Abstract
Sodium intake shows a positive correlation with blood pressure, resulting in an increased risk for cardiovascular diseases (CVD). Salt reduction is a key step toward the WHO's goal of 25% reduction in mortality from non‐communicable diseases (NCDs) by 2025. This study aims to assess the current condition and temporal changes of the global CVD burden due to high sodium intake (HSI). We extracted data from the Global Burden of Disease (GBD) study 2019. The numbers and age‐standardized rates of mortality and disability‐adjusted life‐years (DALYs), stratified by location, sex, and socio‐demographic Index (SDI), were used to assess the high sodium intake attributable CVD burden from 1990 to 2019. The relationship between the DALYs rates and related factors was evaluated by stepwise multiple linear regression analysis. Globally, in 2019, the deaths and DALYs of HSI‐related CVD were 1.72 million and 40.54 million, respectively, increasing by 41.08% and 33.06% from 1990. Meanwhile, the corresponding mortality and DALYs rates dropped by 35.1% and 35.2%, respectively. The high‐middle and middle SDI quintiles bore almost two‐thirds of CVD burden caused by HSI. And the leading cause of HSI attributable CVD burden was ischemic heart disease. Universal health coverage (UHC) was associated with the DALYs rates after adjustment. From 1990 to 2019, the global CVD burden attributable to HSI has declined with spatiotemporal and sexual heterogeneity. However, it remains a major public health challenge because of the increasing absolute numbers. Improving UHC serves as an effective strategy to reduce the HSI‐related CVD burden.
Keywords: cardiovascular diseases burden, deaths and DALYs, Global Burden of Disease 2019, high sodium intake
1. INTRODUCTION
Excess sodium consumption is the leading dietary risk factor for cardiovascular disease (CVD) worldwide. 1 , 2 Evidence derived from public health interventions describes a robust relationship between sodium intake and cardiovascular outcomes. 3 , 4 , 5 In the United Kingdom, salt consumption decreased from 9.5 g per day in 2003 to 8.1 g per day in 2011, with a 2.7 mmHg mean decrease in systolic blood pressure reported after adjustment, and stroke and ischemic heart disease mortality decreased by 36%. 4 Although the World Health Organization (WHO) recommends a daily salt intake of 5 g, average levels of sodium consumed far exceed the recommendation, with an estimation of 8.5 to 15 g per day. 6
In 2013, WHO recommended reducing population salt intake by 30% as a part of the goal to reduce non‐communicable diseases (NCDs) by 25% by 2025. 7 As a cost‐effective approach, salt reduction is one of the top priority actions to reduce premature mortality from CVD. 8 , 9 It is important for policy‐makers to know the current CVD burden caused by high sodium intake and take efforts to achieve this goal. In this study, we extracted data from Global Burden of Disease (GBD) 2019 and evaluated the present condition and the time trends of CVD burden attributable to high sodium intake from 1990 to 2019. The relationship between the CVD burden and several socioeconomic factors was further analyzed to provide relevant information for policy‐makers to improve disease prevention and control.
2. METHODS
2.1. Study data
We retrieved data from Global Burden of Disease (GBD) 2019 via the Global Health Data Exchange query tool (http://ghdx.healthdata.org/gbd‐results‐tool). CVD was defined as 11 major cause categories on the basis of International Classification of Disease (ICD) system: ischemic heart disease, stroke, hypertensive heart disease, peripheral artery disease, atrial fibrillation and atrial flutter, cardiomyopathy and myocarditis, endocarditis, rheumatic heart disease, non‐rheumatic valvular heart disease, aortic aneurysm, and other cardiovascular and circulatory disease. The last ‘other’ category included cardiopulmonary disease, disorders of the arteries, capillaries or veins, venous embolism and thrombosis, hypotension, post‐procedural disorders, and cardiovascular disorders in syphilis and other diseases. 10 We analyzed the absolute number, age‐standardized and age‐specific rates of deaths, and disability‐adjusted life‐years (DALYs) of CVD attributable to high sodium intake between 1990 and 2019 by age, sex, country, GBD region, and socio‐demographic index (SDI) quintile. Disability Adjusted Life Years (DALYs) are measuring lost health and are a standardized metric that allow for direct comparisons of disease burdens of different diseases across countries, between different populations, and over time. DALYs represent the sum of years of life lost prematurely (YLLs) and years lived with disability (YLDs).
High sodium intake assessment has been described previously. 11 , 12 Briefly, sodium intake was calculated by 24‐hour urinary sodium. Spatiotemporal Gaussian process regression and Disease Modeling Meta‐regression (DisMod‐MR) were used to estimate sodium intake in each age‐sex‐location‐year using all available data sources, such as population‐representative survey and surveillance data. The optimal level of sodium intake was ascertained according to the lowest stroke risk based on the meta‐analyses examining the association between sodium intake and disease outcomes, and then weighted by the global proportion of corresponding disease outcomes. The uncertainty of the optimal sodium intake level was evaluated by a uniform distribution in uncertainty estimation sampling. As a result, the optimal sodium intake level is 3 g (95% UI: 1 g, 5 g) per day, above which was defined as high sodium intake.
