Spatiotemporal Epidemiology of Endometriosis: Global, Regional, and National Trends from 1990 to 2019

Endometriosis is a chronic pain disorder pathologically defined by the ectopic implantation of endometrial glands and stroma. 1 This condition predominantly affects reproductive-aged women (15–49 years), 2 representing a leading gynecological pathology in premenopausal populations. The hallmark clinical manifestations include chronic pelvic pain and subfertility/infertility. 3 The global prevalence of endometriosis stands at 5–15% among reproductive-aged women, meaning 30–50% of affected individuals suffer severe clinical symptoms. 4 , 5 This persistent disease condition further raises population-level incidence and imposes heavy socioeconomic burden measured by DALYs worldwide. 6 Current diagnostic difficulties imply that the true incidence and prevalence of endometriosis are widely underestimated. Although the disease imposes a heavy global burden, large-scale population epidemiological evidence is scarce, and most existing studies only report simple incidence data. Regional surveys from the UK, Australia and the US have provided partial evidence, 7 yet complete global spatiotemporal analyses are absent. Although researchers such as Zhang et al, 8 Wang et al, 9 and Feng et al 10 only explored endometriosis burden within single national or subnational regions based on limited GBD data, none conducted a systematic global evaluation covering all 21 geographic zones, five SDI tiers and age subgroups, nor did they interpret the paradoxical mismatch between rising incidence and falling DALY burden. Leveraging the most recent Global Burden of Disease (GBD) 2019 dataset, this study employs age-standardized incidence rates and disability-adjusted life years (DALYs) as primary metrics to evaluate spatiotemporal trends in endometriosis burden across populations. Widespread diagnostic barriers lead to massive undercounting of true population incidence and prevalence, which distorts the real global disease burden of endometriosis. Invasive laparoscopy is the gold standard for definitive diagnosis, yet limited specialist resources and absent standardized population screening protocols lead to severe underdiagnosis across low- and middle-income regions. Distinct from prior localized studies, our work further dissects the paradoxical divergent trends between rising age-standardized incidence and falling age-standardized DALY rates, stratifies burden patterns by SDI, region and age group, and provides comprehensive global evidence to fill the gaps left by previous limited regional reports.

In 2019, the global burden of endometriosis comprised 3,781,368.14 cases and 2,148,886.11 DALYs. From 1990 to 2019, case numbers increased by 10.32%, while DALYs rose by 18.07% ( Table 1 and Table 2 ). Trend analysis revealed diverging patterns: the ASIR showed a significant upward trend (EAPC = 0.46, 95% CI: 0.45–0.46; Table 1 and Supplementary Figure 1B ), whereas the age-standardized DALY rate demonstrated a consistent decline (EAPC = −0.82, 95% CI: −0.85 to −0.78; Table 2 and Supplementary Figure 1A ) over the three-decade period. Table 1 The Incident Cases and ASIR Endometriosis in 1990 and 2019 and Its Temporal Trends 1990 1990 2019 2019 EAPC(1990–2019) EAPC(1990–2019) Incidence number ASIR (per 100,000) Incidence number ASIR (per 100,000) Incidence number ASIR (per 100,000) Global 3427,719.86(2,433,344.69,4,931,571.24) 246.35(246.08,246.61) 3,781,368.14(2,743,362.21,5,316,024.19) 197.05(196.85,197.25) 0.35(0.27,0.43) 0.46(0.45,0.46) Sociodemographic index – – – – – – Low SDI 376,111.04(264,063.32,543,934.42) 296.78(295.81,297.75) 639,535.85(447,982.38,916,290.79) 217.91(217.36,218.45) 1.79(1.73,1.84) 0.39(0.39,0.40) Low-middle SDI 815,925.89(577,398.33,1,179,345.03) 286.37(285.73,287.00) 975,084.16(697,747.05,1,390,295.34) 204.00(203.59,204.40) 0.58(0.53,0.63) 0.42(0.41,0.42) Middle SDI 1136,539.30(800,201.94,1,630,213.05) 243.51(243.06,243.97) 1,180,102.89(857,065.73,1,632,029.83) 193.64(193.29,193.99) 0.21(0.07,0.34) 0.46(0.46,0.47) High-middle SDI 669,037.07(477,129.65,955,897.37) 