Abstract
Objective
To explore the impact of hypertension-induced cardiorenal disease on disability rates and mortality, this study reported the burden of cardiorenal disease caused by hypertension (including hypertensive heart disease [HHD] and hypertensive kidney disease) between 1990 and 2021.
Methods
Utilizing data from the Global Burden of Disease (GBD) database, this study delivered a comprehensive analysis of the burden of hypertension-induced cardiorenal disease. Hypertension was estimated in terms of disability-adjusted life years (DALYs) and mortality, age-standardized death rates (ASDRs), and age-standardized DALY rates (ASRs), considering age, gender, geographical distribution, socio-demographic index (SDI), and cardiorenal disease. Additionally, the estimated annual percentage change (EAPC) was calculated to assess trends in ASDRs and ASRs from 1990 to 2021.
Results
In comparison with 1990, the mortality and DALYs of hypertension-induced cardiorenal disease rose in 2021, resulting in 1,332,099 deaths and 25,462,184 DALYs of HHD, as well as 454,358 deaths and 10,850,728 DALYs of chronic kidney disease(CKD). Between 1990 and 2021, the ASDRs and ASRs of hypertensive heart disease decreased by 21.99%(95% UI, -31.92-6.74%) and 25.81%(95% U, -34.45- -10.07%), respectively. In contrast, the ASDRs and ASRs of hypertension-attributable CKD decreased by 29.21%(95%UI, 11.55–39.65%) and 19.15%(95% UI, 4.31–27.76%), respectively. In 2021, the highest ASDR and ASR of HHD were recorded in Central Sub-Saharan Africa and Southern Sub-Saharan Africa, while those of hypertension-attributable CKD peaked in Western Sub-Saharan Africa and Southeast Asia. Projections indicate a continued decline in HHD ASDRs through 2050, whereas hypertension-attributable CKD is expected to exhibit an upward trend over the same period.
Conclusion
Despite the declining mortality rate of HHD, the increasing incidence of hypertension-induced CKD underscores that hypertension-attributable cardiovascular and kidney diseases remain a globally urgent public health concern.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-025-23742-9.
Keywords: Global burden of disease, Hypertensive heart disease, CKD due to hypertension, Disability-adjusted life years, Age-standardized death rates
Introduction
Given the aging population and increasing lifestyle risk factors, including unhealthy eating habits (e.g., high sodium and low potassium intake) and lack of physical activity, the incidence of hypertension is increasing globally. Globally, blood pressure control remains suboptimal, with only 32.5% of treated individuals achieving blood pressure control [1, 2]. Moreover, the global number of patients with elevated BP has increased, primarily in low-and middle-income countries, indicating the widespread impact of hypertension on global population health. Notably, the disease burden is particularly pronounced in low-income countries [3].
HHD, a typical consequence of hypertension damage to targeted organs, is characterized by left ventricular hypertrophy (prevalence of approximately 40% in hypertensive patients), which may further lead to systolic and diastolic dysfunction [4, 5]. HHD presents with diverse clinical manifestations, ranging from asymptomatic or mild chest discomfort and palpitations, to dyspnea, heart failure, and even sudden cardiac death [6]. As cardiac disease stress triggered by hypertension, HHD represents a key underlying mechanism for the occurrence and death of cardiovascular disease and is also identified as the second leading cause in heart failure following ischemic heart disease [7–9]. Hypertension is a major contributor to the burden of CKD, serving as a key risk factor for the development and progression of renal disease. It is reported to affect up to 90% of CKD patients and accelerate disease progression [10, 11]. The intricate relationship between hypertension and renal function—critical to kidney operation and efficiency—has profound and far-reaching implications for global population health [12].
While appropriate medication can effectively control hypertension, the health risks associated with its complications remain a public concern. However, cardiorenal diseases related to hypertension have not been fully resolved, and assessments of their burden are relatively limited. Consequently, this study analyzed trends in mortality and DALYs of hypertension-induced cardiorenal diseases at the global, regional, and national levels from 1990 to 2021 and predicted the mortality for 2050.
Methods
Data sources
Epidemiological information on cardiorenal disease associated with hypertension risk factors from 1990 to 2021 was obtained from the Global Health Data Exchange query tool (https://vizhub.healthdata.org/gbd-results), a digital repository of the GBD 2021 database [13]. Data on mortality, incidence, DALYs, ASDRs, ASRs, and potential RFs for hypertension-induced cardiorenal disease were sourced from the GBD 2021. The research methodology of the GBD has been thoroughly documented in existing literature, and data sources from meta analysis [14]. The socio-demographic index (SDI)—a comprehensive metric—integrates per capita lag-distributed income with educational attainment among individuals aged 15 years and older to characterize regional economic conditions [15]. Based on the SDI, these 204 nations are divided into five distinct zones: low(< 0.46), low-middle (0.46–0.60), middle (0.61–0.69), high-middle (0.70–0.81), and high (> 0.81) [16].
Statistical analysis
To normalize disparities in population age structures, ASDR and ASR data were hereby calculated to evaluate the impact and patterns of hypertension-induced cardiorenal disease across varying areas, utilizing the GBD Standard Population Distribution [17]. The Bayesian Age-Period-Cohort(BAPC) model represents an advanced forecasting model that merges Bayesian statistical techniques with age-period-cohort analysis to investigate the temporal patterns of disease prevalence [18]. Herein, the BAPC model was utilized to forecast the ASDR and ASR for cardiorenal disease associated with hypertension risk factors through 2050.
