The Relationship Between Time Spent on Social Media and Adolescent Cigarette, E-cigarette, and Dual Use: A Longitudinal Analysis of the UK Millennium Cohort Study.

INTRODUCTION: To estimate the effect of social media use in 14 year olds on risk of and inequalities in cigarette, e-cigarette, and dual use at 17 years, using the UK-representative Millennium Cohort Study (born 2000-2002). AIMS AND METHODS: The relationship of time spent on social media (using questionnaires [n = 8987] and time-use-diaries [n = 2520]) with cigarette, e-cigarette, and dual use was estimated using adjusted odds ratios (AORs) or relative risk ratios (ARRRs). Effect modification was examined (using parental education as an indicator for socioeconomic circumstances) by comparing adjusted risk differences within low and high-parental education groups. Analyses accounted for prespecified confounders (identified via directed acyclic graphs), baseline outcome measures (to address reverse causality), sample design, attrition, and item-missingness (through multiple imputation). RESULTS: Time spent on social media was associated with increased risk of cigarette, e-cigarette, and dual use in a dose-response manner. Social media use for ≥2 hours/day (vs. 1-<30 minutes) was associated with increased cigarette (AOR 2.76 [95% confidence interval 2.19 to 3.48]), e-cigarette (3.24 [2.59 to 4.05]), and dual use (ARRR 4.11 [2.77 to 6.08]). The risk of cigarette use among 30 minutes-<1 hour/day users (vs. non-users) were smaller in those with high versus low parental education (ARDs 1.4% vs. 12.4%). Similar findings were observed across the higher time categories. Analyses using time-use-diaries, in complete case samples, and with additional adjustment for baseline outcome measures generally revealed similar findings. CONCLUSIONS: After accounting for observed confounders and potential reverse causality, findings suggest social media use increases the risk of cigarette, e-cigarette, and dual use in a dose-response manner. Guidance addressing adolescent online safety should be prioritized. IMPLICATIONS: This study's identification of a dose-response relationship and differential effects across socioeconomic groups, could assist in the development of guidance on time spent on social media. The adverse effects of social media use on adolescent cigarette, e-cigarette, and dual use supports legislation aimed at promoting adolescent online safety. Study findings strengthen calls to prohibit social media marketing of nicotine-related products and importantly highlight the need to increase awareness and understanding of the underlying algorithms which drive adolescent exposure to nicotine-related content on social media to ensure they are functioning in a way that best serves the adolescent population.

Childhood attention-deficit hyperactivity disorder: socioeconomic inequalities in symptoms, impact, diagnosis and medication.

BACKGROUND: Children from disadvantaged backgrounds are at greater risk of attention-deficit hyperactivity disorder (ADHD)-related symptoms, being diagnosed with ADHD, and being prescribed ADHD medications. We aimed to examine how inequalities manifest across the 'patient journey', from perceptions of impacts of ADHD symptoms on daily life, to the propensity to seek and receive a diagnosis and treatment. METHODS: We investigated four 'stages': (1) symptoms, (2) caregiver perception of impact, (3) diagnosis and (4) medication, in two data sets: UK Millennium Cohort Study (MCS, analytic n ~ 9,000), with relevant (parent-reported) information on all four stages (until 14 years); and a population-wide 'administrative cohort', which includes symptoms (child health checks) and prescriptions (dispensing records), born in Scotland, 2010-2012 (analytic n ~ 100,000), until ~6 years. We described inequalities according to maternal occupational status, with percentages and relative indices of inequality (RII). RESULTS: The prevalence of ADHD symptoms and medication receipt was considerably higher in the least compared to the most advantaged children in the administrative cohort (RIIs of 5.9 [5.5-6.4] and 8.1 [4.2-15.6]) and the MCS (3.08 [2.68-3.55], 3.75 [2.21-6.36]). MCS analyses highlighted complexities between these two stages, however, those from least advantaged backgrounds, with ADHD symptoms, were the least likely to perceive impacts on daily life (15.7% vs. average 19.5%) and to progress from diagnosis to medication (44.1% vs. average 72.5%). CONCLUSIONS: Despite large inequalities in ADHD symptoms and medication, parents from the least advantaged backgrounds were less likely to report impacts of ADHD symptoms on daily life, and their children were less likely to have received medication postdiagnosis, highlighting how patient journeys differed according to socioeconomic circumstances.