220.11(219.58,220.64) 616,663.27(447,836.66,837,846.90) 184.53(184.06,185.00) −0.16(−0.30,−0.01) 0.50(0.50,0.51) High SDI 428,173.52(311,955.25,595,950.50) 204.91(204.29,205.53) 367,517.69(268,500.02,507,434.50) 170.02(169.46,170.58) −0.66(−0.70,−0.61) 0.54(0.53,0.54) Region – – – – – – Andean Latin America 28,422.01(19,989.48,40,623.08) 280.87(277.54,284.23) 34,459.22(24,732.21,48,514.28) 206.73(204.55,208.92) 0.70(0.68,0.72) 0.42(0.42,0.43) Australasia 13,841.84(9701.30,19,733.00) 263.27(258.90,267.71) 14,531.27(10,404.85,20,905.14) 231.16(227.36,235.01) 0.33(0.17,0.50) 0.42(0.41,0.43) Caribbean 23,830.44(16,825.80,34,391.67) 243.25(240.14,246.40) 23,295.83(16,917.20,32,883.97) 194.49(192.00,197.00) −0.01(−0.07,0.05) 0.47(0.46,0.47) Central Asia 49,494.90(34,877.14,70,356.94) 279.11(276.59,281.64) 59,631.03(42,226.48,84,040.10) 247.30(245.31,249.30) 1.04(0.87,1.21) 0.40(0.39,0.40) Central Europe 50,333.04(36,450.24,68,808.99) 171.79(170.29,173.31) 36,953.13(26,698.86,50,398.99) 156.76(155.11,158.42) −1.11(−1.16,−1.07) 0.62(0.62,0.63) Central Latin America 111,658.07(77,767.43,160,243.98) 249.15(247.66,250.66) 106,855.42(74,395.25,151,459.18) 158.59(157.64,159.54) −0.27(−0.36,−0.19) 0.51(0.50,0.52) Central sub-Saharan Africa 36,666.48(25,433.08,53,149.24) 271.66(268.81,274.54) 66,581.81(46,280.15,97,004.70) 197.96(196.43,199.51) 2.20(2.09,2.32) 0.44(0.44,0.45) East Asia 726,256.73(504,125.62,1,029,001.81) 212.18(211.68,212.68) 537,001.73(391,755.36,725,687.71) 151.07(150.65,151.49) −0.88(−1.11,−0.65) 0.56(0.56,0.57) Eastern Europe 145,890.40(104,997.51,201,071.63) 270.56(269.16,271.96) 119,880.45(85,212.38,161,896.00) 265.46(263.88,267.04) −0.42(−0.57,−0.27) 0.40(0.40,0.40) Eastern sub-Saharan Africa 123,494.86(86,091.43,178,126.30) 261.73(260.22,263.25) 212,482.17(148,496.93,306,955.92) 192.62(191.78,193.46) 1.84(1.77,1.91) 0.45(0.44,0.46) High-income Asia Pacific 112,438.92(81,103.98,158,887.72) 247.82(246.36,249.27) 83,514.01(61,306.94,114,214.31) 219.98(218.42,221.54) −1.25(−1.36,−1.14) 0.43(0.43,0.43) High-income North America 141,500.01(98,609.85,201,983.09) 186.36(185.38,187.34) 103,086.53(77,451.10,139,197.96) 126.65(125.87,127.43) −1.62(−1.78,−1.46) 0.65(0.64,0.66) North Africa and middle East 293,930.99(204,763.76,421,921.59) 339.48(338.22,340.74) 403,070.92(287,838.06,572,353.27) 253.68(252.90,254.47) 1.23(1.13,1.34) 0.35(0.34,0.35) Oceania 4992.52(3472.08,7040.04) 309.89(301.17,318.84) 9537.91(6651.26,13,545.16) 278.92(273.32,284.60) 2.32(2.26,2.38) 0.41(0.41,0.41) South Asia 804,434.30(571,211.90,1,145,323.00) 296.11(295.45,296.77) 1,031,147.97(738,364.00,1,474,013.45) 209.68(209.28,210.09) 0.81(0.75,0.87) 0.40(0.40,0.41) Southeast Asia 330,966.56(235,630.62,465,919.60) 263.31(262.40,264.22) 398,258.07(284,951.82,548,608.51) 223.78(223.09,224.48) 0.66(0.52,0.79) 0.42(0.42,0.42) Southern Latin America 25,301.36(18,171.05,36,478.82) 201.90(199.41,204.40) 29,097.37(20,718.57,40,640.11) 172.69(170.70,174.69) 0.58(0.54,0.62) 0.56(0.55,0.56) Southern sub-Saharan Africa 33,482.34(23,455.93,47,736.10) 228.55(226.05,231.08) 37,079.10(26,330.56,52,847.73) 172.57(170.82,174.34) 0.38(0.24,0.52) 0.52(0.51,0.52) Tropical Latin America 96,269.63(65,545.16,141,009.83) 230.79(229.32,232.27) 106,818.66(76,360.97,151,183.52) 182.38(181.28,183.48) 0.31(0.20,0.42) 0.50(0.49,0.50) Western Europe 15,2131.80(108,769.01,221,656.76) 165.32(164.49,166.16) 134,387.89(95,459.10,193,553.57) 160.25(159.37,161.12) −0.29(−0.38,−0.20) 0.61(0.60,0.61) Western sub-Saharan Africa 122,382.68(85,545.05,176,319.29) 257.62(256.13,259.12) 233,697.65(164,779.23,338,051.82) 192.79(191.99,193.59) 2.22(2.13,2.31) 0.46(0.45,0.46) Table 2 The DALY Cases and Age-Standardized DALY Rate Endometriosis in 1990 and 2019 and Its Temporal Trends 1990 1990 2019 2019 EAPC(1990–2019) EAPC(1990–2019) DALY number Age-standardized DALY rate (per 100,000) DALY number Age-standardized DALY rate (per 100,000) DALY number Age-standardized DALY rate (per 100,000) Global 1820,057.29(1,069,738.59,2,902,416.60) 137.46(137.26,137.66) 2,148,886.11(1,281,021.94,3,411,822.07) 109.55(109.40,109.70) 0.55(0.48,0.63) −0.82(−0.85,−0.78) Sociodemographic