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.

Robust genetic nurture effects on education: A systematic review and meta-analysis based on 38,654 families across 8 cohorts.

Similarities between parents and offspring arise from nature and nurture. Beyond this simple dichotomy, recent genomic studies have uncovered "genetic nurture" effects, whereby parental genotypes influence offspring outcomes via environmental pathways rather than genetic transmission. Such genetic nurture effects also need to be accounted for to accurately estimate "direct" genetic effects (i.e., genetic effects on a trait originating in the offspring). Empirical studies have indicated that genetic nurture effects are particularly relevant to the intergenerational transmission of risk for child educational outcomes, which are, in turn, associated with major psychological and health milestones throughout the life course. These findings have yet to be systematically appraised across contexts. We conducted a systematic review and meta-analysis to quantify genetic nurture effects on educational outcomes. A total of 12 studies comprising 38,654 distinct parent(s)-offspring pairs or trios from 8 cohorts reported 22 estimates of genetic nurture effects. Genetic nurture effects on offspring's educational outcomes (ßgenetic nurture = 0.08, 95% CI [0.07, 0.09]) were smaller than direct genetic effects (ßdirect genetic = 0.17, 95% CI [0.13, 0.20]). Findings were largely consistent across studies. Genetic nurture effects originating from mothers and fathers were of similar magnitude, highlighting the need for a greater inclusion of fathers in educational research. Genetic nurture effects were largely explained by observed parental education and socioeconomic status, pointing to their role in environmental pathways shaping child educational outcomes. Findings provide consistent evidence that environmentally mediated parental genetic influences contribute to the intergenerational transmission of educational outcomes, in addition to effects due to genetic transmission.

The association between cognitive ability and body mass index: A sibling-comparison analysis in four longitudinal studies.

BACKGROUND: Body mass index (BMI) and obesity rates have increased sharply since the 1980s. While multiple epidemiologic studies have found that higher adolescent cognitive ability is associated with lower adult BMI, residual and unobserved confounding due to family background may explain these associations. We used a sibling design to test this association accounting for confounding factors shared within households. METHODS AND FINDINGS: We used data from four United States general youth population cohort studies: the National Longitudinal Study of Youth 1979 (NLSY-79), the NLSY-79 Children and Young Adult, the NLSY 1997 (NLSY-97), and the Wisconsin Longitudinal Study (WLS); a total of 12,250 siblings from 5,602 households followed from adolescence up to age 62. We used random effects within-between (REWB) and residualized quantile regression (RQR) models to compare between- and within-family estimates of the association between adolescent cognitive ability and adult BMI (20 to 64 years). In REWB models, moving from the 25th to 75th percentile of adolescent cognitive ability was associated with -0.95 kg/m2 (95% CI = -1.21, -0.69) lower BMI between families. Adjusting for family socioeconomic position reduced the association to -0.61 kg/m2 (-0.90, -0.33). However, within families, the association was just -0.06 kg/m2 (-0.35, 0.23). This pattern of results was found across multiple specifications, including analyses conducted in separate cohorts, models examining age-differences in association, and in RQR models examining the association across the distribution of BMI. Limitations include the possibility that within-family estimates are biased due to measurement error of the exposure, confounding via non-shared factors, and carryover effects. CONCLUSIONS: The association between high adolescent cognitive ability and low adult BMI was substantially smaller in within-family compared with between-family analysis. The well-replicated associations between cognitive ability and subsequent BMI may largely reflect confounding by family background factors.

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.

Mental health in relation to changes in sleep, exercise, alcohol and diet during the COVID-19 pandemic: examination of four UK cohort studies.

