Global, regional, and national burden and trend of infertility and its subtypes from 1990 to 2021, with projections to 2035

Purpose To study the global, regional and national burden and trend of primary and secondary infertility, by sex and sociodemographic index (SDI), over the period 1990–2021.

Data on the prevalence and disability-adjusted life years (DALYs) due to infertility and its subtypes were retrieved from the GBD study 2021 for 204 countries and territories from 1990 to 2021. The counts and age-standardized rates are presented, along with their corresponding 95% uncertainty intervals (UIs). Estimated annual percentage changes (EAPCs) were computed using linear regression analysis. Decomposition analysis was conducted to determine the effects of population growth, aging, and epidemiological shifts on disease burden. Frontier analysis was performed to identify potential improvement areas and disparities among countries by development status. Bayesian age-period-cohort analysis (BAPC) predicted global lung cancer mortality from 2020 to 2035.

Globally, the age-standardized prevalence rate (ASPR) of infertility changed from 4071.04 (95% UI: 2660.05, 6223.25) per 100,000 in 1990 to 5030.42 (3207.13, 7918.99) per 100,000 in 2021, with the EAPC being 0.65. The age-standardized DALYs rate (ASDR) changed from 23.15 (8.91, 53.73) per 100,000 in 1990 to 28.54 (11.05, 67.94) per 100,000 in 2021, with the EAPC being 0.52. It is anticipated that the ASPR exhibits a downward trend for overall primary infertility, whereas they are expected to show an upward trend for overall secondary infertility by 2035, in comparison with 2021.

Governments and the public should recognize the magnitude of the issue of infertility and prioritize implementing targeted interventions and strategies to improve reproductive health worldwide. Supplementary Information The online version contains supplementary material available at 10.1007/s10815-025-03592-5.

Infertility, Global Burden of Disease, Prevalence, Disability Adjusted Life Years

Infertility is characterized as a condition of the reproductive system, indicated by the inability to achieve a clinical pregnancy following 12 months or more of consistent, unprotected sexual activity. Research indicates that approximately 10–20% of couples globally experience challenges related to infertility [1]. Reproductive capacity is fundamental in the context of family planning and is considered vital for the attainment of the 17 Sustainable Development Goals set forth by the United Nations. A thorough grasp of the breadth of infertility is essential for the effective observation, assessment, and improvement of fair access to high-quality fertility services, as well as for tackling its associated risk factors and outcomes. Infertility can be delineated into primary and secondary categories, contingent upon the clinical pregnancy history of the female, male, or their partner. Additionally, it can be classified according to its underlying causes into female infertility, male infertility, and infertility of unknown origin. Prominent factors contributing to female infertility encompass ovulation disorders and pelvic conditions, which affect the production, maturation, release, transport, and fertilization of oocytes, as well as the initial stages of embryonic development, implantation, and associated processes [2]. Predominantly, male infertility arises from sexual dysfunction and semen abnormalities, including azoospermia, oligospermia, or asthenospermia, as well as basic seminal plasma abnormalities [3]. The clinical definitions of infertility established by the World Health Organization (WHO) facilitate the prompt identification and management of infertility, employing medical histories and diagnostic assessments [1]. The Global Burden of Disease (GBD) employs a consistent demographic framework for the integration of household survey data, thereby enabling prompt, precise, and pertinent assessments of the infertility burden (Ferrari et al., 2024). The GBD 2021 characterized infertility as the lack of a live birth among couples in a partnership for a minimum of five years while attempting to conceive, as well as for those who have refrained from using contraceptives for the same period after their most recent live birth. In earlier versions of the GBD, the assessment focused on the global effects of infertility among both females and males [4, 5]. However, the GBD 2021 expanded its scope by integrating insights from 43 novel data sources and encompassing information from three more countries [6]. Consequently, the GBD 2021 provides a more current and thorough representation of infertility prevalence, including regions with scarce data. This recent version incorporates supplementary data regarding the prevalence of infertility during the pandemic years (2020–2021), thereby offering more up-to-date and reliable estimates. Previous research has investigated infertility across various age demographics collectively [4, 5], yet it is acknowledged that the cumulative likelihood of conception decreases as age increases [7]. The decrease in male fertility associated with advancing age, while not as extensively studied, is nonetheless corroborated by available data [8]. Given that various age cohorts exhibit specific probabilities of conception and fecundability, examining infertility prevalence across all age groups could obscure significant differences in fertility patterns. Recently, Liang et al. observed an increasing occurrence of infertility in both females and males within the childbearing age demographic worldwide from 1990 to 2021, predicting that this trend will continue at least until 2040 [9]. Nevertheless, there exists a gap in the exploration of distinct analyses and trend projections pertaining to primary and secondary infertility. Our aim is to perform an in-depth examination and comparison of the burden of infertility, focusing on both primary and secondary infertility, as well as male and female infertility. Our objective is to delineate the patterns of these indicators across diverse age cohorts globally, at both regional and national scales, spanning from 1990 to 2021. Additionally, we intend to forecast the incidence of infertility over the forthcoming 15 years. This article aims to explore the intricate patterns of infertility on a global scale and formulate approaches to improve reproductive health services.