index – – – – – – Low SDI 199,270.80(116,460.16,321,782.36) 175.14(174.36,175.93) 339,336.35(199,101.13,558,718.45) 128.54(128.10,128.98) 1.82(1.75,1.88) −1.10(−1.16,−1.04) Low-middle SDI 430,309.84(250,908.96,693,762.38) 165.98(165.48,166.49) 533,870.40(314,961.22,864,027.88) 115.10(114.79,115.41) 0.68(0.62,0.73) −1.31(−1.34,−1.28) Middle SDI 578,549.98(338,925.39,921,938.96) 134.03(133.68,134.39) 677,590.28(401,393.44,1,072,280.99) 106.30(106.05,106.55) 0.57(0.44,0.70) −0.80(−0.85,−0.74) High-middle SDI 364,716.53(213,119.41,585,351.09) 121.37(120.98,121.77) 373,073.90(222,068.54,586,326.22) 101.27(100.94,101.60) 0.17(0.06,0.28) −0.61(−0.67,−0.55) High SDI 246,178.21(144,695.70,390,105.68) 113.71(113.26,114.16) 223,611.02(136,134.31,346,378.20) 95.74(95.34,96.15) −0.53(−0.61,−0.45) −0.77(−0.86,−0.69) Region – – – – – – Andean Latin America 14601.43(8462.02,23,650.10) 157.53(154.94,160.16) 18,942.13(11,314.62,30,477.56) 113.43(111.82,115.06) 0.97(0.93,1.01) −1.05(−1.12,−0.97) Australasia 8030.00(4654.60,12,974.48) 148.69(145.45,151.99) 8762.73(5239.89,14,203.95) 128.07(125.37,130.81) 0.40(0.20,0.60) −0.37(−0.53,−0.20) Caribbean 12,728.87(7472.29,20,654.91) 137.81(135.39,140.26) 13,332.87(7771.12,21,535.90) 109.68(107.83,111.56) 0.12(0.06,0.19) −0.79(−0.81,−0.77) Central Asia 26,933.77(15,596.50,43,663.01) 158.13(156.19,160.10) 35,100.44(20,562.70,56,024.43) 139.72(138.26,141.20) 1.21(1.04,1.38) −0.25(−0.41,−0.10) Central Europe 28,849.43(17,117.53,45,634.16) 95.58(94.47,96.69) 22,997.05(13,620.62,36539.86) 87.31(86.15,88.48) −0.79(−0.80,−0.77) −0.33(−0.45,−0.21) Central Latin America 57,236.41(33,903.63,92,585.16) 139.75(138.58,140.92) 59,438.56(34,345.43,94,475.98) 87.78(87.07,88.49) −0.01(−0.11,0.09) −1.70(−1.76,−1.64) Central sub-Saharan Africa 18,762.74(10,841.77,30,654.35) 155.16(152.89,157.46) 34,395.71(20,060.49,56,581.13) 113.11(111.89,114.34) 2.22(2.12,2.32) −1.01(−1.13,−0.90) East Asia 369,709.91(214,737.65,596,467.95) 114.91(114.53,115.29) 323,534.76(194,424.61,510,426.96) 82.22(81.93,82.51) −0.45(−0.70,−0.20) −1.19(−1.35,−1.03) Eastern Europe 87,409.96(51,362.21,139,771.38) 153.09(152.07,154.12) 77,315.76(46,032.51,122,506.09) 150.05(148.96,151.16) −0.15(−0.24,−0.06) 0.16(0.01,0.31) Eastern sub-Saharan Africa 62,252.08(36,308.70,101,687.85) 150.04(148.82,151.27) 110,666.20(64,606.13,181,317.34) 112.66(111.99,113.35) 1.99(1.94,2.04) −1.00(−1.04,−0.96) High-income Asia Pacific 62,289.14(36,670.24,101,119.78) 135.54(134.48,136.62) 49,160.28(30,186.05,76,355.81) 118.10(117.01,119.20) −1.11(−1.22,−0.99) −0.74(−0.84,−0.64) High-income North America 73,644.38(41,167.75,121,639.73) 94.18(93.50,94.87) 56,534.22(35,387.77,86,987.71) 66.39(65.84,66.94) −1.49(−1.66,−1.32) −1.67(−1.80,−1.53) North Africa and middle East 150,027.28(87,061.64,244,760.50) 192.61(191.62,193.61) 229,694.14(136,495.97,372,943.45) 143.18(142.60,143.77) 1.64(1.55,1.74) −0.94(−1.00,−0.88) Oceania 2633.84(1534.17,4196.46) 178.09(171.21,185.21) 5371.50(3108.89,8734.33) 162.67(158.33,167.11) 2.54(2.48,2.60) −0.28(−0.31,−0.26) South Asia 431,218.11(252,927.07,694,763.20) 171.68(171.16,172.20) 566,345.92(333,624.77,921,454.84) 118.52(118.21,118.83) 0.87(0.80,0.93) −1.38(−1.42,−1.34) Southeast Asia 171,904.77(100,605.41,275,281.46) 147.10(146.39,147.81) 225,193.48(132,019.05,354,561.51) 124.18(123.66,124.69) 0.97(0.82,1.11) −0.53(−0.57,−0.49) Southern Latin America 13,947.25(8003.79,22,641.37) 113.24(111.37,115.14) 16,580.24(9556.38,26,898.39) 95.28(93.84,96.75) 0.68(0.63,0.74) −0.53(−0.59,−0.47) Southern sub-Saharan Africa 17,004.65(9925.23,27,548.74) 128.26(126.29,130.25) 20,730.07(12,015.98,33,372.18) 95.86(94.55,97.18) 0.68(0.61,0.76) −0.95(−0.99,−0.90) Tropical Latin America 49,518.99(28,347.61,82,671.00) 124.85(123.74,125.97) 63,157.74(37,399.62,103,054.27) 103.40(102.60,104.22) 0.76(0.71,0.80) −0.75(−0.85,−0.64) Western Europe 99,648.76(58,609.31,160,130.40) 102.98(102.34,103.63) 90,056.11(53,337.24,144,516.38) 97.19(96.54,97.84) −0.32(−0.35,−0.29) −0.22(−0.28,−0.17) Western sub-Saharan Africa 61,705.52(36,077.44,99,719.51) 146.27(145.08,147.47) 121,576.22(70,952.45,195,211.37) 