Abstract
Background
Hypertension remains a major public health challenge in China, particularly in socioeconomically transitioning regions. This study aims to evaluate changes in hypertension prevalence, awareness, treatment, and control rates between 2019 and 2024 in a Tibetan-predominant area of Sichuan Province.
Methods
Two cross-sectional surveys were conducted in 2019 (n = 1,880) and 2024 (n = 1,870). Inverse probability of treatment weighting (IPTW) and age-standardization were applied to enhance comparability. Subgroup analyses were performed to examine disparities across gender, residence, age, and education groups.
Results
Age-standardized hypertension prevalence decreased significantly from 22.86% to 15.53%. Awareness, treatment, and control rates all improved markedly, from 24.63% to 53.43%, 16.08% to 43.93%, and 3.98% to 17.37%, respectively. Health inequities narrowed substantially between urban and rural areas and between genders. However, absolute control rates remained suboptimal (18.14% in 2024). Rising obesity prevalence (5.11% to 11.44%) and persistent gaps in treatment quality were observed.
Conclusions
Substantial progress in hypertension management and health equity was observed in the area between 2019 and 2024. However, persistently low control rates and rising obesity highlight the need to enhance treatment quality and implement integrated cardiovascular risk reduction strategies. These findings provide important insights for chronic disease management in similar transitioning regions.
Keywords: Hypertension, cross-sectional survey, inverse probability weighting, primary health care
KEY MESSAGES
Significant advances in hypertension care equity: Between 2019 and 2024, Aba Prefecture showed marked increases in awareness and treatment rates, with pronounced narrowing of urban–rural and gender gaps.
Persistently low control and the trend of youthfulness crisis: Despite improved access, age-standardized control rate remained <20%, while rising obesity and therapeutic inertia in primary care shifted the hypertension burden toward younger, working-age adults.
Region–specific barriers: The study identifies a high prevalence of “aware but untreated” (particularly among women) and “treated but uncontrolled” patients, pointing to the interplay between culturally shaped health beliefs and systemic weaknesses in primary care quality (e.g., therapeutic inertia) as key obstacles.
Transferable policy model: The study provides real-world evidence that the National Essential Public Health Services Program can be effectively implemented in resource-limited, multi-ethnic highland settings, offering an evidence-based template for precise hypertension interventions and policy design in comparable regions.
GRAPHICAL ABSTRACT
Introduction
Hypertension is associated with 12.8% of all-cause mortality worldwide [1]. Among the more than 1.3 billion individuals affected globally, 82% reside in low- and middle-income countries. As of 2015, China alone accounted for an estimated 244.5 million adults with hypertension [2,3]. Hypertension represents not only a pervasive global health challenge but also a critical public health issue demanding urgent intervention [4,5]. Furthermore, hypertension is a major modifiable risk factor for cardiovascular disease (CVD), stroke, and chronic kidney disease (CKD) [6,7]. According to the China Cardiovascular Health and Disease Report (2022), CVD is the leading cause of death among both urban and rural residents in China. The economic burden is substantial, with total costs associated with CVD hospitalizations reaching 212.11 billion yuan (approximately 29.3 billion USD), placing significant strain on the healthcare system [8]. The prevalence of hypertension in China continues to rise annually, with an increasing trend observed among younger demographics. As a leading preventable contributor to CVD-related disability worldwide, effective management of hypertension has the potential to substantially reduce the global disease burden [9]. Nonetheless, rates of public awareness, treatment, and control of hypertension remain unacceptably low [10].
The Aba region is uniquely located within the transitional zone between the Tibetan Plateau and the Sichuan Basin in the southwest of China. With an average elevation ranging from 2,500 to 3,000 meters, it constitutes a typical high-altitude mountainous area. This region is ethnically diverse, comprising Tibetan, Qiang, and Han populations, and represents the second largest Tibetan community in China, characterized by significant cultural and ethnic diversity. However, due to historical, economic, and geographical constraints, local economic development remains relatively underdeveloped. Average household incomes are low, classifying Aba as an economically disadvantaged region [11].
In recent years, the Aba region has experienced urbanization, rising income levels, and significant lifestyle changes. While these developments reflect broader socioeconomic progress, they have also introduced new public health challenges [12]. However, there is a scarcity of comprehensive epidemiological data to examine changes in hypertension control and identify opportunities for improving blood pressure management in the area.
