Self-Rated Health in middle-aged and elderly Chinese: distribution, determinants and associations with cardio-metabolic risk factors

The current study is part of the "Nutrition and Health of Aging Population in China" study [18]. To provide a representative sample of elderly people in China, a cross-sectional survey of 3289 subjects (1,458 men and 1,831 women) aged 50 to 70 years from one urban and two rural areas of Beijing and Shanghai (cities of north and south of China) was conducted from March to June 2005. Streets or villages were randomly selected. Then participants were randomly selected from the eligible candidates listed in the residential registration record who were stable residents for 20 years in the area and were free from the following condition: 1) severe psychological disorders, physical disabilities, cancer, CVD, Alzheimer's disease or dementia, within 6 months; or 2) currently diagnosed with tuberculosis, AIDS and other communicable disease. The sampling was conducted with an emphasis on enlisting at least 40% of men, a similar number of rural/urban residents of Beijing and Shanghai and with representation from all levels of education and income. From a residency registration list in the selected streets or villages, 3533 potential participants were identified and interviewed in their households. The total response rate was 93.1% with no difference between the cities (93.5% in Beijing and 92.7% in Shanghai). A face to face interview with one respondent per household was completed by trained physicians or public health workers using a standardized questionnaire. 3379 persons agreed to participate in the study while 3289 eligible participants with complete information from questionnaire, physical examination and biomarkers were included in the final analysis. Self-rated health status and extensive socio-demographical, lifestyle and chronic disease information were collected from the participants. The study was approved by the Institutional Review Board of Institute for Nutrition Sciences, and informed consent was obtained from each participant. Further details about the questionnaire can be found elsewhere [19].

SRH was initially recorded in 5 levels (very good, good, fair, poor, and very poor), and then categorized into two categories good (very good and good) and poor (fair, poor and very poor) [2, 13].

Socio-demographic variables included age (categorized as 50-59 and 60-70 yrs), gender, geographic region (Beijing/Shanghai), residential area (urban/rural), marital status (defined as married or without spouse (single, separated or widow)) and living status (defined as living alone versus with others). Socio-economic variables included educational attainment (categorized into low, moderate and high, based on the number of years of education as 0-6, 7-9, and ≥10 years respectively), employment status (grouped as currently employed, unemployed/on welfare system/retired) and total household income (categorized as low, moderate and high on the basis of <10,000, 10,000-29,999 and > = 30,000 RMB annually).

Lifestyle variables included social activity (defined as "yes"/"no" on the basis of frequently participating in at least one of social activities such as painting, playing chess, singing and dancing), smoking habit [defined as never, current (daily smoking, >6 months) and former (cessation of smoking >6 months)]; alcohol drinking ("yes "/"no"); physical activity level (classified as low, moderate, or high according to the guidelines for data processing and analysis of the International Physical Activity Questionnaire [5, 20]); sleep quality during the last month (well, common or poor); and sleep quantity: average total hours of daily sleep during last month (categorized as under, normal and over (<7, 7 to 9, and >9 hours per day, respectively)).

Body mass index (BMI) levels were categorized as underweight (<18.5 kg/m2), normal weight (18.5 to <24.0 kg/m2), overweight (24.0 to <28.0 kg/m2) and obese (≥28.0 kg/m2)[21].

Medical insurance defined as "yes"/"no" on the basis of benefiting from one type of medical insurance such as social, commercial or governmental paid.

Three measurements of blood pressure were taken using an electronic blood pressure monitor and the mean of the last two measurements was used for analysis. Hypertension was defined if either the systolic blood pressure (SBP) is greater than 140 mmHg or diastolic blood pressure (DBP) is greater than 90 mmHg or taking anti-hypertensives. Presence of diabetes was defined as either measured fasting glucose greater than 7.0 mmol/L or being diagnosed with type-2 diabetes or taking anti-diabetic drugs or insulin. Presence of cardiovascular disease (CVD) was defined as the presence of one or more definite manifestations of coronary heart disease or stroke. Metabolic syndrome defined according to the updated National Cholesterol Education Program Adult Treatment Panel III (ATP III) criteria for Asian Americans[19, 22].