Short-term impacts of Universal Basic Income on population mental health inequalities in the UK: A microsimulation modelling study.

BACKGROUND: Population mental health in the United Kingdom (UK) has deteriorated, alongside worsening socioeconomic conditions, over the last decade. Policies such as Universal Basic Income (UBI) have been suggested as an alternative economic approach to improve population mental health and reduce health inequalities. UBI may improve mental health (MH), but to our knowledge, no studies have trialled or modelled UBI in whole populations. We aimed to estimate the short-term effects of introducing UBI on mental health in the UK working-age population. METHODS AND FINDINGS: Adults aged 25 to 64 years were simulated across a 4-year period from 2022 to 2026 with the SimPaths microsimulation model, which models the effects of UK tax/benefit policies on mental health via income, poverty, and employment transitions. Data from the nationally representative UK Household Longitudinal Study were used to generate the simulated population (n = 25,000) and causal effect estimates. Three counterfactual UBI scenarios were modelled from 2023: "Partial" (value equivalent to existing benefits), "Full" (equivalent to the UK Minimum Income Standard), and "Full+" (retaining means-tested benefits for disability, housing, and childcare). Likely common mental disorder (CMD) was measured using the General Health Questionnaire (GHQ-12, score ≥4). Relative and slope indices of inequality were calculated, and outcomes stratified by gender, age, education, and household structure. Simulations were run 1,000 times to generate 95% uncertainty intervals (UIs). Sensitivity analyses relaxed SimPaths assumptions about reduced employment resulting from Full/Full+ UBI. Partial UBI had little impact on poverty, employment, or mental health. Full UBI scenarios practically eradicated poverty but decreased employment (for Full+ from 78.9% [95% UI 77.9, 79.9] to 74.1% [95% UI 72.6, 75.4]). Full+ UBI increased absolute CMD prevalence by 0.38% (percentage points; 95% UI 0.13, 0.69) in 2023, equivalent to 157,951 additional CMD cases (95% UI 54,036, 286,805); effects were largest for men (0.63% [95% UI 0.31, 1.01]) and those with children (0.64% [95% UI 0.18, 1.14]). In our sensitivity analysis assuming minimal UBI-related employment impacts, CMD prevalence instead fell by 0.27% (95% UI -0.49, -0.05), a reduction of 112,228 cases (95% UI 20,783, 203,673); effects were largest for women (-0.32% [95% UI -0.65, 0.00]), those without children (-0.40% [95% UI -0.68, -0.15]), and those with least education (-0.42% [95% UI -0.97, 0.15]). There was no effect on educational mental health inequalities in any scenario, and effects waned by 2026. The main limitations of our methods are the model's short time horizon and focus on pathways from UBI to mental health solely via income, poverty, and employment, as well as the inability to integrate macroeconomic consequences of UBI; future iterations of the model will address these limitations. CONCLUSIONS: UBI has potential to improve short-term population mental health by reducing poverty, particularly for women, but impacts are highly dependent on whether individuals choose to remain in employment following its introduction. Future research modelling additional causal pathways between UBI and mental health would be beneficial.

Causal Assessment of Income Inequality on Self-Rated Health and All-Cause Mortality: A Systematic Review and Meta-Analysis.