Therefore, this study aimed to: 1) Compare the prevalence, awareness, treatment, and control rates of hypertension in the Aba region between 2019 and 2024; 2) Assess changes in health equity across gender, residence, age, and education groups; 3) Identify persistent gaps and emerging challenges to inform targeted public health interventions.
Methods
Data availability
Because of the sensitive nature of the data collected for this study, requests to access the data set from qualified researchers trained in human subject confidentiality protocols may be sent to the corresponding author. Proposals will be reviewed by the Data Access Committee of Sichuan Provincial People’s Hospital in China. A signed data access agreement is required, and data can only be used for the approved purpose.
Data source and sample selection
Data on quality of life among residents in Aba were sourced from the Sichuan Provincial Bureau of Statistics [13]. Two cross-sectional surveys were conducted in the Aba area: the first from September 2018 to June 2019, and the second from June 2023 to April 2024. The surveys encompassed major residential settlements randomly selected for inclusion. Participants were primarily recruited from five high-altitude regions (ranging in elevation from 2,500 to 3,800 meters): Maerkang City, Jinchuan County, Aba County, Hongyuan County, and Xiaojin County. Eligible participants were local residents aged 18 to 80 years who had resided in the plateau area for at least three years. Exclusion criteria included pregnancy, lactation, diagnosed mental disorders, and any physical condition that could impede completion of the survey. All participants provided written informed consent prior to participation.
Data measurement and collection
As detailed in our prior publication [14], in-person, detailed health interviews were carried out to collect socio-demographic information. All surveys were administered by trained research personnel. Ambiguous or inconsistent responses were subsequently clarified through follow-up telephone verification. The questionnaires employed remained identical in structure and content across both survey rounds.
Anthropometric indices (height, weight, and waist circumference) were obtained by certified staff using calibrated instruments. After a 5-minute seated rest, each participant’s blood pressure was recorded twice with an automated oscillometric device (Omron HBP-9020, Kyoto, Japan). Following an overnight fast of ≥8 h, venous blood was drawn and transported to accredited local laboratories for analysis of fasting glucose (FBG), triglycerides, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C).
The classification was consistent with the cut-off values previously described [10]: a body mass index (BMI) of 24–28 kg/m2 indicated overweight, and ≥28 kg/m2 indicated obesity [15]. Central obesity was diagnosed when waist circumference exceeded 90 cm in men or 85 cm in women.
Hypertension was defined as an average systolic blood pressure (SBP) ≥140 mmHg, diastolic blood pressure (DBP) ≥ 90 mmHg, and/or ongoing use of antihypertensive medication. Awareness referred to the proportion of hypertensive individuals who reported a previous physician diagnosis or were currently using antihypertensive drugs. Treatment was characterized as the percentage of hypertensive patients who self-reported taking at least one prescribed antihypertensive medication. Control was defined as the proportion of hypertensive participants with measured SBP < 140 mmHg and DBP < 90 mmHg at the time of survey.
Statistical analyses
Statistical analyses were performed using IBM SPSS Statistics (version 26.0) and R software (version 4.3.2). Age-standardized estimates for the prevalence, awareness, treatment, and control of hypertension were computed. Inverse probability of treatment weighting (IPTW) was applied to adjust for demographic confounding factors. IFor data from the 2019 and 2024 surveys, intergroup comparisons were performed using one-way analysis of variance (ANOVA), χ2 tests, or non-parametric tests, as appropriate for the variable type and distribution. Continuous variables were summarized as mean ± standard deviation (SD) for normally distributed data or median with interquartile range (IQR) for non-normally distributed data, and categorical variables were expressed as frequency percentages. Between-group differences were evaluated using T-tests, Mann-Whitney U tests, or χ2 tests, depending on data characteristics. All P-values were two-sided, with statistical significance defined as p < 0.05.
Ethical approval
Ethical approval for this study was obtained from the Institutional Review Board of Sichuan Provincial People’s Hospital, China (Approval No.: 2018-237 and 2022-312). The study was conducted in accordance with the ethical principles for medical research involving human subjects as set forth in the Declaration of Helsinki (2014). Written informed consent was obtained from all participants prior to their enrollment in the study.