111.69(111.04,112.33) 2.38(2.29,2.47) −0.92(−0.97,-0.87) The Incident Cases and ASIR Endometriosis in 1990 and 2019 and Its Temporal Trends The DALY Cases and Age-Standardized DALY Rate Endometriosis in 1990 and 2019 and Its Temporal Trends Global epidemiological analysis of 204 countries in 2019 revealed a consistent age-specific pattern for endometriosis, with peak incidence rates occurring in the 20–24 age group and the lowest rates observed among women aged 45–49 ( Supplementary Table 3 , Supplementary Figures 2 and 3A ). This trend persisted across all 21 geographical regions and 5 SDI strata. Notably, incidence rates in SDI regions followed a characteristic rise-and-fall pattern, reaching maximum values in low SDI regions. DALY rates mirrored this epidemiological pattern, demonstrating an initial increase followed by decline across SDI regions, with the highest burden similarly concentrated in low SDI areas. These findings are comprehensively documented in Supplementary Tables 3 – 4 and Supplementary Figures 2 , 3A and B . The 2019 data demonstrate significant disparities in endometriosis burden across socioeconomic regions ( Tables 1, 2 ; Supplementary Figure 4 ). A consistent inverse relationship was observed between SDI levels and endometriosis metrics, with rates progressively declining along the socioeconomic spectrum: Low SDI > Low-middle SDI > High-middle SDI > High SDI. Consistent increases in ASIR of endometriosis were observed across all SDI regions between 1990 and 2019 ( Table 1 and Table 2 and Supplementary Figure 1 ). The most pronounced upward trend occurred in High SDI regions (EAPC = 0.54), followed by High-middle SDI (EAPC = 0.50), while Low SDI regions showed the most modest increase (EAPC = 0.39). Conversely, age-standardized DALY rates demonstrated significant declines throughout all SDI categories, with the most substantial reduction occurring in Low-middle SDI regions (EAPC = −1.31). Our analysis of ASIR and DALY rates across 21 SDI regions revealed distinct epidemiological patterns ( Supplementary Figure 5A ). The ASIR-SDI relationship followed an inverted U-curve, peaking at approximately SDI=0.7, with Oceania, Eastern Europe, North Africa, and the Middle East consistently exhibiting elevated ASIR values throughout the study period (1990–2019). The temporal trends in EAPC displayed a complex trajectory, initially decreasing, then increasing, before declining again. Regionally, areas with SDI≈0.6 showed the lowest EAPC values, while those near SDI≈0.8 demonstrated the highest. Notably, high-income regions including North America, Central Europe, and Western Europe experienced substantially greater ASIR growth than predicted. Parallel analyses of DALY rates showed comparable trends with SDI ( Supplementary Figure 5B ). At the national level, 2019 data demonstrated significant inverse correlations between SDI and both ASIR (indicating decreasing incidence with higher development) and DALY rates ( Supplementary Figure 6 ). In 2019, Oceania had the highest ASIR of endometriosis (278.92 per 100,000), while High-income North America presented the lowest value across all 21 global regions ( Table 1 ). From 1990 to 2019, ASIRs rose across all regions; High-income North America, Central Europe and Western Europe witnessed the steepest upward trends, whereas growth was mildest in North Africa/Middle East and Central Asia ( Table 1 and Supplementary Figures 1B , 3A , 4B ). Consistent with incidence patterns, Oceania bore the highest age-standardized DALY rate in 2019, and High-income North America the lowest. DALY trends diverged markedly: only Eastern Europe saw a slight DALY rise over the three decades, and Central Latin America, High-income North America and South Asia had the most dramatic DALY reductions ( Table 2 and Supplementary Figures 1A , 3B , 4A ). Wide national disparities in endometriosis ASIR were observed in 2019. New Zealand had the highest national ASIR, and Iceland the lowest. Long-term trend analysis showed extreme heterogeneity: San Marino had the fastest rising ASIR, while Niue exhibited the sharpest ASIR decline from 1990 to 2019 ( Supplementary Figure 7C and D , F ). For DALY burden, New Zealand recorded the highest age-standardized DALY rate globally, and Portugal the lowest. DALY temporal trends also varied sharply by country: Sweden had the largest increase in DALY rates, whereas Guatemala saw the most prominent reduction over the study period ( Supplementary Figure 7A and B , E ). Full country-specific ASIR, DALY and EAPC estimates covering all 204 countries and territories are available in Supplementary Tables 1 and 2 for detailed reference.

