Recent research on health inequalities moves beyond illustrating the importance of psychosocial factors for health to a more in-depth study of the specific psychosocial pathways involved. Social capital is a concept that captures both a buffer function of the social environment on health, as well as potential negative effects arising from social inequality and exclusion. This systematic review assesses the current evidence, and identifies gaps in knowledge, on the associations and interactions between social capital and socioeconomic inequalities in health. Through this systematic review we identified studies on the interactions between social capital and socioeconomic inequalities in health published before July 2012. The literature search resulted in 618 studies after removal of duplicates, of which 60 studies were eligible for analysis. Self-reported measures of health were most frequently used, together with different bonding, bridging and linking components of social capital. A large majority, 56 studies, confirmed a correlation between social capital and socioeconomic inequalities in health. Twelve studies reported that social capital might buffer negative health effects of low socioeconomic status and five studies concluded that social capital has a stronger positive effect on health for people with a lower socioeconomic status. There is evidence for both a buffer effect and a dependency effect of social capital on socioeconomic inequalities in health, although the studies that assess these interactions are limited in number. More evidence is needed, as identified hypotheses have implications for community action and for action on the structural causes of social inequalities.

Early interventions are recognised as key to improving life chances for children and reducing inequalities in health and well-being, however there is a paucity of high quality research into the effectiveness of interventions to address childhood health and development outcomes. Planning and implementing standalone RCTs for multiple, individual interventions would be slow, cumbersome and expensive. This paper describes the protocol for an innovative experimental birth cohort: Born in Bradford’s Better Start (BiBBS) that will simultaneously evaluate the impact of multiple early life interventions using efficient study designs. Better Start Bradford (BSB) has been allocated £49 million from the Big Lottery Fund to implement 22 interventions to improve outcomes for children aged 0–3 in three key areas: social and emotional development; communication and language development; and nutrition and obesity. The interventions will be implemented in three deprived and ethnically diverse inner city areas of Bradford. The BiBBS study aims to recruit 5000 babies, their mothers and their mothers’ partners over 5 years from January 2016-December 2020. Demographic and socioeconomic information, physical and mental health, lifestyle factors and biological samples will be collected during pregnancy. Parents and children will be linked to their routine health and local authority (including education) data throughout the children’s lives. Their participation in BSB interventions will also be tracked. BiBBS will test interventions using the Trials within Cohorts (TwiCs) approach and other quasi-experimental designs where TwiCs are neither feasible nor ethical, to evaluate these early life interventions. The effects of single interventions, and the cumulative effects of stacked (multiple) interventions on health and social outcomes during the critical early years will be measured. The focus of the BiBBS cohort is on intervention impact rather than observation. As far as we are aware BiBBS is the world’s first such experimental birth cohort study. While some risk factors for adverse health and social outcomes are increasingly well described, the solutions to tackling them remain elusive. The novel design of BiBBS can contribute much needed evidence to inform policy makers and practitioners about effective approaches to improve health and well-being for future generations.

Almost all studies in health research control or investigate socioeconomic position (SEP) as exposure or confounder. Different measures of SEP capture different aspects of the underlying construct, so efficient methodologies to combine them are needed. SEP and ethnicity are strongly associated, however not all measures of SEP may be appropriate for all ethnic groups. We used latent class analysis (LCA) to define subgroups of women with similar SEP profiles using 19 measures of SEP. Data from 11,326 women were used, from eight different ethnic groups but with the majority from White British (40%) or Pakistani (45%) backgrounds, who were recruited during pregnancy to the Born in Bradford birth cohort study. Five distinct SEP subclasses were identified in the LCA: (i) "Least socioeconomically deprived and most educated" (20%); (ii) "Employed and not materially deprived" (19%); (iii) "Employed and no access to money" (16%); (iv) "Benefits and not materially deprived" (29%) and (v) "Most economically deprived" (16%). Based on the magnitude of the point estimates, the strongest associations were that compared to White British women, Pakistani and Bangladeshi women were more likely to belong to groups: (iv) "benefits and not materially deprived" (relative risk ratio (95% CI): 5.24 (4.44, 6.19) and 3.44 (2.37, 5.00), respectively) or (v) most deprived group (2.36 (1.96, 2.84) and 3.35 (2.21, 5.06) respectively) compared to the least deprived class. White Other women were more than twice as likely to be in the (iv) "benefits and not materially deprived group" compared to White British women and all ethnic groups, other than the Mixed group, were less likely to be in the (iii) "employed and not materially deprived" group than White British women. LCA allows different aspects of an individual’s SEP to be considered in one multidimensional indicator, which can then be integrated in epidemiological analyses. Ethnicity is strongly associated with these identified subgroups. Findings from this study suggest a careful use of SEP measures in health research, especially when looking at different ethnic groups. Further replication of these findings is needed in other populations.