To measure the presence of clinically relevant depressive symptoms, we used the Center for Epidemiologic Studies Depression Scale (CES-D) [23], which has been previously validated in Chinese populations [24, 25]. Using a generally accepted cutoff point of 16 for the sum of scores, CES-D score of 0-15 was defined as no or minimal depression and ≥16 was defined as minor depression [23, 26] to be consistent with the previous publications[18, 27, 28].

In order to evaluate the association between SRH and cardio-metabolic disorders (e.g. cardiovascular disease, metabolic syndrome, diabetes mellitus) we measured a number of biomarkers in our population. Overnight fasting blood samples were collected in tubes containing liquid ethylenediaminetetraacetic acid (EDTA), centrifuged at 4°C, and stored at -80°C until analysis. Total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides (TG), and glucose were measured enzymatically on an automatic analyzer (Hitachi 7080, Japan) with reagents purchased from Wako Pure Chemical Industries (Osaka, Japan). Plasma C-reactive protein (CRP) was measured by a particle-enhanced immunoturbidimetric assay (Ultrasensitive CRP kit, Orion Diagnostica, Espoo, Finland) using microparticles coated with anti-human CRP antibodies. Retinol-binding protein 4 (RBP4) was measured by a sandwich ELISA developed in-house, utilizing affinity-chromatography purified polyclonal and monoclonal antibodies generated against recombinant human RBP4, more details can be found elsewhere [29]. Interleuikin-6 (IL-6) was measured with high-sensitivity enzyme-linked immuno-sorbent assay (ELISA) (Quantikine HS IL-6 Immunoassay, R&D Systems, Inc., Minneapolis, Minnesota) with a low detect limit of 0.04 pg/ml.

Plasma adiponectin, resistin and active plasminogen activator inhibitor-1 (PAI-1) concentrations were measured by Luminex xMAPTM Technology (Linco Research Inc, St Charles, Mo) on a Bio-Rad Multiplex Suspension Array System (more details can be found elsewhere [18]. Fasting insulin was determined by radioimmunoassay (Linco Research, MO). Index of insulin resistance was calculated using updated homeostasis model assessment methods (HOMA2-IR, using the HOMA2 calculator, http://​www.​dtu.​ox.​ac.​uk) [30].

First, we evaluated the distribution of SRH by gender, geographic region and area of residence. Then using the chi-square test, analysis of variance or Wilcoxon rank-sum test, we evaluated the associations between SRH and potential determinants, based on previous literature (Table 1). Factors that significantly modified SRH in the univariate analysis or that were consistently reported as significant determinants in previous publications were included in multivariate analysis (Table 2).

All analyses were repeated stratifying by gender, region and residence one at a time and by stratifying for two of these factors simultaneously.

The associations between SRH and biomarkers of cardio-metabolic disease were tested by parametric t-test (after logarithmic transformation of the data if deemed necessary to satisfy normality assumptions), or/and non-parametric Wilcoxon rank-sum test. Biomarkers included were: resistin, PAI-1, RBP4, adiponectin, IL-6, CRP, insulin, HOMA-IR, HOMA2-IR, SBP, DBP, HDL cholesterol, LDL cholesterol, total cholesterol and triglycerides. These analyses were performed on the total population and on a sub-sample of participants that were free from CVD, cancer and diabetes.

Statistical analyses were performed with the SAS statistical package version 9.1 (SAS Institute, Cary, NC). Statistical tests were two-sided and at the 5% level of significance.

The mean age of the participants was 58.6. There were more women than men (55.7% vs. 44.3%) (Table 3). Participants were mostly married (88%), more than half of the participants were retired, 51% reported to be actively involved in social activities and 53% to have a good sleep quality. Although the majority of the participants were non-smokers (72.1% total, 95% women and 44% men), reported not to drink alcohol (71.4% total, 90% women and 48% men) and had moderate or high levels of physical activity (92.5% total, 92% women and 93% men), more than half of the population were overweight or obese (53.4% total, 56% women, 50% men). Nine percent of participants had depressive symptoms, 14% diabetes, 10% CVD, 55% hypertension and 43% had metabolic syndrome (Table 3).