Results
Population characteristics before and after IPTW adjustment (2019 vs. 2024)
A total of 1,880 participants from the 2019 survey and 1,870 from the 2024 survey were included in this study. Baseline demographic characteristics differed between the two survey periods. To facilitate comparative analysis, IPTW was applied to adjust for confounding variables including age, gender, and urban-rural distribution, achieving balance with all standardized mean differences (SMDs) falling within the range of −0.1 to 0.1. The balance of covariates before and after weighting was presented in Supplementary Table 1 and Supplementary Figure 1. The demographic and clinical characteristics of the participants in both survey years, before and after IPTW adjustment, were summarized in Table 1.
Table 1.
Population characteristics before and after IPTW adjustment (2019 vs. 2024).
| Variables | Unweighted groups |
Weighted groups |
|||
|---|---|---|---|---|---|
| 2019 | 2024 | 2019 | 2024 | P | |
| Age [Years, median (IQR)] | 43 (33, 55) | 39 (31, 50) | 42 (32, 55) | 40 (31, 50) | 0.62a |
| Gender [Female, n (%)] | 1080/1880 (57.45) | 934 /1870 (49.95) | 1013 /1883 (53.80) | 998/1863 (53.57) | 0.88a |
| Residence [Urban, n (%)] | 1108/1880 (58.94) | 942 /1870 (50.37) | 1039/1883 (55.18) | 1026/1864 (55.04) | 0.93a |
| Age [year, mean (SD)] | |||||
| Below 40 yrs | 780/1880 (41.49) | 939/1870 (50.21) | 897/1882 (47.66) | 818/1863 (43.91) | <0.001a |
| 40–59 yrs | 716/1880 (38.09) | 859/1870 (45.94) | 688/1882 (36.56) | 949/1863 (50.94) | |
| Above 60 yrs | 384/1880 (20.43) | 72/1870 (3.85) | 287/1882 (15.78) | 96/1863 (5.15) | |
| Education level, n (%) | |||||
| Elementary school or lower | 776/1880 (41.28) | 186/1870 (9.94) | 742/1882 (39.43) | 214/1864 (11.48) | <0.001a |
| Middle school | 324/1880 (17.23) | 576/1870 (30.80) | 313/1882 (16.63) | 606/1864 (32.51) | |
| High school or above | 780/1880 (41.49) | 1107/1870 (59.20) | 827/1882 (43.94) | 1045/1864 (56.06) | |
| Anthropometric and laboratory measurements | |||||
| BMI [kg/m2, median (IQR)] | 23.33 (21.38, 25.43) | 23.44 (21.36, 25.95) | 23.24 (21.36, 25.39) | 24.13 (21.94, 26.70) | <0.001c |
| WC [cm, median (IQR)] | 86 (79, 95) | 80 (75, 88) | 85 (78, 94) | 80 (74, 89) | <0.001c |
| SBP [mmHg, median (IQR)] | 128 (120, 136) | 115 (105, 125) | 128 (120, 136) | 113 (102, 124) | <0.001c |
| DBP [mmHg, median (IQR)] | 78 (72, 85) | 74 (67, 81) | 78 (72, 85) | 71 (63 79) | 0.014c |
| TG [mmol/L, median (IQR)] | 1.15 (0.84, 1.64) | 1.29 (0.95, 1.86) | 1.14 (0.80, 1.62) | 1.21 (0.85, 1.81) | 0.002c |
| TC [mmol/L, median (IQR)] | 4.53 (4.00, 5.29) | 4.36 (3.73, 5.00) | 4.51(4.00, 5.29) | 4.41 (3.90, 5.05) | 0.002c |
| HDL-C [mmol/L, median (IQR)] | 1.27 (1.10, 1.49) | 1.31 (1.10, 1.57) | 1.28 (1.10, 1.49) | 1.26 (1.06, 1.49) | 0.002c |
| LDL-C [mmol/L, median (IQR)] | 2.43 (2.05, 3.040 | 2.44 (1.89, 2.96) | 2.41 (2.02, 2.99) | 2.63 (2.16, 3.12) | 0.65c |
| FPG [mmol/L, mean (SD)] | 5.38 (1.75) | 4.98 (1.59) | 5.27 (1.65) | 5.03 (1.44) | 0.030b |
BMI: body mass index; WC: waist circumference; SBP: systolic blood pressure; DBP: diastolic blood pressure; TG: Triglycerides; TC: Total cholesterol; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; FPG: fasting plasma glucose; SD: standard deviation; IQR: interquartile range.
aP value of chi-square test in weighted groups.
bP value of ANOVA test in weighted groups.
cP value of Mann-Whitney U test in weighted groups.
