Wave 2 assessed 8780 core participants. Our inclusion criteria were consent to data linkage and availability of linked data, and completion of baseline self completion interview and questionnaire, which provided data on baseline receptive arts engagement and covariates. A total of 8552 participants gave consent to data linkage and their records were followed up (97.4%); 7620 completed the questionnaire; and 6710 provided full usable data across all measures so were included in analyses ( fig 1 ).

We included participants from the English Longitudinal Study of Ageing (ELSA), a multiwave, nationally representative cohort study of community dwelling adults aged 50 years and older. Households included had previously responded to the Health Survey for England in 1998, 1999, or 2001 (wave 0). 25 ELSA started in 2002 and the same people have been interviewed every two years. For our analysis, we used data from wave 2 of ELSA (2004-05) as our baseline because this wave contained relevant data on our exposure and covariates. Core participants who provided data at wave 2 were included in our study and followed up by linkage to mortality data from the National Health Service central register. The latest available mortality data were from March 2018 (an average follow-up of 12 years and two months, maximum 13.8 years).

Social covariates included perceived loneliness (measured using the four item University of California, Los Angeles (UCLA) loneliness scale); the number of reported close friends (0, 1-2, 3-5, and 6 or more); whether participants lived alone; the frequency with which participants engaged in civic activities (including political parties, trade unions, environmental groups, tenants or residents associations, neighbourhood watch, church or religious groups, charitable associations, evening classes, social clubs, sports clubs, exercise classes, or other clubs or societies); the frequency with which people saw friends, family, or children (less than once a month, once or twice a month, once or twice a week, or three or more times a week); and whether participants had a hobby or pastime.

Health related covariates were self reported eyesight (fair or poor v excellent, very good, or good), self reported hearing (fair or poor v excellent, very good, or good), and depressive symptoms (as a continuous measure using the Centre for Epidemiological Studies Depression scale); whether participants had been diagnosed as having any other psychiatric condition (including anxiety, psychosis, major depression, mood swings, or other emotional problems); whether participants reported currently having a diagnosis of cancer, lung disease, or cardiovascular disease (including high blood pressure, angina, a previous heart attack, heart failure, a heart murmur, an abnormal rhythm, diabetes, a previous stroke, high cholesterol, or other heart trouble); whether participants reported having a history of any other long term condition (including arthritis, asthma, osteoporosis, Parkinson’s disease, Alzheimer’s disease, or dementia); whether participants currently smoked; frequency of alcohol consumption (1-2 days a week, 3-4 days a week, 5-6 days a week, or daily); whether participants were sedentary (categorised as engaging in mild, moderate, or vigorous activity less than once a week); whether participants had any problems with their mobility (including walking 100 yards, sitting for two hours, getting up from a chair, climbing stairs, stooping, extending their arms, moving large objects, carrying weights, or picking up objects); whether participants had any difficulty in carrying out daily tasks (including dressing, bathing, eating, using a toilet, shopping, taking drugs, or making telephone calls); whether participants had osteoporosis; and cognition (an average of standardised scores of memory, executive function, processing speed, and orientation in time using validated measures from a neuropsychological battery 29 ).

We identified factors that predicted receptive arts engagement and mortality by using directed acyclic graphs and included these factors as covariates. 27 Demographic and socioeconomic covariates were age, sex, marital status (married or cohabiting v single, widowed, or divorced), and ethnicity (white British v other); educational qualifications (no educational qualifications; education to GCE, O level, national vocational qualification (NVQ) 2 (qualifications at age 16); education to NVQ3, GCE, A level (qualifications at age 18); higher qualification, NVQ4, NVQ5, degree); total non-pension wealth (which combines net financial and physical wealth with net owner occupied housing wealth, categorised in fifths) 28 ; employment status (working full or part time v not working or retired); and occupational status (managerial and professional occupations, intermediate occupations, small employers and self employed, lower supervisory and technical occupations, and semiroutine occupations; categorised using the five item National Statistics Socio-economic Classification).

We focused specifically on receptive arts activities at baseline (2004-05), including going to the theatre, concerts, opera, museums, art galleries, and exhibitions (“receptive arts engagement”). 26 Frequency of engagement with any of these activities was categorised as never, infrequent (less than once a year; once or twice a year), or frequent (every few months; monthly or more).

