18 19 A medical diagnosis was considered to exist if a participan

18 19 A medical diagnosis was considered to exist if a participant answered ‘yes’ when asked supplier Olaparib whether a doctor had ever told them they had the condition of interest. For arthritis, a follow-up question asked whether they had been told they had osteoarthritis, rheumatoid or other arthritis. Treatment for depression and diabetes was defined by reported achievement of quality of care indicators, derived through a robust process of literature reviews, expert panel assessment and piloting.20 21 For depression, the quality indicator was about receipt of treatment since the previous wave:

“if a person is diagnosed with clinical depression, then antidepressive treatment, talking treatment or electroconvulsive treatment should be offered within 2 weeks after diagnosis unless within that period the patient has improved, or unless the patient has substance abuse or dependence, in which case treatment may wait until 8 weeks after

the patient is in a drug-or alcohol-free state.” For diabetes, treatment was measurement of HbA1c or fructosamine levels in the preceding 12 months. Treatment for angina was defined as ever being offered or currently taking β-blockers (ELSA variables hebeta or hebetb). Treatment for osteoarthritis and cataract was defined as reporting ever having had surgery for the condition. For osteoarthritis, this excluded those with hips or knees replaced due to fracture. Data on hip and knee replacements were only available for respondents aged 60 and over, and so respondents aged less than 60 years (n=3186) were excluded from the analysis of osteoarthritis. Wealth was defined as

the sum of financial, physical and housing wealth plus state and private pension income. Age was categorised into three groups: 50–59, 60–74 and 75 years and older. Analysis We used two approaches to analysis, a main analysis using serial cross-sectional data and then a subsidiary analysis using longitudinal data. Multivariable logistic regression analysis was used, with the outcome variables defined as one of illness burden, self-reported medical diagnosis or treatment for each of the five conditions in each cross-sectional wave (STATA statistical software V.12.1). This regression analysis was repeated for each of the four waves Entinostat of ELSA from 2004 to 2011 separately and then ‘overall’ for all four waves combined. For the ‘overall’ analysis, the data were reshaped into ‘long’ format in Stata statistical software, with each participant having a separate record for each wave. Intraperson correlation of outcomes was accounted for using robust adjustment with Stata, with each participant’s unique identifier included in the regression equation as a cluster variable. Missing data were excluded from the analyses. The independent variables were age group, sex and slope order of inequality.

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