Policy Points Income is thought to impact a broad range of health outcomes. However, whether income inequality (how unequal the distribution of income is in a population) has an additional impact on health is extensively debated. Studies that use multilevel data, which have recently increased in popularity, are necessary to separate the contextual effects of income inequality on health from the effects of individual income on health. Our systematic review found only small associations between income inequality and poor self-rated health and all-cause mortality. The available evidence does not suggest causality, although it remains methodologically flawed and limited, with very few studies using natural experimental approaches or examining income inequality at the national level. CONTEXT: Whether income inequality has a direct effect on health or is only associated because of the effect of individual income has long been debated. We aimed to understand the association between income inequality and self-rated health (SRH) and all-cause mortality (mortality) and assess if these relationships are likely to be causal. METHODS: We searched Medline, ISI Web of Science, Embase, and EconLit (PROSPERO: CRD42021252791) for studies considering income inequality and SRH or mortality using multilevel data and adjusting for individual-level socioeconomic position. We calculated pooled odds ratios (ORs) for poor SRH and relative risk ratios (RRs) for mortality from random-effects meta-analyses. We critically appraised included studies using the Risk of Bias in Nonrandomized Studies - of Interventions tool. We assessed certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework and causality using Bradford Hill (BH) viewpoints. FINDINGS: The primary meta-analyses included 2,916,576 participants in 38 cross-sectional studies assessing SRH and 10,727,470 participants in 14 cohort studies of mortality. Per 0.05-unit increase in the Gini coefficient, a measure of income inequality, the ORs and RRs (95% confidence intervals) for SRH and mortality were 1.06 (1.03-1.08) and 1.02 (1.00-1.04), respectively. A total of 63.2% of SRH and 50.0% of mortality studies were at serious risk of bias (RoB), resulting in very low and low certainty ratings, respectively. For SRH and mortality, we did not identify relevant evidence to assess the specificity or, for SRH only, the experiment BH viewpoints; evidence for strength of association and dose-response gradient was inconclusive because of the high RoB; we found evidence in support of temporality and plausibility. CONCLUSIONS: Increased income inequality is only marginally associated with SRH and mortality, but the current evidence base is too methodologically limited to support a causal relationship. To address the gaps we identified, future research should focus on income inequality measured at the national level and addressing confounding with natural experiment approaches.

Social media use and health risk behaviours in young people: systematic review and meta-analysis.

OBJECTIVES: To examine the association between social media use and health risk behaviours in adolescents (defined as those 10-19 years). DESIGN: Systematic review and meta-analysis. DATA SOURCES: EMBASE, Medline, APA PsycINFO, SocINDEX, CINAHL, SSRN, SocArXic, PsyArXiv, medRxiv, and Google Scholar (1 January 1997 to 6 June 2022). METHODS: Health risk behaviours were defined as use of alcohol, drugs, tobacco, electronic nicotine delivery systems, unhealthy dietary behaviour, inadequate physical activity, gambling, and anti-social, sexual risk, and multiple risk behaviours. Included studies reported a social media variable (ie, time spent, frequency of use, exposure to health risk behaviour content, or other social media activities) and one or more relevant outcomes. Screening and risk of bias assessments were completed independently by two reviewers. Synthesis without meta-analysis based on effect direction and random-effects meta-analyses was used. Effect modification was explored using meta-regression and stratification. Certainty of evidence was assessed using GRADE (Grading of Recommendations, Assessment, Development and Evaluations). RESULTS: Of 17 077 studies screened, 126 were included (73 included in meta-analyses). The final sample included 1 431 534 adolescents (mean age 15.0 years). Synthesis without meta-analysis indicated harmful associations between social media and all health risk behaviours in most included studies, except inadequate physical activity where beneficial associations were reported in 63.6% of studies. Frequent (v infrequent) social media use was associated with increased alcohol consumption (odds ratio 1.48 (95% confidence interval 1.35 to 1.62); n=383 068), drug use (1.28 (1.05 to 1.56); n=117 646), tobacco use (1.85, 1.49 to 2.30; n=424 326), sexual risk behaviours (1.77 (1.48 to 2.12); n=47 280), anti-social behaviour (1.73 (1.44 to 2.06); n=54 993), multiple risk behaviours (1.75 (1.30 to 2.35); n=43 571), and gambling (2.84 (2.04 to 3.97); n=26 537). Exposure to content showcasing health risk behaviours on social media (v no exposure) was associated with increased odds of use of electronic nicotine delivery systems (1.73 (1.34 to 2.23); n=721 322), unhealthy dietary behaviours (2.48 (2.08 to 2.97); n=9892), and alcohol consumption (2.43 (1.25 to 4.71); n=14 731). For alcohol consumption, stronger associations were identified for exposure to user generated content (3.21 (2.37 to 4.33)) versus marketer generated content (2.12 (1.06 to 4.24)). For time spent on social media, use for at least 2 h per day (v <2 h) increased odds of alcohol consumption (2.12 (1.53 to 2.95); n=12 390). GRADE certainty was moderate for unhealthy dietary behaviour, low for alcohol use, and very low for other investigated outcomes. CONCLUSIONS: Social media use is associated with adverse health risk behaviours in young people, but further high quality research is needed to establish causality, understand effects on health inequalities, and determine which aspects of social media are most harmful. STUDY REGISTRATION: PROSPERO, CRD42020179766.

