Economic gradients in loneliness, social isolation and social support : evidence from the UK Biobank

Despite the substantial literature on how loneliness is associated with poor health and premature mortality, there is little detailed research on the extent of its economic gradients. We provide this evidence using a sample of around 400,000 respondents aged 40–70 years from the UK Biobank, who were assessed between 2006 and 2010. We focus on differences in loneliness, as well as social isolation and a lack of social support, across educational attainment, household income, local area deprivation, and recent experience of financial stress. We employ two statistical approaches, the first exploiting the large sample size and detailed geographical information about where respondents live, so we compare individuals who differ in their economic status but reside within the same postcode district. The second approach exploits the fact that for around 36,000 respondents we observe their social health and economic circumstances at two points in time (second wave of assessment conducted between 2014 and 2020), so we conduct a panel analysis that accounts for intercorrelations between the social health measures, and controls for incomplete follow-up of panel members. Across both approaches, we find a substantially higher probability of reporting loneliness, social isolation and a lack of social support, for men and women with lower economic status. Together with the existing health-loneliness literature, these findings establish a ‘loneliness pathway’ contributing to health inequalities, and consequently a need for effective interventions that might address loneliness and social isolation as part of a broad policy initiative on health inequalities

Does EQ-5D Tell the whole story? Statistical methods for comparing the thematic coverage of clinical and generic outcome measures, with application to breast cancer

Objectives This study aimed to develop the following: (1) methods for assessing claims in any specific application that a generic outcome measure, such as EQ-5D is deficient in its coverage of 1 or more specified domains, and (2) a simple method of judging whether any such deficiency is likely to be quantitatively important enough to call into question evaluations based on the generic instrument. Also to demonstrate the applicability of the methods in the important area of breast cancer. Methods The methodology requires a data set with observations from a generic instrument (eg, EQ-5D) and also a more comprehensive clinical instrument (eg, FACT-B [Functional Assessment of Cancer Therapy – Breast]). A standardized 3-component statistical analysis is proposed for investigating the claim that the generic measure inadequately captures some specified dimension covered by the latter instrument. A theoretically based upper bound on the bias induced by deficient coverage is derived based on the assumption that the designers of the (k-dimensional) generic instrument did succeed in identifying the k most important domains. Results Data from the MARIANNE breast cancer trial were analyzed and results suggested that impacts on personal appearance and relationships may be inadequately represented by EQ-5D. Nevertheless, the indications are that the bias in quality-adjusted life-year differences from deficient coverage by EQ-5D is likely to be modest. Conclusions The methodology offers a systematic approach to determining whether there is clear evidence consistent with any claim that a generic outcome measure such as EQ-5D misses an important specific domain. The approach is readily implementable using data sets that are available in many randomized controlled trials