Socioeconomic inequalities in cardiovascular disease: a causal perspective.

Socioeconomic inequalities in cardiovascular disease (CVD) persist in high-income countries despite marked overall declines in CVD-related morbidity and mortality. After decades of research, the field has struggled to unequivocally answer a crucial question: is the association between low socioeconomic position (SEP) and the development of CVD causal? We review relevant evidence from various study designs and disciplinary perspectives. Traditional observational, family-based and Mendelian randomization studies support the widely accepted view that low SEP causally influences CVD. However, results from quasi-experimental and experimental studies are both limited and equivocal. While more experimental and quasi-experimental studies are needed to aid causal understanding and inform policy, high-quality descriptive studies are also required to document inequalities, investigate their contextual dependence and consider SEP throughout the lifespan; no simple hierarchy of evidence exists for an exposure as complex as SEP. The COVID-19 pandemic illustrates the context-dependent nature of CVD inequalities, with the generation of potentially new causal pathways linking SEP and CVD. The linked goals of understanding the causal nature of SEP and CVD associations, their contextual dependence, and their remediation by policy interventions necessitate a detailed understanding of society, its change over time and the phenotypes of CVD. Interdisciplinary research is therefore key to advancing both causal understanding and policy translation.

Trends in the ability of socioeconomic position to predict individual body mass index: an analysis of repeated cross-sectional data, 1991-2019.

BACKGROUND: The widening of group-level socioeconomic differences in body mass index (BMI) has received considerable research attention. However, the predictive power of socioeconomic position (SEP) indicators at the individual level remains uncertain, as does the potential temporal variation in their predictive value. Examining this is important given the increasing incorporation of SEP indicators into predictive algorithms and calls to reduce social inequality to tackle the obesity epidemic. We thus investigated SEP differences in BMI over three decades of the obesity epidemic in England, comparing population-wide (SEP group differences in mean BMI) and individual-level (out-of-sample prediction of individuals' BMI) approaches to understanding social inequalities. METHODS: We used repeated cross-sectional data from the Health Survey for England, 1991-2019. BMI (kg/m2) was measured objectively, and SEP was measured via educational attainment, occupational class, and neighbourhood index of deprivation. We ran random forest models for each survey year and measure of SEP adjusting for age and sex. RESULTS: The mean and variance of BMI increased within each SEP group over the study period. Mean differences in BMI by SEP group also increased: differences between lowest and highest education groups were 1.0 kg/m2 (0.4, 1.6) in 1991 and 1.3 kg/m2 (0.7, 1.8) in 2019. At the individual level, the predictive capacity of SEP was low, though increased in later years: including education in models improved predictive accuracy (mean absolute error) by 0.14% (- 0.9, 1.08) in 1991 and 1.05% (0.18, 1.82) in 2019. Similar patterns were obtained for occupational class and neighbourhood deprivation and when analysing obesity as an outcome. CONCLUSIONS: SEP has become increasingly important at the population (group difference) and individual (prediction) levels. However, predictive ability remains low, suggesting limited utility of including SEP in prediction algorithms. Assuming links are causal, abolishing SEP differences in BMI could have a large effect on population health but would neither reverse the obesity epidemic nor reduce much of the variation in BMI.

Weakening of the cognition and height association from 1957 to 2018: Findings from four British birth cohort studies.