Trends in the prevalence, awareness, treatment, and control of hypertension from 2019 to 2024
Following standardization based on the 2019 and 2023 Chinese national population data [16], the age-standardized prevalence of hypertension decreased from 22.86% to 15.53%. Age-standardized awareness rates improved from 24.63% to 53.43%, treatment rates from 16.08% to 43.93%, and control rates from 3.98% to 17.37%.
Figure 1(A–D) displays both crude and age-standardized prevalence, awareness, treatment, and control rates of hypertension, stratified by gender. Age-standardized rates of overweight (35.11% vs. 33.36%), obesity (5.21% vs. 12.10%), and central obesity (43.63% vs. 28.59%), disaggregated by gender, are presented in Supplementary Figure 3(A-C). Detailed data are available in Supplementary Table 2.
Figure 1.
Trends in hypertension prevalence, awareness, treatment, and control rate (2019 vs 2024). (A) Crude and age-standardized prevalence. (B) Crude and age-standardized awareness. (C) Crude and age-standardized treatment. (D) Crude and age-standardized control.
Furthermore, after adjusting for covariates including age, gender, and urban-rural distribution using IPTW, the changes in hypertension prevalence, awareness, treatment, and control status between 2019 and 2024 were summarized in Supplementary Figure 4.
Trends in living standards and hypertension-related disease burden in the general population
Supplementary Figure 2 illustrates changes in socioeconomic indicators and blood pressure-related cardiovascular disease (CVD) burden among Aba residents between 2018 and 2023. Over this five-year period, urbanization continued to advance. Disposable incomes increased in both urban and rural areas, while Engel coefficients exhibited a declining trend. Despite these improvements, the burden of BP-related CVD continued to rise. Specifically, cerebrovascular disease mortality increased from 116.63 to 161.02 per 100,000 population, and ischemic heart disease deaths rose from 72.58 to 124.53 per 100,000 population.
Figure 2(A–D) presents the temporal trends in hypertension prevalence (Figure 2A), awareness (Figure 2B), treatment (Figure 2C), and control rates (Figure 2D) across urban and rural populations. The results indicate statistically significant improvements in hypertension management within all three age groups and across different educational levels.
Figure 2.
Trends in hypertension status among the population*. (A) Prevalence of hypertension in urban and rural, (B) Awareness of hypertension in urban and rural, (C) Treatment of hypertension in urban and rural, (D) Control of hypertension in urban and rural. *Each marker points represents one patient of a certain age with specified education level.
As summarized in Table 2, hypertension management outcomes improved markedly from 2019 to 2024. A decline in prevalence was accompanied by substantial increases in awareness, treatment, and control rates. Unlike the 2019 survey, findings from 2024 revealed that hypertension awareness, treatment, and control rates no longer differed significantly between urban and rural areas, gender groups, or age segments.
Table 2.
Hypertension status and characteristics in 2019 and 2024 after inverse probability of treatment weighting (IPTW).
