Introduction: Depression in old age often has a poor clinical course, although there is substantial variability in depressive symptom trajectories. We aimed to characterise old-age depressive symptom trajectories, assess their multifactorial correlates, and their impact on mortality.

Methods: We used cohort data from 2118 dementia-free community-dwelling adults aged ≥60 years participating in the Swedish National study on Aging and Care in Kungsholmen (SNAC-K). Depressive symptoms were evaluated using the Montgomery-Åsberg Depression Rating Scale at baseline and 1–3 follow-ups over 9 years. Sociodemographic (age, sex, marital status, socioeconomic status), psychosocial (social connections and support), clinical (multimorbidity), and functional (gait speed; cognitive impairment) factors at baseline were considered as trajectory correlates. Generalised growth mixture models and multinomial logit models estimated depression trajectories and their correlates. Cox proportional hazard models estimated all-cause mortality risk.

Results: Three trajectory classes emerged: low, increasing, and U-shaped trajectories of depressive symptoms. Compared to the low trajectory, socioeconomic status involving high financial strain and poor social support was more common in the increasing and U-shaped trajectories. Slow gait speed was linked to higher odds of increasing depressive symptoms, while greater multimorbidity was associated with the U-shaped trajectory. The increasing and U-shaped trajectories were associated with higher mortality risk, and the association for increasing was robust to the adjustment of covariates.

Conclusions: Depressive symptom trajectories in late life are heterogeneous and linked to diverse socio-economic, clinical, and functional factors, some of which are trajectory-specific. Given its association with mortality, older people should be carefully monitored for depressive symptomatology.

Objective To assess the effectiveness of NHS Talking Therapies (NHSTT) service for working-age adults with mild to moderate depression or anxiety and to evaluate the impact of multiple physical long-term conditions (LTCs) on treatment outcomes. Method We have linked routinely collected data from the NHSTT services in South London (UK) with primary care data for aged 18-64 years who had accessed the services between August 2008 and March 2021. The main outcome measures were NHSTT service key performance indicators of 'recovery' and 'reliable improvement'. Multiple and specific physical LTCs represented the exposure of interest. Cox proportional hazard models were used to assess associations between physical LTC exposures and outcomes. Findings Among 35 814 adults (mean age=37, 67% women) attending the NHSTT, physical LTCs were associated with moderately lower 'recovery' rate (adjusted HR (aHR)=0.91, 95% CI 0.88 to 0.95) relative to no LTCs. A dose-response relationship was also observed: the likelihood of 'recovery' decreased with the number of physical LTCs (one condition: aHR=0.95, 95% CI 0.91 to 0.98; two conditions: aHR=0.88, 95% CI 0.83 to 0.93; three conditions: aHR=0.82, 95% CI 0.75 to 0.91; four or more conditions: aHR=0.72, 95% CI 0.61 to 0.85). Conclusion Among working-age adults, the effectiveness of NHSTT services varied with the number and type of physical LTCs. These findings highlight the need for tailored interventions for patients with multiple physical LTCs to improve treatment outcomes.

Introduction The native-born children of migrants represent one of the fastest-growing and most diverse young populations in the world today. A growing body of research highlights an elevated young adult mortality risk in this ‘second generation’ (G2) relative to the majority population at the same ages. Previous studies have tried to understand this increased risk by examining its association with inequality in the adult socioeconomic background (SEB) of the G2. Here, we instead analyse the association of second-generation status with childhood SEB.

Methods We use administrative register data from Sweden to fit multistate, competing-risk, flexible parametric survival models on a data set of 13404 deaths in 2.35million young adults. We examine mortality from all causes and specific causes of death at the generational level and by parental region of birth, both before and after having adjusted for childhood SEB.