Background: Taller individuals have been repeatedly found to have higher scores on cognitive assessments. Recent studies have suggested that this association can be explained by genetic factors, yet this does not preclude the influence of environmental or social factors that may change over time. We thus tested whether the association changed across time using data from four British birth cohorts (born in 1946, 1958, 1970, and 2001). Methods: In each cohort height was measured and cognition via verbal reasoning, vocabulary/comprehension, and mathematical tests; at ages 10/11 and 14/17 years (N=41,418). We examined associations between height and cognition at each age, separately in each cohort, and for each cognitive test administered. Linear and quantile regression models were used. Results: Taller participants had higher mean cognitive assessment scores in childhood and adolescence, yet the associations were weaker in later (1970 and 2001) cohorts. For example, the mean difference in height comparing the highest with lowest verbal cognition scores at 10/11 years was 0.57 SD (95% CI = 0.44-0.70) in the 1946 cohort, yet 0.30 SD (0.23-0.37) in the 2001 cohort. Expressed alternatively, there was a reduction in correlation from 0.17 (0.15-0.20) to 0.08 (0.06-0.10). This pattern of change in the association was observed across all ages and cognition measures used, was robust to adjustment for social class and parental height, and modeling of plausible missing-not-at-random scenarios. Quantile regression analyses suggested that these differences were driven by differences in the lower centiles of height, where environmental influence may be greatest. Conclusions: Associations between height and cognitive assessment scores in childhood-adolescence substantially weakened from 1957-2018. These results support the notion that environmental and social change can markedly weaken associations between cognition and other traits. Funding: DB is supported by the Economic and Social Research Council (grant number ES/M001660/1); DB and LW by the Medical Research Council (MR/V002147/1). The Medical Research Council (MRC) and the University of Bristol support the MRC Integrative Epidemiology Unit [MC_UU_00011/1]. NMD is supported by an Norwegian Research Council Grant number 295989. VM is supported by the CLOSER Innovation Fund WP19 which is funded by the Economic and Social Research Council (award reference: ES/K000357/1) and Economic and Social Research Council (ES/M001660/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Polygenic and socioeconomic risk for high body mass index: 69 years of follow-up across life.

Genetic influences on body mass index (BMI) appear to markedly differ across life, yet existing research is equivocal and limited by a paucity of life course data. We thus used a birth cohort study to investigate differences in association and explained variance in polygenic risk for high BMI across infancy to old age (2-69 years). A secondary aim was to investigate how the association between BMI and a key purported environmental determinant (childhood socioeconomic position) differed across life, and whether this operated independently and/or multiplicatively of genetic influences. Data were from up to 2677 participants in the MRC National Survey of Health and Development, with measured BMI at 12 timepoints from 2-69 years. We used multiple polygenic indices from GWAS of adult and childhood BMI, and investigated their associations with BMI at each age. For polygenic liability to higher adult BMI, the trajectories of effect size (ß) and explained variance (R2) diverged: explained variance peaked in early adulthood and plateaued thereafter, while absolute effect sizes increased throughout adulthood. For polygenic liability to higher childhood BMI, explained variance was largest in adolescence and early adulthood; effect sizes were marginally smaller in absolute terms from adolescence to adulthood. All polygenic indices were related to higher variation in BMI; quantile regression analyses showed that effect sizes were sizably larger at the upper end of the BMI distribution. Socioeconomic and polygenic risk for higher BMI across life appear to operate additively; we found little evidence of interaction. Our findings highlight the likely independent influences of polygenic and socioeconomic factors on BMI across life. Despite sizable associations, the BMI variance explained by each plateaued or declined across adulthood while BMI variance itself increased. This is suggestive of the increasing importance of chance ('non-shared') environmental influences on BMI across life.

Religiosity and Mental Wellbeing Among Members of Majority and Minority Religions: Findings From Understanding Society: the UK Household Longitudinal Study.

It is unclear whether links between religiosity and mental health are found in contexts outside the United States or are causal. We examined differences in mental wellbeing and associations between mental wellbeing and religiosity among the religiously unaffiliated, White and non-White Christians, Muslims of Pakistani, Bangladeshi, and other ethnicities, and other minority ethnoreligious groups. We used 4 waves of Understanding Society: the UK Household Longitudinal Study (2009-2013; n = 50,922). We adjusted for potential confounders (including socioeconomic factors and personality) and for household fixed effects to account for household-level unobserved confounding factors. Compared with those with no religious affiliation, Pakistani and Bangladeshi Muslims and members of other minority religions had worse wellbeing (as measured using the Shortened Warwick-Edinburgh Mental Wellbeing Scale and General Health Questionnaire). Higher subjective importance of religion was associated with lower wellbeing according to the General Health Questionnaire; associations were not found with the Shortened Warwick-Edinburgh Mental Wellbeing Scale. More frequent religious service attendance was associated with higher wellbeing; effect sizes were larger for those with religious affiliations. These associations were only partially attenuated by adjustment for potential confounding factors, including household fixed effects. Religious service attendance and/or its secular alternatives may have a role in improving population-wide mental wellbeing.

