Different predictors of pain severity across age and gender of a Chinese rural population: a cross-sectional survey

Author:

Liu Xiao-kun,Xiao Shui-yuan,Zhou Liang,Hu Mi,Liu Hui-ming

Abstract

ObjectivesTo investigate a 4-week period of pain prevalence and the risk factors of experiencing pain among a rural Chinese population sample. To explore the psychosocial and health condition predictors of pain severity and the interactions of age and gender with these factors in real-life situations among the general adult population in China.MethodsData were collected from a random multistage sample of 2052 participants (response rate=95%) in the rural areas of Liuyang, China. Visual analogue scale was used to assess participants’ pain experienced and a series of internationally validated instruments to assess their sociodemographic characteristics, self-reported health status, depression symptoms, anxiety symptoms, sleep quality, self-efficacy and perceived stress.ResultsThe pain prevalence over the 4-week period in rural China was 66.18% (62.84% for men and 68.82% for women). A logistic regression model revealed that being female (adjusted OR=1.58, 95% CI 1.24 to 2.02), age (adjusted OR=1.03, 95% CI 1.02 to 1.05), depressive symptoms (adjusted OR=1.07, 95% CI 1.02 to 1.13) and medium-quality sleep (adjusted OR=2.14, 95% CI 1.26 to 3.64) were significant risk factors for experiencing pain. General linear model analyses revealed that (1) pain severity of rural Chinese was related to self-rated physical health and social health; (2) the interactions of age, gender with employment status, depression symptoms, perceived stress and physical health were significant. Simple effect testing revealed that in different age groups, gender interacted with employment status, depression symptoms, perceived stress and physical health differently.ConclusionsImproving physical and social health could be effective in reducing the severity of pain and the treatment of pain should be designed specifically for different ages and genders among the general population.

Funder

the National Science and Technology Support Program, China

China Medical Board (CMB)

Publisher

BMJ

Subject

General Medicine

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