2.2. Selection of country‐level factors
Several different country‐level demographic and socioeconomic factors were selected as potential associated factors with CVD burden due to high sodium intake from the open databases based on previous published studies (Table S1). The SDI, extracted from the GHDx (http://ghdx.healthdata.org), is a composite index per capita income, educational attainment, and total fertility rate of all areas, identifying the socio‐demographic development status of countries or other geographic areas. SDI is calculated as the geometric mean on a scale of 0 to 1, by which countries are divided into five groups: low SDI, middle‐low SDI, middle SDI, middle‐high SDI, and high SDI. The universal health coverage (UHC) index is measured on a scale from 0 (worst) to 100 (best) based on the average coverage of essential health services including reproductive, maternal, newborn and child health, infectious diseases, non‐communicable diseases, and service capacity and access. 13 The human development index (HDI) was collected from the United Nations Development Programme (UNDP) database (http://hdr.undp.org/en/data), which is a summary measurement of average achievements in key dimensions of human development, combining four indicators: life expectancy at birth, expected years of schooling, and mean years of schooling, as well as Gross National Income per capita for standard of living. On a scale of 0 (worst) to 1 (best), countries were classified into four categories: low (<0.550), medium (0.550–0.699), high (0.700–0.799), and very high (0.800 or greater) HDI. The inequality‐adjusted human development index (IHDI), also collected from the UNDP (http://ghdx.healthdata.org), was used to further comprehend the distributions of the four indicators mentioned above. Current health expenditure, collected from the World Bank (https://databank.worldbank.org/home.aspx), is defined as spending on healthcare goods and services, expressed as a percentage of gross domestic product (GDP). It shows the importance of the health sector in the whole economy and indicates the societal priority which health is given measured in monetary terms. The old‐age dependency ratio (OADR), based on the current chronological‐age structure to measure the aging burden, is defined as the ratio of the number of elderly people at an age when they are generally economically inactive (i.e., aged 65 and over), compared to the number of people of working age (i.e., 15−64 years old). 14
2.3. Statistical analysis
Age standard rate (ASR) of deaths/DALYs, the corresponding estimated annual percentage change (EAPC) and its 95% CI were estimated to assess the disease burdens and its trends during a specific period. The DALYs rate was calculated as the number of cases per 100 000 population, and the age‐standardized DALYs rate was a weighted average of the age‐specific DALYs rates adjusted by the population size and age structure. The EAPC is calculated by a well‐established formula described previously, 15 , 16 and an EAPC of 0, positive or negative value indicates that rates are stable, in a downward or upward trend over time, respectively. And the absolute value of EAPC indicates the extent of rate changes over time.
Trends in disease burden reflect the changes in deaths and DALY rates, as well as changes in demography. We used a recently developed decomposition method to divide the net difference of the absolute numbers of high sodium intake related CVD burden over 30 years into three dimensions: population growth, population aging, and ASR of deaths/DALYs, using 1990 as the reference year. 17 , 18
A stepwise multiple linear regression analysis was conducted to explore the associations between the DALYs rate and country‐level socioeconomic factors. Variables at a level of p ≤ .05 were included in the multiple stepwise regression model for further analysis. The R program (Version 4.1.1 GUI 1.77; High Sierra build) and SPSS (Version 24.0.0.0) were used to perform statistics and map the figures. The p < .05 was considered to be statistically significant.
3. RESULTS
3.1. Current global burden and temporal changes
In 2019, globally, a total number of 1.72 million deaths and 40.54 million DALYs were caused by CVD due to dietary high sodium, increasing by 41.08% and 33.06% from 1990, respectively (Tables 1 and 2). The countries with the highest absolute burden were China (deaths: 788 587 and DALYs: 19 308 628). India, Indonesia, the Russian Federation, the United States of America, and Brazil were all on the list of the most burdened countries (Figure 1A,B). The ASR of deaths and DALYs were 21.51/105 and 490.68/105 respectively, dropping by 35.1% and 35.2% from 1990 (Tables 1 and 2). In general, countries in Central Europe, East Asia, and Central Asia had higher age‐standard deaths and DALYs rates. North Macedonia had the highest recorded deaths rate (98.9 per 100 000) and Indonesia had the highest DALYs rate (1016.7 per 100 000) (Figure 1C,D).
TABLE 1.