Inequalities in body mass index, diet and physical activity in the UK: Longitudinal evidence across childhood and adolescence.

We use longitudinal data across a key developmental period, spanning much of childhood and adolescence (age 5 to 17, years 2006-2018) from the UK Millennium Cohort Study, a nationally representative study with an initial sample of just over 19,000. We first examine the extent to which inequalities in overweight, obesity, BMI and body fat over this period are consistent with the evolution of inequalities in health behaviours, including exercise and healthy diet markers (i.e., skipping breakfast) (n = 7,220). We next study the links between SES, health behaviours and adiposity (BMI, body fat), using rich models that account for the influence of a range of unobserved factors that are fixed over time. In this way, we improve on existing estimates measuring the relationship between SES and health behaviours on the one hand and adiposity on the other. The advantage of the individual fixed effects models is that they exploit within-individual changes over time to help mitigate biases due to unobserved fixed characteristics (n = 6,883). We observe stark income inequalities in BMI and body fat in childhood (age 5), which have further widened by age 17. Inequalities in obesity, physical activity, and skipping breakfast are observed to widen from age 7 onwards. Ordinary Least Square estimates reveal the previously documented SES gradient in adiposity, which is reduced slightly once health behaviours including breakfast consumption and physical activity are accounted for. The main substantive change in estimates comes from the fixed effects specification. Here we observe mixed findings on the SES associations, with a positive association between income and adiposity and a negative association with wealth. The role of health behaviours is attenuated but they remain important, particularly for body fat.

Bullying victimisation in adolescence: prevalence and inequalities by gender, socioeconomic status and academic performance across 71 countries.

BACKGROUND: Bullying victimisation is of global importance due to its long-term negative consequences. We examined the prevalence of victimisation and its inequalities in 15-year-olds across 71 countries. METHODS: Data were from the Programme for International Student Assessment (March-August 2018). Students reported frequencies of relational, physical, and verbal victimisation during the last 12 months, which were analysed separately and combined into a total score. Prevalence of frequent victimisation (> a few times a month) was estimated, followed by mean differences in total score by gender, wealth and academic performance quintiles in each country. Meta-analyses were used to examine country differences. FINDINGS: Of 421,437 students included, 113,602 (30·4%) experienced frequent victimisation, yet this varied by country-from 9·3% (Korea) to 64·8% (Philippines). Verbal and relational victimisation were more frequent (21·4%, 20.9%, respectively) than physical victimisation (15·2%). On average, boys (vs girls +0·23SD, 95%CI: 0·22-0·24), students from the lowest wealth (vs highest +0·09SD, 0·08-0·10) and with lowest academic performance (vs highest +0·49SD, 0·48-0·50) had higher scores. However, there was substantial between-country heterogeneity in these associations (I2=85%-98%). Similar results were observed for subtypes of victimisation-except relational victimisation, where gender inequalities were smaller. INTERPRETATION: Globally, bullying victimisation was high, although the size, predominant subtype and strength of associations with risk factors varied by country. The large cross-country differences observed require further replication and empirical explanation, and suggest the need to and the large scope for reducing bullying victimisation and its inequity in the future. FUNDING: Japan Foundation for Pediatric Research.

Socioeconomic inequalities in prevalence and development of multimorbidity across adulthood: A longitudinal analysis of the MRC 1946 National Survey of Health and Development in the UK.