The burden of hypertension-induced cardiorenal disease in 1990–2021
In 1990, the global number of HHD death cases was 713,935 (95%UI, 577,533–795,258), which increased to 1,332,099 (95%UI, 1,121,130-1,468,851) in 2021, representing an overall increase of 86.59%(95%UI, 62.76-126.51%). The ASDR for HHD was 20.92 (95%UI, 17.14–23.21) per 100,000 person-years in 1990, which, however, decreased to 16.32 (95%UI, 13.76–18.01) in 2021, reflecting an overall decrease of 21.99% (95%UI, −31.92–6.74%). The EAPC was − 0.68 (95%CI, −0.77–0.58) (Table 1; Fig. 1A). In 1990, the global number of deaths from hypertension-attributable CKD was 148,983 (95%UI, 123,166–176,984), which increased to 454,358 (95% UI, 381290–524688) in 2021, representing an overall increase of 204.97% (95% UI, 161.77-232.08%). The ASDR for Hypertension-attributable CKD was 4.29 (95% UI, 3.55–5.11) per 100,000 person-years in 1990, which increased to 5.54 (95%UI, 4.68–6.41) in 2021, reflecting an overall increase of 29.21% (95%UI, 11.55–39.65%). Moreover, the EAPC was 0.97 (95%CI, 0.90–1.03) (Table 2; Fig. 1B).
Table 1.
Death of hypertensive heart disease between 1990 and 2021 at the global and regional level
| Location | Rate per 100,000 (95% Ul) | ||||||
|---|---|---|---|---|---|---|---|
| 1990-Both | 2021-Both | 1990–2021 | |||||
| Death Case | Death Rate | Death Case | Death Rate | Case change | Rate change | EAPCs | |
| Global | 713935.24(577533.95,795258.05) | 20.92(17.14,23.21) | 1332099.18(1121130.98,1468851.97) | 16.32(13.76,18.01) | 86.59(62.76,126.51) | −21.99(−31.92,−6.74) | −0.68(−0.77,−0.58) |
| SDI | |||||||
| High-middle SDI | 145582.17(128528.02,161926.85) | 17.83(15.57,19.73) | 275365.29(237570.98,312977.93) | 14.60(12.53,16.52) | 89.15(61.07,130.01) | −18.11(−29.76,−1.09) | −0.41(−0.52,−0.29) |
| High SDI | 93389.66(85035.94,98125.19) | 8.56(7.74,9.01) | 189009.76(157234.20,209886.19) | 7.70(6.54,8.53) | 102.39(84.25,119.36) | −9.98(−15.70,−2.94) | 0.11(−0.07,0.29) |
| Low-middle SDI | 132745.25(95311.17,158999.27) | 28.04(21.09,33.87) | 274885.98(225956.16,315308.87) | 23.15(19.06,26.62) | 107.08(74.36,161.20) | −17.44(−30.14,2.65) | −0.56(−0.61,−0.51) |
| Low SDI | 70360.63(46597.58,89469.14) | 40.54(28.07,50.81) | 129352.33(90728.39,159533.11) | 33.58(24.66,40.58) | 83.84(50.40,141.62) | −17.17(−32.82,5.94) | −0.62(−0.71,−0.52) |
| Middle SDI | 270962.91(190726.95,306788.77) | 35.19(25.55,39.43) | 461729.81(349647.01,546063.30) | 20.26(15.30,23.96) | 70.40(43.34,123.31) | −42.41(−51.43,−25.40) | −1.76(−1.98,−1.53) |
| Regions | |||||||
| East Asia | 238411.25(161564.66,281395.86) | 41.86(30.02,48.57) | 340500.57(235952.65,438264.69) | 18.73(13.00,24.13) | 42.82(9.68,114.35) | −55.25(−66.49,−34.36) | −2.63(−3.01,−2.25) |
| Southeast Asia | 62278.36(43376.37,75569.90) | 29.57(20.74,35.80) | 128532.12(93845.41,148677.63) | 22.92(16.89,26.49) | 106.38(72.13,168.89) | −22.50(−35.85,−0.60) | −0.82(−0.87,−0.77) |
| Oceania | 615.15(385.39,836.16) | 26.11(17.29,34.39) | 1215.84(823.17,1758.25) | 18.97(13.06,26.88) | 97.65(50.55,172.62) | −27.34(−42.80,−4.21) | −1.11(−1.17,−1.06) |
| Central Asia | 6687.08(5814.37,7780.66) | 16.04(13.85,18.83) | 13575.21(11626.11,15907.45) | 20.62(17.75,23.92) | 103.01(61.14,148.28) | 28.53(1.36,57.43) | 1.31(0.70,1.92) |
| Central Europe | 31130.30(29587.11,32630.45) | 23.30(21.94,24.53) | 60801.38(54777.33,65338.00) | 25.38(22.89,27.31) | 95.31(78.70,110.35) | 8.96(−0.36,17.13) | 0.84(0.58,1.11) |
| Eastern Europe | 11685.48(11105.22,12232.11) | 4.48(4.25,4.70) | 26346.39(23721.63,28591.19) | 7.41(6.68,8.04) | 125.46(106.61,146.21) | 65.33(51.68,80.26) | 1.71(0.78,2.66) |
| High-income Asia Pacific | 17175.73(15077.32,18444.76) | 10.54(9.05,11.39) | 21393.58(16165.18,25059.57) | 2.97(2.34,3.47) | 24.56(4.98,50.39) | −71.77(−74.91,−65.46) | −3.66(−4.41,−2.89) |
| Australasia | 742.28(667.33,789.77) | 3.45(3.05,3.70) | 1506.46(1239.34,1666.98) | 2.35(1.96,2.59) | 102.95(84.22,117.10) | −31.82(−36.57,−27.46) | −1.04(−1.46,−0.63) |
| Western Europe | 51680.91(46518.75,54541.14) | 8.66(7.77,9.16) | 107186.00(85267.27,119112.34) | 8.21(6.66,9.07) | 107.40(81.68,120.89) | −5.14(−14.58,0.20) | 0.40(0.21,0.60) |
| Southern Latin America | 6842.26(6398.91,7159.12) | 16.29(15.14,17.08) | 12725.09(11072.42,13670.70) | 13.77(12.01,14.78) | 85.98(71.87,98.63) | −15.52(−21.46,−10.15) | −0.16(−0.33,0.01) |
| High-income North America | 24618.34(22278.15,25860.86) | 6.93(6.29,7.27) | 70913.47(60613.96,78750.06) | 10.41(9.06,11.52) | 188.05(160.18,213.01) | 50.28(36.60,63.09) | 1.51(1.33,1.70) |