The Global Health Data Exchange (GHDx) serves as an open-access repository providing comprehensive global population health metrics, including data from the GBD 2019 ( https://ghdx.healthdata.org/gbd-2019 ). This study utilized GBD 2019 endometriosis data spanning 1990–2019, incorporating 95% uncertainty intervals (UIs), with analyses focusing on age-standardized incidence rates and DALY rates across reproductive age groups (15–49 years, stratified into seven 5-year cohorts), temporal trends (1990–2019), and geographical distributions (regional and national levels). The 2019 dataset specifically provided estimates for women aged 15–49 years categorized into discrete age bands (15–19, 20–24, 25–29, 30–34, 35–39, 40–44, and 45–49 years). This study is a secondary analysis of de-identified, publicly available data from the GBD 2021 study. Therefore this study was exempt from institutional ethical approval based on item 1 and 2 of Article 32 of the Measures for Ethical Review of Life Science and Medical Research Involving Human Subjects dated February 18, 2023, China. The GBD 2021 study was approved by the University of Washington Institutional Review Board, which waived informed consent. All procedures complied with the Declaration of Helsinki (1975, as revised in 2024). All downloaded outputs contained age-standardized metrics, raw case counts, DALY counts, and corresponding uncertainty intervals generated by DisMod-MR 2.1. Global standard population adopted by GBD 2019 was used for age standardization of ASIR and age-standardized DALY rates. Data filtering excluded males and women outside the reproductive age range (15–49 years). Endometriosis is a gynecological disorder characterized by the ectopic growth of endometrial-like tissue outside the uterine cavity, typically resulting in chronic pelvic pain, dysmenorrhea, and dyspareunia. The GBD Study 2019 defines endometriosis cases according to the American College of Obstetricians and Gynecologists (ACOG) diagnostic criteria, which require clinical evaluation supported by laparoscopic or histopathological confirmation. Distinctions exist across three tiers of endometriosis diagnosis worldwide: clinically suspected cases solely identified through symptoms and physical examination, intraoperatively visualized lesions confirmed via laparoscopy, and definitive cases verified by postoperative histopathological testing. The GBD 2019 standard adopts ACOG criteria requiring laparoscopic or histopathological confirmation to define valid cases, while many regional epidemiological surveys only enroll patients with pathological verification. Uneven access to laparoscopy and pathological testing across low-, middle-, and high-SDI regions leads to inconsistent capture of suspected, visualized, and histologically confirmed cases, which introduces measurement bias and may underestimate the true population incidence and burden of endometriosis in under-resourced areas. Previous epidemiological studies, however, often restricted case definitions to those with pathological verification alone-, 11 potentially underestimating disease prevalence due to diagnostic variability. This condition predominantly manifests with cyclical symptoms that correlate with menstrual periods, including abnormal uterine bleeding and severe pain during menstruation or intercourse, contributing to its substantial burden on reproductive-aged women worldwide. The Socio-Demographic Index (SDI) serves as a comprehensive measure of regional development status, integrating three core dimensions of regional socioeconomic conditions: total fertility