BACKGROUND: We aimed to estimate multimorbidity trajectories and quantify socioeconomic inequalities based on childhood and adulthood socioeconomic position (SEP) in the risks and rates of multimorbidity accumulation across adulthood. METHODS AND FINDINGS: Participants from the UK 1946 National Survey of Health and Development (NSHD) birth cohort study who attended the age 36 years assessment in 1982 and any one of the follow-up assessments at ages 43, 53, 63, and 69 years (N = 3,723, 51% males). Information on 18 health conditions was based on a combination of self-report, biomarkers, health records, and prescribed medications. We estimated multimorbidity trajectories and delineated socioeconomic inequalities (based on childhood and adulthood social class and highest education) in multimorbidity at each age and in longitudinal trajectories. Multimorbidity increased with age (0.7 conditions at 36 years to 3.7 at 69 years). Multimorbidity accumulation was nonlinear, accelerating with age at the rate of 0.08 conditions/year (95% CI 0.07 to 0.09, p < 0.001) at 36 to 43 years to 0.19 conditions/year (95% CI 0.18 to 0.20, p < 0.001) at 63 to 69 years. At all ages, the most socioeconomically disadvantaged had 1.2 to 1.4 times greater number of conditions on average compared to the most advantaged. The most disadvantaged by each socioeconomic indicator experienced an additional 0.39 conditions (childhood social class), 0.83 (adult social class), and 1.08 conditions (adult education) at age 69 years, independent of all other socioeconomic indicators. Adverse adulthood SEP was associated with more rapid accumulation of multimorbidity, resulting in 0.49 excess conditions in partly/unskilled compared to professional/intermediate individuals between 63 and 69 years. Disadvantaged childhood social class, independently of adulthood SEP, was associated with accelerated multimorbidity trajectories from age 53 years onwards. Study limitations include that the NSHD cohort is composed of individuals of white European heritage only, and findings may not be generalizable to the non-white British population of the same generation and did not account for other important dimensions of SEP such as income and wealth. CONCLUSIONS: In this study, we found that socioeconomically disadvantaged individuals have earlier onset and more rapid accumulation of multimorbidity resulting in widening inequalities into old age, with independent contributions from both childhood and adulthood SEP.

Changes in the behavioural determinants of health during the COVID-19 pandemic: gender, socioeconomic and ethnic inequalities in five British cohort studies.

BACKGROUND: The COVID-19 pandemic is expected to have far-reaching consequences on population health. We investigated whether these consequences included changes in health-impacting behaviours which are important drivers of health inequalities. METHODS: Using data from five representative British cohorts (born 2000-2002, 1989-1990, 1970, 1958 and 1946), we investigated sleep, physical activity (exercise), diet and alcohol intake (N=14 297). We investigated change in each behaviour (pre/during the May 2020 lockdown), and differences by age/cohort, gender, ethnicity and socioeconomic position (childhood social class, education attainment and adult financial difficulties). Logistic regression models were used, accounting for study design and non-response weights, and meta-analysis used to pool and test cohort differences in association. RESULTS: Change occurred in both directions-shifts from the middle part of the distribution to both declines and increases in sleep, exercise and alcohol use. Older cohorts were less likely to report changes in behaviours while the youngest reported more frequent increases in sleep, exercise, and fruit and vegetable intake, yet lower alcohol consumption. Widening inequalities in sleep during lockdown were more frequent among women, socioeconomically disadvantaged groups and ethnic minorities. For other outcomes, inequalities were largely unchanged, yet ethnic minorities were at higher risk of undertaking less exercise and consuming lower amounts of fruit and vegetables. CONCLUSIONS: Our findings provide new evidence on the multiple changes to behavioural outcomes linked to lockdown, and the differential impacts across generation, gender, socioeconomic circumstances across life, and ethnicity. Lockdown appeared to widen some (but not all) forms of health inequality.

Socioeconomic inequalities across life and premature mortality from 1971 to 2016: findings from three British birth cohorts born in 1946, 1958 and 1970.