The relationship between time spent on social media and adolescent alcohol use: a longitudinal analysis of the UK Millennium Cohort Study.

BACKGROUND: To estimate the effect of social media use in 14 year olds on risk of and inequalities in alcohol use and binge drinking at 17 years. METHODS: Using the UK-representative Millennium Cohort Study, the relationship between time spent on social media (assessed using questionnaires [n = 8987] and time-use-diaries [n = 2520]) with frequency of alcohol use in the past month and binge drinking was estimated using adjusted odds ratios (AORs) or adjusted relative risk ratios (ARRRs). Associations within low and high parental education groups were compared to examine effect modification. Analyses accounted for pre-specified confounders, baseline outcome measures (to address reverse causality), sample design, attrition and item-missingness (through multiple imputation). RESULTS: Questionnaire-reported time spent on social media was associated with increased risk of alcohol use and binge drinking in a dose-response manner. Compared to 1-< 30 min/day social media users, 30 min-<1 h/day users were more likely to report alcohol use ≥6 times/month (ARRR 1.62 [95% confidence interval 1.20 to 2.20]) and binge drinking (AOR 1.51 [1.22 to 1.87]), as were 1-<2 h/day users (ARRR 2.61 [1.90 to 3.58]; AOR 2.06 [1.69 to 2.52]) and ≥2 h/day users (ARRR 4.80 [3.65 to 6.32]; AOR 3.07 [2.54 to 3.70]). Social media measured by time-use-diary was associated with higher risks, although not always demonstrating a dose-response relationship. The effect of social media use (vs no-use) on binge drinking was larger in the higher (vs lower) parental education groups. Analyses repeated in complete case samples, and with adjustment for baseline outcome measures revealed consistent findings. CONCLUSIONS: Findings suggest social media use may increase risk of alcohol use and binge drinking. Regulatory action protecting adolescents from harmful alcohol-related social media content is necessary.

Understanding inequalities in mental health by family structure during COVID-19 lockdowns: evidence from the UK Household Longitudinal Study.

PURPOSE: The COVID-19 pandemic increased psychiatric distress and impacts differed by family structure. We aimed to identify mechanisms contributing to these inequalities. METHODS: Survey data were from the UK Household Longitudinal Study. Psychiatric distress (GHQ-12) was measured in April 2020 (first UK lockdown; n = 10,516), and January 2021 (lockdown re-introduced following eased restrictions; n = 6,893). Pre-lockdown family structure comprised partner status and presence of children (< 16 years). Mediating mechanisms included: active employment, financial strain, childcare/home-schooling, caring, and loneliness. Monte Carlo g-computation simulations were used to adjust for confounding and estimate total effects and decompositions into: controlled direct effects (effects if the mediator was absent), and portions eliminated (PE; representing differential exposure and vulnerability to the mediator). RESULTS: In January 2021, after adjustment, we estimated increased risk of distress among couples with children compared to couples with no children (RR: 1.48; 95% CI 1.15-1.82), largely because of childcare/home-schooling (PE RR: 1.32; 95% CI 1.00-1.64). Single respondents without children also had increased risk of distress compared to couples with no children (RR: 1.55; 95% CI 1.27-1.83), and the largest PE was for loneliness (RR: 1.16; 95% CI 1.05-1.27), though financial strain contributed (RR: 1.05; 95% CI 0.99-1.12). Single parents demonstrated the highest levels of distress, but confounder adjustment suggested uncertain effects with wide confidence intervals. Findings were similar in April 2020 and when stratified by sex. CONCLUSION: Access to childcare/schooling, financial security and social connection are important mechanisms that need addressing to avoid widening mental health inequalities during public health crises.

