Background: Loneliness in later life is largely presented as a problem of the individual focusing upon antecedents such as demographic or health factors. Research examining the role of the broader living environments is much rarer. We examined the relationship between loneliness and three dimensions of the lived environment: geographical region, deprivation, and area classification (urban or rural). Methods: Our sample consisted of 4663 core members (44% males) aged 50+ (wave 7 mean age 72.8, S.D. = 7.1) present both in waves 3 (2006) and 7 (2014) of the English Longitudinal Study of Ageing (ELSA). Loneliness was measured using two approaches, individual and area-based, and both waves included these questions. Individualbased (self-reported) loneliness was assessed using the three item University of California Los Angeles (UCLA) scale (ranging from 3 = not lonely to 9 = lonely) with a score of 6+ defining loneliness. We also used a novel question which asked participants to evaluate how often they felt lonely in their area of residence (area-based; ranging from 1 = often to 7 = never, using cut off 4+ to define loneliness). The lived environment was classified in three different ways: the Index of Multiple Deprivation (IMD), Government Office Regions (GOR), and area classification (urban or rural). Covariates with established relationship with loneliness including demographic factors, social engagement and health, were included in the analyses. Results: In wave 7, the prevalence of individual-based loneliness was 18% and area-based was 25%. There was limited congruence between measures: 68% participants reported no individual-or area-based loneliness and 9% reported loneliness for both measures. After adjusting for individual co-variates only one significant relationship was observed between loneliness and area-based characteristics. A significant association was observed between areabased loneliness and deprivation score, with higher levels of loneliness in more deprived areas (OR = 1.4 for highest quintile of deprivation). Conclusions: Our results indicate that loneliness in older adults is higher in the most deprived areas independent of individual-level factors. In order to develop appropriate interventions further research is required to investigate how area-level factors combine with individual-level loneliness vulnerability measures to generate increased levels of loneliness in deprived areas.

Background Despite the widespread use of the single item self-rated health (SRH) question, its reliability has never been evaluated in Chinese population. Methods We used data from the China Health and Retirement Longitudinal Study, waves 1–4 (2011–2019). In wave 1, the same SRH question was asked twice, separated by other questions, on a subset of 4533 subjects, allowing us to examine the test–retest reliability of SRH. In addition, two versions of SRH questions (the WHO and US versions) were asked (n = 11,429). Kappa (κ), weighted kappa ($${\kappa}_{w}$$ κ w ), and polychoric correlation coefficient (ρ) were used for reliability assessment. Cox proportional-hazards models were estimated to assess the predictive validity of SRH measurement for mortality over 7 years of follow up. To do so, relative index of inequality (RII) and slope index of inequality (SII) were estimated for each SRH scale. Results There was moderate to substantial test–retest reliability (κ = 0.54, $${\kappa}_{w}$$ κ w =0.63) of SRH; 31% of respondents who used the same scale twice changed their ratings after answering other questions. There was strong positive association between the two SRH measured by the two scales (ρ > 0.8). Compared with excellent/very good SRH, adjusted hazard ratios (HR) of death are 2.30 (95% CI, 1.70–3.13) for the US version and 1.86 (95% CI, 1.33–2.60) for the WHO version. Using slope indices of inequality, the WHO version estimated slightly larger mortality differences (RII = 3.50, SII = 15.53) than the US version (RII = 3.25, SII = 14.80). Conclusions In Chinese middle-aged and older population, the reliability of SRH is generally good, although the two commonly used versions of SRH scales could not be compared directly. Both indices predict mortality, with similar predictive validity.

Background Studies found that maternal education is the most frequently assessed predictor of child’s birth weight. Lower level of education was consistently found as indicator of lower child’s birthweight. In turn, inequalities in child’s birthweight have been repeatedly shown to be closely related to inequalities in later adult health. The aim of this project is to evaluate the association between the highest achieved level of maternal education and birthweight of single born babies in large English and Welsh population sample, taking into account factors such as child’s gender, parity, maternal age, partnership status, ethnicity, and household socioeconomic characteristics. Methods Using Office for National Statistics Longitudinal Study (ONS LS) based on English and Welsh Census data, information from almost quarter of a million children born since 1981 to ONS LS sample mothers were used. Maternal education was categorised in 3 categories (below secondary, completed secondary education, degree and higher), and its association with child’s birth weight was analysed by logistic regression accounting for range of available covariates. Results Significant association between the level of education and birth weight was found in crude analysis (p < 0.001). When adjusted, the magnitude of the association with education gradient declined but remained highly significant and was found to considerably increase over the years. The birth weight difference between those born to mothers with below secondary education and those born to mothers with degree increased by more than 60 grams (p for change <0.001) between 1981 and 2016. Conclusions These findings support previous evidence based on different population samples. According to our results, children of mothers with below secondary education tend to have lower birth weight. Our results suggest that the inequalities in birth weight by the highest education level achieved by mother significantly increased since 1981. Key messages • Lower levels of maternal education predict low birth weight in children. • The differences in birth weight by maternal educational demonstrate increase in inequalities over the years.