Spatial analysis of gender variation in the prevalence of hypertension among the middle-aged and elderly population in Zhejiang Province, China

Hypertension prevalence in Iran's elderly according to new criteria: the Tehran Geriatric Eye Study

Purpose

To determine the prevalence of hypertension in a population above 60 years of age and its relationship with demographic and anthropometric factors.

Methods

A cross-sectional population-based study was conducted in 2019. Using a multistage random cluster sampling, 160 clusters were selected from 22 districts of Tehran. All participants were interviewed to collect demographic, anthropometric, and socioeconomic information. Then, systolic (SBP) and diastolic (DBP) blood pressures were measured under standard conditions twice, 10 min apart. A third measurement was performed if the two measurements showed a difference of ≥ 10 mmHg in SBP or ≥ 5 mmHg in DBP. Hypertension was defined as a SBP > 130 mmHg or a DBP > 80 mmHg (new criteria), being a known case of hypertension, or use of blood pressure lowering medications.

Results

Of 3791 invitees, 3310 participated in the study (87.3%). The mean age of the participants was 68.25 ± 6.54 years (60-97 years). The prevalence of hypertension was 81.08% (95% CI: 79.57-82.59) in the whole sample; 82.96% (95% CI: 81.02-84.91) in females, and 79.15% (95% CI: 76.6 -81.69) in males. The prevalence of hypertension ranged from 75.47% (95% CI: 72.65-78.29) in the age group 60-64 years to 88.40% (95% CI: 83.71-93.08) in the age group ≥ 80 years. The prevalence of hypertension unawareness was 32.84% (95% CI: 30.82-34.86). The highest and lowest prevalence of hypertension was seen in illiterate subjects (89.41%) and those with a university education (77.14%), respectively. According to the multiple logistic regression analysis, older age, lower education level, obesity and overweight, neck circumference, and diabetes were significantly associated with the prevalence of hypertension.

Conclusion

A significant percentage of Iranian elderly have hypertension and one of every 3 affected individuals is unaware of their disease. Considering the population aging in Iran, urgent and special attention should be paid to the elderly population. Caring for the elderly, informing families, and using non-traditional screening methods are recommended by families at the first level and policymakers at the macro level.

Bayesian Spatial Modeling of Diabetes and Hypertension: Results from the South Africa General Household Survey

Determining spatial links between disease risk and socio-demographic characteristics is vital in disease management and policymaking. However, data are subject to complexities caused by heterogeneity across host classes and space epidemic processes. This study aims to implement a spatially varying coefficient (SVC) model to account for non-stationarity in the effect of covariates. Using the South Africa general household survey, we study the provincial variation of people living with diabetes and hypertension risk through the SVC model. The people living with diabetes and hypertension risk are modeled using a logistic model that includes spatially unstructured and spatially structured random effects. Spatial smoothness priors for the spatially structured component are employed in modeling, namely, a Gaussian Markov random field (GMRF), a second-order random walk (RW2), and a conditional autoregressive (CAR) model. The SVC model is used to relax the stationarity assumption in which non-linear effects of age are captured through the RW2 and allow the mean effect to vary spatially using a CAR model. Results highlight a non-linear relationship between age and people living with diabetes and hypertension. The SVC models outperform the stationary models. The results suggest significant provincial differences, and the maps provided can guide policymakers in carefully exploiting the available resources for more cost-effective interventions.

Association of long-term exposure to PM2.5 with hypertension and diabetes among the middle-aged and elderly people in Chinese mainland: a spatial study

Background

Epidemiological evidence has shown an association between long-term exposure to fine particulate matter (PM_2.5) and hypertension and diabetes, but few studies have considered the spatial properties of the samples. This study aimed to investigate the long-term effect of PM_2.5 exposure on hypertension and diabetes among middle-aged and elderly people in China based on a spatial study.

Methods

We conducted a national cross-sectional study of the most recently launched wave 4 2018 data of the China Health and Retirement Longitudinal Study (CHARLS) to calculate the prevalence of hypertension and diabetes. The exposure data of annual average PM_2.5 concentrations were estimated combined with satellite observations, chemical transport modeling, and ground-based monitoring. A shared component model (SCM) was used to explore the association of PM_2.5 with hypertension and diabetes, in which these two diseases borrowed information on spatial variations from each other. Then, we evaluated the effect variations in PM_2.5 in different periods and smoking status on changes in outcomes.

Results

The prevalence of hypertension and diabetes was 44.27% and 18.44%, respectively, among 19,529 participants. The annual average PM_2.5 concentration in 31 provinces ranged from 4.4 μg/m³ to 51.3 μg/m³ with an average of 27.86 μg/m³ in 2018. Spatial auto-correlations of the prevalence of hypertension and diabetes and PM_2.5 concentrations were seen (Moran’s I = 0.336, p = 0.01; Moran’s I = 0.288, p = 0.03; Moran’s I = 0.490, p = 0.01). An interquartile range (IQR: 16.2 μg/m³) increase in PM_2.5 concentrations was significantly associated with a higher prevalence of hypertension and diabetes with odds ratios (ORs) of 1.070 [95% credible interval (95% CrI): 1.034, 1.108] and 1.149 (95% CrI: 1.100, 1.200), respectively. Notably, the effect of PM_2.5 on both hypertension and diabetes was relatively stronger among non-smokers than smokers.

