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Background: We investigated the potential impacts of child poverty (CP) reduction scenarios on population health and health inequalities in England between 2024 and 2033., Methods: We combined aggregate local authority-level data with published and newly created estimates on the association between CP and the rate per 100 000 of infant mortality, children (aged <16) looked after, child (aged <16) hospitalisations for nutritional anaemia and child (aged <16) all-cause emergency hospital admissions. We modelled relative, absolute (per 100 000) and total (per total population) annual changes for these outcomes under three CP reduction scenarios between 2024 and 2033- low-ambition (15% reduction), medium-ambition (25% reduction) and high-ambition (35% reduction)-compared with a baseline CP scenario (15% increase). Annual changes were aggregated between 2024 and 2033 at national, regional and deprivation (IMD tertiles) levels to investigate inequalities., Results: All CP reduction scenarios would result in substantial improvements to child health. Meeting the high-ambition reduction would decrease total cases of infant mortality (293; 95% CI 118 to 461), children looked after (4696; 95% CI 1987 to 7593), nutritional anaemia (458, 95% CI 336 to 574) and emergency admissions (32 650; 95% CI 4022 to 61 126) between 2024 and 2033. Northern regions (eg, North East) exhibited the greatest relative and absolute benefit. The most deprived tertile would experience the largest relative, absolute and total benefit; under high-ambition reduction, total infant mortality cases were predicted to fall by 126 (95% CI 51 to 199) in the most deprived tertile compared with 71 (95% CI 29 to 112) in the least between 2024 and 2033., Conclusions: Achieving reductions in CP could substantially improve child health and reduce health inequalities in England., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Background: In many high-income countries, body mass index (BMI)/obesity levels are inversely associated with socio-economic position (SEP). Little is known whether socio-economic patterns in BMI trajectories throughout childhood differ by ethnicity, especially in the United Kingdom., Objectives: To investigate socio-economic disparities in child-to-adolescent BMI trajectories and risks of overweight and obesity during adolescence across ethnic groups., Methods: Mixed-effects fractional polynomial and multinomial regression models were applied to estimate socio-economic differences in BMI trajectories (3-14 years) and risk of overweight/obesity at 14 years, respectively, in the UK Millennium Cohort Study (n = 15 996). Analysis was stratified by ethnicity., Result: Poverty was associated with higher BMI in children of White and South Asian origins, with a small difference at 3 years, which widened with age to 0.75 kg/m 2 (95% CI, 0.59-0.91) and 0.77 kg/m 2 (0.26-1.27) at 14 years for the White and South Asian groups, respectively. There was a reverse income-BMI association in children of Black (African-Caribbean) origin with the poverty group having a lower BMI (-0.37 kg/m 2 [-0.71 to -0.04] at 5 years; -0.95 kg/m 2 [-1.79 to -0.11] at 14 years). These patterns also presented with maternal education as a SEP indicator and for obesity at 14 years., Conclusions: Socio-economic advantage may not be universally associated with lower BMI, which should be considered when planning obesity interventions. The positive SEP-BMI association in children of Black origin requires replication and merits further investigation into underpinning mechanisms., (© 2019 The Authors. Pediatric Obesity published by John Wiley & Sons Ltd on behalf of World Obesity Federation.)

Background: Despite rises in reconstituted and lone-parent families, relatively little is known about how the health of children in different family types varies, and the extent to which any differences might be explained by poverty. The authors examined this using cross-sectional data on 13 681 seven-year-olds from the Millennium Cohort Study., Methods: The authors estimated RRs and 95% CIs for having poor physical (general health, long-standing illness, injury, overweight, asthma, fits) and mental health (using strengths and difficulties scores) according to family structure using Poisson regression. The authors adjusted for confounders (aRR) and then investigated the role of poverty as a mediator by entering a poverty score (based on income, receipt of benefits, subjective poverty and material deprivation) into the main model., Results: Children living in reconstituted and lone-parent families were at a slight increased risk of poor health compared with those living with two natural parents. Adjusting for poverty tended to remove the elevated risk of poor physical health in children living in lone-parent and reconstituted families. However, for the mental health outcomes, poverty tended to remove the elevated risk for lone parents but not for reconstituted families. For example, the aRR for borderline-abnormal total difficulties fell from 1.45 (1.22 to 1.72) to 1.34 (1.13 to 1.59) in children living in reconstituted families and from 1.29 (1.14 to 1.45) to 1.05 (0.92 to 1.19) in those living with lone parents., Conclusions: Poor physical and mental health was slightly more prevalent in children living in lone-parent or reconstituted families. Poverty reduction may help to reduce these differences, especially for children living with lone parents; however, alternative mechanisms should be also explored, particularly for children living in reconstituted families.

