No abstract

navigation is a person-centred intervention delivered by lay or professional workers ('health navigators'), addressing individualised barriers to accessing healthcare. Despite recognition of health navigation as a promising intervention for migrant women, there remains a significant paucity of research on stakeholders' perspectives. The aim of this study is to understand migrant women service users' experiences and perceptions of health navigation. Methods This study is based on a multiple, instrumental case study carried out between May 2019 and January 2020 in two English cities, in collaboration with a grassroots charity and a National Health Service (NHS) programme -both providing health navigators to support migrant women. Through purposeful sampling, semi-structured interviews were conducted with migrant women using these services (n=14), with interviews conducted in English (n=9), or with interpretation in Arabic (n=4) or French (n=1). Additionally, organisational documents were examined for information on women's needs upon referral to the services. Data from interviews and documents were coded in NVivo, and analysed using reflexive thematic analysis. Results Study participants were refugee, asylum-seeking or trafficked women. They were pregnant or recent mothers, aged between 19 and 41 years. Five overarching themes were developed: 'Need for support', 'Knowledge', 'Tools for life in Britain', 'Close relationships' and 'Expectations'. Women reported needing companionship, material support and signposting -which mainstream NHS services have limited capacity to provide. They described having gained knowledge of NHS services and of pregnancy, birth and early motherhood -which they perceived as empowering and as increasing their access to healthcare. Health navigators reportedly reduced women's social isolation and helped to improve their English language proficiency, supporting women's integration into British society and promoting their general wellbeing. Finally, women described having close relationships with health navigators, but had expectations of them beyond health navigators' remit and boundaries. These themes were consistent across both case study sites. Conclusion Health navigation was viewed positively by migrant women in this study. They perceived it as improving their access to maternity care -and other healthcare servicesas well as improving their wellbeing, although greater clarity on health navigators' roles may help to manage women's expectations. Future research could explore health navigation interventions for migrant women operating beyond the first six weeks of motherhood.

Background Obesity is a key public health issue worldwide. Accurate estimates of its full impacts on health, social, and economic outcomes are required, but are difficult to obtain due to bias from confounding and reverse causality (the impact of social and economic factors on obesity). Methods Using data from the UK Biobank and ALSPAC, we applied a genetic causal inference approach (Mendelian Randomization, MR) to estimate the impact of body mass index (BMI) on key social and economic outcomes. Because genetic variants are assigned before birth and cannot change, estimates from MR studies are less liable to confounding and reverse causation. Results Effects of higher BMI were often larger in MR than conventional (non-genetic) models, suggesting previous studies may have underestimated the impact of BMI. For example, in adolescents, MR models implied a standard deviation increase in BMI led to exam scores around 1/3 of a grade lower in all subjects at age 16, and 8.7% (CI: 1.8% to 16.1%) more school absence. In adults a 5kg/m2 increase in BMI corresponded, among other negative outcomes, to £2,778 less annual household income (CI: £1,864 to £3,693), less chance of owning one's home (-1.6%, CI: -2.4% to -0.8%), and higher chance of being lonely (2.4%, CI: 1.4% to 3.5%). At £21.22 (CI: £14.35 to £28.07) per person per marginal kg/m2 per year, MR estimates for inpatient hospital costs were around 40% higher than conventional estimates. Conclusions Findings from causal inference based on genetic variation indicate that high BMI has negative impacts on social and economic outcomes that may be larger than previously estimated. This evidence highlights the potential social and economic value of preventing high BMI across the life course. Key messages High BMI has considerable negative impacts not only for health, but for individuals’ education and socioeconomic outcomes, and overall health care costs. Previous attempts to quantify these effects may have underestimated BMI’s full impact.