Death cases and age‐standardized mortality rate of CVD due to high dietary salt in 1990 and 2019, and its temporal trends from 1990 to 2019.
| 1990 | 2019 | 1990–2019 | |||
|---|---|---|---|---|---|
| Characteristics |
Death cases No.× 103 (95% UI) |
ASR per 100 000 No. (95% UI) |
Death cases No.× 103 (95% UI) |
ASR per 100 000 No. (95% UI) |
EAPC No. (95% UI) |
| Overall | 1215.85 (397.66–2505.38) | 33.16 (10.39–69.96) | 1715.38 (454.45–3713.24) | 21.51 (5.58–47.20) | −1.53 (−1.57, −1.49) |
| Sex | |||||
| Male | 726.72 (271.11–1389.67) | 44.26 (15.56–87.21) | 1089.09 (328.45–2173.32) | 29.98 (8.82–61.22) | −1.34 (−1.38, −1.30) |
| Female | 489.13 (122.37–1105.69) | 24.35 (5.96–55.91) | 626.29 (105.84–1535.05) | 14.28 (2.41–34.99) | −1.95 (−2.01, −1.89) |
| Social‐demographic index | |||||
| High | 175.39 (37.53–440.75) | 16.77 (3.60–42.13) | 156.03 (22.99–418.89) | 7.50 (1.14–19.75) | −3.08 (−3.25, −2.91) |
| High‐middle | 422.23 (151.25–824.94) | 43.08 (14.85–86.11) | 516.47 (159.26–1047.65) | 25.79 (7.84–52.52) | −1.96 (−2.07, −1.85) |
| Middle | 429.96 (165.75–780.77) | 33.16 (10.39–69.96) | 700.52 (215.25–1379.82) | 30.62 (8.85–62.04) | −1.34 (−1.42, −1.26) |
| Low‐middle | 141.99 (32.87–328.42) | 26.51 (5.43–64.03) | 265.23 (47.54–637.91) | 20.95 (3.47–51.84) | −0.76 (−0.80, −0.73) |
| Low | 45.89 (3.51–127.32) | 22.67 (1.75–63.34) | 76.51 (4.48–224.76) | 17.32 (1.02–50.93) | −0.92 (−0.95, −0.90) |
| Region | |||||
| Central Asia | 23.05 (4.80–48.57) | 55.15 (11.37–116.92) | 22.89 (2.07–59.56) | 41.23 (3.71–106.42) | −1.41 (−1.73, −1.09) |
| Central Europe | 135.59 (59.23–224.10) | 101.04 (43.33–167.08) | 112.08 (37.79–202.26) | 50.21 (17.00–90.61) | −2.79 (−2.92, −2.66) |
| Eastern Europe | 69.56 (6.51–197.21) | 26.55 (2.46–77.21) | 77.45 (7.16–223.93) | 22.55 (2.09–64.84) | −1.16 (−1.68, −0.64) |
| Australasia | 1.54 (0.14–6.03) | 6.79 (0.64–26.31) | 1.36 (0.14–5.41) | 2.56 (0.24–9.99) | −3.76 (−3.98, −3.54) |
| High‐income Asia Pacific | 55.89 (15.65–102.82) | 30.44 (8.15–56.97) | 40.47 (5.81–91.37) | 7.40 (1.12–16.45) | −5.32 (−5.59, −5.04) |
| High‐income North America | 33.27 (2.25–114.78) | 9.22 (0.62–31.68) | 46.54 (3.14–142.25) | 7.15 (0.49–21.47) | −1.06 (−1.20, −0.91) |
| Southern Latin America | 8.52 (0.51–22.60) | 20.07 (1.20–53.68) | 8.86 (0.46–24.26) | 10.41 (0.54–28.47) | −2.36 (−2.54, −2.18) |
| Western Europe | 64.95 (4.89–208.67) | 11.17 (0.85–35.69) | 51.56 (3.90–168.69) | 4.91 (0.37–15.67) | −3.08 (−3.30, −2.85) |
| Andean Latin America | 2.56 (0.12–6.89) | 13.97 (0.63–38.16) | 4.22 (0.23–11.73) | 7.86 (0.42–21.87) | −1.93 (−2.18, −1.69) |
| Caribbean | 3.58 (0.17–11.38) | 15.12 (0.72–47.99) | 5.35 (0.27–17.65) | 10.30 (0.52–33.98) | −1.39 (−1.57, −1.20) |
| Central Latin America | 13.33 (1.69–32.53) | 18.29 (2.26–45.17) | 28.02 (3.40–69.44) | 12.37 (1.49–30.76) | −1.57 (−1.71, −1.44) |
| Tropical Latin America | 20.07 (1.18–53.88) | 25.12 (1.51–66.34) | 27.31 (1.84–72.19) | 11.64 (0.78–30.73) | −2.76 (−2.85, −2.67) |
| North Africa and Middle East | 13.71 (2.23–54.88) | 8.75 (1.64–35.22) | 24.79 (4.21–97.54) | 6.31 (1.20–24.80) | −1.25 (−1.30, −1.19) |
| South Asia | 88.24 (6.61–249.08) | 17.60 (1.22–51.52) | 202.25 (16.18–552.70) | 15.32 (1.17–42.74) | −0.35 (−0.46, −0.24) |
| East Asia | 525.35 (237.68–877.26) | 67.64 (27.52–118.86) | 807.84 (311.72–1420.13) | 41.85 (15.12–75.90) | −1.47 (−1.57, −1.37) |
| Oceania | 0.81 (0.12–1.95) | 35.70 (4.97–83.90) | 1.96 (0.19–4.76) | 34.74 (3.33–83.64) | −0.22 (−0.32, −0.13) |
| Southeast Asia | 113.91 (33.91–206.56) | 49.44 (13.40–92.87) | 188.23 (32.98–391.08) | 34.06 (5.61–72.19) | −1.32 (−1.40, −1.24) |
| Central Sub‐Saharan Africa | 2.08 (0.15–8.94) | 11.60 (0.86–49.39) | 4.29 (0.28–18.48) | 10.32 (0.70–42.43) | −0.51 (−0.59, −0.43) |
| Eastern Sub‐Saharan Africa | 26.68 (2.18–64.42) | 42.10 (3.44–101.43) | 34.87 (1.76–94.11) | 27.30 (1.38–71.54) | −1.67 (−1.75, −1.60) |
| Southern Sub‐Saharan Africa | 8.52 (0.51–22.60) | 10.84 (0.57–39.88) | 4.36 (0.28–17.43) | 8.76 (0.60–35.72) | −0.74 (−1.11, −0.37) |
| Western Sub‐Saharan Africa | 10.32 (0.46–38.94) | 13.72 (0.64–51.87) | 20.56 (0.83–74.24) | 13.09 (0.55–47.41) | −0.06 (−0.14, −0.01) |
Abbreviations: ASR, age‐standardized rate; CVD, cardiovascular diseases; EAPC, estimated annual percentage change.