Co-occurring homelessness, justice involvement, opioid dependence and psychosis: a cross-sectoral data linkage study.

BACKGROUND: Administrative data offer unique opportunities for researching experiences which pose barriers to participation in primary research and household surveys. Experiencing multiple social disadvantages is associated with very poor health outcomes, but little is known about how often this occurs and what combinations are most common. We linked administrative data across public services to create a novel population cohort containing information on experiences of homelessness, justice involvement, opioid dependence and psychosis. METHODS: We securely linked administrative data from (i) a population register derived from general practitioner registrations; (ii) local authority homelessness applications; (iii) prison records; (iv) criminal justice social work reports; (v) community dispensing for opioid substitution therapy; and (vi) a psychosis clinical register, for people aged ≥18 years resident in Glasgow, Scotland between 01 April 2010 and 31 March 2014. We estimated period prevalence and compared demographic characteristics for different combinations. RESULTS: Of 536 653 individuals in the cohort, 28 112 (5.2%) had at least one of the experiences of interest during the study period and 5178 (1.0%) had more than one. Prevalence of individual experiences varied from 2.4% (homelessness) to 0.7% (psychosis). The proportion of people with multiple co-occurring experiences was highest for imprisonment (50%) and lowest for psychosis (14%). Most combinations showed a predominance of men living in the most deprived areas of Scotland. CONCLUSIONS: Cross-sectoral record linkage to study multiple forms of social disadvantage showed that co-occurrence of these experiences was relatively common. Following this demonstration of feasibility, these methods offer opportunities for evaluating the health impacts of policy and service change.

Effects of poverty on mental health in the UK working-age population: causal analyses of the UK Household Longitudinal Study.

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.

To what extent does income explain the effect of unemployment on mental health? Mediation analysis in the UK Household Longitudinal Study.

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.

Psychological distress, depression, anxiety, and life satisfaction following COVID-19 infection: evidence from 11 UK longitudinal population studies.

BACKGROUND: Evidence on associations between COVID-19 illness and mental health is mixed. We aimed to examine whether COVID-19 is associated with deterioration in mental health while considering pre-pandemic mental health, time since infection, subgroup differences, and confirmation of infection via self-reported test and serology data. METHODS: We obtained data from 11 UK longitudinal studies with repeated measures of mental health (psychological distress, depression, anxiety, and life satisfaction; mental health scales were standardised within each study across time) and COVID-19 status between April, 2020, and April, 2021. We included participants with information available on at least one mental health outcome measure and self-reported COVID-19 status (suspected or test-confirmed) during the pandemic, and a subset with serology-confirmed COVID-19. Furthermore, only participants who had available data on a minimum set of covariates, including age, sex, and pre-pandemic mental health were included. We investigated associations between having ever had COVID-19 and mental health outcomes using generalised estimating equations. We examined whether associations varied by age, sex, ethnicity, education, and pre-pandemic mental health, whether the strength of the association varied according to time since infection, and whether associations differed between self-reported versus confirmed (by test or serology) infection. FINDINGS: Between 21 Dec, 2021, and July 11, 2022, we analysed data from 54 442 participants (ranging from a minimum age of 16 years in one study to a maximum category of 90 years and older in another; including 33 200 [61·0%] women and 21 242 [39·0%] men) from 11 longitudinal UK studies. Of 40 819 participants with available ethnicity data, 36 802 (90·2%) were White. Pooled estimates of standardised differences in outcomes suggested associations between COVID-19 and subsequent psychological distress (0·10 [95% CI 0·06 to 0·13], I2=42·8%), depression (0·08 [0·05 to 0·10], I2=20·8%), anxiety (0·08 [0·05 to 0·10], I2=0·0%), and lower life satisfaction (-0·06 [-0·08 to -0·04], I2=29·2%). We found no evidence of interactions between COVID-19 and sex, education, ethnicity, or pre-pandemic mental health. Associations did not vary substantially between time since infection of less than 4 weeks, 4-12 weeks, and more than 12 weeks, and were present in all age groups, with some evidence of stronger effects in those aged 50 years and older. Participants who self-reported COVID-19 but had negative serology had worse mental health outcomes for all measures than those without COVID-19 based on serology and self-report. Participants who had positive serology but did not self-report COVID-19 did not show association with mental health outcomes. INTERPRETATION: Self-reporting COVID-19 was longitudinally associated with deterioration in mental health and life satisfaction. Our findings emphasise the need for greater post-infection mental health service provision, given the substantial prevalence of COVID-19 in the UK and worldwide. FUNDING: UK Medical Research Council and UK National Institute for Health and Care Research.