BACKGROUND: Responses to the COVID-19 pandemic have included lockdowns and social distancing with considerable disruptions to people's lives. These changes may have particularly impacted on those with mental health problems, leading to a worsening of inequalities in the behaviours which influence health. METHODS: We used data from four national longitudinal British cohort studies (N = 10 666). Respondents reported mental health (psychological distress and anxiety/depression symptoms) and health behaviours (alcohol, diet, physical activity and sleep) before and during the pandemic. Associations between pre-pandemic mental ill-health and pandemic mental ill-health and health behaviours were examined using logistic regression; pooled effects were estimated using meta-analysis. RESULTS: Worse mental health was related to adverse health behaviours; effect sizes were largest for sleep, exercise and diet, and weaker for alcohol. The associations between poor mental health and adverse health behaviours were larger during the May lockdown than pre-pandemic. In September, when restrictions had eased, inequalities had largely reverted to pre-pandemic levels. A notable exception was for sleep, where differences by mental health status remained high. Risk differences for adverse sleep for those with the highest level of prior mental ill-health compared to those with the lowest were 21.2% (95% CI 16.2-26.2) before lockdown, 25.5% (20.0-30.3) in May and 28.2% (21.2-35.2) in September. CONCLUSIONS: Taken together, our findings suggest that mental health is an increasingly important factor in health behaviour inequality in the COVID era. The promotion of mental health may thus be an important component of improving post-COVID population health.

Gender differences in the distribution of children's physical activity: evidence from nine countries.

BACKGROUND: Physical activity in childhood is thought to influences health and development. Previous studies have found that boys are typically more active than girls, yet the focus has largely been on differences in average levels or proportions above a threshold rather than the full distribution of activity across all intensities. We thus examined differences in the distribution of physical activity between girls and boys in a multi-national sample of children. METHODS: We used the harmonised International Children Accelerometry Database (ICAD), including waist-worn accelerometry data from 15,461 individuals (Boys: 48.3%) from 9 countries. Employing Generalised Additive Models of Location, Shape, and Scale (GAMLSS) we investigated gender differences in the distribution of individuals, including comparisons of variability (SD) and average physical activity levels (mean and median) and skewness. We conducted this analysis for each activity intensity (Sedentary, Light, and Moderate-to-Vigorous (MVPA)) and a summary measure (counts per minute (CPM)). RESULTS: Sizable gender differences in the distribution of activity were found for moderate to vigorous activity and counts per minute, with boys having higher average levels (38% higher mean volumes of MVPA, 20% higher CPM), yet substantially more between-person variability (30% higher standard deviation (SD) for MVPA, 17% higher SD for CPM); boys' distributions were less positively skewed than girls. Conversely, there was little to no difference between girls and boys in the distribution of sedentary or light-intensity activity. CONCLUSIONS: Inequality in activity between girls and boys was driven by MVPA. The higher mean volumes of MVPA in boys occurred alongside greater variability. This suggests a need to consider the underlying distribution of activity in future research; for example, interventions which target gender inequality in MVPA may inadvertently lead to increased inequality within girls.

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.

The UK Coronavirus Job Retention Scheme and diet, physical activity, and sleep during the COVID-19 pandemic: evidence from eight longitudinal population surveys.

BACKGROUND: In March 2020, the UK implemented the Coronavirus Job Retention Scheme (furlough) to minimise job losses. Our aim was to investigate associations between furlough and diet, physical activity, and sleep during the early stages of the COVID-19 pandemic. METHODS: We analysed data on 25,092 participants aged 16-66 years from eight UK longitudinal studies. Changes in employment, including being furloughed, were based on employment status before and during the first lockdown. Health behaviours included fruit and vegetable consumption, physical activity, and sleep. Study-specific estimates obtained using modified Poisson regression, adjusting for socio-demographic characteristics and pre-pandemic health and health behaviours, were statistically pooled using random effects meta-analysis. Associations were also stratified by sex, age, and education. RESULTS: Across studies, between 8 and 25% of participants were furloughed. Compared to those who remained working, furloughed workers were slightly less likely to be physically inactive (RR = 0.85; [95% CI 0.75-0.97]; I 2 = 59%) and did not differ overall with respect to low fruit and vegetable consumption or atypical sleep, although findings for sleep were heterogenous (I 2 = 85%). In stratified analyses, furlough was associated with lower fruit and vegetable consumption among males (RR = 1.11; [1.01-1.22]; I 2 = 0%) but not females (RR = 0.84; [0.68-1.04]; I 2 = 65%). Considering changes in quantity, furloughed workers were more likely than those who remained working to report increases in fruit and vegetable consumption, exercise, and hours of sleep. CONCLUSIONS: Those furloughed exhibited similar health behaviours to those who remained in employment during the initial stages of the pandemic. There was little evidence to suggest that adoption of such social protection policies in the post-pandemic recovery period and during future economic crises had adverse effects on population health behaviours.