Data source This research draws on data from the Global Burden of Disease (GBD) 2021 study, which offers systematic estimates of prevalence, incidence, disability-adjusted life years (DALYs) and mortality for 371 diseases and injuries across 204 countries and territories from 1990 to 2021. The GBD 2021 study integrates advanced methodologies and enhanced standardization, providing comprehensive and comparable health metrics that are stratified by age, sex, and country [10, 11]. Detailed methodology of the GBD 2021 study has been described in other publications [12–15]. Data on infertility including prevalence and DALYs were obtained from the Global Health Data Exchange (GHDx) website (https://vizhub.healthdata.org/gbd-results/). The dataset provides 95% uncertainty intervals to reflect the precision of the estimates [16]. This study utilized the Socio-demographic Index (SDI) for each country, an index that combines income per capita, average years of schooling, and fertility rates among females under 25 [17]. The SDI ranges from 0 to 1, with higher values signifying greater socioeconomic status. Countries were grouped into five quintiles based on their 2021 SDI scores. The GBD study uses anonymized data, and the Institutional Review Board at the University of Washington granted a waiver for informed consent. Estimation of disease burden of infertility in GBD 2021 According to the Global Burden of Disease Study 2021 [18], infertility is defined as “impairment”, a condition or specific domains of functional health loss that are spread across many GBD causes as sequelae and for which there are better data to estimate the occurrence of the overall impairment than for each sequela based on the underlying cause. Infertility encompasses both primary infertility and secondary infertility, which are defined as inability to conceive a child and have a livebirth without using contraceptives. Primary infertility is diagnosed in a couple who have not had a livebirth, desire a child, have been in a union for five years or longer, and are not using contraceptives at the time of the survey. Secondary infertility is diagnosed in a couple who last had a livebirth more than five years ago, desire a child, have been in a union for five years or longer, and are not using contraceptives at the time of the survey. GBD 2021 extend this analysis to then estimate the proportion of primary and secondary infertility in couples that are attributable to females and males, and we execute a “causal attribution” process to assign cases of primary female infertility, primary male infertility, secondary female infertility, and secondary male infertility to likely underlying causes. Meanwhile, GBD 2021 assumed zero infertility prior to age 15 or after age 50 years. In the GBD 2021 study, the prevalence was estimated using the Bayesian meta regression tool DisMod-MR-2.1. This modeling tool synthesizes data from population surveys, cohort studies, health system administrative records, and registry microdata [19]. DALYs were calculated by summing the years of life lost due to premature death and the years lived with disability [20]. The GBD analyzed infertility among population between 15 and 49 years old. The age-standardized prevalence and DALYs rates are calculated by applying a standard age distribution to the observed rates for females across different age groups, thereby removing the influence of age structure on these rates. This analysis adheres to the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) [21]. Statistical analysis Data analyses and visualizations were carried out using R software (version 4.4.1) and the Joinpoint Regression Program (version 5.2.0). Statistical significance was defined as a two-sided P-value of less than 0.05. Trends in infertility burden from 1990 to 2021 were illustrated by estimating prevalence and DALYs rates, including their 95% uncertainty intervals (UIs), expressed per 100,000 population. Estimated annual percentage changes (EAPCs) in prevalence and DALYs rates for infertility and its subtypes from 1990 to 2021 were computed using linear regression analysis to examine secular trends. In this analysis, β denotes the estimated slope from the regression model, with the 95% confidence intervals for the EAPC derived from the slope’s standard error. The EAPC serves as an indicator of rate trends over time, where a positive EAPC points to an upward trend and a negative EAPC signifies a downward trend. This study also applied Pearson’s correlation tests to evaluate the correlation between SDI and the prevalence and DALYs rate of infertility, further deepening our understanding of the relationship between disease burden and socioeconomic development levels. To elucidate the principal factors influencing the changes in the burden of infertility between 1990 and 2021, a decomposition analysis was performed. Decomposition analysis was used to quantify the contributions of aging, epidemiological changes, and population growth to the observed changes in infertility prevalence and DALYs. This method helps to identify the relative impact of these factors on disease trends, facilitating targeted public health interventions [22, 23]. The decomposition analysis involved calculating the effect of each factor on the overall trend and determining whether it contributed to an increase or decrease in the burden of infertility. Frontier analysis was used to analyse the ideal level of prevalence and DALYs of infertility for the 204 countries and territories at the corresponding SDI levels [24]. Through frontier analysis, the countries and territories exhibiting the most pronounced disparities have been identified, including (1) the 15 countries with the largest gap