Background: Employment and income are important determinants of mental health (MH), but the extent that unemployment effects are mediated by reduced income is unclear. We estimated the total effect (TE) of unemployment on MH and the controlled direct effect (CDE) not acting via income. Methods: We included adults 25–64 years from nine waves of the UK Household Longitudinal Study (n = 45 497/ obs = 202 297). Unemployment was defined as not being in paid employment; common mental disorder (CMD) was defined as General Health Questionnaire-12 score ≥4. We conducted causal mediation analysis using double-robust marginal structural modelling, estimating odds ratios (OR) and absolute differences for effects of unemployment on CMD in the same year, before (TE) and after (CDE) blocking the income pathway. We calculated percentage mediation by income, with bootstrapped standard errors. Results: The TE of unemployment on CMD risk was OR 1.66 (95% CI 1.57–1.76), with 7.09% (6.21–7.97) absolute difference in prevalence; equivalent CDEs were OR 1.55 (1.46–1.66) and 6.08% (5.13–7.03). Income mediated 14.22% (8.04–20.40) of the TE. Percentage mediation was higher for job losses [15.10% (6.81–23.39)] than gains [8.77% (0.36–17.19)]; it was lowest for those 25–40 years [7.99% (−2.57 to 18.51)] and in poverty [2.63% (−2.22 to 7.49)]. Conclusions: A high proportion of the short-term effect of unemployment on MH is not explained by income, particularly for younger people and those in poverty. Population attributable fractions suggested 16.49% of CMD burden was due to unemployment, with 13.90% directly attributable to job loss rather than resultant income changes. Similar analytical approaches could explore how this differs across contexts, by other factors, and consider longer-term effects. [ABSTRACT FROM AUTHOR]

Background Addressing poverty through taxation or welfare policies is likely important for public mental health; however, few studies assess poverty's effects using causal epidemiology. We estimated the effect of poverty on mental health. Methods We used data on working-age adults (25–64 years) from nine waves of the UK Household Longitudinal Survey (2009–19; n  = 45 497/observations = 202 207 following multiple imputation). We defined poverty as a household equivalized income <60% median, and the outcome likely common mental disorder (CMD) as a General Health Questionnaire-12 score ≥4. We used double-robust marginal structural modelling with inverse probability of treatment weights to generate absolute and relative effects. Supplementary analyses separated transitions into/out of poverty, and stratified by gender, education, and age. We quantified potential impact through population attributable fractions (PAFs) with bootstrapped standard errors. Results Good balance of confounders was achieved between exposure groups, with 45 830 observations (22.65%) reporting poverty. The absolute effect of poverty on CMD prevalence was 2.15% [%-point change; 95% confidence interval (CI) 1.45, 2.84]; prevalence in those unexposed was 20.59% (95% CI 20.29%, 20.88%), and the odds ratio was 1.17 (95% CI 1.12, 1.24). There was a larger absolute effect for transitions into poverty [2.46% (95% CI 1.56, 3.36)] than transitions out of poverty [–1.49% (95% CI –2.46, –0.53)]. Effects were also slightly larger in women than men [2.34% (95% CI 1.41, 3.26) versus 1.73% (95% CI 0.72, 2.74)]. The PAF for moving into poverty was 6.34% (95% CI 4.23, 8.45). Conclusions PAFs derived from our causal estimates suggest moves into poverty account for just over 6% of the burden of CMD in the UK working-age population, with larger effects in women. [ABSTRACT FROM AUTHOR]

Children living in reconstituted and lone parent families are at greater risk of poorer socio-emotional wellbeing than those in couple families. A life course approach can help us to understand the dynamics of family structure and how they influence child wellbeing, through consideration of sensitive and critical periods, accumulation, and trajectories of stability or change. We do this using data on 10,357 children from the UK Millennium Cohort Study from infancy to middle childhood. Family structure (natural couple, lone parent, reconstituted family) was measured at 9 months, 3, 5 and 7 years. We used a structured life course approach to examine how family structure might influence socio-emotional wellbeing throughout childhood. We also considered the role of early-life selection, and cumulative poverty (number of sweeps spent in income poverty). We found no evidence of sensitive or critical periods for exposure to certain family types. A measure capturing trajectories of family structure stability or change was as predictive of socio-emotional wellbeing at age 7 as a saturated measure representing all permutations of family structure over time. Compared to children living in a natural couple family throughout, all other groups were more likely to experience poor socio-emotional wellbeing, although children who were living in a natural couple family which transitioned to a lone parent family had a lower prevalence ratio (PR 1.80 [95% confidence interval: 1.54, 2.10]) than the other trajectory types, such as lone parent family throughout (PR=2.77 [2.34, 3.29]), or a lone parent family which transitioned to a reconstituted family (2.66 [1.99, 3.56]). Number of sweeps spent in a lone parent or reconstituted family was also as predictive of poor socio-emotional wellbeing as the saturated model, with the elevated risk increasing incrementally with every sweep spent in either of these family types (PR=1.86 [1.52, 2.26]) for 1 sweep, rising to 2.87 [2.46, 3.56] for 4). The association between both family structure measures and socioemotional wellbeing were, in most cases, substantially attenuated after adjustment for early-life selection factors (such as maternal social class and separation of the mother's parents in childhood) and cumulative poverty throughout childhood. This analysis confirms that policies to provide support to vulnerable families in the early years and to reduce poverty are likely to benefit child wellbeing. [ABSTRACT FROM AUTHOR]