Psychological distress from early adulthood to early old age: evidence from the 1946, 1958 and 1970 British birth cohorts.

BACKGROUND: Existing evidence on profiles of psychological distress across adulthood uses cross-sectional or longitudinal studies with short observation periods. The objective of this research was to study the profile of psychological distress within the same individuals from early adulthood to early old age across three British birth cohorts. METHODS: We used data from three British birth cohorts: born in 1946 (n = 3093), 1958 (n = 13 250) and 1970 (n = 12 019). The profile of psychological distress - expressed both as probability of being a clinical case or a count of symptoms based on comparable items within and across cohorts - was modelled using the multilevel regression framework. RESULTS: In both 1958 and 1970 cohorts, there was an initial drop in the probability of being a case between ages 23-26 and 33-34. Subsequently, the predicted probability of being a case increased from 12.5% at age 36 to 19.5% at age 53 in the 1946 cohort; from 8.0% at age 33 to 13.7% at age 42 in the 1958 cohort and from 15.7% at age 34 to 19.7% at age 42 in the 1970 cohort. In the 1946 cohort, there was a drop in the probability of caseness between ages 60-64 and 69 (19.5% v. 15.2%). Consistent results were obtained with the continuous version of the outcome. CONCLUSIONS: Across three post-war British birth cohorts midlife appears to be a particularly vulnerable phase for experiencing psychological distress. Understanding the reasons for this will be important for the prevention and management of mental health problems.

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 body mass index and blood pressure association across time: Evidence from multiple cross-sectional and cohort studies.

Although body mass index (BMI) is considered a key determinant of high blood pressure, its importance may differ over time and by age group. We utilised separate data sources to investigate temporal changes in this association: 23 independent (newly sampled), repeated cross-sectional studies (Health Survey for England (HSE)) at ≥25 years (1994-2018; N = 126,742); and three British birth cohorts at 43-46 years (born 1946, 1958, and 1970; N = 18,657). In HSE, associations were weaker in more recent years, with this trend most pronounced amongst older adults. After adjustment for sex, anti-hypertensive treatment and education, the mean difference in systolic blood pressure (SBP) per 1 kg/m2 increase in BMI amongst adults ≥55 years was 0.75 mmHg (95%CI: 0.60-0.90) in 1994, 0.66 mmHg (0.46-0.85) in 2003, and 0.53 mmHg (0.35-0.71) in 2018. In the 1958 and 1970 cohorts, BMI and SBP associations were of similar magnitude yet weaker in the 1946 cohort, potentially due to differences in blood pressure measurement device. Quantile regression analyses suggested that associations between BMI and SBP were present both below and above the hypertension threshold. A weaker association between BMI and blood pressure may partly offset the public health impacts of increasing obesity prevalence. However, despite sizable increases in use of antihypertensive medication, BMI remains positively associated with SBP in all ages. Our findings highlight the need to tackle non-medical factors such as population diet which influence both BMI and blood pressure, and the utility of using multiple datasets to obtain robust inferences on trends in risk factor-outcome associations across time.

Prevalence and early-life determinants of mid-life multimorbidity: evidence from the 1970 British birth cohort.