| Caribbean | 4754.49(4028.22,5539.24) | 20.24(17.29,23.27) | 10816.03(9110.01,12603.35) | 19.72(16.59,22.99) | 127.49(99.23,158.10) | −2.56(−14.14,9.39) | 0.40(0.18,0.62) |
| Andean Latin America | 2565.63(2225.37,2905.66) | 14.45(12.57,16.33) | 4700.55(3728.17,5792.28) | 8.43(6.70,10.38) | 83.21(52.29,120.08) | −41.65(−51.45,−30.16) | −1.17(−1.56,−0.79) |
| Central Latin America | 12434.23(11776.81,12862.26) | 18.63(17.40,19.38) | 22489.12(18586.36,26047.45) | 9.63(7.97,11.13) | 80.86(52.84,108.65) | −48.31(−55.88,−40.64) | −2.21(−2.41,−2.00) |
| Tropical Latin America | 17381.71(16368.36,18044.14) | 23.10(21.23,24.19) | 30406.23(26624.76,33180.71) | 12.39(10.80,13.52) | 74.93(58.89,88.03) | −46.38(−50.77,−42.81) | −1.81(−1.94,−1.68) |
| North Africa and Middle East | 71361.33(54461.67,85226.72) | 56.89(43.87,68.05) | 138260.72(109922.95,161917.88) | 39.54(31.48,46.22) | 93.75(58.80,144.46) | −30.50(−42.51,−13.61) | −1.04(−1.20,−0.88) |
| South Asia | 76637.86(49356.52,103624.10) | 17.92(11.73,24.22) | 196771.96(155294.69,256586.56) | 16.54(13.11,21.44) | 156.76(93.35,289.01) | −7.71(−30.18,38.27) | −0.17(−0.30,−0.03) |
| Central Sub-Saharan Africa | 10737.39(5994.26,15055.53) | 67.53(40.70,91.84) | 24396.05(15347.03,34210.76) | 66.29(42.22,92.93) | 127.21(69.49,237.53) | −1.84(−25.45,39.73) | −0.09(−0.14,−0.04) |
| Eastern Sub-Saharan Africa | 32510.70(20661.10,41346.14) | 58.45(39.64,72.82) | 52210.86(35806.26,66306.14) | 42.56(29.44,54.66) | 60.60(31.42,114.52) | −27.18(−39.98,−6.94) | −1.14(−1.21,−1.07) |
| Southern Sub-Saharan Africa | 8661.58(7510.61,10960.11) | 38.20(32.67,49.17) | 21605.13(19013.47,25148.33) | 47.42(41.51,55.21) | 149.44(118.44,182.69) | 24.12(8.24,41.00) | 0.84(0.39,1.30) |
| Western Sub-Saharan Africa | 25023.17(18234.19,31428.21) | 34.57(25.65,43.67) | 45746.41(28908.71,56512.37) | 28.78(18.85,34.87) | 82.82(21.51,138.99) | −16.75(−43.85,7.18) | −0.77(−0.93,−0.61) |
Abbreviations: EAPC estimated annual percentage change, SDI SocioDemographic Index, UI Uncertainty Interval
aEAPC is expressed as 95% confidence interval
bChange shows the percentage change
Fig. 1.
The EAPC of ASDRs and ASRs for cardiorenal disease caused by hypertension in the global distribution. Age-standardized rates for deaths (A), DALYs (B) of HHD across 204 countries and territories, 2021. Age-standardized rates for deaths (C), DALYs (D) of CKD due to hypertension disease across 204 countries and territories, 2021. DALYs, disability adjusted life-years; CKD, chronic kidney disease
Table 2.
Death of chronic kidney disease due to hypertension between 1990 and 2021 at the global and regional level
| Location | Rate per 100,000 (95% Ul) | ||||||
|---|---|---|---|---|---|---|---|
| 1990-Both | 2021-Both | 1990–2021 | |||||
| Death Case | Death Rate | Death Case | Death Rate | Case change | Rate change | EAPCs | |
| Global | 148983.07(123166.76,176984.91) | 4.29(3.55,5.11) | 454358.54(381290.78,524688.46) | 5.54(4.68,6.41) | 204.97(161.77,232.08) | 29.21(11.55,39.65) | 0.97(0.90,1.03) |
| SDI | |||||||
| High-middle SDI | 24908.53(20319.33,30229.46) | 2.98(2.44,3.58) | 64744.80(52652.84,78132.50) | 3.42(2.78,4.13) | 159.93(114.24,196.53) | 14.52(−3.80,27.06) | 0.57(0.50,0.65) |
| High SDI | 25961.46(21214.18,31197.05) | 2.40(1.95,2.86) | 102337.62(81584.04,118816.82) | 4.09(3.34,4.71) | 294.19(253.84,342.09) | 70.79(57.94,85.41) | 2.23(2.06,2.40) |
| Low-middle SDI | 28276.85(22511.71,35715.22) | 5.46(4.37,6.99) | 83172.16(67290.48,99390.08) | 6.62(5.44,7.85) | 194.14(130.22,239.94) | 21.15(−6.78,39.64) | 0.61(0.55,0.66) |
| Low SDI | 15304.56(12180.66,18931.71) | 8.69(7.03,10.73) | 33879.71(27406.89,41452.22) | 8.62(7.09,10.51) | 121.37(95.68,149.68) | −0.79(−12.48,11.00) | −0.08(−0.20,0.05) |
| Middle SDI | 54387.79(45047.08,64626.26) | 6.53(5.39,7.75) | 169821.64(140032.26,198167.32) | 7.13(5.86,8.28) | 212.24(155.75,247.64) | 9.17(−10.62,20.50) | 0.34(0.25,0.42) |
| Regions | |||||||
| East Asia | 30316.49(24328.79,37692.95) | 4.47(3.60,5.52) | 69216.75(52629.18,86964.30) | 3.60(2.76,4.53) | 128.31(73.39,186.64) | −19.45(−37.99,−1.82) | −0.72(−0.80,−0.64) |
| Southeast Asia | 25868.91(21718.71,31347.45) | 10.96(9.15,13.14) | 79828.68(66506.08,93797.09) | 13.77(11.63,16.22) | 208.59(154.67,258.72) | 25.73(2.11,45.07) | 0.72(0.64,0.79) |
| Oceania | 52.52(35.09,73.78) | 2.21(1.51,3.11) | 167.53(126.79,220.68) | 2.69(1.99,3.54) | 219.01(123.66,362.00) | 22.02(−12.52,71.83) | 0.56(0.46,0.66) |