| Total, n |
Prevalence, n (%) |
Awareness, n (%) |
Treatment, n (%) |
Control, n (%) |
||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Characteristics | 2019 | 2024 | 2019 | 2024 | 2019 | 2024 | 2019 | 2024 | 2019 | 2024 |
| Subjects | 1883 | 1863 | 430 (22.84) | 254 (13.63) | 126 (29.30) | 142 (55.91) | 86 (20.00) | 123 (48.43) | 24 (5.58) | 50 (19.69) |
| Gender | ||||||||||
| Female | 1013 | 998 | 137 (13.52) | 61 (6.11) | 29 (21.17) | 35 (57.38) | 19 (13.87) | 26 (42.63) | 7 (5.11) | 9 (14.75) |
| Male | 870 | 865 | 293 (33.68) | 193 (22.31) | 97 (33.11) | 107 (55.44) | 67 (22.87) | 97 (50.26) | 17 (5.80) | 41 (21.24) |
| P | – | – | <0.001 | <0.001 | 0.012 | 0.88 | 0.038 | 0.38 | 1.00 | 0.36 |
| Residence | ||||||||||
| Urban | 1039 | 1026 | 156 (15.01) | 133 (12.96) | 60 (38.46) | 78 (58.65) | 43 (27.56) | 70 (52.24) | 18 (11.54) | 30 (22.56) |
| Rural | 844 | 837 | 274 (32.46) | 121 (14.46) | 66 (24.09) | 64 (52.89) | 43 (15.69) | 53 (43.80) | 6 (2.19) | 20 (16.53) |
| P | – | – | <0.001 | 0.42 | 0.002 | 0.45 | 0.004 | 0.21 | 0.02 | 0.27 |
| Age | ||||||||||
| <40 yrs | 897 | 818 | 63 (7.02) | 39 (4.77) | 6 (9.52) | 17 (43.59) | 3 (4.76) | 13 (33.33) | 0 (-) | 3 (7.69) |
| 40–59 yrs | 688 | 949 | 211 (30.67) | 180 (18.97) | 81 (38.39) | 103 (57.22) | 54 (25.59) | 88 (48.89) | 18 (8.53) | 34 (18.89) |
| ≥60 yrs | 287 | 96 | 156 (54.36) | 35 (36.46) | 39 (25.00) | 22 (62.86) | 29 (18.59) | 22 (62.86) | 6 (3.85) | 12 (34.29) |
| P | – | – | <0.001 | <0.001 | <0.001 | 0.20 | 0.001 | 0.039 | 0.017 | 0.012 |
| Education level | ||||||||||
| Elementary school or lower | 742 | 214 | 268 (36.12) | 55 (25.70) | 61 (22.76) | 36 (65.45) | 46 (17.16) | 31 (56.36) | 6 (2.24) | 12 (21.82) |
| Middle school | 313 | 606 | 54 (17.25) | 101 (16.67) | 20 (37.04) | 55 (54.46) | 14 (25.93) | 47 (46.53) | 4 (7.41) | 19 (18.81) |
| High school or above | 827 | 1045 | 108 (13.06) | 98 (9.38) | 45 (41.67) | 51 (52.04) | 25 (23.15) | 45 (45.92) | 14 (14.29) | 19 (19.39) |
| P | – | – | <0.001 | <0.001 | <0.001 | 0.27 | 0.18 | 0.50 | <0.001 | 0.90 |
| Weight | ||||||||||
| Obesity | 101 | 216 | 55 (54.46) | 59 (27.31) | 20 (36.36) | 28 (47.46) | 7 (12.73) | 22 (37.29) | 0 (-) | 12 (20.34) |
| Overweight | 639 | 600 | 201 (31.46) | 117 (19.50) | 57 (28.36) | 73 (62.39) | 42 (20.79) | 64 (54.70) | 14 (6.97) | 20 (17.09) |
| Other | 1143 | 1022 | 173 (15.14) | 75 (7.34) | 49 (28.32) | 39 (52.00) | 37 (21.39) | 34 (45.33) | 10 (5.78) | 16 (21.33) |
| P | <0.001 | <0.001 | 0.47 | 0.13 | 0.35 | 0.081 | 0.14 | 0.72 | ||
| Central obesity | ||||||||||
| Yes | 795 | 506 | 236 (29.69) | 111 (21.94) | 77 (32.63) | 65 (58.56) | 54 (22.88) | 52 (46.85) | 10 (4.24) | 24 (21.62) |
| No | 1085 | 1333 | 194 (17.88) | 143 (10.73) | 49 (25.26) | 77 (39.69) | 32 (16.49) | 70 (48.95) | 14 (7.22) | 26 (18.18) |
| P | – | – | <0.001 | <0.001 | <0.001 | 0.12 | 0.01 | 0.01 | 0.05 | 0.07 |
| Hyperlipoidemia | ||||||||||
| Yes | 815 | 876 | 244 (29.94) | 160 (18.26) | 88 (36.07) | 87 (54.38) | 61 (25.00) | 71 (44.38) | 19 (7.79) | 28 (17.50) |
| No | 1068 | 988 | 186 (17.42) | 94 (9.51) | 38 (20.43) | 55 (58.51) | 25 (13.44) | 51 (54.26) | 5 (2.69) | 22 (23.40) |
| P | – | – | <0.001 | <0.001 | <0.001 | 0.15 | <0.001 | 0.30 | <0.001 | <0.001 |
| Fasting plasma glucose ≥ 6.1 mmol/L | ||||||||||
| Yes | 195 | 163 | 79 (40.51) | 60 (36.81) | 25 (31.01) | 37 (61.67) | 11 (13.92) | 31 (51.67) | 2 (2.53) | 15 (25.00) |
| No | 1682 | 1698 | 345 (20.51) | 194 (11.43) | 78 (22.78) | 105 (54.12) | 75 (21.74) | 91 (46.91) | 22 (6.38) | 35 (18.04) |
| P | – | – | <0.001 | <0.001 | 0.17 | 0.37 | 0.16 | 0.55 | 0.28 | 0.27 |
Sensitivity analysis