BACKGROUND: We sought to: [1] estimate the prevalence of multimorbidity at age 46-48 in the 1970 British Cohort Study-a nationally representative sample in mid-life; and [2] examine the association between early-life characteristics and mid-life multimorbidity. METHOD: A prospective longitudinal birth cohort of a community-based sample from the 1970 British Cohort Study (BCS70). Participants included all surviving children born in mainland Britain in a single week in April 1970; the analytical sample included those with valid data at age 46-48 (n = 7951; 2016-2018). The main outcome was multimorbidity, which was operationalised as a binary indicator of two or more long-term health conditions where at least one of these conditions was of physical health. It also included symptom complexes (e.g., chronic pain), sensory impairments, and alcohol problems. RESULTS: Prevalence of mid-life multimorbidity was 33.8% at age 46-48. Those with fathers from unskilled social occupational class (vs professional) at birth had 43% higher risk of mid-life multimorbidity (risk ratio = 1.43, 95% confidence interval 1.15 to 1.77). After accounting for potential child and family confounding, an additional kilogram of birthweight was associated with 10% reduced risk of multimorbidity (risk ratio = 0.90, 95% confidence interval 0.84 to 0.96); a decrease of one body mass index point at age 10 was associated with 3% lower risk (risk ratio = 1.03, 95% confidence interval 1.01 to 1.05); one standard deviation higher cognitive ability score at age 10 corresponded to 4% lower risk (risk ratio = 0.96, 95% confidence interval 0.91 to 1.00); an increase of one internalising problem at age 16 was equated with 4% higher risk (risk ratio = 1.04, 95% confidence interval 1.00 to 1.08) and of one externalising problem at age 16 with 6% higher risk (risk ratio = 1.06, 1.03 to 1.09). CONCLUSION: Prevalence of multimorbidity was high in mid-life (33.8% at age 46-48) in Britain. Potentially modifiable early-life exposures, including early-life social circumstances, cognitive, physical and emotional development, were associated with elevated risk of mid-life multimorbidity.

Mental health in higher education students and non-students: evidence from a nationally representative panel study.

Despite increasing policy focus on mental health provision for higher education students, it is unclear whether they have worse mental health outcomes than their non-student peers. In a nationally-representative UK study spanning 2010-2019 (N = 11,519), 17-24 year olds who attended higher education had lower average psychological distress (GHQ score difference = - 0.37, 95% CI - 0.60, - 0.08) and lower odds of case-level distress than those who did not (OR = 0.91, 95% CI 0.81, 1.02). Increases in distress between 2010 and 2019 were similar in both groups. Accessible mental health support outside higher education settings is necessary to prevent further widening of socioeconomic inequalities in mental health.

Duration of obesity exposure between ages 10 and 40 years and its relationship with cardiometabolic disease risk factors: A cohort study.

BACKGROUND: Individuals with obesity do not represent a homogeneous group in terms of cardiometabolic risk. Using 3 nationally representative British birth cohorts, we investigated whether the duration of obesity was related to heterogeneity in cardiometabolic risk. METHODS AND FINDINGS: We used harmonised body mass index (BMI) and cardiometabolic disease risk factor data from 20,746 participants (49.1% male and 97.2% white British) enrolled in 3 British birth cohort studies: the 1946 National Survey of Health and Development (NSHD), the 1958 National Child Development Study (NCDS), and the 1970 British Cohort Study (BCS70). Within each cohort, individual life course BMI trajectories were created between 10 and 40 years of age, and from these, age of obesity onset, duration spent obese (range 0 to 30 years), and cumulative obesity severity were derived. Obesity duration was examined in relation to a number of cardiometabolic disease risk factors collected in mid-adulthood: systolic (SBP) and diastolic blood pressure (DBP), high-density-lipoprotein cholesterol (HDL-C), and glycated haemoglobin (HbA1c). A greater obesity duration was associated with worse values for all cardiometabolic disease risk factors. The strongest association with obesity duration was for HbA1c: HbA1c levels in those with obesity for <5 years were relatively higher by 5% (95% CI: 4, 6), compared with never obese, increasing to 20% (95% CI: 17, 23) higher in those with obesity for 20 to 30 years. When adjustment was made for obesity severity, the association with obesity duration was largely attenuated for SBP, DBP, and HDL-C. For HbA1c, however, the association with obesity duration persisted, independent of obesity severity. Due to pooling of 3 cohorts and thus the availability of only a limited number harmonised variables across cohorts, our models included adjustment for only a small number of potential confounding variables, meaning there is a possibility of residual confounding. CONCLUSIONS: Given that the obesity epidemic is characterised by a much earlier onset of obesity and consequently a greater lifetime exposure, our findings suggest that health policy recommendations aimed at preventing early obesity onset, and therefore reducing lifetime exposure, may help reduce the risk of diabetes, independently of obesity severity. However, to test the robustness of our observed associations, triangulation of evidence from different epidemiological approaches (e.g., mendelian randomization and negative control studies) should be obtained.