TABLE 2.
The DALYs cases and age‐standardized DALYs rate of CVD due to high dietary salt in 1990 and 2019, and its temporal trends from 1990 to 2019.
| 1990 | 2019 | 1990–2019 | |||
|---|---|---|---|---|---|
| Characteristics |
DALYs cases No.× 103 (95% UI) |
ASR per 100 000 No. (95% UI) |
DALYs cases No.× 103 (95% UI) |
ASR per 100 000 No. (95% UI) |
EAPC No. (95% UI) |
| Overall | 30468.48 (19829.44–49.419.30) | 756.66 (262.03–1495.60) | 40540.67 (12262.91–83022.36) | 490.68 (92.67–1148.66) | −1.54 (−1.57, −1.50) |
| Sex | |||||
| Male | 19124.77 (7417.64–35451.26) | 1009.89 (382.47–1905.66) | 27088.93 (9056.93–51778.77) | 690.09 (224.08–1329.28) | −1.31 (−1.34, −1.27) |
| Female | 11343.71 (3290.80–24070.09) | 533.77 (153.0–1136.30) | 13451.74 (2724.65–31555.47) | 308.27 (62.52–723.24) | −2.03 (−2.09, −1.96) |
| Social‐demographic index | |||||
| High | 3606.97 (873.63–8624.37) | 350.63 (85.36–833.77) | 2925.02 (461.66–7537.70) | 162.70 (26.29–414.07) | −2.92 (−3.07, −2.76) |
| High‐middle | 10119.36 (3949.85–18648.50) | 945.77 (362.03–1773.29) | 11519.05 (4157.31–21797.37) | 568.61 (203.31–1075.70) | −1.96 (−2.10, −1.83) |
| Middle | 11536.41(4836.85–20090.11) | 1082.13 (432.55–1935.13) | 17227.01 (6108.45–32177.54) | 681.05 (231.08–1298.72) | −1.48 (−1.54, −1.41) |
| Low‐middle | 3957.71 (1005.02–8848.81) | 624.34 (150.02–833.77) | 6891.85 (1341.68–16079.97) | 488.23 (92.67–1148.66) | −0.78 (−0.83, −0.74) |
| Low | 1238.62 (89.30–3513.42) | 507.00 (37.89–1417.64) | 1963.47 (116.35–5810.82) | 372.33 (21.72–1082.58) | −1.06 (−1.09, −1.03) |
| Region | |||||
| Central Asia | 497.37 (103.47–1047.14) | 1078.88 (225.74–2276.03) | 506.69 (46.23–1318.76) | 728.50 (65.75–1908.91) | −1.84 (−2.15, −1.52) |
| Central Europe | 2735.11 (1217.13–4439.14) | 1900.79 (838.68–3105.59) | 1870.17 (622.43–3338.16) | 873.98 (294.13–1556.75) | −3.10 (−3.25, −2.95) |
| Eastern Europe | 1657.15 (167.95–4383.55) | 595.47 (61.67–1593.87) | 1727.87 (175.18–4582.10) | 518.85 (54.23–1356.24) | −1.16 (−1.76, −0.55) |
| Australasia | 33.76 (2.71–122.19) | 147.44 (11.70–527.20) | 25.33 (2.12–91.82) | 55.06 (4.23–191.34) | −3.69 (−3.93, −3.45) |
| High‐income Asia Pacific | 1212.83 (381.88–2160.09) | 609.96 (188.04–1095.62) | 688.02 (106.64–1521.49) | 160.05 (25.57–348.58) | −5.10 (−5.35, −4.85) |
| High‐income North America | 661.89 (42.37–2216.22) | 191.95 (12.13–636.80) | 996.20 (68.06–2845.50) | 170.42 (11.81–477.40) | −0.43 (−0.55, −0.31) |
| Southern Latin America | 180.74 (10.98–480.98) | 397.42 (24.06–1052.55) | 168.44 (9.08–454.60) | 203.76 (11.18–550.29) | −2.44 (−2.62, −2.26) |
| Western Europe | 1240.87 (95.46–3805.54) | 220.46 (17.34–666.42) | 839.80 (63.95–2597.33) | 96.41 (7.49–285.84) | −3.07 (−3.30, −2.83) |
| Andean Latin America | 58.49 (2.67–159.38) | 282.06 (31.18–1422.74) | 86.34 (4.56–238.63) | 153.80 (8.09–424.63) | −2.08 (−2.32, −1.84) |
| Caribbean | 73.18 (3.69–240.39) | 285.36 (49.60–889.61) | 108.04 (5.44–363.56) | 208.84 (10.54–701.69) | −1.11 (−1.31, −0.91) |
| Central Latin America | 310.69 (41.80–740.82) | 369.36 (49.60–889.61) | 579.74 (73.32–1404.15) | 245.70 (31.35–595.64) | −1.63 (−1.76, −1.49) |
