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Regional economic development, household income, gender and hypertension: evidence from half a million Chinese

BACKGROUND: Hypertension may be influenced by multiple factors, including social and individual determinants. Regional and individual economic disparity in China is closely associated with such factors that may give rise to diverse health outcomes. This study examines the relationship between region...

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Detalles Bibliográficos
Autores principales: Tang, Kun, Zhang, Yu, Wang, Hanyu, Tan, Shi Hui, Bai, Lin, Liu, Yuning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7288507/
https://www.ncbi.nlm.nih.gov/pubmed/32522178
http://dx.doi.org/10.1186/s12889-020-09002-y
Descripción
Sumario:BACKGROUND: Hypertension may be influenced by multiple factors, including social and individual determinants. Regional and individual economic disparity in China is closely associated with such factors that may give rise to diverse health outcomes. This study examines the relationship between regional economic development, household income, gender and hypertension prevalence in China. METHODS: This study utilized data from the China Kadoorie Biobank (CKB), a population-based study on half a million Chinese adults from 10 geographically distinct regions. Hypertension was identified by a measured systolic blood pressure/diastolic blood pressure ≥ 140/90 mmHg or receiving treatment. Regional economic development was inferred from GDP per capita at the time of the study. A logistic regression based method was used in calculating the prevalence of hypertension in different household income, regional economic development, and gender groups, adjusting for demographic, social-economic and lifestyle factors. RESULTS: The prevalence of hypertension was the lowest in the medium GDP per capita areas in both male (31.62, 95% CI: 31.26–31.98%) and female (22.85, 95% CI: 22.50–23.19%) as compared to that in the low GDP per capita regions (male: 32.75, 95% CI 32.41–33.08%; female: 32.12, 95% CI: 31.78–32.47%) and high GDP per capita areas (male: 39.74, 95% CI: 39.33–40.16%; female: 35.19, 95% CI: 34.74–35.65%). There was an inverse relationship between hypertension and household income in the low and high GDP areas and an U-shaped association in the medium GDP per capita areas. Higher hypertension prevalence was observed in males across all GDP per capita areas. The negative correlation between hypertension and household income (across all GDP per captia areas) was stronger in females than in males. CONCLUSIONS: The present study underlined the important influence of regional economic development, household income and gender on hypertension. Interventions for hypertension prevention and management should take into consideration the influence of sex difference and socioeconomic disparities at both micro- and macro- levels, in addition to a person-centered approach.