rates among women under 25 years, average educational attainment levels, and per capita income. Using SDI values, 204 countries and territories are classified into five distinct development tiers: low SDI, low-middle SDI, middle SDI, high-middle SDI, and high SDI regions. The five SDI strata were partitioned strictly following the official GBD 2019 cut-off thresholds, and all 204 countries and territories were assigned to corresponding groups via built-in GHDx classification files. The study employed DisMod-MR 2.1, a Bayesian meta-regression tool, to generate epidemiological estimates of endometriosis incidence, prevalence, and disability burden stratified by age, sex, year, and geographic location. In alignment with previous GBD methodologies, we considered incidence rates to be clinically insignificant outside the reproductive age range (15–50 years). This approach reflects the biological plausibility that endometriosis development requires reproductive capacity, coupled with evidence suggesting possible spontaneous resolution following menopause. The DisMod-MR 2.1 Bayesian meta-regression model integrated multiple sources of population hospital data, clinical registries, and published epidemiological literatures to fit disease incidence, prevalence and disability estimates. The model incorporated geographic, age, sex, and year random effects to adjust cross-group heterogeneity, and propagated all sampling and modeling uncertainty to generate 95% uncertainty intervals (UIs) for all outcomes. All model default calibration parameters followed the official GBD 2019 standardized pipeline without manual modification. This study employed the estimated annual percentage change (EAPC) to quantify temporal trends in endometriosis incidence and DALY rates over a 30-year period. Using a linear regression model, we analyzed the association between age-standardized incidence rates (ASIRs) or age-standardized DALY rates and calendar years. The EAPC and its 95% confidence interval (CI) were calculated using the formula: EAPC = 100 × [exp(β) - 1], where β represents the regression coefficient for annual rate changes. To address potential serial autocorrelation within time-series data, the Prais–Winsten iterative regression approach was applied to adjust first-order residual autocorrelation when fitting linear models. The 95% CIs of EAPC were derived from the standard errors of regression coefficients generated by the Prais–Winsten model, following standard GBD analytical pipelines. For all statistical tests conducted in this descriptive burden analysis, no formal multiple comparison correction (eg, Bonferroni or false discovery rate adjustment) was implemented. The primary objective of this work was to describe population-level temporal trends and stratified intergroup disparities rather than conduct confirmatory pairwise hypothesis testing. Consistent with standard analytical protocols of published GBD-based epidemiological studies, strict multiple testing correction would drastically reduce statistical power and mask clinically and public health meaningful disparities across regions, countries, and SDI subgroups. All P values are reported unadjusted; readers should interpret subgroup-level significant results cautiously and prioritize the magnitude of changes in ASIR and DALY rates when drawing conclusions. A statistically significant positive EAPC (with its 95% CI entirely above zero) indicates an increasing trend, while a negative value suggests a decreasing trend; non-significant values reflect stable rates. All analyses, including computation of age-standardized rates (ASIR and DALY) and EAPCs, were performed using R software (version 4.3.0), with statistical significance defined as p < 0.05. It should be emphasized that this study adopts an ecological research design relying on aggregated population-level model estimates from GBD 2019. All temporal and geographic trends presented herein only reflect population-level epidemiological patterns of endometriosis, and cannot be used to assess or infer individual-level disease risk factors or causal associations at the personal level.

