title: Associations of blood pressure with common factors among left-behind farmers in rural China: a cross-sectional study using quantile regression analysis.
abstract: The whole range of blood pressure (BP) has important implications. Yet, published studies focus primarily on hypertension and hypotension, the two extremes of BP continuum. This study aims at exploring quantile-specific associations of BP with common factors. The study used cross-sectional survey, collected information about gender, age, education, body mass index (BMI), alcohol intake, diet risk behavior, life event index, physical activity, fasting capillary glucose (FCG), and systolic/diastolic blood pressure (SBP/DBP) and pulse pressure (PP) from farmers living in 18 villages from rural Anhui, China, and performed descriptive and multivariate and quantile regression (QR) analysis of associations of SBP, DBP, or PP with the 9 factors surveyed. A total of 4040 (86.3%) eligible farmers completed the survey. Average hypertension prevalence rate and SBP, DBP, and PP values estimated 43.20 ± 0.50% and 141.37 ± 21.98, 87.76 ± 12.23, and 53.63 ± 15.72 mm Hg, respectively. Multivariate regression analysis revealed that all the 9 factors were significantly (P < 0.05) associated with one or more of SBP, DBP, and PP. QR coefficients of SBP, DBP, or PP with different factors demonstrated divergent patterns and age, BMI, FCG, and life event index showed substantial trends along the quantile axis. Hypertension prevalence rate was high among the farmers. QR modeling provided more detailed view on associations of SBP, DBP, or PP with different factors and uncovered apparent quantile-related patterns for part of the factors. Both the population group studied and the trends in QR coefficients identified merit specific attention.
authors.affiliation: From the School of Health Services Management (XS, PC, RF, HL, GT, JC, JC, DW), Anhui Medical University, Hefei; and Lu'an Center for Diseases Prevention and Control (KL, YS, SX), Lu'an, China.
authors.forename: Xingrong
authors.initials: X
authors.lastname: Shen
authors.forename: Kaichun
authors.initials: K
authors.lastname: Li
authors.forename: Penglai
authors.initials: P
authors.lastname: Chen
authors.forename: Rui
authors.initials: R
authors.lastname: Feng
authors.forename: Han
authors.initials: H
authors.lastname: Liang
authors.forename: Guixian
authors.initials: G
authors.lastname: Tong
authors.forename: Jing
authors.initials: J
authors.lastname: Chen
authors.forename: Jing
authors.initials: J
authors.lastname: Chai
authors.forename: Yong
authors.initials: Y
authors.lastname: Shi
authors.forename: Shaoyu
authors.initials: S
authors.lastname: Xie
authors.forename: Debin
authors.initials: D
authors.lastname: Wang
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000428:Alcohol Drinking / Q000453:epidemiology; D001786:Blood Glucose / Q000032:analysis*; D001795:Blood Pressure Determination; D015992:Body Mass Index; D002681:China / Q000453:epidemiology; D003430:Cross-Sectional Studies; D003710:Demography; D005247:Feeding Behavior; D005260:Female; D006801:Humans; D006973:Hypertension / Q000097:blood / Q000175:diagnosis / Q000453:epidemiology / Q000523:psychology; D008297:Male; D008875:Middle Aged; D009043:Motor Activity / Q000502:physiology*; D015995:Prevalence; D012044:Regression Analysis; D012307:Risk Factors; D012424:Rural Population / Q000706:statistics & numerical data; D012959:Socioeconomic Factors
chemical_list: D001786:Blood Glucose