Dataset Information

Illness prevalence rate in Tibet, China: data from the 2018 National Health Service Survey.

ABSTRACT:

Background

Tibet is located in the high-altitude area of Southwest China, where the health level is influenced by specific factors such as the natural environment and living habits. However, there has been little research that has focused on Tibetan health conditions. The two-week prevalence rate is an important indicator of the health level of residents. The purpose of this study was to understand the health status of the residents and the health service needs in Tibet.

Methods

The two-week prevalence rate was calculated using data from a population of 10,493 individuals aged 15 and above that was obtained from the 2018 Sixth National Health Service Survey of Tibet. We initially analysed the types and associated factors of two-week illnesses in Tibetan. The influencing factors for the two-week prevalence rate in Tibet were determined by multivariate logistic regression analysis. Subsequently, we assessed the severity of two-week illnesses by calculating the average days of the duration of the disease, the days of being bedridden and the days of being off work.

Results

The two-week illness prevalence rate was 20.1% in Tibet. Digestive system diseases were frequent, and hypertension was the most common disease. According to the multivariate logistic regression analysis, the two-week prevalence rate was associated with gender, age, residence, marital status, and employment status. In addition, the severity of two-week illnesses differed among the residents.

Conclusion

This study identified that health service needs have increased in Tibet and that the health status of the local residents needs to be improved. Moreover, hypertension has become a major health hazard for the residents and should be considered in the utilization of health services.

SUBMITTER: Deng R

PROVIDER: S-EPMC7302388 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Illness prevalence rate in Tibet, China: data from the 2018 National Health Service Survey.

Deng Rendan R Labasangzhu Zhaxideji Wang Guihua G Hong Peiwei P Li Jiaqi J Li Qiwen Q Wan Yang Y Xiong Hai H

BMC public health 20200618 1

<h4>Background</h4>Tibet is located in the high-altitude area of Southwest China, where the health level is influenced by specific factors such as the natural environment and living habits. However, there has been little research that has focused on Tibetan health conditions. The two-week prevalence rate is an important indicator of the health level of residents. The purpose of this study was to understand the health status of the residents and the health service needs in Tibet.<h4>Methods</h4>T ...[more]

PMID: 32552694

Similar Datasets

Project description:BackgroundThe two-week illness prevalence rate is an important and comparable indicator of health service needs. High-spatial-resolution, age-specific risk mapping of this indicator can provide valuable information for health resource allocation. The age-prevalence relationships may be different among areas of the study region, but previous geostatistical models usually ignored the spatial-age interaction.MethodsWe took Guangdong province, the province with the largest population and economy in China, as a study case. We collected two-week illness data and other potential influencing predictors from the fifth National Health Services Survey in 2013 and other open-access databases. Bayesian geostatistical binary regression models were developed with spatial-age structured random effect, based on which, high-resolution, age-specific two-week illness prevalence rates, as well as number of people reporting two-week illness, were estimated. The equality of health resource distribution was further evaluated based on the two-week illness mapping results and the health supply data.ResultsThe map across all age groups revealed that the highest risk was concentrated in the central (i.e., Pearl River Delta) and northern regions of the province. These areas had a two-week illness prevalence > 25.0%, compared with 10.0-20.0% in other areas. Age-specific maps revealed significant differences in prevalence between age groups, and the age-prevalence relationships also differed across locations. In most areas, the prevalence rates decrease from age 0 to age 20, and then increase gradually. Overall, the estimated age- and population-adjusted prevalence was 16.5% [95% Bayesian credible interval (BCI): 14.5-18.6%], and the estimated total number of people reporting illness within the two-week period was 17.5 million (95% BCI: 15.5-19.8 million) in Guangdong Province. The Lorenz curve and the Gini coefficient (resulted in 0.3526) showed a moderate level of inequality in health resource distribution.ConclusionsWe developed a Bayesian geostatistical modeling framework with spatial-age structured effect to produce age-specific, high-resolution maps of the two-week illness prevalence rate and the numbers of people reporting two-week illness in Guangdong province. The methodology developed in this study can be generalized to other global regions with available relevant survey data. The mapping results will support plans for health resource allocation.

Dataset Information

Illness prevalence rate in Tibet, China: data from the 2018 National Health Service Survey.

Background

Methods

Results

Conclusion

Publications

Illness prevalence rate in Tibet, China: data from the 2018 National Health Service Survey.

Similar Datasets

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