| Tropical Latin America | 502.80 (28.35–1308.77) | 538.34 (31.18–1422.74) | 614.97 (39.00–1626.71) | 251.86 (15.86–668.29) | −2.75 (−2.83, −2.67) |
| North Africa and Middle East | 367.79 (52.57–1443.51) | 202.01 (31.66–801.82) | 646.44 (93.14–2493.20) | 141.64 (22.19–551.61) | −1.35 (−1.41, −1.30) |
| South Asia | 2546.63 (212.66–7039.51) | 414.21 (31.84–1175.98) | 5575.39 (504.97–14646.68) | 375.41 (32.46–1002.81) | −0.13 (−0.26, −0.01) |
| East Asia | 14201.31 (7052.20–22596.70) | 1563.30 (740.98–2554.39) | 19749.75 (9008.83–32572.35) | 942.70 (416.84–1583.23) | −1.62 (−1.69, −1.54) |
| Oceania | 19.58 (2.67–50.04) | 717.82 (99.75–1744.89) | 49.52 (4.56–127.62) | 738.30 (71.45–1796.69) | −0.04 (−0.18, 0.11) |
| Southeast Asia | 3058.76 (992.29–5451.69) | 1160.99 (360.81–2075.70) | 4731.68 (866.36–9601.36) | 763.30 (71.45–1796.69) | −1.51 (−1.60, −1.42) |
| Central Sub‐Saharan Africa | 57.81 (4.11–253.17) | 248.05 (18.42–1051.17) | 113.51 (7.21–494.25) | 209.45 (13.91–894.11) | −0.68 (−0.76, −0.61) |
| Eastern Sub‐Saharan Africa | 700.97 (54.66–1731.36) | 921.77 (74.76–2252.13) | 818.93 (41.54–2290.60) | 533.67 (26.96–1446.81) | −2.11 (−2.22, −2.01) |
| Southern Sub‐Saharan Africa | 85.03 (3.50–296.94) | 278.80 (12.22–982.83) | 113.47 (6.41–444.02) | 193.04 (11.65–762.04) | −1.33 (−1.69, −0.96) |
| Western Sub‐Saharan Africa | 265.70 (11.17–1005.33) | 297.80 (12.22–982.83) | 530.38 (20.69–1906.58) | 275.48 (11.03–984.03) | −0.18 (−0.25, −0.11) |
Abbreviations: ASR, age‐standardized rate; CVD, cardiovascular diseases; DALYs, disability‐adjusted life years; EAPC, estimated annual percentage change.
FIGURE 1.
The global high sodium intake‐related CVD burden in 2019, by 204 countries and territories. The absolute numbers (A and B) and rates (per 100 000 persons) (C and D) of deaths and DALYs in 204 countries and territories. CVD, cardiovascular vascular diseases; DALYs, disability‐adjusted life years.
We used the decomposition method to analyze the contributions of population growth, population aging, and ASR to the net changes in the high dietary sodium‐related CVD burden, with 1990 as the reference year. From 1990 to 2019, the global increase in absolute deaths and DALYs numbers was mainly driven by population growth (deaths: 169.8%; DALYs: 204.9%) and population aging (deaths: 66.2%; DALYs: 56.6%), while the age‐specific rates contributed negatively (deaths: –136.0%; DALYs: –161.5%). (Figure S1A)
In terms of the temporal changes, high sodium intake attributable CVD deaths and DALYs decreased annually across the world over the past decades, except for several Asian and African countries, including Pakistan, Nepal, Bangladesh, Ghana, Bhutan, and so on (Figure 2A,B). Countries in high‐income Asia Pacific exhibited the largest descent with a mortality EAPC of –5.32 (–5.59, –5.04, Table 1) and DALYs EAPC of –5.10 (–5.35, –4.85, Table 2). In contrast, males in South Asia (0.21, 95% CI 0.04–0.39) and high‐income North America (0.12, 95% CI –0.07–0.31) experienced a slight annual increase in DALYs (Figure 2C).