Results The G2 have higher all-cause mortality hazard rates (HR=1.29 (95% CIs=1.23 to 1.34)) than the majority population before adjusting for childhood SEB. Following adjustment, the size of the hazard rate is smaller, but remains higher than the majority population (aHR=1.16 (95% CIs=1.11 to 1.21)). The G2 additionally experience persistent and higher hazard rates of mortality from suicide (aHR=1.29 (95% CIs=1.20 to 1.39)), substance misuse (aHR=1.41 (95% CIs=1.26 to 1.58)) and assault (aHR=2.54 (95% CIs=2.02 to 3.20)). By parental origins, similar patterns to those described are documented among G2 that have at least one parent born in Finland, the other Nordic countries, former Yugoslavia, the rest of Europe, sub-Saharan Africa, Northern Africa, and Iran and Iraq. However, higher all-cause (aHR=1.42 (95% CIs=1.33 to 1.51)) and external-cause hazard rates of mortality (aHR=1.59 (95% CIs=1.48 to 1.72)) only persist among G2 with parent(s) born in Finland.

Conclusions G2 with various parental origins have higher mortality rates than the majority population do, and this difference is partly explained by their childhood SEB.

Objectives This study aims to determine how workplace experiences of National Health Service (NHS) staff varied by ethnicity during the COVID-19 pandemic and how these experiences are associated with mental and physical health at the time of the study.

Methods An online Inequalities Survey was conducted by the Tackling Inequalities and Discrimination Experiences in Health Services study in collaboration with NHS CHECK. This Inequalities Survey collected measures relating to workplace experiences (such as personal protective equipment (PPE), risk assessments, redeployments and discrimination) as well as mental health (Patient Health Questionnaire (PHQ-9), Generalised Anxiety Disorder 7 (GAD-7)), and physical health (PHQ-15) from NHS staff working in the 18 trusts participating with the NHS CHECK study between February and October 2021 (N=4622).

Results Regression analysis of this cross-sectional data revealed that staff from black and mixed/other ethnic groups had greater odds of experiencing workplace harassment (adjusted OR (AOR) 2.43 (95% CI 1.56 to 3.78) and 2.38 (95% CI 1.12 to 5.07), respectively) and discrimination (AOR 4.36 (95% CI 2.73 to 6.96) and 3.94 (95% CI 1.67 to 9.33), respectively) compared with white British staff. Staff from black ethnic groups also had greater odds than white British staff of reporting PPE unavailability (AOR 2.16 (95% CI 1.16 to 4.00)). Such workplace experiences were associated with negative physical and mental health outcomes, though this association varied by ethnicity. Conversely, understanding employment rights around redeployment, being informed about and having the ability to inform redeployment decisions were associated with lower odds of poor physical and mental health.

Conclusions Structural changes to the way staff from ethnically minoritised groups are supported, and how their complaints are addressed by leaders within the NHS are urgently required.

Objectives

The progression of long-term conditions (LTCs) from zero-to-one (initiation), and from one-to-many (progression)are common trajectories that impact a person’s quality of life including their ability to work. This study aimed to explore the demographic, socioeconomic, psychosocial, and health-related determinants of LTC initiation and progression, with a focus on work participation.

Methods

Data from 622 working-age adults who had completed two waves (baseline and follow-up) of the South-East London Community Health survey were analysed. Chi square tests and multinomial logistic regression were used to describe the associations between self-reported demographic, socioeconomic, psychosocial, and health-related variables, and the progression of LTCs.

Results

Small social networks, an increased number of stressful life events, low self-rated health, functional impairment, and increased somatic symptom severity were all associated with both the progression from zero-to-one LTC and from one LTC to multimorbidity (two or more LTCs). Renting accommodation (RRR 1.73 [95% CI 1.03–2.90]), smoking (RRR 1.91 [95% CI 1.16–3.14]) and being overweight (RRR 1.88 [95% CL 1.12–3.16]) were unique risk factors of developing initial LTCs, whereas low income (RRR 2.53 [95% CI 1.11–5.80]), working part-time (RRR 2.82 ([95% CL 1.12–7.10]), being unemployed (RRR 4.83 [95% CI 1.69–13.84]), and making an early work exit (RRR 16.86 [95% CI 3.99–71.30]) all increased the risk of progressing from one LTC to multimorbidity compared to being employed full-time. At follow-up, depression was the most prevalent LTC in the unemployed group whereas musculoskeletal conditions were the most prevalent in those working.