to frontier infertility prevalence and DALYs among all countries; (2) the 5 countries with the smallest gap to frontier values among relatively low SDI (SDI 0.85) regions. In order to ascertain the precise number of countries and regions included in each annotation, we referred to previous professional literature to confirm the values [25]. The Bayesian age-period-cohort analysis (BAPC) technique was utilized to project the global prevalence and DALYs rate of infertility from 2022 through 2035. BAPC considers the effects of age, time period, and generational cohorts on disease outcomes. This forecast relied on data concerning worldwide infertility prevalence rate from the GBD database, covering the time span from 1990 to 2021. The BAPC model is a sophisticated statistical tool that combines prior information about unknown parameters with sample information, resulting in the estimation of posterior distributions and the inference of these unknown parameters [26]. To approximate the posterior marginal distribution efficiently, we adopted the integrated nested Laplace approximation (INLA) algorithm. Given that the impacts of sequential time frames might be comparable, we utilized a second-order random walk (RW2) model. This allowed us to delve into the influence of various factors, including age brackets, time periods, and generational groups, on the number of incidences, specific age incidence rates, and normalized incidence rates.

Infertility burden at global level Globally, the age-standardized prevalence rate (ASPR) of infertility changed from 4071.04 (95% UI: 2660.05, 6223.25) per 100,000 in 1990 to 5030.42 (3207.13, 7918.99) per 100,000 in 2021, with the EAPC being 0.65 (0.51, 0.79). The age-standardized DALYs rate (ASDR) changed from 23.15 (8.91, 53.73) per 100,000 in 1990 to 28.54 (11.05, 67.94) per 100,000 in 2021, with the EAPC being 0.52 (0.37, 0.67) (Table 1–2 and Fig. 1). As shown in Supplementary Fig. 1, the ASPR of female infertility [7345.28 (4683.96,11,703.81) per 100,000] was 2.64 folds that of male infertility [2774.45 (1654.51,4460.12) per 100,000]. Regarding the ASPR for female infertility, primary infertility [1473.58 (736.40, 2630.70) per 100,000] accounted for 20%, while secondary infertility [5871.69 (3415.79, 9855.49) per 100,000] comprised 80%. As for the ASPR of male infertility, primary infertility [855.36, (383.34, 1669.79) per 100,000] accounted for 30%, while secondary infertility [1919.09 (1008.85,3409.56) per 100,000] comprised 70%. Table 1. | Age-standardized prevalence rate per 100000 population (95% UI) | EAPC (95% CI) to 1990-2021 | || |---|---|---|---| | 1990 | 2021 | || | Overall infertility | ||| | Global | 4071.04 (2660.05 to 6223.25) | 5030.42 (3207.13 to 7918.99) | 0.65 (0.51 to 0.79) | | High SDI | 3035.41 (1941.27 to 4667.61) | 3744.71 (2270.69 to 5857.89) | 0.74 (0.60 to 0.87) | | High-middle SDI | 4982.48 (3025.51 to 8012.04) | 5751.02 (3400.08 to 9439.75) | 0.38 (0.36 to 0.40) | | Middle SDI | 4221.45 (2674.84 to 6496.79) | 5389.09 (3362.71 to 8611.95) | 0.84 (0.78 to 0.90) | | Low-middle SDI | 3684.26 (2491.28 to 5482.31) | 5181.43 (3389.58 to 8007.33) | 1.06 (0.63 to 1.50) | | Low SDI | 4250.93 (3029.30 to 6016.00) | 4276.07 (2893.69 to 6234.14) | −0.11 (−0.43 to 0.20) | | Overall primary infertility | ||| | Global | 952.28 (511.96 to 1731.20) | 1160.49 (591.12 to 2105.11) | 0.50 (0.33 to 0.67) | | High SDI | 932.36 (492.43 to 1625.88) | 1028.4 (494.66 to 1872.77) | 0.32 (0.12 to 0.53) | | High-middle SDI | 887.37 (449.98 to 1621.58) | 931.48 (463.38 to 1673.71) | 0.09 (0.04 to 0.13) | | Middle SDI | 841.03 (431.44 to 1557.25) | 1133.54 (568.07 to 2047.47) | 0.96 (0.86 to 1.06) | | Low-middle SDI | 1160.03 (632.57 to 2129.25) | 1443.34 (727.32 to 2676.80) | 0.42 (0.07 to 0.77) | | Low SDI | 1099.69 (623.65 to 1927.12) | 1081.91 (553.64 to 1964.85) | −0.40 (−0.68 to −0.11) | | Overall secondary infertility | ||| | Global | 3118.75 (1867.71 to 5187.39) | 3869.93 (2254.44 to 6535.70) | 0.69 (0.56 to 0.83) | | High SDI | 2103.05 (1183.19 to 3651.83) | 2716.32 (1443.63 to 4785.47) | 0.90 (0.79 to 1.01) | | High-middle SDI | 4095.12 (2294.14 to 6993.65) | 4819.54 (2729.34 to 8435.77) | 0.44 (0.41 to 0.46) | | Middle SDI | 3380.42 (1980.61 to 5543.84) | 4255.55 (2400.56 to 7310.11) | 0.81 (0.75 to 0.86) | | Low-middle SDI | 2524.23 (1574.11 to 4102.52) | 3738.09 (2266.01 to 6282.76) | 1.34 (0.86 to 1.83) | | Low SDI | 3151.24 (2172.02 to 4767.30) | 3194.16 (2068.64 to 5028.16) | −0.01 (−0.34 to 0.32) | | Female infertility | ||| | Global | 5871.13 (3834.80 to 9327.25) | 7345.28 (4683.96 to 11703.81) | 0.69 (0.55 to 0.83) | | High SDI | 4150.78 (2601.25 to 6409.92) | 5279.15 (3159.59 to 8413.47) | 0.83 (0.71 to 0.96) | | High-middle SDI | 7120.72 (4261.04 to 11826.48) | 8500.57 (5008.25 to 14095.64) | 0.48 (0.46 to 0.51) | | Middle SDI | 6195.86 (3896.78 to 9991.30) | 7979.53 (4870.34 to 12945.84) | 0.87 (0.81 to 0.93) | | Low-middle SDI | 5405.27 (3679.23 to 8118.77) | 7552.92 (4931.77 to 11780.67) | 1.04 (0.60 to 1.49) | | Low SDI | 6101.08 (4335.69 to 8884.22) | 6085.72 (4143.02 to 9185.99) | −0.12 (−0.44 to 0.19) | | Primary female infertility | ||| | Global | 1195.39 (630.20 to 2153.45) | 1473.58 (736.40 to 2630.70) | 0.52 (0.34 to 0.69) | | High SDI | 1096.29 (572.05 to 1927.02) | 1217.75 (579.05 to 2259.09) | 0.34 (0.13 to 0.55) | | High-middle SDI | 1050.52 (517.52 to 1962.68) | 1131.43 (563.36 to 2040.59) | 0.15 (0.10 to 0.19) | | Middle SDI | 1074.61 (539.79 to 1965.73) | 1453.66 (719.39 to 2612.22) | 0.97 (0.87 to 1.07) | | Low-middle SDI | 1535.25 (831.90 to 2776.50) | 1882.96 (931.27 to 3441.28) | 0.34 (−0.02 to 0.70) | | Low SDI | 1410.11 (781.54 to 2497.37) | 1371.71 (686.32 to 2561.29) | −0.44 (−0.73 to −0.15) | | Secondary female infertility | ||| | Global | 4675.74 (2793.79 to 7827.00) | 5871.69 (3415.79 to 9855.49) | 0.73 (0.60 to 0.87) | | High SDI | 3054.49 (1708.29 to 5270.07) | 4061.41 (2152.59 to 7141.93) | 0.99 (0.89 to 1.10) | | High-middle SDI | 6070.20 (3426.63 to 10613.74) | 7369.14 (4081.19 to 12777.89) | 0.54 (0.51 to 0.57) | | Middle SDI | 5121.25 (2955.24 to 8625.67) | 6525.87 (3719.13 to 11095.48) | 0.85 (0.79 to 0.90) | | Low-middle SDI | 3870.03 (2392.61 to 6282.62) | 5669.96 (3388.73 to 9623.17) | 1.31 (0.82 to 1.80) | | Low SDI | 4690.97 (3186.18 to 7101.30) | 4714.01 (3004.29 to 7547.36) | −0.03 (−0.37 to 0.31) | | Male infertility | ||| | Global | 2317.81 (1386.24 to 3677.28) | 2774.45 (1654.51 to 4460.12) | 0.53 (0.38 to 0.68) | | High SDI | 1955.49 (1170.61 to 3224.62) | 2304.55 (1336.12 to 3895.03) | 0.61 (0.46 to 0.76) | | High-middle SDI | 2910.67 (1702.86 to 4845.79) | 3165.19 (1807.41 to 5314.96) | 0.18 (0.15 to 0.22) | | Middle SDI | 2317.20 (1361.27 to 3715.24) | 2872.42 (1714.87 to 4625.13) | 0.72 (0.65 to 0.79) | | Low-middle SDI | 1995.81 (1212.18 to 3087.54) | 2827.18 (1663.65 to 4509.23) | 1.09 (0.67 to 1.52) | | Low SDI | 2361.38 (1512.31 to 3515.00) | 2424.28 (1478.45 to 3746.11) | −0.10 (−0.39 to 0.19) | | Primary male infertility | ||| | Global | 715.50 (342.11 to 1319.95) | 855.36 (383.34 to 1669.79) | 0.47 (0.31 to 0.63) | | High SDI | 773.64 (367.26 to 1437.04) | 850.68 (375.53 to 1653.05) | 0.33 (0.12 to 0.54) | | High-middle SDI | 729.28 (338.30 to 1378.82) | 743.44 (337.41 to 1420.49) | 0.03 (−0.01 to 0.07) | | Middle SDI | 615.75 (281.18 to 1187.90) | 822.54 (363.43 to 1651.83) | 0.94 (0.83 to 1.04) | | Low-middle SDI | 791.92 (381.92 to 1492.29) | 1006.92 (445.95 to 2036.33) | 0.55 (0.20 to 0.89) | | Low SDI | 782.66 (379.67 to 1451.70) | 785.36 (356.14 to 1555.73) | −0.33 (−0.60 to −0.05) | | Secondary male infertility | ||| | Global | 1602.31 (862.40 to 2797.41) | 1919.09 (1008.85 to 3409.56) | 0.56 (0.42,0.71) | | High SDI | 1181.85 (607.07 to 2123.02) | 1453.87 (726.69 to 2638.94) | 0.78 (0.66,0.90) | | High-middle SDI | 2181.39 (1124.46 to 3920.03) | 2421.75 (1243.47 to 4420.61) | 0.23 (0.19,0.28) | | Middle SDI | 1701.45 (888.91 to 3027.32) | 2049.89 (1066.84 to 3709.34) | 0.64 (0.58,0.70) | | Low-middle SDI | 1203.89 (675.80 to 2104.30) | 1820.26 (945.98 to 3281.85) | 1.43 (0.93,1.92) | | Low SDI | 1578.72 (928.75 to 2607.20) | 1638.92 (904.08 to 2745.18) | 0.01 (−0.29,0.32) | CI confidence interval, EAPC estimated annual percentage change, SDI sociodemographic index, UI uncertainty interval Table 2. | Age-standardized DALYs rate per 100000 population (95% UI) | EAPC (95% CI) to 1990-2021 | ||| |---|---|---|---|---| | 1990 | 2021 | ||| | Overall infertility | |||| | Global | 23.15 (8.91 to 53.73) | 28.54 (11.05 to 67.94) | 0.52 (0.37 to 0.67) | | | High SDI | 17.85 (6.81 to 43.57) | 21.73 (8.26 to 53.51) | 0.56 (0.41 to 0.72) | | | High-middle SDI | 27.72 (10.46 to 67.88) | 31.75 (11.95 to 78.18) | 0.17 (0.14 to 0.20) | | | Middle SDI | 23.67 (9.00 to 56.54) | 30.33 (11.67 to 73.44) | 0.74 (0.67 to 0.82) | | | Low-middle SDI | 21.6 (8.34 to 46.99) | 29.93 (11.43 to 70.29) | 1.01 (0.60 to 1.42) | | | Low SDI | 24.33 (9.51 to 52.04) | 24.43 (9.41 to 54.60) | −0.13 (−0.41 to 0.16) | | | Overall primary infertility | |||| | Global | 7.13 (2.74 to 16.69) | 8.68 (3.25 to 19.80) | 0.50 (0.33 to 0.67) | | | High SDI | 7 (2.65 to 15.46) | 7.72 (2.79 to 17.58) | 0.33 (0.12 to 0.54) | | | High-middle SDI | 6.65 (2.47 to 15.83) | 6.98 (2.58 to 15.74) | 0.09 (0.05 to 0.13) | | | Middle SDI | 6.29 (2.36 to 15.02) | 8.47 (3.14 to 19.25) | 0.97 (0.87 to 1.07) | | | Low-middle SDI | 8.66 (3.33 to 20.29) | 10.77 (4.03 to 25.42) | 0.42 (0.06 to 0.77) | | | Low SDI | 8.21 (3.21 to 18.83) | 8.08 (3.10 to 18.85) | −0.40 (−0.69 to −0.11) | | | Overall secondary infertility | |||| | Global | 16.02 (5.63 to 40.37) | 19.87 (6.98 to 51.07) | 0.69 (0.56 to 0.83) | | | High SDI | 10.85 (3.74 to 27.70) | 14.01 (4.73 to 35.60) | 0.90 (0.80 to 1.01) | | | High-middle SDI | 21.06 (7.42 to 54.01) | 24.77 (8.92 to 64.65) | 0.44 (0.41 to 0.46) | | | Middle SDI | 17.37 (6.10 to 43.06) | 21.85 (7.43 to 55.94) | 0.81 (0.75 to 0.86) | | | Low-middle SDI | 12.94 (4.48 to 30.84) | 19.16 (6.59 to 46.10) | 1.34 (0.86 to 1.83) | | | Low SDI | 16.12 (5.87 to 38.13) | 16.36 (5.78 to 38.79) | −0.01 (−0.35 to 0.32) | | | Female infertility | |||| | Global | 32.94 (12.55 to 78.40) | 41.12 (16.03 to 97.65) | 0.67 (0.53 to 0.82) | | | High SDI | 23.96 (9.16 to 60.00) | 30.06 (11.21 to 76.00) | 0.78 (0.65 to 0.91) | | | High-middle SDI | 39.08 (14.74 to 97.61) | 46.33 (17.40 to 116.17) | 0.46 (0.44 to 0.48) | | | Middle SDI | 34.34 (12.52 to 83.85) | 44.34 (17.08 to 104.58) | 0.87 (0.81 to 0.94) | | | Low-middle SDI | 31.26 (12.19 to 69.74) | 43.06 (16.55 to 97.95) | 0.97 (0.54 to 1.40) | | | Low SDI | 34.47 (13.43 to 75.34) | 34.34 (13.47 to 75.74) | −0.15 (−0.46 to 0.16) | | | Primary female infertility | |||| | Global | 8.92 (3.25 to 20.22) | 10.99 (3.96 to 25.18) | 0.52 (0.34 to 0.69) | | | High SDI | 8.21 (2.99 to 18.67) | 9.12 (3.21 to 21.30) | 0.34 (0.13 to 0.55) | | | High-middle SDI | 7.86 (2.77 to 18.16) | 8.46 (2.95 to 19.02) | 0.14 (0.10 to 0.19) | | | Middle SDI | 8.02 (2.84 to 18.75) | 10.84 (3.90 to 25.11) | 0.97 (0.87 to 1.07) | | | Low-middle SDI | 11.44 (4.28 to 26.50) | 14.02 (4.95 to 32.50) | 0.34 (−0.01 to 0.70) | | | Low SDI | 10.49 (4.02 to 23.67) | 10.21 (3.73 to 23.20) | −0.44 (−0.73 to −0.15) | | | Secondary female infertility | |||| | Global | 24.02 (8.31 to 59.44) | 30.13 (10.41 to 75.46) | 0.73 (0.60 to 0.87) | | | High SDI | 15.75 (5.26 to 39.73) | 20.94 (6.91 to 54.09) | 0.99 (0.89 to 1.10) | | | High-middle