INTRODUCTION: Disadvantaged socioeconomic position (SEP) in early and adult life has been repeatedly associated with premature mortality. However, it is unclear whether these inequalities differ across time, nor if they are consistent across different SEP indicators. METHODS: British birth cohorts born in 1946, 1958 and 1970 were used, and multiple SEP indicators in early and adult life were examined. Deaths were identified via national statistics or notifications. Cox proportional hazard models were used to estimate associations between ridit scored SEP indicators and all-cause mortality risk-from 26 to 43 years (n=40 784), 26 to 58 years (n=35 431) and 26 to 70 years (n=5353). RESULTS: More disadvantaged SEP was associated with higher mortality risk-magnitudes of association were similar across cohort and each SEP indicator. For example, HRs (95% CI) from 26 to 43 years comparing lowest to highest paternal social class were 2.74 (1.02 to 7.32) in 1946c, 1.66 (1.03 to 2.69) in 1958c, and 1.94 (1.20 to 3.15) in 1970c. Paternal social class, adult social class and housing tenure were each independently associated with mortality risk. CONCLUSIONS: Socioeconomic circumstances in early and adult life show persisting associations with premature mortality from 1971 to 2016, reaffirming the need to address socioeconomic factors across life to reduce inequalities in survival to older age.

Childhood correlates of adult positive mental well-being in three British longitudinal studies.

BACKGROUND: Previous evidence has shown how experiences within childhood, such as parenting and socioeconomic conditions, are associated later on in life with adult mental well-being. However, these studies tend to focus on childhood experiences in isolation, and fewer studies have investigated how multiple aspects of the childhood environment, including both socioeconomic and psychosocial aspects, are associated with adult positive mental well-being. Using data from three British birth cohort studies, we investigated how prospective measures of the childhood environment up to the age of 16 years were associated with midlife adult mental well-being and whether similar associations were replicated across different generations. METHODS: Childhood environment comprised socioeconomic circumstances, psychosocial factors (child-rearing and parenting, family instability) and parental health. The Warwick-Edinburgh Mental Wellbeing Scale, a validated instrument measuring both hedonic and eudaemonic aspects of well-being, was administered in mid-life. We modelled associations between childhood environment domains and well-being. RESULTS: Despite changes in social context in all three studies, poorer quality parent-child relationships and poor parental mental health were strongly and independently associated with poorer adult mental well-being. Socioeconomic circumstances were also associated with adult mental well-being, but the association was weaker than for the measures of parenting or parental mental health. CONCLUSION: These findings confirm that parenting and parental mental health, as well as socioeconomic circumstances, are important for adult mental well-being. Interventions in early childhood aimed at reducing socioeconomic adversity and offering support to parents might be warranted, to enhance adult mental well-being later on in the life course.

Socioeconomic inequalities in blood pressure: co-ordinated analysis of 147,775 participants from repeated birth cohort and cross-sectional datasets, 1989 to 2016.