According to the 2019 Global Burden of Disease study, the global incidence of endometriosis and related DALYs increased significantly between 1990 and 2019. While the age-standardized incidence rate demonstrated an upward trend, the age-standardized DALY rate exhibited a decline during this period. The burden of endometriosis varies considerably across regions with different socioeconomic development levels. Low SDI regions, particularly Oceania, remain disproportionately affected, whereas High SDI regions show a notable rise in incidence. For example, in high-income North America, the age-standardized incidence rate increased across 21 regions, while the age-standardized DALY rate declined—with Eastern Europe being the sole exception. This study delivers three distinct novel findings. First, we systematically contrasted the decoupled trend of rising global ASIR and falling age-standardized DALY rates across all 21 GBD regions, and singled out Eastern Europe as the only region with growing DALY burdens for targeted interpretation. Second, we quantified stratified burden trends by five SDI tiers and further unpacked dual drivers of diagnostic ascertainment and real disease risk to explain SDI-based disparities, rather than simplifying regional incidence shifts to medical access alone. Third, we pinpointed women aged 20–29 as the highest-risk subgroup and proposed disease-specific targeted intervention strategies instead of universal public health recommendations, filling gaps in granular age-stratified interpretation and actionable clinical policy proposals in prior literature. This divergent epidemiological trend forms a striking paradox, which can be explained by two core clinical and public health drivers. Advances in pelvic ultrasound and laparoscopic techniques over recent decades greatly improved diagnostic sensitivity, identifying large numbers of mild endometriosis patients with minimal disability and pushing up overall ASIR. Meanwhile, widely standardized hormonal therapy and minimally invasive surgery effectively relieved severe disabling symptoms including chronic pelvic pain and infertility, lowering average disability weights and leading to continuous falls in age-standardized DALY rates. Given these trends, targeted monitoring and improved treatment strategies are especially crucial for women aged 20–29 years. Endometriosis is a heterogeneous and complex disease whose pathological and developmental mechanisms remain incompletely understood. Current evidence suggests that genetic and environmental factors contribute equally (approximately 50% each) to its etiology. 12 , 13 Key risk factors include lifestyle habits (eg, alcohol consumption 14 and smoking 15 ), body mass index, 16 reproductive history (such as dysmenorrhea, pregnancy, parity, and infertility), 17 , 18 and early-life factors (including preterm birth, low birth weight, and infant feeding practices), as well as racial disparities. 1 , 19 However, no single set of risk factors applies universally to all women with endometriosis, and individualized assessment—considering medical history and surgical options—may be necessary. 20 Diagnosing endometriosis remains challenging, as medical history, physical examinations, and non-invasive tests often lack sufficient sensitivity and specificity. Definitive diagnosis typically requires visual confirmation via endoscopy or histopathological examination following laparotomy. 21 The accuracy of diagnosis is further influenced by the surgeon’s expertise, experience, and clinical interest in the disease. 22 These diagnostic limitations can lead to delays in identification and introduce biases that obscure true incidence and prevalence rates. Given the invasive nature of current diagnostic approaches, there is an urgent need to advance non-invasive screening tools and expand research efforts in this field. Age is a key determinant in endometriosis incidence patterns. 11 Globally, the ASIR reaches its peak among women aged 20–24 years, while the highest DALY rates occur in the 25–29 age group. As a condition predominantly affecting reproductive-aged women, endometriosis accounts for more than 30% of all gynecological diagnoses 23 , 24 and is present in 20–50% of women experiencing infertility. 25 The rising trend of delayed first pregnancies and increased menstrual frequency may contribute to higher endometriosis risk among women in their twenties, with significant implications for fertility. Notably, disease prevalence declines substantially after age 40, likely attributable to decreasing hormonal activity. These epidemiological patterns underscore the importance of targeted screening and early diagnosis in adolescents and young reproductive-aged women to mitigate potential fertility consequences. The offset between peak ASIR (20–24 years) and peak DALY burden (25–29 years) can be explained by clinical care-seeking trajectories. Women aged 20–24 often present with mild intermittent pelvic pain but experience diagnostic delay due to infrequent gynecological visits; subclinical lesions are only captured via routine screening, driving up recorded incidence without severe disability. By age 25–29, many patients attempt conception and seek infertility evaluation, leading to definitive laparoscopic diagnosis of advanced lesions with persistent severe symptoms, which elevates DALY metrics linked to impaired fertility and chronic discomfort. Varied healthcare utilization and fertility-seeking behavior therefore create this age-shifted burden pattern, providing clinical guidance for early intervention before childbearing plans. Our analysis revealed modest increases in the ASIR of endometriosis across all five SDI regions over the past three decades, while age-standardized DALY rates demonstrated a substantial global decline. The disease burden exhibited distinct variations by SDI level, with Low SDI regions bearing the highest burden and High SDI regions the lowest. Notably, developed regions including North America, New Zealand, and Switzerland showed the most pronounced ASIR growth rates - a pattern potentially attributable to their advanced healthcare systems that facilitate greater access to diagnostic technologies and specialist care. This rising ASIR trend in high-SDI regions cannot be solely attributed to improved diagnostic detection, and we must distinguish true population-level disease risk from elevated case ascertainment. Multiple confounding drivers jointly shape this regional disparity. First, universal health insurance and abundant gynecological specialists enable broader screening and laparoscopic examination, capturing mild asymptomatic cases missed in low-resource settings, which inflates recorded incidence rather than reflecting genuine risk elevation. 