SDI | 31.23 (10.60 to 79.38) | 37.87 (13.05 to 99.69) | 0.54 (0.51 to 0.56) | | | Middle SDI | 26.31 (9.04 to 65.89) | 33.50 (11.18 to 85.17) | 0.84 (0.79 to 0.90) | | | Low-middle SDI | 19.82 (6.87 to 47.18) | 29.05 (9.82 to 70.03) | 1.31 (0.82 to 1.80) | | | Low SDI | 23.97 (8.52 to 55.47) | 24.13 (8.49 to 56.97) | −0.02 (−0.36 to 0.31) | | | Male infertility | |||| | Global | 13.62 (5.01 to 32.02) | 16.29 (5.95 to 38.77) | 0.52 (0.37 to 0.67) | | | High SDI | 11.94 (4.49 to 28.54) | 13.92 (5.08 to 33.49) | 0.56 (0.41 to 0.72) | | | High-middle SDI | 16.70 (6.01 to 41.48) | 18.04 (6.60 to 44.75) | 0.17 (0.14 to 0.20) | | | Middle SDI | 13.38 (4.78 to 31.88) | 16.71 (6.12 to 40.21) | 0.74 (0.67 to 0.82) | | | Low-middle SDI | 12.13 (4.62 to 27.60) | 16.89 (6.13 to 39.71) | 1.01 (0.60 to 1.42) | | | Low SDI | 13.97 (5.27 to 31.99) | 14.30 (5.30 to 32.74) | −0.13 (−0.41 to 0.16) | | | Primary male infertility | |||| | Global | 5.38 (1.79 to 13.05) | 6.42 (2.09 to 15.30) | 0.46 (0.30 to 0.62) | | | High SDI | 5.83 (1.99 to 13.60) | 6.41 (2.06 to 15.17) | 0.33 (0.12 to 0.54) | | | High-middle SDI | 5.49 (1.78 to 13.53) | 5.59 (1.84 to 13.41) | 0.03 (−0.02 to 0.07) | | | Middle SDI | 4.63 (1.47 to 11.70) | 6.17 (2.02 to 14.88) | 0.93 (0.82 to 1.03) | | | Low-middle SDI | 5.94 (1.96 to 14.26) | 7.55 (2.41 to 18.71) | 0.54 (0.20 to 0.88) | | | Low SDI | 5.88 (1.96 to 13.97) | 5.89 (1.90 to 14.16) | −0.33 (−0.60 to −0.05) | | | Secondary male infertility | |||| | Global | 8.24 (2.62 to 20.06) | 9.86 (3.17 to 24.51) | 0.56 (0.42 to 0.71) | | | High SDI | 6.11 (1.88 to 15.94) | 7.51 (2.29 to 19.70) | 0.78 (0.65 to 0.90) | | | High-middle SDI | 11.21 (3.61 to 29.48) | 12.45 (4.03 to 31.35) | 0.24 (0.19 to 0.28) | | | Middle SDI | 8.75 (2.85 to 20.91) | 10.54 (3.38 to 26.28) | 0.64 (0.58 to 0.70) | | | Low-middle SDI | 6.18 (2.05 to 14.84) | 9.34 (2.97 to 22.82) | 1.42 (0.93 to 1.92) | | | Low SDI | 8.10 (2.80 to 18.62) | 8.41 (2.77 to 19.83) | 0.01 (−0.29 to 0.32) | DALYs disability-adjusted life-year, CI confidence interval, EAPC estimated annual percentage change, SDI sociodemographic index, UI uncertainty interval The burden of female infertility and male infertility showed a consistent increasing trend between 1990 and 2021. As shown in Table 1 and Supplementary Fig. 1, the ASPR of female infertility and male infertility changed from 5871.13 (3834.80, 9327.25) and 2317.81 (1386.24, 3677.28) per 100,000 in 1990 to 7345.28 (4683.96, 11,703.81) and 2774.45 (1654.51, 4460.12) per100,000 in 2021, with the EAPC being 0.69 (0.55, 0.83) and 0.53 (0.38, 0.68). The ASPR of primary female infertility and male infertility changed from 1195.39 (630.20, 2153.45) and 715.50 (342.11, 1319.95) per 100,000 in 1990 to 1473.58 (736.40, 2630.70) and 855.36 (383.34, 1669.79) per100,000 in 2021, with the EAPC being 0.52 (0.34, 0.69) and 0.47 (0.31, 0.63). The ASPR of secondary female infertility and male infertility changed from 4675.74 (2793.79, 7827.00) and 1602.31 (862.40, 2797.41) per 100,000 in 1990 to 5871.69 (3415.79, 9855.49) and 1919.09 (1008.85, 3409.56) per100,000 in 2021, with the EAPC being 0.73 (0.60, 0.87) and 0.56 (0.42, 0.71). When stratified by SDI, as for both female and male infertility, the high-middle SDI countries had the highest ASRP [Female: 8500.57 (5008.25, 14,095.64) per 100,000; male: 3165.19 (1807.41, 5314.96) per 100,000] and ASDR [female: 46.33 (17.40, 116.17) per 100,000; male: 18.04 (6.60, 44.75) per 100,000], whereas the high SDI countries had the lowest ASPR [female: 5279.15 (3159.59, 8413.47) per 100,000; male: 2304.55 (1336.12, 3895.03) per 100,000] and ASDR [female: 30.06 (11.21 to 76.00) per 100,000; male: 13.92 (5.08, 33.49) per 100,000] in 2021 (Table 1–2 and Supplementary Fig. 1). When we performed categorical statistics on primary infertility and secondary infertility, we found that, for primary infertility, the low-middle SDI countries had the highest ASPR [female: 1882.96 (931.27, 3441.28) per 100,000; male: 1006.92 (445.95 2036.33) per 100,000], whereas the high-middle SDI countries had the lowest ASPR [female: 1131.43 (563.36, 2040.59) per 100,000; male: 743.44 (337.41, 1420.49) per 100,000] and ASDR [female: 8.46 (2.95, 19.02); male: 5.59 (1.84, 13.41) per 100,000] in 2021. However, for secondary infertility, the high-middle SDI countries had the highest ASRP [female: 7369.14(4081.19 to 12,777.89) per 100,000; male: 2421.75 (1243.47, 4420.61) per 100,000], whereas the high-middle SDI countries had the lowest ASPR [female: 4061.41 (2152.59, 7141.93) per 100,000; male: 1453.87 (726.69, 2638.94) per 100,000] in 2021. From 1990 to 2021, except for the low SDI region, both the ASPR and ASDR exhibited a decline trend in in various subcategories of infertility. As shown in Table 1–2, the middle SDI region had the fastest increase in ASPR (EAPC = 0.97 and 0.94, respectively) for primary female and male infertility. while the low-middle SDI region had the fastest increase in ASPR (EAPC = 1.31 and 1.42, respectively) for secondary female and male infertility. Infertility burden at regional and national levels As shown in Supplementary Table 1–2, among the 21 GBD regions in 2021, for primary infertility, South Asia and Eastern Europe had the highest ASPR [female: 2381.45 (1163.37, 4385.05) and 1819.98 (870.22, 3328.09) per 100,000; male: 1140.59 (490.94, 2349.12) and 1439.52 (638.02, 2776.57) per 100,000], while Andean Latin America and High-income Asia Pacific had the lowest ASPR [female: 523.16 (248.22, 936.49) and 645.19 (298.47, 1210.13) per 100,000; male: 333.59 (145.22, 639.74) and 483.76 (209.34, 940.50) per 100,000] in 2021. As for secondary infertility, East Asia and Eastern Europe had the highest ASPR [9668.49(5295.56 to 