| Central Asia | 95.20(71.01,128.25) | 0.21(0.15,0.29) | 416.66(307.46,536.61) | 0.58(0.42,0.76) | 337.65(257.83,426.55) | 179.92(123.42,245.34) | 2.98(2.50,3.45) |
| Central Europe | 2293.76(1856.47,2797.32) | 1.72(1.40,2.09) | 4153.28(3288.55,4959.70) | 1.74(1.38,2.09) | 81.07(59.15,105.04) | 1.42(−8.90,11.91) | 0.91(0.56,1.27) |
| Eastern Europe | 943.77(756.19,1166.74) | 0.36(0.29,0.43) | 2273.93(1750.90,2856.83) | 0.64(0.50,0.80) | 140.94(106.28,178.57) | 81.21(58.83,103.94) | 1.91(1.26,2.56) |
| High-income Asia Pacific | 3499.48(2864.71,4249.18) | 2.02(1.63,2.46) | 11331.83(8011.36,15009.03) | 1.68(1.22,2.16) | 223.81(169.87,279.99) | −17.07(−25.99,−9.98) | −0.44(−0.76,−0.12) |
| Australasia | 370.09(310.90,433.96) | 1.74(1.42,2.09) | 1553.54(1144.38,1999.77) | 2.38(1.78,3.03) | 319.77(254.99,381.95) | 36.44(18.09,56.57) | 1.54(1.25,1.83) |
| Western Europe | 9770.78(7483.68,12395.29) | 1.64(1.27,2.06) | 29752.75(21810.83,37712.83) | 2.28(1.71,2.85) | 204.51(161.64,258.85) | 38.54(24.49,53.65) | 1.77(1.58,1.96) |
| Southern Latin America | 3268.83(2667.80,3878.50) | 7.79(6.41,9.25) | 6773.53(5405.09,8196.68) | 7.37(5.90,8.90) | 107.22(87.61,127.98) | −5.40(−12.94,1.45) | 0.05(−0.26,0.35) |
| High-income North America | 12436.11(10169.29,14669.11) | 3.39(2.79,3.99) | 59545.39(48903.44,66833.73) | 8.21(6.83,9.16) | 378.81(327.14,442.58) | 142.28(117.56,171.68) | 3.31(3.10,3.51) |
| Caribbean | 1358.90(1112.35,1679.90) | 5.73(4.71,7.04) | 4185.50(3401.97,5097.81) | 7.67(6.21,9.38) | 208.01(162.81,260.53) | 33.95(15.13,54.09) | 1.37(1.23,1.50) |
| Andean Latin America | 1727.02(1404.75,2095.95) | 9.49(7.67,11.66) | 7135.77(5341.74,8845.08) | 12.65(9.46,15.65) | 313.18(234.71,408.75) | 33.35(8.44,64.13) | 0.90(0.54,1.26) |
| Central Latin America | 4744.59(3863.14,5629.03) | 6.90(5.51,8.23) | 23821.59(18809.30,28673.41) | 9.88(7.84,11.86) | 402.08(350.37,458.73) | 43.17(27.72,59.78) | 1.67(1.22,2.13) |
| Tropical Latin America | 4638.14(3845.09,5400.69) | 6.01(4.94,7.06) | 15800.96(12758.01,18750.74) | 6.40(5.14,7.61) | 240.67(211.82,267.58) | 6.48(0.14,11.66) | 0.29(0.14,0.44) |
| North Africa and Middle East | 14094.90(10484.94,21743.04) | 10.95(7.99,16.97) | 47445.09(37870.73,56493.87) | 13.21(10.51,15.76) | 236.61(106.95,321.07) | 20.61(−25.97,50.97) | 0.84(0.64,1.04) |
| South Asia | 14238.31(10766.82,17766.28) | 2.88(2.20,3.63) | 43579.59(33262.73,55428.53) | 3.37(2.63,4.27) | 206.07(140.08,269.17) | 17.26(−7.82,40.44) | 0.37(0.21,0.53) |
| Central Sub-Saharan Africa | 2281.48(1699.79,2964.61) | 14.41(11.29,18.24) | 5891.33(4160.86,7849.89) | 14.95(10.66,19.79) | 158.22(93.01,243.33) | 3.69(−22.41,34.60) | 0.01(−0.10,0.12) |
| Eastern Sub-Saharan Africa | 5458.21(4175.79,6865.76) | 9.27(7.14,11.63) | 11039.34(8588.00,13749.15) | 8.86(6.94,10.92) | 102.25(74.40,132.01) | −4.46(−19.95,9.67) | −0.38(−0.52,−0.25) |
| Southern Sub-Saharan Africa | 1710.98(1426.84,2167.87) | 7.39(6.05,9.46) | 6871.12(5841.86,8207.31) | 14.64(12.49,17.23) | 301.59(214.92,359.89) | 98.14(51.82,128.02) | 1.84(1.36,2.33) |
| Western Sub-Saharan Africa | 9814.59(7905.01,11962.28) | 14.22(11.53,17.24) | 23574.39(19008.27,28530.30) | 15.83(13.00,19.13) | 140.20(103.37,180.20) | 11.30(−6.42,28.87) | 0.23(0.16,0.29) |
Abbreviations: EAPC estimated annual percentage change, SDI Sociodemographic Index, UI uncertainty interval
aEAPC is expressed as 95% confidence interval
bChange shows the percentage change
In 1990, the global number of HHD DALYs cases was 15,473,830 (95%UI, 12,310,725 − 17,311,822), which increased to 25,462,184 (95%UI, 21,493,311 − 28,047,521) in 2021, reflecting an overall increase of 64.55% (95%UI, 44.48-102.28%). The ASRs for HHD was 406.51 (95%UI, 328.94-452.24) per 100,000 person-years in 1990, which, however, decreased to 301.58 (95%UI, 255.06-332.06) in 2021, reflecting an overall decrease of 25.81% (95%UI, −34.45-10.07%). Moreover, the EAPC was − 0.90 (95%CI, −0.99-0.80) (Supplement Table 1; Fig. 1C). In 1990, the DALYs from hypertension-attributable CKD were 4,344,896 (95%UI, 3,676,494-5,110,004), which increased to 10,850,728 (95%UI, 9207080–12320650) in 2021, representing an overall increase of 149.74% (95%UI, 119.25-168.46%). In 1990, the ASRs for hypertension-attributable CKD were 107.77 (95%UI, 91.26-126.92) per 100,000 person-years. In 2021, ASRs increased to 128.41 (95%UI, 109.14-145.64), reflecting an overall increase of 19.15% (95%UI, 4.31–27.76%). Additionally, the EAPC was 0.63(95%CI, 0.58–0.67) (Supplement Table 2; Fig. 1D).