Statistical analysis

Table 1 shows the importance of baseline differences between participants based on end mortality status and arts engagement, which was calculated using χ2 tests. We estimated cumulative mortality by using the Kaplan-Meier method. Unadjusted and adjusted hazard ratios of mortality and 95% confidence intervals were calculated using Cox proportional hazards regression models. We measured survival time in months from birth date to death, censoring (the date of the last interview before drop out), or latest available follow-up (165 months from baseline). Sensitivity analyses that used survival time from baseline interview produced comparable results. We adjusted models for demographic variables (age, sex, marital status, ethnicity, educational qualifications, wealth, employment status, and occupational status); health related variables (eyesight, hearing, depressive symptoms, other psychiatric conditions, diagnosis of cancer, lung disease or cardiovascular disease, history of any other long-term condition, smoking, alcohol consumption, sedentary behaviours, mobility, problems in undertaking activities of daily living, osteoporosis, and cognition); and social covariates (loneliness, number of close friends, living alone, frequency of civic engagement, frequency of social engagement, and whether participants had a hobby or pastime).

Table 1 Demographic characteristics of sample according to deaths and receptive arts engagement View this table:

We stratified analyses by age at which participants’ arts engagement was recorded, whether participants had cancer at baseline, and whether participants had problems that affected mobility. With these adjustments made, the proportionate hazards assumption was met (tested using the Schoenfeld residuals test). To explore the minimum strength of association that any unmeasured confounder would need to fully explain away any association, we calculated the E value, which is a measure of whether the inclusion of further confounders is likely to lead to the attenuation of results.30 All analyses were weighted using inverse probability weights to ensure national representation and to take account of differential non-response. We additionally explored whether differences in baseline factors between those who do and do not engage in arts could explain an association between receptive arts engagement and mortality by rerunning analyses using nested models of covariates and by calculating the percentage of protective association explained (PPAE) by including such variables in the model using the equation: PPAE=(HR (E+C+X)–HR (E+C))/(1–HR (E+C))*100, where HR=hazard ratio, E=exposure, C=covariates, and X=explanatory variable being tested.31 We confirmed that there were no issues with collinearity and all models met regression assumptions.

We carried out three sets of sensitivity analyses. Our first set assessed whether results were found consistently across subgroups (by rerunning analyses on subgroups) or if certain factors acted as moderators (by including interaction terms in models). In relation to demographics, we tested age and sex specifically. In relation to socioeconomic factors, we tested employment status, wealth, education, and social status. Finally, in relation to social factors, we tested marital status, living alone, loneliness, number of friends, frequency of social engagement, and civic engagement.

Our second set of sensitivity analyses tested with greater rigour whether some of our identified confounders could account for any associations by including a range of further factors that could have acted as confounders. To test whether results were because of physical function, in addition to controlling for sedentary behaviours, we further adjusted for frequency of vigorous physical activity and presence of any mobility problems that affected walking. To test whether broader aspects of socioeconomic status could have confounded associations, we additionally included wealth in tenths rather than fifths for greater nuance; and controlled for retirement status, whether participants were spending time regularly volunteering, or whether participants had undertaken any further education or training in the past 12 months. Further, we considered whether, regardless of socioeconomic status, aspects of life demands, autonomy, or discretion over free time activities could affect ability to engage in cultural activities and longevity. So we additionally adjusted for whether participants felt they had control over what happened in most situations, whether they felt they had different demands in their lives that were hard to combine, and whether they felt they had enough time to do everything they wanted to. Finally, to test whether results were related to accessibility, perhaps because participants lived in more rural areas or areas of higher deprivation, we additionally controlled for the type of residential area in which participants lived (urban v town, and fringe v village v hamlet or other sparse dwelling); we also linked lower layer super output areas data from ELSA with data from the index of multiple deprivation (the official measure of relative deprivation for small areas of England) and included these scores in fifths for each participant in the analysis.

Our third set of sensitivity analyses tested the broader assumptions of our statistical models. To try and reduce the potential for reverse causality (whereby participants had unidentified health conditions that might have affected their participation in cultural activities and predisposed them to premature mortality), we excluded deaths in the two years after baseline. To deal with missing data on covariates and exposure for people who had completed questionnaires but omitted certain items (12%), we used multiple imputation by chained equations using predictor variables in the mortality models to create 20 imputed datasets, which returned the sample size to 7620. We did not impute data on participants who had not completed questionnaires because we could not confirm that these data were missing at random. Additionally, in our main analyses, we used semiparametric methods. But as these did not estimate the baseline hazard, we also tested whether results were consistent when using a parametric model. Because the hazard function showed similarities to an exponential distribution, we used an exponential proportional hazards model, with Akaike’s information criterion and the Bayesian information criterion showing similarity of fit to a Weibull model; however, Wald tests for ĸ=1 confirmed best fit for the exponential model compared with other parametric proportional hazard models tested.

Finally, we used ICD-10 (international classification of diseases, 10th revision) codes to recategorise death by cause of death into four main categories (cardiovascular disease, cancer, respiratory, and other), and reran analyses to determine if results varied by cause of death. Only two participants were omitted owing to unknown cause of death. All analyses were carried out using Stata version 14 (Statacorp).