Conclusions

The journey to multimorbidity is complex, with both common and unique risk factors. Non-full-time employment was associated with an increased risk of progression to multimorbidity. Future research should explore the risk and benefit pathways between employment and progression of LTCs. Interventions to prevent progression of LTCs should include mitigation of modifiable risk factors such as social isolation.

Background: the socioeconomic distribution of unplanned hospital admissions in older adults is poorly understood. We compared associations of two life-course measures of socioeconomic status (SES) with unplanned hospital admissions while comprehensively accounting for health, and examined the role of social network in this association.

Methods: in 2,862 community-dwelling adults aged 60+ in Sweden, we derived (i) an aggregate life-course SES measure grouping individuals into Low, Middle or High SES based on a summative score, and (ii) a latent class measure that additionally identified a Mixed SES group, characterised by financial difficulties in childhood and old age. The health assessment combined measures of morbidity and functioning. The social network measure included social connections and support components. Negative binomial models estimated the change in hospital admissions over 4 years in relation to SES. Stratification and statistical interaction assessed effect modification by social network.

Results: adjusting for health and social network, unplanned hospitalisation rates were higher for the latent Low SES and Mixed SES group (incidence rate ratio [IRR] = 1.38, 95% confidence interval [CI]: 1.12–1.69, P = 0.002; IRR = 2.06, 95% CI: 1.44–2.94, P < 0.001; respectively; ref: High SES). Mixed SES was at a substantially greater risk of unplanned hospital admissions among those with poor (and not rich) social network (IRR: 2.43, 95% CI: 1.44–4.07; ref: High SES), but the statistical interaction test was non-significant (P = 0.493).

Conclusion: socioeconomic distributions of older adults’ unplanned hospitalisations were largely driven by health, although considering SES dynamics across life can reveal at-risk sub-populations. Financially disadvantaged older adults might benefit from interventions aimed at improving their social network.

Introduction

Prevention of cardiovascular disease and diabetes is a priority in low- and middle-income countries, especially in South Asia where these are leading causes of morbidity and mortality. The metabolic syndrome is a tool to identify cardiometabolic risk, but the validity of the metabolic syndrome as a clinical construct is debated. This study tested the existence of the metabolic syndrome, explored alternative cardiometabolic risk characterisations, and examined genetic and environmental factors in a South Asian population sample.

Methods

Data came from the Colombo Twin and Singleton follow-up Study, which recruited twins and singletons in Colombo, Sri Lanka, in 2012–2015 (n = 3476). Latent class analysis tested the clustering of metabolic syndrome indicators (waist circumference, high-density lipoprotein cholesterol, triglycerides, blood pressure, fasting plasma glucose, medications, and diabetes). Regression analyses tested cross-sectional associations between the identified latent cardiometabolic classes and sociodemographic covariates and health behaviours. Structural equation modelling estimated genetic and environmental contributions to cardiometabolic risk profiles. All analyses were stratified by sex (n = 1509 men, n = 1967 women).

Results

Three classes were identified in men: 1) “Healthy” (52.3%), 2) “Central obesity, high triglycerides, high fasting plasma glucose” (40.2%), and 3) “Central obesity, high triglycerides, diabetes” (7.6%). Four classes were identified in women: 1) “Healthy” (53.2%), 2) “Very high central obesity, low high-density lipoprotein cholesterol, raised fasting plasma glucose” (32.8%), 3) “Very high central obesity, diabetes” (7.2%) and 4) “Central obesity, hypertension, raised fasting plasma glucose” (6.8%). Older age in men and women, and high socioeconomic status in men, was associated with cardiometabolic risk classes, compared to the “Healthy” classes. In men, individual differences in cardiometabolic class membership were due to environmental effects. In women, genetic differences predicted class membership.

Conclusion

The findings did not support the metabolic syndrome construct. Instead, distinct clinical profiles were identified for men and women, suggesting different aetiological pathways.