Time trends of hypertension-induced cardiorenal disease burden in regions with diverse SDI levels from 1990 to 2021
From 1990 to 2021, global reductions were observed in the ASDRs and ASRs of HHD. However, significant increases in ASDRs and ASRs were identified for Hypertension-attributable CKD (Table 1; Fig. 2). The ASDRs and ASRs of HHD initially decreased and then increased in high SDI from 1990 to 2021 (Fig. 2A and B), with all of the remaining SDI decreasing. The ASDRs and ASRs of hypertension-attributable CKD increased in high SDI, high middle SDI, middle SDI, and low-middle SDI, with the exception of low SDI regions (Fig. 2C and D).
Fig. 2.
Time of trend of death and DALYs rate of cardiorenal disease caused by hypertension in 1990–2021(per 1000.000 person years). A The ASDRs of HHD. B The ASRs of HHD (C) The ASDRs of CKD due to hypertension disease. D The ASRs of CKD due to hypertension disease. DALYs, disability adjusted life-years, CKD, Chronic Kidney Disease
Hypertension-induced cardiorenal disease and its relationship with SDI
Figure 3 depicts the long-term trends in the ASDRs and ASRs for hypertension-induced cardiorenal disease across SDI quintile categories by geographical area from 1990 to 2021, together with the projected rates derived exclusively from the SDI measurements of worldwide regions. In 2021, among the 21 GBD regions, Central Sub-Saharan Africa demonstrated the highest ASDR of HHD per 100,000 individuals, with values of 66.29 (95%UI, 42.22–92.93) (Fig. 3A; Table 1), and Southern Sub-Saharan Africa demonstrated the highest ASR of HHD per 100,000 individuals, with values of 889.11 (95%UI, 785.13-1034.16) (Fig. 3B, Table S1). Western Sub-Saharan Africa exhibited the highest ASDR of hypertension-attributable CKD at 15.83 per 100,000 individuals (95%UI, 13.00-19.13) (Fig. 3C; Table 2). Conversely, Southeast Asia recorded the highest ASR of hypertension-attributable CKD, at 339.64 per 100,000 individuals (95%UI, 282.05-395.38) (Fig. 3D, Table S2).
Fig. 3.
The trend in age-standardized death (A) and DALYs (B) rates of HHD and age-standardized death (C) and DALYs (D) rates of CKD due to hypertension disease in 21 GBD regions by SDI, 1990–2021. For each region, points from left to right depict estimates from each year from 1990 to 2021. The blue line represents the average expected relationship between SDI and burden estimates rates for cardiorenal disease caused by hypertension based on values from each geographical region over the 1990–2021 estimation period. DALYs, Disability-Adjusted Life-Years, SDI Socio-Demographic Index, CKD, Chronic Kidney Disease
At the national level, in 2021, the EAPC in ASDR of HHD exhibited no correlation with SDI (R = 0.1, P = 0.14). However, there was a significant correlation between the EAPC of ASDR and ASDR itself (R = 0.17, P = 0.013) (Fig. 4A). Similarly, the EAPC in ASR of HHD was no correlated with SDI (R = 0.084, P = 0.23), but exhibited a significant correlation with ASR itself (R = 0.16, P = 0.02) (Fig. 4B). The EAPC in ASDR of hypertension-attributable CKD demonstrated a significant positive correlation with SDI (R = 0.28, P = 5.2e-05). Meanwhile, a pronounced negative correlation between the EAPC of ASDR and ASDR itself (R = −0.17, P = 0.012) (Fig. 4C). The EAPC in ASDR of hypertension-attributable CKD exhibited a significant positive correlation with SDI (R = 0.18, P = 0.0083). However, there was no correlation between the EAPC of ASDR and ASDR itself (R = 0.12, P = 0.098)(Fig. 4D).
Fig. 4.
Correlation between EAPC and cardiorenal disease caused by hypertension and SDI in 2021. A EAPC of ASDR per 100,000 people and SDI for HHD, B EAPC of ASRs per 100,000 people and SDI for HHD, C EAPC of ASDR per 100,000 people and SDI for CKD due to hypertension disease, D EAPC of ASRs per 100,000 people and SDI for CKD due to hypertension disease. DALYs, disability adjusted life-years; CKD, chronic kidney disease; HHD, Hypertensive Heart Disease
Burden of hypertension risk factors for cardiorenal disease projections up to 2050
Based on predictions from the BAPC model, the ASDR for HHD is expected to present a significant downward trend. In contrast, the ASDR for hypertension-attributable CKD is projected to follow the opposite trend (Fig. 5A and B). Similarly, the ASR for HHD is anticipated to decline significantly, while hypertension-attributable CKD is expected to show an opposing trend (Supplementary Fig. 1A and B).
