Essays on Human Capital, Income and Health

In this dissertation I focus on the interactions between mental health and other aspects of human capital. In the first chapter, I examine whether longer compulsory schooling has a causal effect on mental health, exploiting a 1972 reform which raised the minimum school leaving age from age 15 to 16 in Great Britain. Using a regression discontinuity design, I find that the reform did not improve mental health. I provide evidence that extending the duration of compulsory schooling impacts mental health through channels other than increased educational attainment. I argue that these effects may mitigate or offset the health returns to increased educational attainment.In the second chapter, I examine the long-term labour market effects of Entry to Employment (E2E), an intervention designed to improve the non-cognitive skills of low-achieving adolescents in England. Using an instrumental variable (IV) approach, I find that E2E courses substantially increased earnings of participants in the long-run. The increase is primarily driven by a large and significant effect on the probability to be in employment. Placebo tests and robustness checks provide further support that the link is unlikely to be affected by unobserved confounders.In the third chapter, I analyse the effect of suffering from depressive symptoms on cognitive abilities. Cognitive skills are important determinants of employment and productivity in older adults. Although cognitive decline is often linked to changes in mental health, the causal nature of the association between mental illness and cognitive performance is not established. I analyse the effect of depressive symptoms on cognitive function. Based on longitudinal data for older adults of working age, I use an instrumental variable approach to show that worsening depressive symptoms lead to a decline in cognitive skills. The economic consequences of impaired cognition caused by depressive symptoms may be a large component of mental illness’s social costs.In the fourth chapter, I examine whether the extra income received from the UK State Pension has a causal effect on health. To isolate the effect of pension income, I focus on women who had already left the labour force before reaching their State Pension Age. I use a major pension reform to compare the mental health and well-being of women of the same age but with different pension eligibility. I find that becoming eligible to the State Pension improves the financial well-being for women of low Socio-Economic Status (SES) but not for high SES women. The extra income provided by the State Pension has a strong positive effect on a wide range of physical and mental health outcomes and well-being indicators for low SES women but not for high SES women.<br/

Employment outcomes of people with Long Covid symptoms:community-based cohort study

Background: Evidence on the long-term employment consequences of SARS-CoV-2 infection is lacking. We used data from a large, community-based sample in the UK to estimate associations between Long Covid and employment outcomes.Methods: This was an observational, longitudinal study using a pre-post design. We included survey participants from 3 February 2021 to 30 September 2022 when they were aged 16-64 years and not in education. Using conditional logit modelling, we explored the time-varying relationship between Long Covid status ≥12 weeks after a first test-confirmed SARS-CoV-2 infection (reference: pre-infection) and labour market inactivity (neither working nor looking for work) or workplace absence lasting ≥4 weeks.Results: Of 206,299 participants (mean age 45 years, 54% female, 92% white), 15% were ever labour market inactive and 10% were ever long-term absent during follow-up. Compared with pre-infection, inactivity was higher in participants reporting Long Covid 30 to &lt;40 weeks (adjusted odds ratio [aOR]: 1.45; 95% CI: 1.17 to 1.81) or 40 to &lt;52 weeks (aOR: 1.34; 95% CI: 1.05 to 1.72) post-infection. Combining with official statistics on Long Covid prevalence, and assuming a correct statistical model, our estimates translate to 27,000 (95% CI: 6,000 to 47,000) working-age adults in the UK being inactive because of Long Covid in July 2022.Conclusions: Long Covid is likely to have contributed to reduced participation in the UK labour market, though it is unlikely to be the sole driver. Further research is required to quantify the contribution of other factors, such as indirect health effects of the pandemic

Changes in the trajectory of Long Covid symptoms following COVID-19 vaccination: community-based cohort study

OBJECTIVE: To estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination. DESIGN: Observational cohort study using individual-level interrupted time series analysis. SETTING: Random sample from the community population of the UK. PARTICIPANTS: 28,356 COVID-19 Infection Survey participants (mean age 46 years, 56% female, 89% white) aged 18 to 69 years who received at least their first vaccination after test-confirmed infection. MAIN OUTCOME MEASURES: Presence of Long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021. RESULTS: Median follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (84% of participants). First vaccination was associated with an initial 12.8% decrease (95% confidence interval: -18.6% to -6.6%, p<0.001) in the odds of Long Covid, with the data being compatible with both increases and decreases in the trajectory (+0.3% per week, 95% CI: -0.6% to +1.2% per week, p=0.51) after this. Second vaccination was associated with an 8.8% decrease (95% CI: -14.1% to -3.1%, p=0.003) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (-1.2% to -0.4%, p<0.001) per week. There was no statistical evidence of heterogeneity in associations between vaccination and Long Covid by socio-demographic characteristics, health status, whether hospitalised with acute COVID-19, vaccine type (adenovirus vector or mRNA), or duration from infection to vaccination. CONCLUSIONS: : The likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and there was evidence of a sustained improvement after the second dose, at least over the median follow-up time of 67 days. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed

