and limited reproductive medical resources should be the priority of intervention, while high-SDI regions with rapidly growing burden also require targeted fertility management. According to the regional, SDI-stratified and age-based burden disparities observed in this study, differentiated public health strategies are urgently needed. High-SDI areas should widely provide fertility counseling and ovarian function screening to mitigate infertility related to delayed childbearing. Low- and middle-SDI regions need increased investment in grassroots reproductive medical services, professional clinicians, and campaigns to eliminate fertility-related stigma. Global age-specific reproductive health education is also vital for early intervention to reduce infertility burden.

Finally, several limitations should be noted. This ecological descriptive analysis cannot confirm causal relationships, and inconsistent regional data recording standards may compromise data accuracy. Therefore, all results ought to be interpreted cautiously. Another limitation is that intergroup statistical comparisons across continents relied solely on point estimates of DALY indicators rather than integrating the full 95% uncertainty intervals of GBD predictions, which may underestimate the overall uncertainty of our intercontinental difference results. Therefore, all results ought to be interpreted cautiously.

Acknowledgments

We thank all authors for their contributions to the article.

Funding Statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data Sharing Statement

The data that support this study are available in [Global Burden of Disease Study (GBD)] at [http://ghdx.healthdata.org/gbd-results-tool].

Statement of Ethics

This research study was exempted from formal ethical review in accordance with Items 1 and 2 of Article 32 of the Measures for the Ethical Review of Life Science and Medical Research Involving Human Subjects issued by China on February 18, 2023. The relevant legal provisions stipulate that this type of research does not require institutional ethical approval. All data utilized in this work were publicly available aggregated population data without identifiable individual personal information; no human participants were directly recruited or interviewed, and no biological specimens were collected. Therefore, we confirm that all standardized ethical procedures specified by national regulatory guidelines have been fully followed in the present study.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report there are no competing interests to declare.

References

  • 1.WHO Guidelines Approved by the Guidelines Review Committee. Guideline for the Prevention, Diagnosis and Treatment of Infertility. Geneva: World Health Organization;2025. [PubMed] [Google Scholar]
  • 2.Weiss RV, Clapauch R. Female infertility of endocrine origin. Arquivos brasileiros de endocrinologia e metabologia. 2014;58(2):144–11. doi: 10.1590/0004-2730000003021 [DOI] [PubMed] [Google Scholar]
  • 3.Borumandnia N, Majd HA, Khadembashi N, Alaii H. Assessing the trend of infertility rate in 198 countries and territories in last decades. Iran J Public Health. 2021;50(8):1735–1737. doi: 10.18502/ijph.v50i8.6840 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Collaborators. Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403(10440):2057–2099. doi: 10.1016/S0140-6736(24)00550-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Sun H, Gong TT, Jiang YT, Zhang S, Zhao YH, Wu QJ. Global, regional, and national prevalence and disability-adjusted life-years for infertility in 195 countries and territories, 1990-2017: results from a global burden of disease study, 2017. Aging. 2019;11(23):10952–10991. doi: 10.18632/aging.102497 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Vos T, Lim SS, Abbafati C, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1204–1222. doi: 10.1016/S0140-6736(20)30925-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Murray CJL. The global burden of disease study at 30 years. Nature Med. 2022;28(10):2019–2026. doi: 10.1038/s41591-022-01990-1 [DOI] [PubMed] [Google Scholar]
  • 8.Liu Z, Jiang Y, Yuan H, et al. The trends in incidence of primary liver cancer caused by specific etiologies: results from the Global Burden of Disease Study 2016 and implications for liver cancer prevention. J Hepatol. 2019;70(4):674–683. doi: 10.1016/j.jhep.2018.12.001 [DOI] [PubMed] [Google Scholar]
  • 9.Clegg LX, Hankey BF, Tiwari R, Feuer EJ, Edwards BK. Estimating average annual per cent change in trend analysis. Stat Med. 2009;28(29):3670–3682. doi: 10.1002/sim.3733 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Egbe TO, Mbaki CN, Tendongfor N, Temfack E, Belley-Priso E. Infertility and associated factors in three hospitals in Douala, Cameroon: a cross-sectional study. Afr Health Sci. 2020;20(4):1985–1995. doi: 10.4314/ahs.v20i4.57 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Dhont N, van de Wijgert J, Luchters S, Muvunyi C, Vyankandondera J, Temmerman M. Sexual violence, HSV-2 and HIV are important predictors for infertility in Rwanda. Hum Reprod. 2010;25(10):2507–2515. doi: 10.1093/humrep/deq189 [DOI] [PubMed] [Google Scholar]
  • 12.Legese N, Tura AK, Roba KT, Demeke H. The prevalence of infertility and factors associated with infertility in Ethiopia: analysis of Ethiopian Demographic and Health Survey (EDHS). PLoS One. 2023;18(10):e0291912. doi: 10.1371/journal.pone.0291912 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Ombelet W, Campo R. Affordable IVF for developing countries. Reproduct Biomed Online. 2007;15(3):257–265. doi: 10.1016/S1472-6483(10)60337-9 [DOI] [PubMed] [Google Scholar]
  • 14.Nachtigall RD. International disparities in access to infertility services. Fertil Sterility. 2006;85(4):871–875. doi: 10.1016/j.fertnstert.2005.08.066 [DOI] [PubMed] [Google Scholar]
  • 15.Zhang W, Cui Y, Liu J. The association between aldehydes exposure and female infertility: a cross-sectional study from NHANES. Medicine. 2023;102(25):e33849. doi: 10.1097/MD.0000000000033849 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kundu S, Ali B, Dhillon P. Surging trends of infertility and its behavioural determinants in India. PLoS One. 2023;18(7):e0289096. doi: 10.1371/journal.pone.0289096 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Mascarenhas MN, Flaxman SR, Boerma T, Vanderpoel S, Stevens GA. National, regional, and global trends in infertility prevalence since 1990: a systematic analysis of 277 health surveys. PLoS Med. 2012;9(12):e1001356. doi: 10.1371/journal.pmed.1001356 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Njagi P, Groot W, Arsenijevic J, Dyer S, Mburu G, Kiarie J. Economic costs of infertility care for patients in low-income and middle-income countries: a systematic review protocol. BMJ open. 2020;10(11):e042951. doi: 10.1136/bmjopen-2020-042951 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Inhorn MC, Patrizio P. Infertility around the globe: new thinking on gender, reproductive technologies and global movements in the 21st century. Human Reproduction Update. 2015;21(4):411–426. doi: 10.1093/humupd/dmv016 [DOI] [PubMed] [Google Scholar]
  • 20.Carson SA, Kallen AN. Diagnosis and management of infertility: a review. Jama. 2021;326(1):65–76. doi: 10.1001/jama.2021.4788 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Maheshwari A, Hamilton M, Bhattacharya S. Effect of female age on the diagnostic categories of infertility. Hum Reprod. 2008;23(3):538–542. doi: 10.1093/humrep/dem431 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support this study are available in [Global Burden of Disease Study (GBD)] at [http://ghdx.healthdata.org/gbd-results-tool].


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