FIGURE 2.
The annual variation of high sodium intake‐related CVD burden from 1990 to 2019, by location. EAPCs of death/DALYs rates (per 100 000 persons) in 204 countries/territories (A and B), and in 5 SDI quintiles and 21 GBD World Regions, by sex (C). CVD, cardiovascular vascular diseases; DALYs, disability‐adjusted life years; EAPC, estimated annual percentage changes; GBD, Global Burden of Disease; SDI, social‐demographic index.
3.2. Disparities across SDI quintiles
All SDI quintiles exhibited an upward trend in the absolute CVD burden due to high sodium intake over the past three decades, except for the high‐SDI quintile (Figure 3A). Meanwhile, the ASR of deaths and DALYs showed a downward trend in 5 SDI quintiles (Figure 3B, Figure S2B). The high SDI quintile leaded the largest reduction in CVD burden due to high sodium intake, with an EAPC of −3.08 (−3.25, −2.91; Table 1) in deaths and an EAPC of −2.92 (−3.07, −2.76; Table 2) in DALYs. Although experiencing remarkable declines in both deaths and DALY rates, high‐middle and middle SDI regions bore almost two‐thirds of the absolute CVD burden among all SDI quintiles. The low SDI quintile had the least absolute burden of CVD caused by high sodium intake (Figure 3A).
FIGURE 3.
The changing trends of high sodium intake‐related CVD burden during 1990 to 2019, by sex and SDI quintiles. The changing trends of deaths/DALYs numbers (A) and rates (B) in 5 SDI quintiles, by sex. CVD, cardiovascular vascular diseases; DALYs, disability‐adjusted life years; EAPC, estimated annual percentage changes; GBD, Global Burden of Disease; SDI, social‐demographic index.
The estimated contributions of three factors—population growth, population aging, and ASR—varied significantly across the SDI quintiles. Population aging occurred in all SDI quintiles except for the low‐SDI quintile. The high SDI quintile experienced the most noticeable population aging, particularly in death burden (315.59%). Population growth had the most salient impact on the DALYs burden in the high‐middle SDI quintile (363.78%) (Figure S1B).
3.3. Heterogeneities across sex and ages
Significant sex differences were observed in the CVD burden due to high sodium intake globally and regionally. Males exceeded females in both absolute numbers and age‐standardized rates (Tables 1 and 2, Figure 3A,B). A massive sex disparity was observed in Central Europe, high‐income Asia Pacific, and East Asia, where deaths and DALYs rates of men almost three times those of women (Figure 4A). As for age groups, the deaths and DALYs numbers of CVD due to high sodium intake increased with age and reached a peak at 65−69 years old (Figure 4B). It is noteworthy that males aged 30−34 had the least decrease in both deaths (−19.52%) and DALYs (−19.01%) rates among all age groups over the past 30 years (Table S3 and S4).
FIGURE 4.
The sex and age distribution of high sodium intake‐related CVD burden in 1990 and 2019. (A) Deaths/DALYs rates (per 100 000 persons) in 21 GBD world regions, by sex, in 1990 and 2019. (B) Global numbers of deaths/DALYs in different age stratifications, by sex, in 2019. (C and D) CVD, cardiovascular vascular diseases; DALYs, disability‐adjusted life years; EAPC, estimated annual percentage changes; GBD, Global Burden of Disease; SDI, social‐demographic index.
3.4. Cause‐specific proportions and relative distributions
Globally in 2019, ischemic heart disease (IHD, death: 777 204.3) was the largest cause of CVD deaths due to high sodium intake, followed by stroke (death: 700 983.6) and hypertensive heart disease (HHD, death: 170 320.4). The DALYs outcomes exhibited roughly similar trends (Figure 5, Table S2, and Figure S4). And the largest proportions of IHD, stroke, and HHD were observed in Central Europe, East Asia, and Eastern Sub‐Saharan Africa, respectively (Figure 5). Rheumatic heart disease had the rapidest reduction in annual mortality rate of with an EAPC of −3.99 (−4.06, −3.91, Table S2). The proportions of IHD, atrial fibrillation and flutter pumped out in the high SDI region, as did the proportion of HHD in the low SDI region. And the proportion of stroke ranked first in the middle SDI region (Figure S2). Notably, for hypertensive heart disease in the high SDI region and ischemic heart disease in the low‐middle SDI region, males had an annual increase in both mortality rate and DALYs rate (Figure S3).
FIGURE 5.
The condition of high sodium intake‐related CVD burden in 2019, by causes and locations.
3.5. Relationship of DALYs rates and socioeconomic factors
We further analyzed the relationship between DALYs rates of CVD attributable to high sodium intake and several socioeconomic factors in 204 countries and territories, including SDI, UHC, HDI, IHDI, current health expenditure (% of GDP), and OADR (Table 3). In the univariate linear regression, SDI, UHC, HDI and the two components of IHDI, life expectancy at birth and gross national income per capita, had significant negative associations with the DALYs rate. For the stepwise multiple regression analysis, UHC and life expectancy at birth were related to the DALYs rates after adjustment.