16,500.50) and 6955.91 (3578.51, 13,400.47) per 100,000; male: 2945.22 (1457.37, 5577.87) and 2851.80 (1296.75, 5461.19) per 100,000], while Australasia had the lowest ASPR [female: 2111.76 (1130.50, 3784.55) per 100,000; male: 793.57 (383.44, 1500.86) per 100,000] in 2021. For primary infertility, Tropical Latin America and Andean Latin America experienced the fastest increase in ASPR (EAPC = 1.39 and 1.34 for female; 1.37 and 1.40 for male), while Eastern Sub-Saharan Africa and Southern Sub-Saharan Africa saw the deepest decline in ASPR (EAPC = − 1.25 and − 1.16 for female; − 1.10 and − 0.78 for male) from 1990 to 2021. For secondary infertility, Andean Latin America and Tropical Latin America also experienced the fastest increase in ASPR (EAPC = 3.28 and 2.72 for female; 2.83 and 2.54 for male), while Eastern Sub-Saharan Africa and Oceania saw the deepest decline in ASPR (EAPC = − 0.91 and − 0.91 for female; − 0.95 and − 0.83 for male) from 1990 to 2021. As shown in Supplementary Table 3–4, Fig. 2 and Supplementary Fig. 2, among 204 countries and territories in 2021, for primary infertility, Pakistan had the highest ASPR [female: 3811.53 (918.88, 9999.07) per 100,000; male: 1834.77 (393.19, 5363.95) per 100,000], while Slovenia had the lowest ASPR [273.74 (124.52, 505.44) per 100,000] for primary female infertility, and Malawi had the lowest ASPR [132.31 (74.49, 209.38) per 100,000] for primary male infertility. As for secondary infertility in 2021, Djibouti had the highest ASPR [11127.00 (6369.72, 17,933.61) per 100,000] for secondary female infertility, and Liberia had the highest ASPR [4278.52 (2218.05, 7048.43) per 100,000] for secondary male infertility, while Denmark had the lowest ASPR [female: 1012.70 (486.14, 2060.86) per 100,000; male: 340.73 (139.63, 727.41) per 100,000] in 2021. For primary infertility, Philippines experienced the fastest increase in ASPR (EAPC = 4.85 for female; 4.87 for male), while Malawi saw the deepest decline in ASPR (EAPC = − 4.97 for female; − 5.02 for male) from 1990 to 2021. For secondary infertility, Philippines also experienced the fastest increase in ASPR (EAPC = 5.94 for female; 5.85 for male), while Pakistan saw the deepest decline in ASPR (EAPC = − 3.61 for female, − 3.93 for male). Infertility burden among different age group In 2021, as shown in the Supplementary Table 5–6 and Fig. 3, the prevalence and DALYs of infertility and its subtypes across various age groups both demonstrated a unimodal distribution pattern. Specifically, for primary infertility, the prevalence and DALYs rate reached their peak among individuals aged 25–29 [female: 2480.15 (758.69, 6032.43) and 18.4 (4.64, 53.11) per 100,000; male: 1499.51 (417.96, 3888.07) and 11.21 (2.51, 34.24) per 100,000]. For secondary infertility, the prevalence and DALYs rate reached their peak among individuals aged 35–39 [female: 12,120.26 (3862.32, 26,458.19) and 56.93 (15.32, 150.11) per 100,000; male: 3890.41 (1274.58, 8476.21) and 18.94 (4.81, 53.15) per 100,000]. Additionally, the prevalence and DALYs rates among individuals aged 20 to 49 experienced an upward trend for primary female and male infertility, and the fastest growth was in the 25–29 age group. The prevalence and DALYs rates among individuals aged 15 to 44 experienced an upward trend for secondary female and male infertility, and the fastest growth was in the 20–24 age group (Supplementary Table 5–6). Drivers of infertility — ageing, population growth, and epidemiological change We further developed a decomposition analysis of raw prevalence and DALYs age-standardized rates to evaluate to what extent the forces of ageing, population growth, and epidemiological changes have shaped infertility epidemiology over the past 30 years. As shown in Supplementary Table 7–8 and Fig. 4, globally, the prevalence and DALYs of overall infertility, primary infertility, and secondary infertility increased significantly, and the largest increased group was the low-middle SDI quintile in the past 30 years. As shown in Supplementary Table 7–8 and Fig. 4, globally, between 1990 and 2021, the prevalence of overall infertility has increased by 0.65% due to the aging of the global population, by 69.19% because of population growth, and by 30.16% as a consequence of epidemiological changes. The prevalence of overall primary infertility has declined by 11.05% with the aging of the global population, whereas surged by 70.90% due to population growth, and increased by 40.15% as a consequence of epidemiological change. The prevalence of overall secondary infertility has surged by 4.08% because of the aging of the global population, surged by 68.69% due to population growth, and increased by 27.23% as a result of epidemiological change. The DALYs of overall infertility has decreased by 0.43% due to the aging of the global population, whereas increased by 69.47% because of population growth, and by 30.96% as a consequence of epidemiological changes. The DALYs of overall primary infertility has increased by 3.94% with the aging of the global population, by 69.61% due to population growth, and by 26.45% as a consequence of epidemiological change. The DALYs of secondary infertility has surged by 4.11% because of the aging of the global population, surged by 68.79% due to population growth, and increased by 27.10% as a result of epidemiological changes. For prevalence and DALYs of overall infertility, the most pronounced contributions of aging, population growth and epidemiological change occurred in the low SDI quintile (54.41% and 54.45%), high-middle SDI quintile (162.87% and 168.02%), and high SDI quintile (66.60% and 66.95%), respectively (Supplementary Table 7–8 and Fig. 4A). Among High-SDI and high-middle SDI