To address potential bias from differences in age distribution between the survey periods, a sensitivity analysis was performed. The key findings regarding improvements in hypertension management indicators were robust and were detailed in Supplementary Table 3.
Discussion
This study employed a repeated cross-sectional design, which was well-suited for monitoring population-level trends and evaluating the equity of health system performance over time. Unlike cohort studies, this design cannot track individual-level changes or directly attribute outcomes to specific interventions. However, it provides essential evidence on whether the population as a whole was benefiting from health system reforms - a key question for universal health coverage.
This repeated cross-sectional study documents a remarkable transformation in the epidemiological profile of hypertension in a transitioning, high-altitude, multi-ethnic region of Sichuan Province in southwestern China between 2019 and 2024. The most encouraging finding of this study was the remarkable decline in both crude and age-standardized prevalence of hypertension, accompanied by substantial improvements in awareness, treatment, and control rates. The age-standardized prevalence of hypertension declined from 22.86% to 15.53%. A parallel decline was also observed in crude prevalence (24.89% to 12.09%). It was accompanied by marked improvements across the entire management cascade: standardized awareness rates increased from 24.63% to 53.43%, treatment rates from 16.08% to 43.93%, and control rates from 3.98% to 17.37%.
The downward trend of the prevalence of hypertension in this region was inconsistent with the upward trend shown in other regions of China [17]. Previous surveys in 2021 indicated that the prevalence of hypertension among the Tibetan population (31.4%) was significantly higher than the Chinese average (27.5%) [18], but the data from Aba Tibetan area in Sichuan province remained unclear. Some scholars focusing on hypertension prevalence among populations lifted out of poverty in China noted that although an overall upward trend had been observed, distinct spatial distribution patterns existed. Specifically, the southwestern region exhibited a low-low clustering pattern in hypertension prevalence. In Sichuan province, the prevalence remained below 10% in 2023, almost consistent with the results in our survey [19]. To enable a more rigorous analysis of hypertension trends in this region, statistical methods were employed to address potential biases arising from sampling variations. Although IPTW was applied to adjust for age between the two surveys, eliminating significant overall differences in age distribution (p > 0.05), structural disparities in the age composition of the sampled populations remained. Notably, the proportion of individuals aged ≥ 60 years in the 2024 sample was substantially lower than that in 2019 (weighted: 5.15% vs. 15.78%). This difference may reflect sampling variation or actual demographic shifts in the study population. But given the strong positive association between hypertension risk and age, this difference should be considered [20]. To minimize the bias, age-standardized rates based on Chinese data were calculated, as presented in Supplementary Table 2. The downward trend persisted too. Hypertension age-standardized prevalence decreased from 22.86% in 2019 to 15.53% in 2024. Furthermore, subgroup analyses provided supporting evidence (Table 2). Hypertension prevalence in 2024 was lower than in 2019 across all age strata. Thus, our findings support the possibility of a true decline in hypertension prevalence in the region. This pattern might be related to factors such as the region’s distinctive dietary preferences, high-altitude environment, socioeconomic status, and cultural background. This trend should be further investigated in future studies.
