Association between social health status and health-related quality of life among community-dwelling elderly in Zhejiang

Our data were derived from “Development of health assessment instruments and parameter specification for the elderly” project, which has been described in detail previously [15]. Briefly, this was a cross-sectional study based on community-dwelling elderly individuals from July 2018 to September 2018 in Zhejiang, China. Subjects were enrolled from 12 communities of Yiwu county in Jinhua city and Jianggan district in Hangzhou city, Zhejiang. A convenience sampling method stratified by gender and age was used in each community, based on the distribution of age and gender in the elderly population in Zhejiang. Community-dwelling persons aged 60 years and older were recruited in the current study. Individuals were not eligible if they were bed-ridden or could not participate in their daily living activities by themselves due to serious physical disease or had cognitive problems. All participants were informed to be face-to-face interviewed at adjacent community health centers by strictly trained interviewers. This study was approved by the Ethics Committee of School of Medicine, Zhejiang University, Hangzhou, China. Written informed consent was obtained from all participants before the face-to-face interview.

Social health status was measured through the long-form of the SHSE (SHSE-L). The 25-item scale was designed to assess social health status of the elderly (including two aspects: individual and society). Individual dimensions consist of Social Support (including emotional support, information support, and instrumental support), and Social Adjustment (including social participation, social relationships, and ego system); Social dimension is perceived environment resource (including built environment and community manage/service) [15]. Three different scoring methods were used in this study: 1. For multiple option items, scoring was based on the number of selected options; 2. For single option items, scoring was based on the serial number of the single option; 3. For items about passage time, scoring was based on the estimated time and means of transportation. Detailed information and scoring criteria could be available in the additional file 1. Crude total score of scale was transformed into standard score (T score), based on a previous study performed by Hembling (1984) [23]. T score was divided into three categories of social health status according to standard norm: poor (T score ≤ 40), moderate(40 < T score ≤ 60), and good (60 < T score ≤ 90) [15]. The SHSE-L has been established and validated in the Hangzhou elderly population. The test-retest variability was 0.77, internal consistency reliability- Cronbach’s alpha was 0.79, concurrent validity was 0.64, and goodness of fit was 0.95 in construct validity [15].

We used the 12-item Short-Form Health Survey (SF-12) to evaluate the HR-QOL; SF-12 is a concise questionnaire that evaluates the quality of life in Chinese elderly [24]. The 12 items in SF-12 are grouped into 8 main domains: general health, physical functioning, physical role functioning, bodily pain, vitality, social functioning, emotional role functioning, and mental health. These dimensions can be categorized into the Physical Component Summary (PCS) and the Mental Component Summary (MCS). The PCS was calculated based on the sum of the first four items, and the MCS was determined based on the sum of the last four items [25]. We calculated the scores of PCS, MCS, and SF-12 total score that represented a mean value of the PCS and MCS scores. The detailed calculations of PCS and MCS have been published previously [26], and total score of SF-12 was calculated based on the measurement of SF-36 total score in previous studies [26‐28].

Demographic data were obtained using a standard questionnaire. Three categories of covariates were included in the analyses: socio-demographic characteristics, health-related behaviors, and health conditions. Socio-demographic characteristics included the following variables: region (urban or rural), gender (male or female), age group(60–74 or ≥ 75 years), marital status (married, widowed or others), education level (lower than primary school, primary school, middle school, or high school and higher), monthly income(< 1000, 1000–1999, 2000–2999,3000–3999,≥4000 Chinese Yuan (CNY)), living arrangement (living with spouse, living with children, living with spouse and children, living alone or others), and body mass index (BMI). BMI was calculated as weight in kilograms divided by the square of height in meters and divided into three levels according to the Chinese BMI criteria:<18.5,18.5–23.9 or ≥ 24.0 kg/m². Health-related behaviors included smoking (yes or no), drinking alcohol (yes or no), drinking tea (yes or no) and weekly physical activity (≤1 time, 2–4 times or>4 times). Smokers were defined as individuals who smoked 1 cigarette or more per day for 3 months or more. Alcohol drinkers were defined as individuals who drank one glass of beer, liquor, yellow rice wine or red wine per week for more than 1 year [29]. Tea consumption was defined as drinking at least one cup of tea per day for 1 year. Valid physical activity was defined as at least 15 min at a time [30]. Health conditions included depression symptom (yes or no) and the number of chronic conditions (none, one, two or more). Depression symptom was measured by the Geriatric Depression Scale (GDS). Chronic conditions were self-reported, including hypertension, coronary heart disease (CHD), diabetes, stroke, osteoporosis, and arthritis.

Continuous and categorical variables were described as mean ± standard deviation (SD) and n (%), respectively. T-test and Analysis of Variance (ANOVA) were used to compare the differences in different categories for continuous variables of PCS, MCS and SF-12 total score. We used multivariate linear regression models to estimate beta (β) and 95% confidence intervals (95% CI) for examining the associations of social health status with PCS or MCS or SF-12 total score. All models were adjusted for potential covariates. Collinearity was assessed by using the correlation matrix of the estimated parameters, and variance inflation factor (VIF). For all analyses, P-value < 0.05 (two-sided) was considered to be statistically significant. All data were analyzed using the Statistical Package for Social Sciences (SPSS) version 24.0.