Within each EA, 20 households with one or more 50+ individuals were selected. All the 50+ year olds within the selected SCH772984 ic50 households were then interviewed face-to-face regarding their household characteristics, socio-demographic and work history, perceived health status, risk factors and preventive health behaviors, chronic

conditions and health services coverage, health care utilization, subjective well-being and quality of life, and social cohesion. In addition, anthropometric measurements were recorded and blood spots for biomarkers were collected. Respondents also completed performance tests. Field work and data entry were undertaken between May 2007 and June 2008. The total household population was 27 988 from 5 266 households. In assessing subjective well-being, respondents were asked whether they had enough money and energy to meet their daily needs. They were also asked this website how satisfied they were with their health, themselves, their ability to perform daily living activities (this may be lacking or limited by disability despite having the energy required for these activities), their interpersonal

relationships and the conditions of their living place (place of abode). Then they were asked how satisfied they were with life putting all the above together. Their response to this last question was used as the single item measure for SWB in this study.27 The detailed methods for data collection in the SAGE have been described by Kowal et al.28 Data Analysis The effect of the following variables of interest on life satisfaction as a proxy measure for SWB were assessed in this study; age of respondents, sex of respondents, ethnic background, current marital status, highest level of education completed, income quintile of respondent, religious denomination/affiliation. Although SWB can be measured using three primary types

of instruments, this study used the single item measure of life satisfaction as a measure for SWB because happiness and life satisfaction translate well across cultures, but some of the items in multi-item scales do not. Descriptive statistics (frequencies, percentages, means and standard deviations) were calculated. Bivariate analyses as well as multinomial logistic regression analysis were also carried out at the 95% confidence level to establish any relationship between the independent variables and the outcome variable (level of satisfaction Adenylyl cyclase with life). The level of satisfaction with life was measured on a likert scale ranging from 1(very dissatisfied with life) through to 5 (very satisfied with life). This was recoded into two groups for the purpose of logistic regression. Group 1 (satisfied with life) was made up of those who answered “satisfied” and “very satisfied” to the question on “level of satisfaction with life” while group 2 (not satisfied with life) was made up of those who answered “very dissatisfied”, “dissatisfied” and “indifferent/neutral” to that question.