regions, the prevalence of infertility has decreased by 106.38% and 97.24% to the aging of the global population, however, among low-SDI and low-middle SDI regions, the prevalence of infertility has increased by 54.41% and 25.75% to the aging of the global population. In the subtypes of female and male infertility, we observed comparable results to those observed in overall infertility cases (Supplementary Table 7–8 and Supplementary Fig. 3). Infertility and sociodemographic development For secondary infertility, negative correlations were detected between SDI with ASPR (R = − 0.161, P < 0.001) and ASDR R = − 0.154, P < 0.001) at the regional level from 1990 to 202 l (Fig. 5B), meanwhile, negative correlations were also detected between SDI with ASPR (R = − 0.193, P = 0.006) and ASDR (R = − 0.187, P = 0.007) at the national level in 202 l (Supplementary Fig. 5C). For primary infertility, no significant correlation between ASPR and ASDR with SDI at the regional level from 1990 to 202 l, nor at the national level in 2021 (Fig. 5C and Supplementary Fig. 5B). As shown in Supplementary Fig. 4, negative correlations were detected between SDI with ASPR primary female infertility (R = − 0.106, P = 0.005) and secondary female infertility (R = − 0189, P < 0.001) at the regional level from 1990 to 202l. Positive relationship was detected between SDI with ASPR in primary male infertility (R = 0.146, P < 0.001) at the regional level from 1990 to 2021. Among various types of infertility, at the regional level from 1990 to 2021, ASPR has an increasing trend when SDI is between about 0.5 and 0.7, and significantly decreased with the increase of SDI after it exceeded 0.7. As shown in Supplementary Fig. 6, negative correlations were detected between SDI with ASPR in secondary female infertility (R = − 0149, P = 0.033) at the national level in 2021. When the SDI exceeds 0.8, the ASPR significantly decreases with the SDI, in secondary female and male infertility at the national level in 2021. We further analyzed the relationship between SDI with EAPCs for ASPR and ASDR of infertility. Positive correlations were detected between SDI with EAPCs for female and male infertility for either primary or secondary infertility (Fig. 6 and Supplementary Fig. 7). The burden on EAPCs was most significant in proximity to the SDI value of 0.6. Frontier analysis for the relationship between infertility prevalence and the status of the countries’ development Utilizing data spanning from 1990 to 2021, and employing ASPR and ASDR alongside the SDI, this study performed frontier analysis to assess the potential improvement space for the burden of infertility relative to national development levels (Supplementary Table 9–10, Fig. 7 and Supplementary Fig. 8). Overall, as SDI increases, the effective difference (EF) in SDI tends to be smaller and the variance smaller in both primary and secondary infertility. Compared to primary infertility, secondary infertility has a higher effective difference, indicating a greater burden improvement potential of secondary infertility. The top 10 countries with the highest effective difference in both ASPR and ASDR for primary infertility included Djibouti, Central African Republic, Gabon, Comoros, China, Philippines, Eritrea, Indonesia, Maldives, and Cameroon. The top 10 countries with the highest effective difference in both ASPR and ASDR for secondary infertility included Djibouti, Gabon, Central African Republic, China, Cameroon, Liberia, Cabo Verde, Croatia, Sierra Leone, and Indonesia. These countries have much higher prevalence and DALYs rates than other countries with comparable sociodemographic resources. Global disease burden prediction for infertility to 2035 The Bayesian Age-Period-Cohort (BAPC) model was employed to forecast the future trends of ASPR and ASDR of infertility. It is anticipated that the ASPR and ASDR will demonstrate an upward trend in overall infertility by 2035, in comparison with 2021 (Fig. 8A). It is anticipated that both the ASPR and ASDR will exhibit a downward trend for overall primary infertility (Fig. 8B), whereas they are expected to show an upward trend for overall secondary infertility (Fig. 8C) by 2035, in comparison with 2021. As shown in Supplementary Fig. 9, the ASPR of female infertility and male infertility will reach up to 6194.38/100,000 and 2894.03/100,000 in 2035, showing an increasing trend compared with 2021. The ASPR of primary female infertility and primary male infertility are expected to follow a downward trend compared with 2021, decreasing to 1252.65/100,000 and 756.71/100,000 in 2035. The ASPR of secondary female infertility and secondary male infertility will reach up to 5459.19/100,000 and 2497.71/100,000 in 2035, showing an increasing trend compared with 2021. We conducted a further analysis of various age stratifications concurrently (Supplementary Fig. 10 and Supplementary Fig. 11). Based on the projected data, by 2035, it is expected that the ASPR for female infertility will decrease among women aged 10–24, while it is anticipated to increase among those aged 25–49, as compared to the year 2021. For primary female infertility, the ASPR is expected to decrease in the 15–39 age group and increase in the 40–49 age group. The ASPR for secondary female infertility is projected to decrease in the 10–24 age group and increase in the 25–49 age group. It is expected that the ASPR for male infertility will decrease among women aged 20–29, while it is anticipated to increase among the other age groups. For primary male infertility, the ASPR is expected to decrease in the 15–39 age group and increase in the 40–49 age group. For secondary male infertility, the ASPR is projected to increase in all age groups.