TABLE 3.
Linear regression analysis of the relationship between the DALYs rates of high sodium intake‐related CVDs burden and the socioeconomic variables.
| R square | p‐value | β(95% CI) | |
|---|---|---|---|
| Univariate analysis | |||
| SDI | 0.053 | .001 | −429.993 (−682.301, −177.685) |
| UHC | 0.161 | <.001 | −7.720 (−10.197, −5.244) |
| HDI | 0.045 | .003 | −451.582 (−751.831, −151.333) |
| IHDI | 0.001 | .771 | −41.236 (−238.690, 321.162) |
| Mean years of schooling | 0.008 | .211 | −9.326 (−23.973,5.320) |
| Expected years of schooling | 0.011 | .128 | −4.371 (−10.013, 1.271) |
| Life expectancy at birth | 0.042 | .005 | −8.836 (−15.033, −2.693) |
| Gross national income per capita | 0.089 | <.001 | −.005 (−0.007, −0.003) |
| Current health expenditure (% of GDP) | 0.003 | .443 | −6.132 (−21.877,9.614) |
| OADR | 0.127 | .076 | −3.974 (−8.368, 0.420) |
| Multivariate analysis [only variates with significant association (p < .05) are shown] | |||
| Model 1 a | 0.190 | <.001 | |
| UHC | −13.686 (−18.263, −9.109) | ||
| Life expectancy at birth | 17.764 (7.356, 28.172) |
Abbreviations: GDP, gross domestic product; HDI, human development index; IHDI, inequality‐adjusted HDI; OADR, the old‐age dependency ratio; SDI, socio‐demographic index; UHC: universal health coverage.
Model 1: adjusted for UHC, HDI, life expectancy at birth, and gross national income per capita.
4. DISCUSSION
In 2019, a total number of 1.72 million deaths and 40.54 million DALYs were caused by CVD due to dietary high sodium, respectively, increasing by 41.08% and 33.06% from 1990, which was mainly driven by population growth and population aging. The corresponding ASR of deaths and DALYs dropped by 35.1% and 35.2%, respectively, from 1990. The global CVD burden due to high sodium intake showed substantial disparities in sex, ages, WHO regions, and SDI quintiles. The leading diseases caused by high dietary sodium were ischemic heart disease, stroke, and hypertensive heart disease. Expanding universal health coverage was highlighted to prevent and treat high dietary sodium related CVD burden worldwide.
A general decline of high dietary sodium related CVD burden was observed over the past decades, with the most pronounced decreases in high‐income Asia‐Pacific, Southeast Asia, Western, and Central Europe. This indicates that global sodium reduction measures may have had a relatively good effect. In 2019, a total of 96 countries has been reported to have national salt reduction initiatives, with an additional 16 countries in their planning stages. 2 The main implementation strategies focus on interventions in settings, food reformulation, consumer education, front of‐pack labeling, and salt taxation. 19 Continuous monitoring and reporting on progress of each intervention approach aids in determining whether these policies are effective, identifying gaps, and planning steps to achieve the targeted 30% reduction in salt intake.
Despite significant reductions in the ASR of deaths and DALYs, high sodium‐related CVD burden remains a major public health challenge. Our results showed exposure to high sodium contributed to 1.72 million deaths and 40.54 million DALYs globally in 2019. The two major countries, India and China, where added salt is the primary source of dietary salt, 20 , 21 have the greatest CVD burden due to high sodium intake. It's difficult to reduce salt intake in these countries due to the difficulty of changing dietary patterns. Evidence has shown salt substitutes lower blood pressure and major adverse cardiovascular events efficiently. 22 The main challenge in both countries now is how to make the necessary adaptations to ensure the strategy of salt substitutes effectively reduces salt intake, like overcoming the extra costs of salt substitutes, which are nearly double the price of standard salt. 23 The Chinese central government has included salt reduction as one of the key components of China's health development agenda and set up the action group “Action on Salt China (ASC)” with the aim of achieving WHO's recommended salt intake in China. 21 Notably, several Asian and African countries, including Pakistan, Nepal, Bangladesh, Ghana, Bhutan, faced an upward trend of high sodium intake‐related CVD burden, which deserves more attention and support from United Nations (UN).