BACKGROUND: High blood pressure (BP) is a key modifiable determinant of cardiovascular disease and a likely determinant of other adverse health outcomes. While socioeconomic inequalities in BP are well documented, it remains unclear (1) how these inequalities have changed across time, given improvements over time in the detection and treatment of high BP (hypertension); (2) whether BP inequalities are present below and above hypertension treatment thresholds; and (3) whether socioeconomic position (SEP) across life has cumulative effects on BP. We sought to address these gaps using evidence from two complementary sources: birth cohort and repeated cross-sectional datasets. METHODS: We used three British birth cohort studies-born in 1946, 1958, and 1970-with BP measured at 43-46 years (in 1989, 2003, and 2016), and 21 repeated cross-sectional datasets-the Health Survey for England (HSE), with BP measured among adults aged ≥ 25 years (1994-2016). Adult education attainment was used as an indicator of SEP in both datasets; childhood father's social class was used as an alternative indicator of (early life) SEP in cohorts. Adjusting for the expected average effects of antihypertensive medication use, we used linear regression to quantify SEP differences in mean systolic BP (SBP), and quantile regression to investigate whether inequalities differed across SBP distributions-below and above hypertension treatment thresholds. RESULTS: In both datasets, lower educational attainment was associated with higher SBP, with similar absolute magnitudes of inequality across the studied period. Differences in SBP by education (Slope Index of Inequality) based on HSE data were 3.0 mmHg (95% CI 1.8, 4.2) in 1994 and 4.3 mmHg (2.3, 6.3) in 2016. Findings were similar for diastolic BP (DBP) and survey-defined hypertension. Inequalities were found across the SBP distribution in both datasets-below and above the hypertension threshold-yet were larger at the upper tail; in HSE, median SBP differences were 2.8 mmHg (1.7, 3.9) yet 5.6 mmHg (4.9, 6.4) at the 90th quantile. Adjustment for antihypertensive medication use had little impact on the magnitude of inequalities; in contrast, associations were largely attenuated after adjustment for body mass index. Finally, cohort data suggested that disadvantage in early and adult life had cumulative independent associations with BP: cohort-pooled differences in SBP were 5.0 mmHg (3.8, 6.1) in a score combining early life social class and own education, yet were 3.4 mmHg (2.4, 4.4) for education alone. CONCLUSION: Socioeconomic inequalities in BP have persisted from 1989 to 2016 in Britain/England, despite improved detection and treatment of high BP. To achieve future reductions in BP inequalities, policies addressing the wider structural determinants of high BP levels are likely required, particularly those curtailing the obesogenic environment-targeting detection and treatment alone is unlikely to be sufficient.

Educational differentials in key domains of physical activity by ethnicity, age and sex: a cross-sectional study of over 40 000 participants in the UK household longitudinal study (2013-2015).

OBJECTIVES: To assess whether educational differentials in three key physical activity (PA) domains vary by age, sex and ethnicity. DESIGN: National cross-sectional survey. SETTING: UK. PARTICIPANTS: Altogether 40 270 participants, aged 20 years and over, from the UK Household Longitudinal Study with information on education, PA and demographics collected in 2013-2015. OUTCOME MEASURES: Participation in active travel (AT), occupational activity (OA) and leisure time physical activity (LTPA) at the time of assessment. RESULTS: Lower educational attainment was associated with higher AT and OA, but lower weekly LTPA activity; these associations were modified by sex, ethnicity and age. Education-related differences in AT were larger for women-the difference in predicted probability of activity between the highest and the lowest education groups was -10% in women (95% CI: -11.9% to 7.9%) and -3% in men (-4.8% to -0.4%). Education-related differences in OA were larger among men -35% (-36.9% to -32.4%) than women -17% (-19.4% to -15.0%). Finally, education-related differences in moderate-to-vigorous LTPA varied by ethnicity; for example, differences were 17% (16.2% to 18.7%) for white individuals compared with 6% (0.6% to 11.6%) for black individuals. CONCLUSIONS: Educational differences in PA vary by domain and are modified by age, sex and ethnicity. A better understanding of physically inactive subgroups may aid development of interventions to both increase activity levels and reduce health inequalities.

Socioeconomic inequalities in childhood-to-adulthood BMI tracking in three British birth cohorts.