Fig. 5.
The change trends of the ASDRs from 1990 to 2050. A Hypertensive heart disease, B CKD due to hypertension disease. CKD, Chronic Kidney Disease
Discussion
In the present study, it was observed that between 1990 and 2021, the ASDRs and ASRs of HHD decreased by 21.99% and 25.81%, respectively, whereas those of hypertension-attributable CKD decreased by 29.21% and 19.15%, respectively. As projected by the BAPC model, the ASDR for HHD is expected to decline from 1990 to 2050. Conversely, hypertension-attributable CKD is predicted to exhibit the opposite trend over the same period.
Hypertension is a health concern affecting approximately 31% of the global adult population (roughly 1.4 billion). The incidence of the disease continues to climb, with individuals affected expected to exceed 1.6 billion by 2025. Hypertension is not only a major risk factor for cardiovascular disease(CVD) but also a major cause of the global increase in DALYs [19–21]. Hypertension is a major risk factor for HHD, and its importance cannot be ignored [22]. Other factors include age, race, excessive weight, physical activity, inactivity, high salt diet, smoking, alcohol consumption, and diabetes [23–25]. Obesity is a key risk factor involving leptin produced by adipocytes, leading to elevated blood pressure [26]. Obesity also increases sympathetic tone, interferes with the body’s regulation of renin and aldosterone levels, and promotes cardiac fibrosis and endothelial dysfunction, thus exacerbating hypertensive heart disease [26, 27]. Obesity promotes disease development through inflammation, tissue lipid accumulation, and dysregulation of intracellular pathways [28–30]. Through interacting neurohormonal pathways, obesity and hypertension jointly contribute to HHD and its complications, such as left ventricular hypertrophy and heart failure [31]. The pathogenesis of hypertensive nephropathy is primarily related to the hemodynamic changes and vascular remodeling caused by hypertension [32, 33]. Under conditions of high blood pressure, these hemodynamic variations lead to functional and structural alterations in renal arteries, resulting in increased vasoconstriction, elevated vascular resistance, and reduced renal blood flow [34–36]. Long-term hypertension can cause structural changes in renal arteries, such as the hypertrophy and proliferation of smooth muscle cells [37, 38]. In addition, it involves an imbalance in the synthesis and secretion of various active substances as well as the participation of vascular endothelial cells. For instance, elevated endothelin-1 levels are accompanied by reduced nitric oxide levels [39–41]. This imbalance induces thickening of the renal arterial wall, luminal narrowing, decreased vascular compliance, reduced renal plasma flow, and subsequent impairment of kidney function [42]. However, not all renal arteries undergo hypertrophic remodeling; other parts of the kidneys exhibit compensatory hyperperfusion, while the glomeruli supplied with blood transition from hypertrophy to focal segmental sclerosis [43]. The pathogenesis of hypertensive nephropathy is extremely complex, underscoring the urgent need for additional research to further elucidate this mechanism in the future.
Previously, Da et al. found that the ASDRs and DALYs for HHD were 12.3 and 209.4 per 100,000 in 2017, representing a 19.3% and 24.0% decline, respectively, from 1990 [44]. In another study, a sharp increase in HHD-related deaths was observed over the past 30 years, rising by 76.6% from 655,000 in 1990 to 1,157,000 in 2019. However, the global ASDRs for HHD exhibited a modest downward trend, decreasing to 15.16 per 100,000 individuals in 2019—a 21.5% decline from 1990 levels [45]. In the present study, it was observed that in 2021, global HHD deaths were 1,332,099, an increase of 86.59% compared to 713,935 in 1990, while the ASDRs decreased by 21.99%. This is consistent with previous research findings, which show that while the absolute number of HHD-related deaths has increased, the mortality rate has trended downward. This discrepancy may be attributed to continuous global population growth, which in turn leads to a decrease in the death ratio. This study also predicted a sustained downward trend in ASDRs for HHD from 1990 to 2050. While mortality rates in all SDI regions decreased compared to 1990, low SDI regions maintained high mortality rates, particularly in Sub-Saharan Africa. In this region, fewer than 40% of individuals with non-communicable disease(NCD) risk factors were aware of their hypertension, and control rates were below 20% and 10%, respectively [46]. Therefore, the implementation of primary prevention and health promotion strategies in response to hypertension and its triggered cardiovascular disease is particularly urgent for low-income countries.
A previous study observed that the global mortality count of hypertension-related CKD increased by 161.90% from 171,878 in 1990 to 450,147 in 2019. While the ASDRs showed a downward trend after 2015, the index has rebounded since 2018. During the period from 1990 to 2019, the EAPC of ASDR and ASMR were 0.49 and 0.64, respectively [3]. Herein, the number of hypertension-induced deaths was observed to increase significantly from 1990 to 2021, and the ASDRs and ASRs of hypertension-attributable CKD also gradually increased, consistent with previous research findings. This might indicate that the burden of hypertension-attributable CKD continued to increase in the two years. In the low SDI regions, both mortality and DALYs from hypertension-induced CKD remained at elevated levels. The ASDR from hypertension-related CKD was closely associated with regional development levels and healthcare accessibility, reflecting the effectiveness of hypertension management and control strategies. Furthermore, dialysis treatment significantly prolonged patient survival [47]. There was no significant difference in ASIRs in low and low-medium SDI regions. However, significantly higher ASDRs were observed in other regions [3].
The study was still subject to multiple limitations, such as potential bias in data collection and inherent limitations of the GBD database. GBD databases are constructed from diverse data sources, which may vary in their quality and thoroughness [48]. Moreover, cardiorenal disease is rarely caused by hypertension alone, and the influence of multiple risk factors should be considered. Additionally, as a repeated cross-sectional study, this research may have limitations in establishing causal relationships.
In conclusion, while the mortality rate of HHD is decreasing, hypertension-attributable CKD is on the rise. Together, these hypertension-related cardiovascular and kidney diseases remain a public health issue demanding urgent attention.