Religious affiliation and the risk of COVID 19 related mortality; a retrospective analysis of variation in pre and post lockdown risk by religious group in England and Wales

AbstractBackgroundCOVID 19 mortality risk is associated with demographic and behavioural factors; furthermore religious gatherings have been linked with the spread of COVID. We sought to understand the variation in the risk of COVID 19 related death across religious groups in the UK both before and after lockdown.MethodsWe conducted a retrospective cohort study of usual residents in England and Wales enumerated at the 2011 Census (n = 48,422,583), for risk of death involving COVID-19 using linked death certificates. Cox regression models were estimated to compare risks between religious groups. Time dependent religion coefficients were added to the model allowing hazard ratios (HRs) pre and post lockdown period to be estimated separately.ResultsCompared to Christians all religious groups had an elevated risk of death involving COVID-19; the largest age adjusted HRs were for Muslim and Jewish males at 2.5 (95% confidence interval 2.3-2.7) and 2.1 (1.9-2.5), respectively. The corresponding HRs for Muslim and Jewish females were 1.9 (1.7-2.1) and 1.5 (1.7-2.1). The difference in risk between groups contracted after lockdown. Those who affiliated with no religion had the lowest risk of COVID 19 related death before and after lockdown.ConclusionThe majority of the variation in COVID 19 mortality risk was explained by controlling for socio demographic and geographic determinants; however, Jews remained at a higher risk of death compared to all other groups. Lockdown measures were associated with reduced differences in COVID 19 mortality rates between religious groups, further research is required to understand the causal mechanisms.</jats:sec

The effect on women's health of extending parental leave: a quasi-experimental registry-based cohort study

BACKGROUND: Parental leave policies have been hypothesized to benefit mothers' mental health. We assessed the impact of a 6-week extension of parental leave in Denmark on maternal mental health. METHODS: We linked individual-level data from Danish national registries on maternal sociodemographic characteristics and psychiatric diagnoses. A regression discontinuity design was applied to study the increase in parental leave duration after 26 March 1984. We included women who had given birth between 1 January 1981 and 31 December 1987. Our outcome was a first psychiatric diagnosis following the child's birth, ascertained as the first day of inpatient hospital admission for any psychiatric disorder. We presented cumulative incidences for the 30-year follow-up period and reported absolute risk differences between women eligible for the reform vs not, in 5-year intervals. RESULTS: In all, 291 152 women were followed up until 2017, death, emigration or date of first psychiatric diagnosis. The median follow-up time was 29.99 years, corresponding to 10 277 547 person-years at risk. The cumulative incidence of psychiatric diagnoses at 30 years of follow-up was 59.5 (95% CI: 57.4 to 61.6) per 1000 women in the ineligible group and 57.5 (95% CI: 55.6 to 59.4) in the eligible group. Eligible women took on average 32.85 additional days of parental leave (95% CI: 29.20 to 36.49) and had a lower probability of having a psychiatric diagnosis within 5 years [risk difference (RD): 2.4 fewer diagnoses per 1000 women, 95% CI: 1.5 to 3.2] and up to 20 years after the birth (RD: 2.3, 95% CI: 0.4 to 4.2). In subgroup analyses, the risk reduction was concentrated among low-educated, low-income and single women. CONCLUSIONS: Longer parental leave may confer mental health benefits to women, in particular to those from disadvantaged backgrounds

Excess mortality among essential workers in England and Wales during the COVID-19 pandemic: an updated analysis