Development processes for e-cigarette public health recommendations lacked transparency in managing conflicts of interest.

OBJECTIVES: To investigate how guideline development groups collect and manage conflicts of interest (COI) when producing electronic cigarette (e-cigarette) recommendations. STUDY DESIGN AND SETTING: Public health bodies that had produced e-cigarette recommendations were identified from four purposively selected jurisdictions (World Health Organization, United Kingdom, Australia, and United States). We analysed their COI policies and conducted 15 interviews with guideline methodologists, policymakers, and academics in guideline development groups. RESULTS: Only five of 10 public health bodies had a publicly available COI policy. Participants discussed the importance of those involved in the development process declaring COI. However, there were differences in who had to report COI, the time period asked about, and what and how declarations are made. COI policies and participants discussed a range of approaches for managing COI, from limiting involvement to disqualification from the recommendation development process. Participants considered the current processes for collecting and managing COI insufficient due to their open interpretation and possibility for partial declarations of interest. CONCLUSION: The management of COI varies across public health bodies, with little standardization and lack of transparency. To improve the collection and management of COI, and ultimately increase the trustworthiness of recommendations, guideline development groups should draw upon a comprehensive and accessible COI policy.

Premature mortality in people affected by co-occurring homelessness, justice involvement, opioid dependence, and psychosis: a retrospective cohort study using linked administrative data.

BACKGROUND: Homelessness, opioid dependence, justice involvement, and psychosis are each associated with an increased risk of poor health and commonly co-occur in the same individuals. Most existing studies of mortality associated with this co-occurrence rely on active follow-up methods prone to selection and retention bias, and focus on a limited set of specific exposures rather than taking a population-based approach. To address these limitations, we did a retrospective cohort study using linked administrative data. METHODS: In this retrospective cohort study, we linked a population register of adults resident in Glasgow, UK, to administrative datasets from homelessness and criminal justice services; community pharmacies; and a clinical psychosis registry with data from April 1, 2010 to March 31, 2014. Linkage to death registrations from April 1, 2014 to March 31, 2019 provided follow-up data on premature mortality (age <75 years) from all causes, non-communicable diseases, and causes considered potentially avoidable through health-care or public health intervention. We estimated hazard ratios (HR) using Poisson regression, adjusting for age, gender, socioeconomic deprivation, and calendar time. FINDINGS: Of 536 653 cohort members, 11 484 (2·1%) died during follow-up. All-cause premature mortality was significantly higher among people with multiple exposures than among people with single exposures, and among people with any exposure than among people with none (eg, homelessness plus other exposures vs no exposures: HR 8·4 [95% CI 7·3-9·5]; homelessness alone vs no exposures: HR 2·2 [1·9-2·5]). Avoidable premature mortality was highest among those with multiple exposures (eg, imprisonment plus other exposures vs no exposures: HR 10·5 [9·1-12·3]; imprisonment alone vs no exposures: HR 3·8 [3·0-4·8]). Premature mortality from non-communicable disease was higher among those with any exposures than among those with none, despite accounting for a lower proportion of deaths in the exposed group; although in some cases there was little difference between estimates for single versus multiple exposures. INTERPRETATION: The co-occurrence of at least two of homelessness, opioid dependence, justice involvement, or psychosis is associated with very high rates of premature mortality, particularly from avoidable causes of death, including non-communicable disease. Responding to these findings demands wide-ranging efforts across health-care provision, public health, and social policy. Future work should examine the timing and sequencing of exposures to better understand the causal pathways underlying excess mortality. FUNDING: Chief Scientist Office, Medical Research Council, NHS Research Scotland.

