Life events and chronic physical conditions among left-behind farmers in rural China a cross-sectional study

BMC Public Health. 2015 Jul 1:15:594. doi: 10.1186/s12889-015-1877-0.

Abstract

Background: This study investigates the relationships between life events and chronic physical conditions among left behind farmers, a newly emerged weak group in vast rural China.

Methods: The study collected information about life events, chronic physical conditions, blood pressure and fasting blood glucose from 4681 famers living in 18 randomly selected villages (Lu'an, Anhui, China) from early November 2013 to the end of December 2013. It compared the risk and odds ratios (RRs/ORs) among different subgroups divided according two life event indices derived by adding up un-weighted-ratings and weighted-ratings based on multivariate logistic regression coefficients respectively.

Results: A total of 4040 (86.3 % eligible) farmers completed the survey. RRs between farmers with lower than the first 1/15-percentile of life event index and with higher life event index scores ranged 1.43-5.79 for chronic gastritis and 0.42-9.07 for prostatitis, 1.01-4.97 for cervicitis/vaginitis, 1.45-3.28 for cardio-cerebrovascular diseases, 1.12-1.58 for hypertension, 1.00-1.66 for diabetes, 1.07-3.35 for pre-diabetes and 5.00-55.00 for "other chronic physical conditions".

Conclusions: Life events were independently linked with most of the chronic physical conditions in a dose-effectiveness way. RRs between subgroups divided by given percentile cutoff points of life event index compiled using logistic regression models turned out to be substantially higher than that between subgroups divided by same cutoff points of life event index produced via summing up the un-weighted Likert ratings of all the events studied.

MeSH terms

  • Adult
  • Aged
  • Blood Glucose
  • Blood Pressure
  • China / epidemiology
  • Chronic Disease / epidemiology*
  • Cross-Sectional Studies
  • Farmers / statistics & numerical data*
  • Female
  • Humans
  • Life Change Events
  • Logistic Models
  • Male
  • Middle Aged
  • Odds Ratio
  • Prevalence
  • Rural Population / statistics & numerical data*

Substances

  • Blood Glucose