[Prevalence and Influencing Factors of Isolated Diastolic Hypertension in Tibetan Population in Tibet]. / è¥¿è—åœ°åŒºè—æ—äººç¾¤å•çº¯èˆ’å¼ æœŸé«˜è¡€åŽ‹çš„æ‚£ç— çŽ°çŠ¶åŠå ¶å½±å“å› ç´ åˆ†æž.

Objective: To investigate the prevalence and influencing factors of isolated diastolic hypertension (IDH) in the Tibetan population in Tibet and to provide some evidence for the prevention and control of hypertension and other related diseases in high-altitude areas. Methods: A multistage stratified whole-group random sampling method was used to enroll participants from Ngari Prefecture, Nagqu City, Shannan City, and Lhasa City, Tibet. A total of 3918 native Tibetans with complete data were enrolled in the survey between June 2020 and August 2023. The participants were aged from 18 to 80. The demographic data, life habits, and chronic disease prevalence of the participants were collected. Fasting venous blood samples were collected to perform the routine blood tests and blood biochemistry tests. The prevalence of IDH in subgroups with different characteristics was analyzed and the influencing factors were analyzed by multivariate logistic regression, accordingly. The predictive value of influencing factors on the prevalence of IDH was analyzed by the receiver operating characteristic (ROC) curve and the findings were compared with those of the previous prediction models for IDH. Results: The prevalence of hypertension in the participants was 33.7% (n=1321), among which, 395 had IDH, accounting for 29.9% of the hypertensive patients. The results of multivariate regression showed that age, heart rate, body mass index, waist circumference, hemoglobin, and low-density lipoprotein cholesterol were associated with risks of developing IDH (P<0.05). The area under the ROC curve (AUC) was 0.71, which indicated improved accuracy for predicting the risks for IDH in comparison with previous predictive models for IDH. Among the influencing factors, BMI showed the best predictive value for IDH risks. Conclusion: The prevalence of IDH is high among Tibetans in Tibet, suggesting the necessity for rational allocation of health resources in accordance. Compared with the previous IDH prediction models, the model proposed in this study is more suited for the Tibetan population. Targeted interventions should be carried out for the high-risk populations, such as young and middle-aged adults and populations suffering from overweight/obesity, central obesity, high-altitude polycythemia, and dyslipidemia, so as to effectively control the occurrence and development of IDH.

[Relationship Between Hearing Loss and Cognitive Function in Elderly Chinese People: A Study Based on Propensity Score Matching]. / åŸºäºŽå€¾å‘å¾—åˆ†åŒ¹é æŽ¢è®¨ä¸­å›½è€å¹´äººå¬åŠ›æŸå¤±ä¸Žè®¤çŸ¥åŠŸèƒ½ä¹‹é—´çš„å ³ç³».

Objective: To explore the relationship between hearing loss and cognitive function in the elderly population through propensity score matching method. Methods: We analyzed the data of 7605 participants aged 60 and above who were included in the 2018 China Health and Retirement Longitudinal Study (CHARLS). The non-substitutable 1∶1 nearest neighbor matching method without caliper value was used for propensity score matching and G-computation was used to estimate the average treatment effect (ATE) of hearing loss on all dimensions of cognitive function. Results: Before matching, there were 3626 (47.68%) women, with 1409 (18.53%) of whom suffering from hearing loss and 3031 (39.86%) of whom suffering from cognitive impairment. After matching, 1409 subjects were included in the hearing loss group and 1409, in the normal hearing group, with both groups sharing similar distribution of basic demographic characteristics. The results for the average treatment effect of the population indicated that the cognitive function scores of the hearing loss group were lower than those of the normal hearing group, with the overall cognitive function being 0.593 points lower (95% confidence intervel [CI]: －0.916-－0.257, P<0.001), orientation being 0.183 points lower (95% CI: －0.302-－0.055, P=0.004), immediate memory being 0.150 points lower (95% CI: －0.218-－0.085, P<0.001), and language skills being 0.178 points lower (95% CI: －0.303-－0.058, P=0.006). The prevalence of cognitive impairment of the hearing loss group was 4.2% higher than that of the normal hearing group (95% CI: 0.007-0.077, P=0.020). Conclusion: Hearing loss adversely affects the orientation, memory, and language skills of the elderly population and forms a potential risk factor for cognitive impairment in the elderly population.

[Comparative Analysis of Influencing Factors of Health Service Utilization Among Urban and Rural Residents in Tibet].