Numerous studies have shown that socioeconomic status has a measurable and significant effect on cardiovascular health. 24 , 25 Residents in low‐income areas were more likely to have insufficient awareness of the risk of excessive salt consumption and to have inadequate standards of care. Socioeconomic status also affects salt‐induction strategies, which are more feasible in high and high‐middle income countries. In 2019, a number of 52 high‐income countries had national salt reduction initiatives in place, with interventions in food reformulation and front‐of‐pack labeling being typical strategic approaches. Meanwhile, 30 upper‐middle and 13 lower‐middle income countries had national salt reduction initiatives, with interventions primarily focused on food reformulation and consumer education. 26 Although the high salt diet‐related CVD burden is the lowest in low SDI quintile, additional support is still warranted to develop policies and interventions to reduce excess salt intake in the low SDI regions, particularly those experiencing a nutrition transition towards greater intake of processed and packaged foods. 27
The CVD burden attributable to high sodium intake was heterogeneous across SDI regions in terms of demographic factors. The effect of population aging was noteworthy in the high SDI quintile but did not occur in the low SDI quintile. Such results likely reflect differences in demographic changes across SDI quintiles. Between 1990 and 2017, the proportion of people aged 65 years and older rose from 12.1% to 17.5% in high‐income countries but dropped from 3.2% to 3.1% in low‐income countries. 17 While population growth contributed significantly to the CVD burden in high‐middle and middle SDI regions, population aging is predicted to be a major issue in these regions. National governments should weigh these variations when developing and implementing action plans in particular regions and countries.
Our findings suggested that women were relatively protected from high sodium intake related CVD, compared with men. This result was consistent with the Dietary Approaches to Stop Hypertension (DASH) diet study, in which the DASH diet with limited dietary sodium lowered more systolic blood pressure in women (10.5 mmHg) than in men (6.8 mmHg). 28 Sex hormones as well as sex chromosomes undoubtedly play a role in the observed sex differences in cardiovascular disease. 29 In our analysis, the gap between males and females gradually decreased after 65−69 years old, the period after menopause, demonstrating this well. Additionally, differences in diet patterns and behaviors contribute to sexual dimorphic patterns. Females were found to have better diet quality and cognitive restraint than males. 30 This clinically meaningful sex difference necessitates rinsing awareness to implement sex‐specific dietary salt control and to improve the prevention and treatment of its concomitant CVD in males.
The high dietary salt‐related CVD burden is highly preventable, and timely intervention significantly improves outcomes. According to Song's prediction model, a 4.3‐year delay in finalizing sodium targets in the United States may cost over 250 000 lives by 2031. 31 It is vital for policy‐makers to take actions to raise awareness of salt reduction among the public as well as to maximize industry compliance with the sodium‐reduction targets as soon as possible. 32 Our results indicated that UHC had a significant association with the CVD burden due to high salt intake among socioeconomic factors. However, at present, few countries specifically mention CVD care in their health benefits packages, and there is still limited information to guide policy around CVD and UHC. 33 Previous studies provided some cost‐effective clinical services, which may serve as a starting point to improve the inclusion of CVD into UHC. 34 , 35 A call for future work from policy‐makers to raise the profile of CVD on the UHC agenda to reach the target of a 25% reduction in NCDs by 2025.
4.1. Study limitations
This study has several limitations. First, the work reported here builds on the database of GBD 2019, which included only 92 sources from 53 countries of the high sodium intake exposure data and 21 sources from 6 countries of the high sodium intake attributable burden data. 36 Therefore, most countries' data was computed by the GBD method, so the reliability may be insufficient. Second, the effect of salt on cardiovascular outcomes was assessed indirectly, relying on the relationship between urine sodium, systolic blood pressure fluctuations, and cardiovascular outcomes, which inevitably raised data uncertainty. Third, the study is subject to all the general limitations described by the GBD collaboration. 37 For example, the sparse data in the low‐SDI quintile may affect the accuracy of the estimates.
5. CONCLUSIONS
In conclusion, our study provides a comprehensive assessment of the CVD burden attributable to high sodium intake from 1990 to 2019. Despite a one‐third reduction in deaths and DALYs rates since 1990, high dietary sodium associated with CVD burden remains a major public health concern. High‐middle and middle SDI quintiles endure the greatest CVD burden due to high sodium, especially in males. Setting CVD service as a top priority in UHC is an effective strategy for policymakers to lower the high sodium‐related CVD burden.
AUTHOR CONTRIBUTIONS
Keke Wang performed the data analysis and wrote the manuscript. Jingchao Lu and Jianjun Mu planned the study and revised this paper. Yaqiong Jin and Mengxiao Wang prepared and analyzed the data. Jing Liu and Xiang Bu helped with the software and data visualization. All authors provided critical comments on the manuscript. All authors read and approved the final manuscript.
CONFLICT OF INTEREST STATEMENT
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Supporting information
Supporting Information
ACKNOWLEDGMENTS
This work was supported by the Program for Excellent Talents in Clinical Medicine of Hebei Province (grant number No. 303‐16‐20‐09) and Key Project of Medical Science Research in Hebei Province (grant number No. 20210155).
Wang K, Jin Y, Wang M, et al. Global cardiovascular diseases burden attributable to high sodium intake from 1990 to 2019. J Clin Hypertens. 2023;25:868–879. 10.1111/jch.14717
DATA AVAILABILITY STATEMENT
The datasets generated and/or analyzed during the current study are available in the GBD database (http://ghdx.healthdata.org/gbd‐results‐tool).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information
Data Availability Statement
The datasets generated and/or analyzed during the current study are available in the GBD database (http://ghdx.healthdata.org/gbd‐results‐tool).