BACKGROUND: Excess mortality from all causes combined during the COVID-19 pandemic in England and Wales in 2020 was predominantly higher for essential workers. In 2021, the vaccination programme had begun, new SARS-CoV-2 variants were identified and different policy approaches were used. We have updated our previous analyses of excess mortality in England and Wales to include trends in excess mortality by occupation for 2021. METHODS: We estimated excess mortality for working age adults living in England and Wales by occupational group for each month in 2021 and for the year as a whole. RESULTS: During 2021, excess mortality remained higher for most groups of essential workers than for non-essential workers. It peaked in January 2021 when all-cause mortality was 44.6% higher than expected for all occupational groups combined. Excess mortality was highest for adults working in social care (86.9% higher than expected). CONCLUSION: Previously, we reported excess mortality in 2020, with this paper providing an update to include 2021 data. Excess mortality was predominantly higher for essential workers during 2021. However, unlike the first year of the pandemic, when healthcare workers experienced the highest mortality, the highest excess mortality during 2021 was experienced by social care workers

Sociodemographic inequality in COVID-19 vaccination coverage among elderly adults in England: a national linked data study.

OBJECTIVE: To examine inequalities in COVID-19 vaccination rates among elderly adults in England. DESIGN: Cohort study. SETTING: People living in private households and communal establishments in England. PARTICIPANTS: 6 655 672 adults aged ≥70 years (mean 78.8 years, 55.2% women) who were alive on 15 March 2021. MAIN OUTCOME MEASURES: Having received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted ORs using logistic regression models. RESULTS: By 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of black African and black Caribbean ethnic backgrounds, where only 67.2% and 73.8% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 to 5.16) and 4.85 (4.75 to 4.96) times greater than the white British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socioeconomic position (proxied by living in a rented home), being disabled and living either alone or in a multigenerational household were also associated with higher odds of not having received the vaccine. CONCLUSION: Research is now urgently needed to understand why disparities exist in these groups and how they can best be addressed through public health policy and community engagement

Common protocol for validation of the QCOVID algorithm across the four UK nations

Introduction: The QCOVID algorithm is a risk prediction tool for infection and subsequent hospitalisation/death due to SARS-CoV-2. At the time of writing, it is being used in important policy-making decisions by the UK and devolved governments for combatting the COVID-19 pandemic, including deliberations on shielding and vaccine prioritisation. There are four statistical validations exercises currently planned for the QCOVID algorithm, using data pertaining to England, Northern Ireland, Scotland and Wales, respectively. This paper presents a common procedure for conducting and reporting on validation exercises for the QCOVID algorithm. Methods and analysis: We will use open, retrospective cohort studies to assess the performance of the QCOVID risk prediction tool in each of the four UK nations. Linked datasets comprising of primary and secondary care records, virological testing data and death registrations will be assembled in trusted research environments in England, Scotland, Northern Ireland and Wales. We will seek to have population level coverage as far as possible within each nation. The following performance metrics will be calculated by strata: Harrell’s C, Brier Score, R2 and Royston's D. Ethics and dissemination: Approvals have been obtained from relevant ethics bodies in each UK nation. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journal

Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting

INTRODUCTION: Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disability and frailty. Disability and frailty are not routinely collated at population level but are associated with increased risk of falls and fractures, which result in hospital admissions. First, we will examine incidence of falls and fractures during COVID-19 (January 2020-March 2022), focusing on differences between incidence over time against expected rates based on historical data, to determine whether there is evidence of new-onset disability and frailty. Second, we will examine whether those with reported SARS-CoV-2 were at higher risk of falls and fractures. METHODS AND ANALYSIS: This study uses the Office for National Statistics (ONS) Public Health Data Asset, a linked population-level dataset combining administrative health records with sociodemographic data of the 2011 Census and National Immunisation Management System COVID-19 vaccination data for England. Administrative hospital records will be extracted based on specific fracture-centric International Classification of Diseases-10 codes in years preceding COVID-19 (2011-2020). Historical episode frequency will be used to predict expected admissions during pandemic years using time series modelling, if COVID-19 had not occurred. Those predicted admission figures will be compared with actual admissions to assess changes in hospital admissions due to public health measures comprising the pandemic response. Hospital admissions in prepandemic years will be stratified by age and geographical characteristics and averaged, then compared with pandemic year admissions to assess more granular changes. Risk modelling will assess risk of experiencing a fall, fracture or frail fall and fracture, if they have reported a positive case of COVID-19. The combination of these techniques will provide insight into changes in hospital admissions from the COVID-19 pandemic. ETHICS AND DISSEMINATION: This study has approval from the National Statistician's Data Ethics Advisory Committee (NSDEC(20)12). Results will be made available to other researchers via academic publication and shared via the ONS website