BACKGROUND: Body mass index (BMI) tracks from childhood-to-adulthood, but the extent to which this relationship varies across the distribution and according to socio-economic position (SEP) is unknown. We aimed to address this using data from three British cohort studies. METHODS: We used data from: 1946 National Survey of Health and Development (NSHD, n = 2470); 1958 National Child Development Study (NCDS, n = 7747); 1970 British Cohort Study (BCS, n = 5323). BMI tracking between 11 and 42 years was estimated using quantile regression, with estimates reflecting correlation coefficients. SEP disparities in tracking were investigated using a derived SEP variable based on parental education reported in childhood. This SEP variable was then interacted with the 11-year BMI z-score. RESULTS: In each cohort and sex, tracking was stronger at the upper end of the distribution of BMI at 42 years. For example, for men in the 1946 NSHD, the tracking estimate at the 10th quantile was 0.31 (0.20, 0.41), increasing to 0.71 (0.61, 0.82) at the 90th quantile. We observed no strong evidence of SEP inequalities in tracking in men in the 1946 and 1958 cohorts. In the 1970 cohort, however, we observed tentative evidence of stronger tracking in low SEP groups, particularly in women and at the higher end of the BMI distribution. For example, women in the 1970 cohort from low SEP backgrounds had tracking coefficients at the 50th, 70th, and 90th quantiles, which were 0.05 (-0.04; 0.15), 0.19 (0.06; 0.31), and 0.22 (0.02; 0.43) units higher, respectively, than children from high SEP groups. CONCLUSION: Tracking was consistently stronger at the higher quantiles of the BMI distribution. We observed suggestive evidence for a pattern of greater BMI tracking in lower (compared to higher) SEP groups in the more recently born cohort, particularly in women and at the higher end of the BMI distribution.

Financial stress and mental health among higher education students in the UK up to 2018: rapid review of evidence.

INTRODUCTION: In the United Kingdom and many other countries, debt accrued during higher education has increased substantially in recent decades. The prevalence of common mental health problems has also increased alongside these changes. However, it is as yet unclear whether there is an association between financial stress and mental health among higher education students. METHODS: We conducted a rapid review of the peer-reviewed scientific literature. Eligible studies were English-language publications testing the association between any indicator of financial stress and mental health among higher education students in the UK. Papers were located through a systematic search of PsychINFO, PubMed and Embase up to November 2018. RESULTS: The search strategy yielded 1272 studies-9 met the inclusion criteria. A further two were identified through hand-searching. The median sample size was 408. Only three of seven studies found an association between higher debt and worse mental health. There was a consistent cross-sectional relationship between worse mental health and both experience of financial difficulties (seven of seven studies) and debt worry/financial concern (four of five studies), though longitudinal evidence was mixed and limited to six studies. CONCLUSION: Among higher education students in the UK, there is little evidence that the amount of debt is associated with mental health. However, more subjective measures of increased financial stress were more consistently associated with worse mental health outcomes. Nevertheless, the identified evidence was judged to be weak; further research is required to examine whether links between financial stress and mental health outcomes are robust and causal in nature.

Post-war (1946-2017) population health change in the United Kingdom: A systematic review.

We systematically reviewed the evidence on secular trends in main chronic conditions, disability and self-assessed general health among adults in the United Kingdom, as reported in primary/secondary care databases and population-based surveys. Searches were conducted separately for: (1) trends in age-standardised or age-specific prevalence of major non-communicable diseases, disability, and self-reported general health; (2) trends in health expectancy. The databases searched were MEDLINE, EMBASE/EMBASE Classic and Web of Science (all from 1946/7). The evidence was synthesised narratively. There were 39 studies reporting trends in prevalence of health conditions and 15 studies in health expectancy. We did not find evidence for improvement in the age-standardised or age-specific prevalence of any of the studied major chronic conditions over the last few decades, apart from Alzheimer's disease and other dementias. Both increasing or stable prevalence rates with simultaneous rising life expectancy support the expansion of morbidity theory, meaning that people are expected to spend a greater number of years with chronic condition(s). The evidence on disability-expressed as prevalence or health expectancy-was mixed, but also appeared to support the expansion of morbidity among those aged 65 or over. The evidence on trends in disability for younger age is lacking. Across the studied period (1946-2017), the UK population endured more years with chronic morbidity and disability, which may place a serious strain on the health care system, the economy and the society.

Correction to: Socioeconomic inequalities in childhood-to-adulthood BMI tracking in three British birth cohorts.

