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

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.

Chronic Pain and Associated Factors Related to Depression among Older Patients in Hanoi, Vietnam

“…Age significantly interacts with pain severity, especially people over 70 years old. This is consistent with a study from China [22]. Therefore, pain management should be modified and designed for different ages and genders.…”

“…It is explained that older patients with chronic pain tend to develop depressive symptoms more often than older people in rural areas with non-chronic pain. The proportion of depressive symptoms in our sample is similar to that in the study from Lauren R [22]. Considering additional probably related factors of depression among the elderly, we found some positive associated factors mentioned above, such as pain location [19,21] and comorbidity [9].…”

Predictors of pain severity among community-dwelling older adults with pain in the United States

“…This parallels the findings of previous research in a Chinese population that also found self-rated physical health was a predictor of pain severity. [ 21 ] Another study found that lower pain intensity among individuals with chronic pain was associated with better self-perception of health. [ 22 ] Interestingly, however, perceived mental health status was not associated with pain severity.…”

Predictors of pain in general ageing populations: results from a multi-country analysis based on ATHLOS harmonized database

“…A large amount of studies identified potential predictors of pain, both in clinical trials and in population or cohort studies. Among population and cohort studies, evidence existed on the impact of sociodemographic characteristics, with females [26][27][28][29][30][31][32][33] and older people [6,27,28,31,32,34] reporting higher pain rates or severity. Also, people with lower education level and those unemployed had higher pain rates [35,36], but contrasting results were found with reference to socioeconomic position: in fact, Chen and colleagues found that people with a lower socioeconomic class had a more severe trajectory with regard to low back pain severity and persistence [37], whereas Elsharydah and colleagues found that higher median household income was associated with higher rate of complex regional pain syndrome type 1 [30].…”