Supplementary Information
Acknowledgements
We thank the Second Affiliated Hospital of Chongqing Medical University for their support. Funding: This work is supported by Application of single-cell biomolecular analysis in the pathogenesis of lung cancer(cstc2022yejh-bgzxm0051).
Authors’ contributions
Lei Yang, YangLi, TingTingZeng, Yating Li, Hongmei Yue and DePeng Jiang wrote the main manuscript text. All authors reviewed the manuscript.
Funding
This work is supported by Application of single-cell biomolecular analysis in the pathogenesis of lung cancer(cstc2022yejh-bgzxm0051) and The mechanism by which METTL3-mediated m6A modification regulates pulmonary interstitial fibrosis through the miR-21-5P/TGF-β1/smad7 signaling pathway(ldyyyn2023-88).
Data availability
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not Applicable.
Competing interests
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.
Lei Yang and Yang Li share first authorship.
Contributor Information
Hongmei Yue, Email: yuehongmei18@sina.com.
DePeng Jiang, Email: gdp116@hospital.cqmu.edu.cn.
References
- 1.Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16(4):223–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Chow CK, Teo KK, Rangarajan S, et al. Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA. 2013;310(9):959–68. [DOI] [PubMed] [Google Scholar]
- 3.Ren Y, Wang Z, Wang Q. The trend of hypertension-related chronic kidney disease from 1990 to 2019 and its predictions over 25 years: an analysis of the global burden of disease study 2019. Int Urol Nephrol. 2024;56(2):707–18. [DOI] [PubMed] [Google Scholar]
- 4.Westaby JD, Miles C, Chis Ster I, et al. Characterisation of hypertensive heart disease: pathological insights from a sudden cardiac death cohort to inform clinical practice. J Hum Hypertens. 2022;36(3):246–53. [DOI] [PubMed] [Google Scholar]
- 5.Cuspidi C, Sala C, Negri F, Mancia G, Morganti A. Italian society of hypertension. Prevalence of left-ventricular hypertrophy in hypertension: an updated review of echocardiographic studies. J Hum Hypertens. 2012;26(6):343–9. [DOI] [PubMed] [Google Scholar]
- 6.Devereux RB, Koren MJ, de Simone G, Okin PM, Kligfield P. Methods for detection of left ventricular hypertrophy: application to hypertensive heart disease. Eur Heart J. 1993;14(Suppl D):8–15. [DOI] [PubMed] [Google Scholar]
- 7.Nwabuo CC, Vasan RS. Pathophysiology of hypertensive heart disease: beyond left ventricular hypertrophy. Curr Hypertens Rep. 2020;22(2):11. [DOI] [PubMed] [Google Scholar]
- 8.Díez J, Butler J. Growing heart failure burden of hypertensive heart disease: A call to action. Hypertension. 2023;80:13–21. [DOI] [PubMed] [Google Scholar]
- 9.Hassannejad R, Shafie D, Turk-Adawi KI, et al. Changes in the burden and underlying causes of heart failure in the Eastern mediterranean region, 1990–2019: an analysis of the global burden of disease study 2019. EClinicalMedicine. 2022;56:101788. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Habas E, Sr, Habas E, Khan FY, et al. Blood pressure and chronic kidney disease progression: an updated review. Cureus. 2022;14(4):e24244. Published 2022 Apr 18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ndumele CE, Rangaswami J, Chow SL, et al. Cardiovascular-kidney-metabolic health: a presidential advisory from the American Heart Association [published correction appears]. Circulation. 2024;149(13):e1023. [DOI] [PubMed] [Google Scholar]
- 12.Yu Z, Rebholz CM, Wong E, et al. Association between hypertension and kidney function decline: the atherosclerosis risk in communities (ARIC) study. Am J Kidney Dis. 2019;74(3):310–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.GBD2019MDC. Global, regional, and National burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the global burden of disease study 2019. Lancet Psychiatry. 2022;9(2):137–50. [DOI] [PMC free article] [PubMed]
- 14.GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the global burden of disease study 2021. Lancet. 2024;403(10440):2133–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bikbov BPCA, Levey AS, et al. Global, regional, and National burden of chronic kidney disease, 1990–2017: a systematic analysis for the global burden of disease study 2017. Lancet. 2020;395(10225):709–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.GBD 2021 Appendicitis Collaborator Group. Trends and levels of the global, regional, and National burden of appendicitis between 1990 and 2021: findings from the global burden of disease study 2021. Lancet Gastroenterol Hepatol. 2024;9(9):825–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Yang X, Chen H, Sang S, Chen H, Li L, Yang X. Burden of all cancers along with attributable risk factors in China from 1990 to 2019: comparison with japan, European union, and USA. Front Public Health. 2022;10:862165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bai Z, Wang H, Shen C, An J, Yang Z, Mo X. The global, regional, and National patterns of change in the burden of non-malignant upper Gastrointestinal diseases from 1990 to 2019 and the forecast for the next decade. Int J Surg. 2025;111(1):80-92. [DOI] [PMC free article] [PubMed]
- 19.Forouzanfar MH, Liu P, Roth GA, et al. Global burden of hypertension and systolic blood pressure of at least 110 to 115 mm Hg, 1990–2015 [published correction appears]. JAMA. 2017;317(6):648. [DOI] [PubMed] [Google Scholar]
- 20.GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016 [published correction appears]. Lancet. 2017;390(10104):1736. [DOI] [PMC free article] [PubMed]