In the original Article, the author names were stated backwards ("Norris Tom" instead of Tom Norris, "Bann David" instead of David Bann and so on). This has been corrected in the HTML and PDF versions of this Article.

Adolescents' physical activity: cross-national comparisons of levels, distributions and disparities across 52 countries.

BACKGROUND: Despite global concerns regarding physical inactivity, limited cross-national evidence exists to compare adolescents' physical activity participation. We analysed data from 52 high- and low-middle income countries, with activity undertaken inside and outside of school in 2015. We investigated gender and socioeconomic disparities, and additionally examined correlations with country-level indices of physical education (PE) curriculum time allocation, wealth, and income inequality. METHODS: We compared adolescents' reported activity levels inside and outside of school using nationally representative cross-sectional data from 52 high- and low-middle income countries (N = 347,935)-the Programme for International Student Assessment (PISA) in 2015. Students reported average attendance (days/week) in PE classes, and the days/week engaged in moderate activity (MPA) and vigorous activity (VPA) outside of school. We also compared gender and socioeconomic disparities, and additionally examined correlations with purported determinants-country-level estimates of PE curriculum time allocation, wealth, and income inequality. RESULTS: Average activity levels differed substantially both between and within regions, with potentially important differences in distributions identified-such as a bimodal distribution in the U.S. and Canada in PE. Males were more active than females, as were those from households with higher rather than lower household wealth; these disparities were modest for PE, but higher for moderate and vigorous activity outside school-there was strong evidence for heterogeneity in the magnitude of these disparities (e.g., I2 > 95% for gender differences across all countries). PE class attendance was positively correlated with PE curriculum time allocation (rho = 0.36); activity outcomes were inconsistently associated with country-level wealth and income inequality. CONCLUSIONS: Our findings reveal extensive cross-country differences in adolescents' physical activity; in turn, these highlight policy areas that could ultimately improve global adolescent health, such as the incorporation of minimum country-level PE classes, and the targeting of gender and socioeconomic disparities in activity conducted outside of school. Our findings also highlight the utility of educational databases such as PISA for use in global population health research.

Education-related disparities in reported physical activity during leisure-time, active transportation, and work among US adults: repeated cross-sectional analysis from the National Health and Nutrition Examination Surveys, 2007 to 2016.

BACKGROUND: Understanding socioeconomic disparities in physical activity is important, given its contribution to overall population-wide health and to health disparities. Existing studies examining trends in these disparities have focused exclusively on physical activity during leisure-time and have not investigated the potential moderators of socioeconomic disparities in physical activity. Using self-reported data from the US National Health and Nutrition Examination Survey (NHANES) 2007 to 2016 for 29,039 adults aged 20 years and over we examined education-related disparities in overall (total) moderate-to-vigorous intensity physical activity, and in its sub-components, recreational (leisure-time) and non-recreational (active transportation and work) activity. We also examined if education-related disparities in physical activity were moderated by age, gender, and race/ethnicity. METHODS: Logistic regression models were used to evaluate disparities in physical activity according to education group and their moderation across age, gender, race/ethnicity, and time-period. RESULTS: Overall activity levels (% ≥150 min/week) were highest amongst highly educated adults, yet contrasting education-related disparities were found for recreational and non-recreational activities (active transportation and work), favoring the highest- and lowest-educated groups respectively. Within each domain of activity, associations were moderated by age and race/ethnicity, and by gender for work-based activity. The net result was that education-related disparities in total activity were substantially larger in older adults (P < 0.001) and amongst women (P < 0.001). For example, the estimated difference in the probability of being active in the highest versus the lowest educational groups was 23.1% (95% CI: 19.1, 27.2) amongst those aged ≥60 years, yet 10.8% (95% CI: 7.1, 14.6) amongst those aged 20-39. CONCLUSIONS: Education-related disparities in physical activity persisted from 2007 to 2016. Our results suggest that understanding and addressing these disparities requires assessment of their multiple domains, and identification of the demographic sub-groups for which the disparities are more or less pronounced.