Concurrently, significant improvements in awareness, treatment, and control rates among hypertensive patients were observed, reflecting substantive enhancements in hypertension management during this period. These improvements occurred during a period of strengthened primary care under the National Essential Public Health Services Program (NEPHSP) [21]. It was consistent with the reports from other regions of China [22,23]. The convergence of awareness and treatment rates across urban-rural, gender, and age groups represented a significant achievement in health equity for this historically underserved region [24], contrasting with the persistent urban-rural and geographical disparities observed in many other parts of China [25]. This positive divergence coincided with the intensified, targeted poverty alleviation and health promotion campaigns implemented in ethnic minority regions in recent years, which may have yielded earlier gains in this population [26]. This trend should be further validated in future studies using more stable population structures.
However, the rise in CVD mortality was a stark reminder that these gains are fragile and can be easily offset by other risk factors and systemic weaknesses in care quality. Attention should be paid to the persistently suboptimal absolute control rate (18.14% in 2024), which is consistent with the national data [2]. This control gap was particularly concerning given the continuous rise in CVD mortality observed in our study. The mortality of CVD remained high in Aba area despite improved healthcare access [27]. The suboptimal control rates are associated with the quality of clinical management at the primary care level. This may reflect therapeutic inertia, suboptimal prescribing patterns, especially underuse of combination therapy and poor long-term adherence. These issues were particularly pronounced in remote and rural healthcare settings, where physician training and support systems are often inadequate [28]. Patient satisfaction with continuous and effective medical care had a positive influence on medication adherence and the effectiveness of treatment [29]. A recent study conducted in the same region specifically demonstrated that physicians in Sichuan’s Tibetan rural areas often lacked confidence and competency in managing hypertension, particularly in treatment intensification and the use of combination therapies [30]. This “therapeutic inertia” at the provider level offers a crucial explanation for our observed high proportion of “treated but uncontrolled” patients and might be increasingly recognized as a major barrier to effective hypertension control in primary care settings across China [31]. On the other hand, the beneficial impact of improved BP control on population-level CVD mortality becomes apparent after a few years. The current mortality rates may thus largely reflect the legacy of poor management in the preceding years. Even with improved treatment rates, a large reservoir of individuals remained at elevated risk for events like stroke and ischemic heart disease. This challenge was further compounded by the rising burden of other risk factors, including obesity and population aging [27]. As emphasized in a recent European Society of Hypertension position paper, frailty and functional status - rather than chronological age alone - should guide blood pressure target individualization in older hypertensive patients [32].
In addition to the clinical management, the persistent proportion of “aware but untreated” patients remained high, particularly among women, as previously observed in this region [33]. Non-financial barriers might continue to impede treatment initiation, such as medication fears, concerns about side effects, and culturally influenced health beliefs. The proportion of “treated but uncontrolled” hypertension increased substantially in both males and females. This pattern was consistent with findings from studies in other Tibetan populations [12,14,16]. Hypertension management still faced unique challenges in ethnic minority regions. Future efforts informed by the Health Belief Model could focus on: (1) enhancing perceived severity by educating patients about the long-term consequences of uncontrolled hypertension; (2) clarifying the perceived benefits of treatment in preventing stroke and heart failure; and (3) reducing perceived barriers through patient counseling on medication dependency and side effects, while integrating cultural beliefs into health messaging.
The divergent trends in weight-related metrics further complicated the results. Population-level studies in East Asia have documented a rightward shift in the BMI distribution, with heterogeneous changes across its segments [34]. However, direct evidence linking such distributional shifts to a concurrent decline in overweight and rise in obesity remains limited. Our findings may reflect an intermediate stage of nutrition transition in this high-altitude, multi-ethnic region - a hypothesis that warrants investigation in future longitudinal studies.These changes might be associated with rapid shifts in dietary patterns and physical activity during economic transition and urbanization [35]. The increase in obesity prevalence (from 5.11% to 11.44%) represented an additional significant challenge [36]. Hypertension management programs should be coupled with community-based obesity prevention initiatives (e.g. promoting healthy food environments) and lifestyle promotion, particularly for young adults. Primary care should be reoriented towards cardiovascular risk factor management rather than single-disease management.