How do income changes impact on mental health and wellbeing for working-age adults? A systematic review and meta-analysis.

BACKGROUND: Lower incomes are associated with poorer mental health and wellbeing, but the extent to which income has a causal effect is debated. We aimed to synthesise evidence from studies measuring the impact of changes in individual and household income on mental health and wellbeing outcomes in working-age adults (aged 16-64 years). METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Science, PsycINFO, ASSIA, EconLit, and RePEc on Feb 5, 2020, for randomised controlled trials (RCTs) and quantitative non-randomised studies. We had no date limits for our search. We included English-language studies measuring effects of individual or household income change on any mental health or wellbeing outcome. We used Cochrane risk of bias (RoB) tools. We conducted three-level random-effects meta-analyses, and explored heterogeneity using meta-regression and stratified analyses. Synthesis without meta-analysis was based on effect direction. Critical RoB studies were excluded from primary analyses. Certainty of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE). This study is registered with PROSPERO, CRD42020168379. FINDINGS: Of 16 521 citations screened, 136 were narratively synthesised (12·5% RCTs) and 86 meta-analysed. RoB was high: 30·1% were rated critical and 47·1% serious or high. A binary income increase lifting individuals out of poverty was associated with 0·13 SD improvement in mental health measures (95% CI 0·07 to 0·20; n=42 128; 18 studies), considerably larger than other income increases (0·01 SD improvement, 0·002 to 0·019; n=216 509, 14 studies). For wellbeing, increases out of poverty were associated with 0·38 SD improvement (0·09 to 0·66; n=101 350, 8 studies) versus 0·16 for other income increases (0·07 to 0·25; n=62 619, 11 studies). Income decreases from any source were associated with 0·21 SD worsening of mental health measures (-0·30 to -0·13; n=227 804, 11 studies). Effect sizes were larger in low-income and middle-income settings and in higher RoB studies. Heterogeneity was high (I2=79-87%). GRADE certainty was low or very low. INTERPRETATION: Income changes probably impact mental health, particularly where they move individuals out of poverty, although effect sizes are modest and certainty low. Effects are larger for wellbeing outcomes, and potentially for income losses. To best support population mental health, welfare policies need to reach the most socioeconomically disadvantaged. FUNDING: Wellcome Trust, Medical Research Council, Chief Scientist Office, and European Research Council.

Association and pathways between shift work and cardiovascular disease: a prospective cohort study of 238 661 participants from UK Biobank.

BACKGROUND: This study aimed to study the association between shift work and incident and fatal cardiovascular disease (CVD), and to explore modifying and mediating factors. METHODS: This is a population-based, prospective cohort study with a median follow-up of 11 years; 238 661 UK Biobank participants who were in paid employment or self-employed at baseline assessment were included. RESULTS: Shift workers had higher risk of incident [hazard ratio (HR) 1.11, 95% confidence interval (CI) 1.06-1.19] and fatal (HR 1.25, 95% CI 1.08-1.44) CVD compared with non-shift workers, after adjusting for socio-economic and work-related factors. The risk was higher with longer duration of shift work, in women and in jobs with little heavy manual labour. Current smoking, short sleep duration, poor sleep quality, adiposity, higher glycated haemoglobin and higher cystatin C were identified as the main potentially modifiable mediators. Mediators collectively explained 52.3% of the associations between shift work and incident CVDs. CONCLUSIONS: Shift workers have higher risk of incident and fatal CVD, partly mediated through modifiable risk factors such as smoking, sleep duration and quality, adiposity and metabolic status. Workplace interventions targeting these mediators have the potential to alleviate shift workers' CVD risk.