Objective: To examine the differences and commonalities of factors influencing the utilization of health services among urban and rural residents in Tibet and to identify vulnerable populations in the utilization of health services, thereby providing references for the formulation of local health policies and the allocation of health resources. Methods: Using the Tibetan area data from the Sixth National Health Service Survey, we conducted statistical analysis of the health service utilization status of 8 297 residents of agro-pastoral areas and 2 179 residents of urban areas with χ 2 test and logistic regression model. Results: The two-week outpatient visit rates of residents in agro-pastoral areas and that of the urban residents were 65.3% and 57.1%, respectively, and the one-year hospitalization rates were 8.3% and 8.9%, respectively. The influencing factors of two-week outpatient visits for rural and pastoral residents included urban and rural health insurance coverage, Three Guarantees in One coverage, distance to medical facilities, chronic disease status, physical examination, family doctor contract status, employment status, and health status self-assessment. The influencing factors of two-week outpatient visit for urban residents included chronic disease status, urban and rural medical insurance coverage, health status self-assessment, health records, and physical examination. The factors influencing hospitalization for agro-pastoral residents were sex, age, marital status, urban and rural medical insurance coverage, Three Guarantees in One coverage, critical illness insurance, health self-assessment, mobility, health records, physical examination, and chronic disease status. The factors influencing the hospitalization of urban residents were sex, marital status, health status self-assessment, health records, urban employee medical insurance coverage, and chronic disease status. The factors influencing the hospitalization of urban residents were sex, marital status, health status self-assessment, health records, urban employee medical insurance coverage, and chronic disease status. Conclusion: The urban and rural residents in Tibet have relatively poor health and their awareness of seeking early medical help after they fall ill is relatively weak. The health institutions concerned should dedicate more attention to the vulnerable populations who have difficulty accessing health services, focus on the commonly shared influencing factors of health service utilization among urban and rural residents, take into account the differences, rationally allocate health resources, and improve the effective utilization rate of health services among residents in Tibet.

Influencing factors of bone mass abnormalities among postmenopausal women in Tibet, China.

BACKGROUND: This study aimed to provide a reference for the prevention and treatment of abnormal bone mass in postmenopausal women by analysing the current situation and influencing factors of bone mass abnormalities in Tibet. METHODS: A total of 229 postmenopausal Tibetan women were randomly selected from six counties by a multistage cluster random sampling method. Multiple logistic regression was utilized to analyse the status and influencing factors of bone mass abnormalities in postmenopausal Tibetan women. RESULTS: Among 229 postmenopausal Tibetan women, the prevalence of osteopenia and osteoporosis was 54.6% and 9.6%, respectively. Age {odds ratio (OR) = 0.022 [95% confidence interval (CI) = 0.003 ~ 0.163]}, BMI [OR = 441.902 (20.899,9343.717)], altitude [OR = 18.818 (1.391,254.585)], and creatinine (CREA) levels [OR = 0.895 (0.825 ~ 0.971)] were significantly associated with the risk of osteoporosis. CONCLUSION: Postmenopausal Tibetan women had high rates of abnormal bone mass. Age, BMI, altitude and CREA levels were associated with osteoporosis. It is suggested that relevant departments should take targeted measures to promote health education on the prevention of osteoporosis in the general population and increase the screening of high-risk groups for osteoporosis to improve the bone health of postmenopausal Tibetan women.

[Effect of the Interaction Between Overweight/Obesity and Dyslipidemia on the Risk of Hypertension in Tibetan Population Living in Tibet].

Objective: To explore the possible interaction between overweight/obesity and dyslipidemia and to provide some evidence for the interaction of the risk of hypertension with overweight/obesity and dyslipidemia. Methods: By using multi-stage stratified cluster random sampling method, the subjects of the study were randomly selected from Naqu city, Shannan city, and Ali prefecture, Tibet. A total of 4047 Tibetans with complete data were included. Investigators obtained relevant information on the subjects through questionnaire surveys, measured their height, body mass index, and blood pressure, and collected fasting venous blood samples. The multivariate logistic regression model was used to analyze the independent effects of overweight/obesity and dyslipidemia and hypertension. Stratified analysis and an additive interaction model were used to evaluate the effect of two-factor interaction on the risk of hypertension. Results: The overall prevalence of hypertension, overweight/obesity, and dyslipidemia among Tibetans living in Tibet was 29.3%, 46.2%, and 40.9%, respectively. Overweight/obesity (odds ratio [ OR]=2.151) and dyslipidemia ( OR=1.240) were risk factors of hypertension. Evaluation results of the effect of additive interaction showed significant additive interaction of overweight/obesity and dyslipidemia on hypertension ( P=0.028), with the synergy index ( SI) being 1.318. Conclusion: Overweight/obesity and dyslipidemia are risk factors for having hypertension and there is an additive interaction between dyslipidemia and overweight/obesity.