More alarmingly, our findings reveal a shift in hypertension epidemiology toward younger, working-age adults, particularly those with low-to-medium education levels in urban areas. The lower perceived risk and poor medication adherence among young adults have been well documented in other cohorts [37]. This trend was consistent with national data showing rising hypertension incidence among younger adults, attributed to increasingly sedentary lifestyles, dietary changes, and rising stress levels. The poor control rates among younger hypertensive patients indicated a systematic loophole in patient engagement and disease management for this population. The tendency of younger individuals to underestimate their personal susceptibility to health threats has been associated with poorer risk perception, delayed symptom recognition, and ultimately, inadequate adherence to treatment and follow-up [37]. The current healthcare delivery model, primarily designed for managing older patients with multiple chronic conditions, remained poorly adapted to address the distinct behavioral and psychological challenges in chronic disease management in younger populations.
Several limitations of this study should be acknowledged. First, the cross-sectional design precludes the establishment of causal inferences. Second, although IPTW was applied to adjust for key demographic variables and age-standardization was performed, structural differences in the age and education distribution may still have introduced confounding bias. Third, data on awareness, treatment, and medication adherence were based on self-report, which may be subject to recall bias and social desirability bias.Importantly, our analysis lacked detailed data on specific antihypertensive agents, behavioral determinants (e.g. dietary salt intake), and psychosocial factors. This limits our ability to explore the underlying drivers of suboptimal control. Future longitudinal studies incorporating objective measures of medication use and mixed-methods approaches are needed to better understand the complex behavioral and systemic barriers to effective hypertension management in this transitioning population.
Despite these considerations, this study provides robust real-world evidence on population-level changes in hypertension management during the implementation of recent hypertension management initiatives in a transitioning ethnic minority region. It highlights measurable improvements in awareness, treatment, and health equity, while simultaneously identifying control gaps and shifting risk profiles that require targeted policy intervention. These insights offer valuable reference for public health planning in similar socio-demographic settings. This study not only describes epidemiological trends but also characterizes the hypertension management cascade and identifies remaining gaps. By highlighting the new crisis of hypertension among young people in the region and alerting women to the importance of treatment, our research findings provide a basis for precise intervention of hypertension. It could offers invaluable insights for public health policy.
Conclusions
Significant progress in hypertension management and equity was observed in the high-altitude multi-ethnic region of China in transition. However, persistently low control rates and rising metabolic risks underscore unresolved challenges. We recommend a strategic shift from expanding coverage to improving care quality, and from single-disease management to integrated cardiovascular risk reduction. Priority actions include strengthening primary care capacity, implementing life-course interventions targeting obesity and hypertension in youth, and developing culturally adapted, patient-centered strategies. This study provides a benchmark and a framework for public health action in similar transitioning, multi-ethnic settings. Future research might prioritize implementing and evaluating integrated, culturally-tailored care models in real-world settings, and investigating the multilevel determinants of control to develop targeted equity interventions.
Supplementary Material
Acknowledgments
We are grateful to all study participants for their active cooperation. We acknowledge contribution of our survey team members, interviewers, leaders, and volunteers for their continuous efforts in the field survey. We would like to thank the Editors of the journal as well as the anonymous referees for their helpful comments and feedback. We would like to thank the Blackstone Studios Chengdu (Yunjian Technology) for their statistical support. All remaining errors are our own.
Funding Statement
This research was funded by Noncommunicable Chronic Diseases-National Science and Technology Major Project (grant number: 2025ZD0551601), Health Commission of Chengdu Medical Science and Technology Program (grant number: 2024124), Chengdu Science and technology Program (grant number: 2024-YF05-01635-SN) and Sichuan Provincial People’s Hospital (grant number: 2022RK07).
Ethics approval and consent to participate
The study protocol was approved by the local Human Ethics and Research Ethics committees of Sichuan Provincial People’s Hospital in China (Approval No. 2018-237 and 2022-312) and conducted in accordance with the human research ethical standards and regulations of the Helsinki Declaration (2014). All subjects provided written informed consent before participation in the study.
Disclosure statement
Authors have no conflict of interests.
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