Worldwide, around 12–15% of married couples experience infertility, a condition that not only influences individual physical and mental well-being but also has considerable implications for societal and national health [27]. Infertility has emerged as a significant global public health concern, profoundly affecting demographic patterns, socioeconomic conditions, and the overall well-being of families (40,073,310 [28]). This situation highlights the necessity for a refined and comprehensive classification of infertility and its various subtypes. The GBD 2021 report indicates that, with the exception of low SDI regions, there was a significant rise in both the ASPR and ASDR across all categories of infertility in the remaining four SDI regions. Particularly post-2010, significant increases were observed in ASPR and ASDR across all infertility subcategories globally. Our study reveals that the relationship between infertility prevalence and SDI is not strictly linear. From 1990 to 2021, the ASPR and ASDR trends escalated when SDI was between 0.5 and 0.7 and decreased significantly once SDI surpassed 0.7. The impact on EAPCs was most noticeable at an SDI of approximately 0.6. Analysis of decomposition revealed that variations in the prevalence of infertility were primarily influenced by the combined effects of population expansion and alterations in epidemiological indicators. In regions characterized by low SDI, the dynamics of aging, coupled with population growth, primarily drove these alterations. In contrast, within regions characterized by high and high-middle SDI, the occurrence of both primary and secondary infertility diminished with advancing age. Conversely, in regions with low and low-middle SDI, there was an observed increase in prevalence. This indicates that multiple factors beyond economic or medical influences affect infertility rates, including economic conditions, cultural norms, ideological perspectives, medical standards, and environmental factors [29–33]). Infertility is categorized into primary and secondary types based on reproductive history. In 2021, ASPR and ASDR for secondary infertility were threefold higher than those for primary infertility. Frontier analysis showed that secondary infertility presented a higher effective difference than primary infertility, suggesting greater potential for reducing its burden. It is projected that both ASPR and ASDR will trend downwards for primary infertility but upwards for secondary infertility by 2035, in comparison to 2021. These outcomes indicate that addressing secondary infertility should be a focal point in future initiatives. Differentiating between primary and secondary infertility is essential for identifying possible etiological factors. Historically, elevated instances of secondary infertility have been associated with infection-related conditions arising from postpartum infections, unsafe abortions [34, 35], and certain sexually transmitted diseases [36], especially in low- and middle-income countries, where the likelihood of increased post-infection infertility rates is significant [37]. Our observations indicate that secondary infertility, impacting both sexes, was particularly prevalent in the high-middle SDI region and exhibited the most significant increase in the low-middle SDI region. We also examined secondary infertility statistics across various age groups, discovering a significant prevalence in individuals aged 30–44 years, which was six times higher than that of primary infertility in the same age group. Consequently, we posit that the rising prevalence of secondary infertility is shaped not only by advancements in medicine and improvements in sanitation but also significantly by the age at which individuals choose to start families. Among various age cohorts, primary infertility exhibits its highest burden and most rapid growth among individuals aged 20–29, both in terms of prevalence and DALYs. Conversely, the 30–44 age group shoulders the heaviest load for secondary infertility, again regarding both prevalence and DALYs. Additionally, the swiftest growth in secondary infertility has been recorded among those aged 15–29, possibly due to an increase in lifestyle-related conditions such as obesity and metabolic diseases [27, 38–40], or rising societal issues like increased elective abortions. Consequently, enhancing reproductive health education for young couples is crucial to safeguard their reproductive well-being. This effort should involve delivering extensive knowledge on reproductive health, elucidating maintenance of reproductive health, prevention of potential issues, and accessing professional assistance as needed. By fostering education and awareness, we can highlight the significance of reproductive health, motivating young couples to actively safeguard their and their family’s well-being. In 2021, the ASPR and ASDR for female infertility were 2.6 times higher than those for male infertility. The trends in ASPR and ASDR for both genders showed consistency. Globally and in most regions, the infertility rate is nearly double in females compared to males. These results are consistent with earlier findings, confirming higher infertility risks in females due to factors such as the anatomy of the female urogenital system and socio-cultural and economic influences [41]. The phenomenon of female infertility is shaped by a range of factors, such as disorders affecting ovulation, obstructions in the fallopian tubes, and the decline in fertility associated with advancing age, all of which represent critical health concerns for women [42]. Conditions such as polycystic ovary syndrome (PCOS) and endometriosis significantly influence the occurrence of female infertility. As age progresses, infertility rates rise in both genders; however, the alterations in male reproductive function are comparatively subtle when juxtaposed with the more significant changes observed in females. Furthermore, societal expectations frequently impose heightened scrutiny on women regarding reproductive capabilities, leading to increased assessments and documentation of fertility issues. In contrast, male infertility may be underreported owing to a lack of awareness regarding male reproductive health and societal norms that dissuade men from pursuing assistance. Moreover, in cases of infertility affecting both partners, there tends to be a greater focus on the female aspect, which leads to the perception of elevated rates of female infertility [43]. In this study, we conducted an extensive analysis of the burden of female and male infertility from 1990 to 2021 at global, regional, and national levels. Differing from prior GBD studies on infertility, our research distinguished between primary and secondary infertility and detected variances in their incidence rates. Nonetheless, several limitations associated with the GBD data should be considered. Primarily, high-quality primary data are scarce in many underdeveloped nations, necessitating reliance on statistical modeling for final estimates. Even when data are available, discrepancies in data quality and accuracy may cause deviations in estimates. There are also significant policy and programmatic challenges due to the low availability, accessibility, and quality of interventions to tackle infertility in most countries. Additionally, the Relative Risks (RRs) associated with each assessed risk factor can differ among various ethnic groups and geographical regions, suggesting that the application of a universal effect size might compromise the validity and accuracy of the estimates. Thirdly, the BAPC model was used to predict the prevalence of infertility and its subtypes in this study, however, BAPC methodology is not designed to incorporate or simulate external disruptive shocks of the nature (e.g., acute climate events, novel large-scale environmental contamination, global pandemics). Furthermore, the definition of infertility provided by the GBD differs from the existing definition established by the WHO. The GBD’s 5-year threshold likely underestimates the true prevalence of infertility compared to the WHO standard. Specifically, using a 5-year threshold without live birth may capture more severe or long-term cases, potentially underestimating the burden for subtypes associated with shorter durations of infertility. Couples experiencing shorter durations of infertility (1–4 years) or pregnancy losses (e.g., miscarriages, stillbirths) are excluded from GBD estimates but meet WHO clinical criteria. This exclusion disproportionately affects regions with high rates of pregnancy loss or limited access to early fertility care. The GBD definition (live birth-dependent) may underestimate secondary infertility, as it requires a prior live birth. Couples with prior pregnancy losses (without live births) are misclassified as “primarily infertile,” inflating primary infertility estimates. While GBD data provide valuable longitudinal insights, our interpretation emphasizes that its definition likely underestimates global infertility burden. We recommend future studies incorporate WHO criteria for clinical relevance. Despite these constraints, our study offers a thorough evaluation of the prevalence of infertility and sheds light on the changes in the infertility burden over recent decades, providing essential data for policymakers and public health efforts aimed at preventing infertility and promoting health.

In summary, from 1990 to 2021, the ASPR and ASDR of infertility among individuals aged 15–49 globally have shown a rising trend, with forecasts suggesting a persistent increase through 2035. It is noteworthy that the age-specific prevalence rate for primary infertility is projected to decrease, whereas the age-specific disability rate for secondary infertility is anticipated to increase. It is essential for both governing bodies and the general populace to acknowledge the significance of this matter and to focus on the execution of specific interventions and strategies designed to improve global reproductive health. Supplementary Information Below is the link to the electronic supplementary material.

We thank the other members of Dr. Yao’s laboratory for their discussion and help. Author contribution XC and JM designed the study and contributed to writing the article. WW, XC, and BL analyzed the data and performed the statistical analyses. LC and BY contributed to the study design, data interpretation. All authors have agreed to be listed and have approved the final article. Funding This work is supported by the National Natural Science Foundation of China (Grant: 82101757), Annual Foundation of Nanjing Jinling Hospital (22LCYY-QH5), and Jiangsu Provincial Medical Key Discipline Cultivation Unit (JSDW202215). Each of the funding contributed to expenses related to specific procedures carried out in the project. Data availability All data that support the findings of this study are available from the corresponding author upon reasonable request. Declarations Ethical approval Not applicable. Conflict of interest The authors declare no competing interests. Footnotes Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Xi Cheng and Jinzhao Ma contributed equally to this work. Contributor Information Li Chen, Email: [email protected]. Bing Yao, Email: [email protected].

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