One third of the study population reported their health status as good or very good (32%), almost half of the population reported their health as fair (53%) and the rest as poor or very poor (15%) (Table 3).

Sixty-four percent of those that reported good SRH were rural residents. Those with poor SRH were more likely to be retired compared to those with good SRH (60.5% vs. 44.2%). Lower prevalence of high physical activity (45.5% vs. 61.4%) and good sleep quality (44.1% vs. 72.5%) and higher prevalence of CVD (14% vs. 2.6%), diabetes (16.9% vs. 7.7%) and depressive symptoms (12.2% vs. 3.6%) was observed among those that reported poor SRH compared to their counterparts (Table 1).

Based on univariate analysis (results not shown, only p-values presented in the Table 1), males, younger people (50-60 yrs), rural residents and those living in Shanghai were more likely to have a good SRH. Single (without spouse) individuals, retired and those with higher level of education or annual income are less likely to report a good SRH. Physically active people, smokers and drinkers had higher odds to report a good level of SRH. Also benefiting from a good sleep quality was significantly associated with a good level of SRH. Depressed, CVD and diabetic participants and those with hypertension and metabolic syndrome were more likely to have a poor SRH. Social activity levels and living status showed no association with SRH in the univariate analysis and were therefore not included in the multivariate analyses.

After adjusting for all selected factors in the multivariate analysis, living in rural area (Odds Ratio (OR) 1.89; 95% Confidence Interval (CI)1.47-2.43), being employed (OR 1.36; 95% CI 1.08-1.71), drinking alcohol (OR 1.26; 95% CI 1.02-1.57), having high levels of physical activity (OR 1.64; 95% CI 1.16-2.33) and benefiting from good sleep quality (OR 2.95; 95% CI 2.22-3.91) increased the chance of reporting a good SRH. Furthermore, being free of diabetes (OR 2.03; 95% CI 1.53-2.69), hypertension (OR1.39; 95% CI 1.17-1.66), CVD (OR 3.68; 95% CI 2.39-5.66) and depression (OR 2.50; 95% CI 1.67-3.73) independent of the other determinants significantly increased the chance of feeling healthier (Table 2).

Similar findings were obtained when the analyses were stratified by residence (urban vs. rural) or gender. Quality of sleep, diabetes and CVD were found significantly associated with SRH for all subgroups. We have also found significant association of depression (apart from male), hypertension (apart from female) and physical activity (apart from rural resident) in most of the subgroups. Among rural residents, drinking alcohol (OR 1.64; 95% CI 1.21-2.23) and among urban residents region of living (Beijing vs. Shanghai OR 1.45; CI 1.10-1.91) was significantly associated with SRH (Table 2). Educational levels and smoking (current vs. never OR 1.85; CI 1.11-3.10), would affect women's SRH while alcohol drinking (No vs. yes OR 0.74; CI 0.57-0.96) was associated with men's SRH (Table 2). Residence of living was found significant for both gender subgroups (female (rural vs. urban OR 1.81; CI 1.25-2.63), male (rural vs. urban OR 2.00; CI 1.40-2.86).

After stratifying the analyses by gender and residence of living simultaneously (Table 4), quality of sleep and CVD remained the most significant determinants of SRH for all subgroups. Hypertension affected males in both urban & rural areas but not females. Region of living and diabetes were significantly associated with SRH in rural women and urban men. Depressive symptoms were significantly associated with SRH for all subgroups except urban males. Educational level, employment status and level of physical activity were only associated with urban female's SRH. Age was significant between urban males and smoking between rural males.

Significant differences in level of biomarkers (except for adiponectin) were observed between the participants with different level of SRH. The level of SRH inversely related to the levels of resistin, CRP, insulin, HOMA-IR, HOMA2-IR, systolic and diastolic blood pressure (Table 5). Trends and significant differences remained for resistin, CRP, insulin and HOMA2-IR among a healthier subgroup of participants that was free from cancer, CVD and diabetes (data not shown).