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.

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.

Differences in the relationship of weight to height, and thus the meaning of BMI, according to age, sex, and birth year cohort.

Background: Weight can be adjusted for height using the Benn parameter (kg/mB), where B is the power that minimises the correlation with height.Aim: To investigate how the Benn parameter changes across age (10-65 years) and time (1956-2015) and differs between sexes.Subjects and methods: The sample comprised 49,717 individuals born in 1946, 1958, 1970 or 2001. Cross-sectional estimates of the Benn parameter were produced and cohort differences at ages 10/11 and 42/43 years were examined using linear regression. Multilevel modelling was used to develop trajectories showing how the Benn parameter changed over age from childhood to mid-adulthood in the three older cohorts.Results: The Benn parameter was closest to 2 in childhood but consistently lower across adulthood, particularly in females and the most recent cohort. At ages 10/11 years, the Benn parameter was greater than 3 in both sexes in the 2001 cohort but between 2.2 and 2.7 in the three older cohorts. This difference was estimated to be +0.67 (0.53, 0.81) in males and +0.53 (0.38, 0.68) in females, compared to the 1946 cohort, and was driven by a much higher weight SD in the 2001 cohort. Conversely, at ages 42/43 years, the Benn parameter was lowest in the 1970 cohort due to a slightly lower weight-height correlation. This difference was estimated to be -0.12 (-0.34, 0.10) in males and -0.15 (-0.42, 0.13) in females, compared to the 1946 cohort.Conclusions: Changes over time in the obesogenic environment appear to have firstly reduced the Benn parameter due to a lowering of the weight-height correlation but secondly and more drastically increased the Benn parameter due to increasing weight variation.

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.

Motor performance in early life and participation in leisure-time physical activity up to age 68 years.

BACKGROUND: This study examined associations between motor performance in early life and leisure-time physical activity (LTPA) participation across adulthood, and whether these changed with age. METHODS: Data were from 2526 participants from the Medical Research Council National Survey of Health and Development. Motor indicators were mother-reported ages at first standing and walking, teacher-rated games ability at age 13, and finger- and foot-tapping speed at age 15. LTPA was reported at ages 36, 43, 53, 60-64, and 68 years and classed at each age as none, moderate (1-4/mo), or regular (≥5/mo). Associations were examined using mixed-effects Poisson regression models with robust error variance. RESULTS: Better ability at games and faster tapping speed were associated with more frequent participation in LTPA across adulthood, for example, fully adjusted relative risk of regular LTPA across adulthood (vs none) for above-average ability (vs below average or average) = 1.46 (95% CI 1.32, 1.61); and per 10-unit higher number of finger-taps/15 seconds = 1.04 (95% CI 1.02, 1.07). These associations did not vary by age (P ≥ .33 for interactions with age at LTPA). Ages at reaching motor milestones were not associated with LTPA (eg, fully adjusted relative risk of regular LTPA across adulthood for walking ≤10 and ≥18 months (vs 11-17 months) were 1.01 (95% CI 0.86, 1.20) and 0.89 (95% CI 0.75, 1.06) respectively. CONCLUSIONS: Better ability at games and faster tapping speed in adolescence were associated with greater participation in LTPA throughout adult life; from age 36 up to age 68. Childhood motor skill interventions may therefore have the potential to promote lifelong LTPA.