- 21.Mills KT, Bundy JD, Kelly TN, et al. Global disparities of hypertension prevalence and control: a systematic analysis of Population-Based studies from 90 countries. Circulation. 2016;134(6):441–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Drazner MH. The progression of hypertensive heart disease. Circulation. 2011;123(3):327–34. [DOI] [PubMed] [Google Scholar]
- 23.Lawson CA, Zaccardi F, Squire I, Okhai H, Davies M, Huang W, et al. Risk factors for heart failure. Circ Heart Fail. 2020;13:e006472. [DOI] [PubMed] [Google Scholar]
- 24.Messerli FH, Rimoldi SF, Bangalore S. The transition from hypertension to heart failure: contemporary update [published correction appears in. JACC Heart Fail. 2017;5(12):948. [DOI] [PubMed] [Google Scholar]
- 25.Roumie CL, Hung AM, Russell GB, et al. Blood pressure control and the association with diabetes mellitus incidence: results from SPRINT randomized trial. Hypertension. 2020;75(2):331–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Saliba LJ, Maffett S. Hypertensive heart disease and obesity: A review. Heart Fail Clin. 2019;15(4):509–17. [DOI] [PubMed] [Google Scholar]
- 27.Murdolo G, Angeli F, Reboldi G, et al. Left ventricular hypertrophy and obesity: only a matter of fat? High Blood Press Cardiovasc Prev. 2015;22(1):29–41. [DOI] [PubMed] [Google Scholar]
- 28.Venteclef N, Guglielmi V, Balse E, Gaborit B, Cotillard A, Atassi F, et al. Human epicardial adipose tissue induces fibrosis of the atrial myocardium through the secretion of adipo-fibrokines. Eur Heart J. 2015;36:795–805. [DOI] [PubMed] [Google Scholar]
- 29.Szczepaniak LS, Dobbins RL, Metzger GJ, Sartoni-D’Ambrosia G, Arbique D, Vongpatanasin W, et al. Myocardial triglycerides and systolic function in humans: in vivo evaluation by localized proton spectroscopy and cardiac imaging. Magn Reson Med. 2003;49:417–23. [DOI] [PubMed] [Google Scholar]
- 30.Garcia JN, Wanjalla CN, Mashayekhi M, Hasty AH. Immune cell activation in obesity and cardiovascular disease. Curr Hypertens Rep. 2022;24(12):627–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.daSilva-deAbreu A, Alhafez BA, Lavie CJ, Milani RV, Ventura HO. Interactions of hypertension, obesity, left ventricular hypertrophy, and heart failure. Curr Opin Cardiol. 2021;36(4):453–60. [DOI] [PubMed] [Google Scholar]
- 32.Zhang C, Booz GW, Yu Q, He X, Wang S, Fan F. Conflicting roles of 20-HETE in hypertension and renal end organ damage. Eur J Pharmacol. 2018;833:190–200. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Mendoza-Torres E, Oyarzún A, Mondaca-Ruff D, et al. ACE2 and vasoactive peptides: novel players in cardiovascular/renal remodeling and hypertension. Ther Adv Cardiovasc Dis. 2015;9(4):217–37. [DOI] [PubMed] [Google Scholar]
- 34.Laurent S, Boutouyrie P. The structural factor of hypertension: large and small artery alterations. Circ Res. 2015;116(6):1007–21. [DOI] [PubMed] [Google Scholar]
- 35.Miyagawa K, Emoto N. Current state of endothelin receptor antagonism in hypertension and pulmonary hypertension. Ther Adv Cardiovasc Dis. 2014;8(5):202–16. [DOI] [PubMed] [Google Scholar]
- 36.Povlsen AL, Grimm D, Wehland M, Infanger M, Krüger M. The vasoactive Mas receptor in essential hypertension. J Clin Med. 2020;9(1):267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Tracy RE. Renal vasculature in essential hypertension: a review of some contrarian evidence. Contrib Nephrol. 2011;169:327–36. [DOI] [PubMed] [Google Scholar]
- 38.Brown IAM, Diederich L, Good ME, et al. Vascular smooth muscle remodeling in conductive and resistance arteries in hypertension. Arterioscler Thromb Vasc Biol. 2018;38(9):1969–85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Li Q, Youn JY, Cai H. Mechanisms and consequences of endothelial nitric oxide synthase dysfunction in hypertension. J Hypertens. 2015;33(6):1128–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Xu M, Lu YP, Hasan AA, Hocher B, Plasma. ET-1 concentrations are elevated in patients with Hypertension - Meta-Analysis of clinical studies. Kidney Blood Press Res. 2017;42(2):304–13. [DOI] [PubMed] [Google Scholar]
- 41.Versmissen J, Mirabito Colafella KM, Koolen SLW, Danser AHJ. Vascular Cardio-Oncology: vascular endothelial growth factor inhibitors and hypertension. Cardiovasc Res. 2019;115(5):904–14. [DOI] [PubMed] [Google Scholar]
- 42.Wu J, Agbor LN, Fang S, et al. Failure to vasodilate in response to salt loading blunts renal blood flow and causes salt-sensitive hypertension. Cardiovasc Res. 2021;117(1):308–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Hill GS. Hypertensive nephrosclerosis. Curr Opin Nephrol Hypertens. 2008;17(3):266–70. [DOI] [PubMed] [Google Scholar]
- 44.Dai H, Bragazzi NL, Younis A, et al. Worldwide trends in prevalence, mortality, and Disability-Adjusted life years for hypertensive heart disease from 1990 to 2017. Hypertension. 2021;77(4):1223–33. [DOI] [PubMed] [Google Scholar]
- 45.Lu WL, Yuan JH, Liu ZY, et al. Worldwide trends in mortality for hypertensive heart disease from 1990 to 2019 with projection to 2034: data from the global burden of disease 2019 study. Eur J Prev Cardiol. 2024;31(1):23–37. [DOI] [PubMed] [Google Scholar]
- 46.NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants [published correction appears]. Lancet. 2022;399(10324):520. [DOI] [PMC free article] [PubMed]
- 47.de Rooij ENM, Meuleman Y, de Fijter JW, et al. Quality of life before and after the start of Dialysis in older patients. Clin J Am Soc Nephrol. 2022;17(8):1159–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Liu J, Liu Y, Ma W, Tong Y, Zheng J. Temporal and Spatial trend analysis of all-cause depression burden based on global burden of disease (GBD) 2019 study. Sci Rep. 2024;14(1):12346. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.