Conclusion

Our nationwide study demonstrated that long-term exposure to PM_2.5 might increase the risk of hypertension and diabetes, and could provide guidance to public policymakers to prevent and control hypertension and diabetes according to the spatial distribution patterns of the above effects in China.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12984-6.

Spatial analysis of the effects of PM2.5 on hypertension among the middle-aged and elderly people in China

Hypertension is currently one of the most common chronic diseases with high global prevalence associated with a huge social and economic burden. In recent years, air pollution has become a focus of research, especially the effects of PM2.5 on hypertension. However, few studies have considered the spatial properties of the sample; thus, the results might be unreliable. Based on the China Health and Retirement Longitudinal Study (CHARLS) and the Environmental Status Bulletin for each province in China, we used the extended shared component model (SCM) to fit the spatial variation of hypertension risk and to reveal the impact of PM2.5 on hypertension in males and females. Our results revealed that the crude prevalence of hypertension for the whole population in China was 32.74% in 2015, with the prevalence in men experiencing slightly higher than that in women (32.92% vs. 32.58%). We found that the distribution of hypertension prevalence exhibited obvious spatial aggregation for the whole population in China (Moran's I = 0.39, P = 0.001), with similar results in both men (Moran's I = 0.18, P = 0.027) and women (Moran's I = 0.52, P = 0.001). Furthermore, the smoothed results obtained using the SCM indicated that some eastern and central provinces had relatively higher hypertension risk, while the risk in southeastern provinces was much lower. The risk was also relatively lower in most western provinces, except for some northwestern regions. Notably, our results showed that PM2.5 was a risk factor for hypertension, and the impact of PM2.5 on women was slightly greater than that on men, with odds ratios (OR) of 1.063 (1.041, 1.086) and 1.048 (1.025, 1.071), respectively. Our findings suggest the existence of distinct spatial differences in the prevalence of hypertension and small sex-related differences in the risk of hypertension in China.

The urban-rural disparity in the prevalence and risk factors of hypertension among the elderly in China-a cross-sectional study

Introduction

This study aimed to assess the prevalence of hypertension and to explore the disparities of its risk factors among urban and rural elderly.

Method

Data of hypertensive patients were collected from the China Health and Retirement Longitudinal Study (CHARLS) 2015. Stratified sample households were selected from 450 villages or communities of 150 counties from 28 provinces. Multivariable logistic regression was performed to analyze the factors correlated with hypertension.

Results

Prevalence of HBP was 47.6% (95% CI [45.2%-50.1%]) in total and it was close between urban and rural population (48.6% vs 47.2%). Factors associated with HBP were different between urban and rural areas. In urban areas, hypertension was significantly associated with literacy and diabetes in both genders, high BMI level and smoke quitters in males, and physical activity and dyslipidemia in females. In rural areas, hypertension was significantly associated with older age, higher BMI level in both males and females, and dyslipidemia in males.

Conclusions

The prevalence are about the same among urban and rural residents, but their risk factors vary from each other. Disparity in the risk factors between urban and rural population should be taken into consideration for further intervention.

Application of SCM with Bayesian B-Spline to Spatio-Temporal Analysis of Hypertension in China

Most previous research on the disparities of hypertension risk has neither simultaneously explored the spatio-temporal disparities nor considered the spatial information contained in the samples, thus the estimated results may be unreliable. Our study was based on the China Health and Nutrition Survey (CHNS), including residents over 12 years old in seven provinces from 1991 to 2011. Bayesian B-spline was used in the extended shared component model (SCM) for fitting temporal-related variation to explore spatio-temporal distribution in the odds ratio (OR) of hypertension, reveal gender variation, and explore latent risk factors. Our results revealed that the prevalence of hypertension increased from 14.09% in 1991 to 32.37% in 2011, with men experiencing a more obvious change than women. From a spatial perspective, a standardized prevalence ratio (SPR) remaining at a high level was found in Henan and Shandong for both men and women. Meanwhile, before 1997, the temporal distribution of hypertension risk for both men and women remained low. After that, notably since 2004, the OR of hypertension in each province increased to a relatively high level, especially in Northern China. Notably, the OR of hypertension in Shandong and Jiangsu, which was over 1.2, continuously stood out after 2004 for males, while that in Shandong and Guangxi was relatively high for females. The findings suggested that obvious spatial-temporal patterns for hypertension exist in the regions under research and this pattern was quite different between men and women.