Which is most important for mental health: Money, poverty, or paid work? A fixed-effects analysis of the UK Household Longitudinal Study.

BACKGROUND: The relative importance of income, poverty and unemployment status for mental health is unclear, and understanding this has implications for income and welfare policy design. We aimed to assess the association between changes in these exposures and mental health. METHODS: We measured effects of three transition exposures between waves of the UK Household Longitudinal Study from 2010/11-2019/20 (n=38,697, obs=173,859): income decreases/increases, moving in/out of poverty, and job losses/gains. The outcome was General Health Questionnaire (GHQ), which measures likelihood of common mental disorder (CMD) as a continuous (GHQ-36) and binary measure (score ≥4 = case). We used fixed-effects linear and linear probability models to adjust for time invariant and time-varying confounders. To investigate effect modification, we stratified analyses by age, sex and highest education. RESULTS: A 10% income decrease/increase was associated with a 0.02% increase (95% CI 0.00, 0.04) and 0.01% reduction (95% CI -0.03, 0.02) in likelihood of CMD respectively. Effect sizes were larger for moving into poverty (+1.8% [0.2, 3.5]), out of poverty (-1.8%, [-3.2, -0.3]), job loss (+15.8%, [13.6, 18.0]) and job gain (-11.4%, [-14.4, -8.4]). The effect of new poverty was greater for women (+2.3% [0.8, 3.9] versus +1.2% [-1.1, 3.5] for men) but the opposite was true for job loss (+17.8% [14.4, 21.2] for men versus +13.5% [9.8, 17.2] for women). There were no clear differences by age, but those with least education experienced the largest effects from poverty transitions, especially moving out of poverty (-2.9%, [-5.7, -0.0]). CONCLUSIONS: Moving into unemployment was most strongly associated with CMD, with poverty also important but income effects generally much smaller. Men appear most sensitive to employment transitions, but poverty may have larger impacts on women and those with least education. As the COVID-19 pandemic recedes, minimising unemployment as well as poverty is crucial for population mental health.

Social inequalities and hospital admission for unintentional injury in young children in Scotland: A nationwide linked cohort study.

BACKGROUND: Unintentional injury is a leading cause of death/disability, with more disadvantaged children at greater risk. Understanding how inequalities vary by injury type, age, severity, and place of injury, can inform prevention. METHODS: For all Scotland-born children 2009-2013 (n=195,184), hospital admissions for unintentional injury (HAUI) were linked to socioeconomic circumstances (SECs) at birth: area deprivation via the Scottish Index of Multiple Deprivation (SIMD), mother's occupational social class, parents' relationship status. HAUI was examined from birth-five, and during infancy. We examined HAUI frequency, severity, injury type, and injury location (home vs. elsewhere). We estimated relative inequalities using the relative indices of inequality (RII, 95% CIs), before and after adjusting for demographics and other non-mediating SECs. FINDINGS: More disadvantaged children were at greater risk of any HAUI from birth-five, RII: 1•59(1•49-1•70), 1•74(1•62-1•86), 1•97(1•84-2•12) for area deprivation, maternal occupational social class, and relationship status respectively. These attenuated after adjustment (1•15 [1•06-1•24], 1.22 [1•12-1•33], 1.32 [1•21-1•44]). Inequalities were greater for severe (vs. non-severe), multiple (vs. one-off) and home (vs. other location) injuries. Similar patterns were seen in infancy, excluding SIMD-inequalities in falls, where infants living in more disadvantaged neighbourhoods were at lower risk (0•79 [0•62-1•00]). After adjustment, reverse SIMD-gradients were also observed for all injuries and poisonings. INTERPRETATION: Children living in more disadvantaged households are more likely to be injured across multiple dimensions of HAUI in Scotland. Upstream interventions which tackle family-level disadvantage may be most effective at reducing childhood HAUI. FUNDING: Wellcome Trust, Medical Research Council, Scottish Government Chief Scientist Office.