Setting and sample
In the current study, we drew the sample from the Chinese Longitudinal Ageing Social Survey (CLASS) in 2014. The CLASS was collected by the National Survey Research Center, Renmin University. A stratified, multi-stage, probabilistic sampling method to select nationally representative sample was employed, covering 28 of 31 provincial areas in China. There were 11,511 older adults were surveyed in total. In the present study, the sample comprised 8711 subjects aged 60 years or older who answered the questions on depressive symptoms and other independent variables of interests. All the participants were interviewed face-to-face by trained interviewers.
Measurement
Depressive symptoms were assessed by using a nine-item Center for Epidemiological Studies Depression Scale (CES-D), including three items assessed positive feelings, two items assessed negative emotions, two items assessed somatic symptoms, and two items assessed sense of marginalization. 9-item CES-D was reliable and valid for detecting non-psychotic mental disorders among Chinese older adults [24]. Each item had a score of 0 (rarely or none of the time), 1 (some of the time), or 2 (most of the time), with the total score ranging from 0 to 18. By reversing the coding of the positive effect items, a higher score indicates a higher level of depressive symptoms. For the current study, on a 9-item scale, the total possible score is 18 (9 items multiplied by 2, the highest response). That total score is divided by 60 (the total possible score on the full 20-item CES-D), which equals 0.3 [25]. Then, the 0.3 is multiplied by 16, resulting in a standardized cut score of 4.8 for the 9-item form of the CES-D. In this study, the internal Cronbach's alpha for the nine items was 0.75.
In the current study, the life negative events exposure was the experience of a life negative event reported by the subjects themselves in the past 12 months. The information of the life negative events, including serious diseases (self or family member), natural disaster/accident, the death of a family member (spouse, children, or relatives), were collected during the survey. Number of life negative events in past 12 months were counted and further categorized (“0”=0, “1”=1, “≥2”=2). Socioeconomic characteristics included gender (male, female), age, marital status (married, widowed/divorced/unmarried), ethnicity (Han, others), residence (rural, urban), education level (junior high school and above, primary school, never attended school), and living arrangements (lives alone, lives with others). Ten-item version of the activities of daily living (ADL) was assessed for physical disability [26]. Chronic diseases, including any health problems: hypertension, diabetes, heart disease, renal disease, liver disease, stroke, tuberculosis, arthritis, respiratory and so on, were categorized into “yes”= 1, and “no”=0.
Statistical analysis
Mean ± SD (standard deviation) was used for the description of continuous variables and percentage for categorical data. General linear regression was used to examine the association between depressive symptom score and number of life negative events in the past 12 months. Logistic regression analysis was used to estimate odds ratios (OR) and 95% confidence intervals (CI) of depression risk for each category with the lowest category as the reference group. Trends of the associations were assessed with ordinal scores assigned to categories of the number of life negative events in the past 12 months. Another analysis was done according to socio-demographical status, gender (male, female), residence (rural, urban) and living arrangements (lives alone, lives with others) to examine associations between the number of negative events in the past 12 months and depression risk under considering confounding variables. Statistical significance was declared with a two-sided p-value < 0.05. Statistical analyses were performed using SAS version 9.3 (SAS Institute Inc., Cary, NC, USA).