Born in Bradford (BiB) is a prospective multi-ethnic pregnancy and birth cohort study that was established to examine determinants of health and development during childhood and, subsequently, adult life in a deprived multi-ethnic population in the north of England. Between 2007 and 2010, the BiB cohort recruited 12,453 women who experienced 13,776 pregnancies and 13,858 births, along with 3353 of their partners. Forty five percent of the cohort are of Pakistani origin. Now that children are at primary school, the first full follow-up of the cohort is taking place. The aims of the follow-up are to investigate the determinants of children’s pre-pubertal health and development, including through understanding parents’ health and wellbeing, and to obtain data on exposures in childhood that might influence future health. We are employing a multi-method approach across three data collection arms (community-based family visits, school based physical assessment, and whole classroom cognitive, motor function and wellbeing measures) to follow-up over 9000 BiB children aged 7–11 years and their families between 2017 and 2021. We are collecting detailed parent and child questionnaires, cognitive and sensorimotor assessments, blood pressure, anthropometry and blood samples from parents and children. Dual x-ray absorptiometry body scans, accelerometry and urine samples are collected on subsamples. Informed consent is collected for continued routine data linkage to health, social care and education records. A range of engagement activities are being used to raise the profile of BiB and to disseminate findings. Our multi-method approach to recruitment and assessment provides an efficient method of collecting rich data on all family members. Data collected will enhance BiB as a resource for the international research community to study the interplay between ethnicity, socioeconomic circumstances and biology in relation to cardiometabolic health, mental health, education, cognitive and sensorimotor development and wellbeing.

BACKGROUND AND OBJECTIVES: Child well-being is important for lifelong health and well-being. Although there is a robust evidence base linking social determinants of health (eg, relative poverty and income inequality) to child well-being, social and public health policy tends to focus on interventions to mitigate their effects, rather than remove the root causes. The goal of this study was to examine associations between child well-being and income inequality. METHODS: We compared reported rates of childhood well-being in the 2007 and 2013 UNICEF reports on child well-being in wealthy countries. Twenty indicators of child well-being (excluding child poverty) were defined consistently in both the 2007 and 2013 reports. These variables were used to create an indicator of change in child well-being over the approximate decade 2000 to 2010. For our analyses of income inequality, we used the Organization for Economic Cooperation and Development Gini coefficient of income inequality for 2009 and change between 2000 and 2009, respectively. RESULTS: The overall index of child well-being in 2013 was closely and negatively correlated with income inequality (r = −0.60, P = .004) but not with average income (r = –0.3460, P = .12). Adjustment for income inequality, children in relative poverty, and the child poverty gap did not change the lack of association between average income and child well-being in 2013 in wealthy countries. Between 2000 and 2010, child well-being scores improved most in Italy, Norway, Portugal, the United Kingdom, and Germany. The biggest declines were seen in Sweden, Canada, Japan, Switzerland, and France. Countries that experienced the largest increases in income inequality had significantly greater declines in child well-being (r = –0.51, P = .02). CONCLUSIONS: Children born into socioeconomically disadvantaged families suffer worse child well-being and its lifelong implications, in all societies, worldwide. Our analyses show, however, that some wealthy societies are able to mitigate these inequalities; these societies have better child well-being, on average. This outcome has less to do with specific welfare policies or targeted interventions for poor children than to a societal commitment to greater equality.