26 , 27 Second, higher public and clinical awareness of endometriosis encourages women with pelvic pain to seek medical consultation earlier, alongside standardized ICD coding practices that reduce missed documentation of cases in hospital registries. 28 Third, delayed childbearing, higher prevalence of hormonal contraceptive use and other lifestyle risk factors prevalent in wealthy populations may independently raise genuine endometriosis susceptibility, partially contributing to the upward ASIR trend. 29 By contrast, low-SDI regions face persistent diagnostic barriers, leading to severe underascertainment that masks their actual disease burden. 30 In contrast, persistent healthcare access barriers in economically disadvantaged regions such as Oceania, Afghanistan, and the Solomon Islands remain a critical concern. Expanded medical insurance improves routine gynecological screening coverage and timely intervention, effectively lowering long-term disability burden associated with endometriosis. Consistent with our SDI-stratified burden data, socioeconomic and geographic medical resource gaps directly shape observed incidence differences. Occupational exposure and epigenetic effects are proposed potential modifiers based on prior basic research, yet they cannot be validated by the population-level ecological data from this study and require dedicated cohort verification. 31 , 32 Eastern Europe represents a notable exception to global trends, exhibiting rising DALY rates that underscore the urgent need for enhanced prevention and treatment strategies in the region. The prominent inverted U-curve relationship between SDI and ASIR deserves further interpretation. First, diagnostic gaps vary drastically across development tiers: low-SDI regions suffer severe underdiagnosis due to limited laparoscopy resources, mid-SDI areas have relatively complete screening systems to capture most mild cases, while high-SDI regions detect numerous asymptomatic mild patients which dilutes overall incidence levels. Second, differentiated healthcare access such as universal gynecological examination services further widens this gap. Third, the unified Bayesian estimation framework of DisMod-MR only slightly adjusts the curve’s curvature and threshold value, and cannot generate this core inverted U pattern independently. Taken together, inconsistent diagnostic coverage and unequal medical resources constitute the primary drivers of this epidemiological feature, rather than model artifacts. This study represents one of the most comprehensive analyses of global endometriosis incidence and DALY rates from 1990 to 2019. By assessing the worldwide disease burden, our findings provide crucial epidemiological data to inform prevention strategies and healthcare policies. However, several limitations should be acknowledged. First, this study relies entirely on GBD modeled outputs, whose accuracy is heavily contingent on variable local primary data quality across 204 countries. Cross-national comparisons are distorted by inconsistent case ascertainment, widespread diagnostic delay in low-resource regions, and heterogeneous clinical diagnostic thresholds, all of which systematically shift estimated ASIR and DALY values. Uneven access to laparoscopic confirmation further exacerbates measurement bias and may cause substantial underestimation of true population incidence. Second, all DisMod-MR 2.1 outputs are constrained by a series of built-in model assumptions. Variations in input data sources and model calibration parameters expand uncertainty intervals and limit direct numerical comparison between nations. Meanwhile, inconsistent diagnostic criteria worldwide introduce extra measurement bias and reduce comparability with independent regional studies. 33 Third, age-standardized metrics eliminate the confounding effect of population age structure, yet they mask absolute changes driven by population growth and global aging. Consistent with our results, total incident cases rose markedly over 30 years even as age-standardized DALY rates declined; standardised rates alone cannot fully reflect the expanding overall disease burden. Finally, this is an ecological aggregated analysis based on population-level modeling data, so all observed trends cannot be extrapolated to individual disease risk or causal relationships between personal factors and endometriosis.

Although the age-standardized disability burden of endometriosis has declined worldwide over the past three decades, this improvement cannot be fully attributed to global public health initiatives, and prominent interregional disparities in disease distribution still exist. Notably, the age-standardized incidence rate continues to show an upward trend worldwide. This concerning pattern is particularly pronounced in low-income regions such as Oceania, where variations in age-specific prevalence contribute to disproportionate disease burdens. These findings highlight the urgent need to implement targeted interventions, with special attention to women aged 20–29 years. In global management strategies for endometriosis, standardized early screening targeting women aged 20–29 should be promoted; specialized endometriosis case registries should be established in high-burden regions such as Oceania; systematic pelvic ultrasound training should be provided for primary care clinicians to break down diagnostic barriers; and stratified long-term hormonal therapy should be widely adopted to reduce disease-related disability burdens.