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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., Competing Interests: Competing interests: KK is member of SAGE and Chair of the SAGE Ethnicity Subgroup. KK also chaired the group that developed the NHS Risk Assessment Framework. Other authors have no competing interests., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Background: Low socioeconomic status is a risk factor for depression. The nature and magnitude of associations can differ cross-culturally and is influenced by a range of contextual factors. We examined the aetiology of socioeconomic indicators and depression symptoms and investigated whether socioeconomic indicators moderate genetic and environmental influences on depression symptoms in a Sri Lankan population., Methods: Data were from a population-based sample of twins (N = 2934) and singletons (N = 1035) in Colombo, Sri Lanka. Standard of living, educational attainment, and financial strain were used to index socioeconomic status. Depression symptoms were assessed using the Revised Beck Depression Inventory. Structural equation modelling explored genetic and environmental influences on socioeconomic indicators and depression symptoms and moderation of aetiological influences on depression symptoms by socioeconomic status., Results: Depression symptoms were associated with lower standard of living, lower educational attainment, and financial strain. Sex differences were evident in the aetiology of standard of living, with a small contribution of genetic influences in females. Educational attainment was moderately heritable in both males and females. Total variance in depression was greater among less socioeconomically advantaged individuals. Modest evidence of moderation of the aetiology of depression by standard of living and education was observed., Limitations: While the sample is representative of individuals living in Colombo District, it may not be representative of different regions of Sri Lanka., Conclusions: The aetiology of depression varies across socioeconomic contexts, suggesting a potential mechanism through which socioeconomic disadvantage increases the risk for depression in Sri Lanka. Findings have implications for cross-cultural investigations of the role of socioeconomic factors in depression and for identifying targets for social interventions., Competing Interests: Declaration of competing interest Matthew Hotopf declares research funding from Innovative Medicines Initiative (European Commission), Janssen, Lundbeck, MSD, Biogen and UCB. All other authors declare no competing interests., (Copyright © 2023. Published by Elsevier B.V.)

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., Competing Interests: This paper represents independent research part funded by NIHR Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, and the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Stagg et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Harber-Aschan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Previous studies have shown associations between major depression and C-reactive protein (CRP) levels. Few studies have considered the extent to which shared genetic and environmental factors contribute to this association, nor have they considered the relationship outside of European populations. We examined the association between CRP levels and depression and their aetiology in a Sri Lankan population., Methods: Data were collected from 2577 twins and 899 singletons in Colombo, Sri Lanka. Depression symptoms were assessed using the revised Beck Depression Inventory (BDI-II). High-sensitive CRP blood levels were assessed using immunoturbidimetry. Linear regressions were performed to test the association between CRP and depression. The heritability of CRP levels was estimated using Structural Equation Modelling., Results: CRP was significantly associated with BMI (p < 0.01) but not depression (p > 0.05). In males, variance in CRP levels was explained by shared environment (51% 95%CIs: 13-62) and non-shared environment (45% 95%CIs: 36-54). In contrast, in females, CRP variance was explained by genetic (41% 95%CIs: 10-52) and non-shared environment (56% 95%CIs: 47-67). A genetic correlation between CRP and BMI was observed in females only., Limitations: CRP level was based on a single data collection point, longer term data collection would give a more accurate picture of an individual's state of inflammation., Conclusions: The lack of association between depression and CRP strengthens the hypothesis that inflammation might contribute to the development of some, but not all types of depression. CRP levels were moderated by the environment, suggesting interventions aimed at reducing CRP levels and risk for inflammatory conditions, particularly in males., (Copyright © 2021. Published by Elsevier B.V.)

Objectives: We set out to develop, evaluate and implement a novel application using natural language processing to text mine occupations from the free-text of psychiatric clinical notes., Design: Development and validation of a natural language processing application using General Architecture for Text Engineering software to extract occupations from de-identified clinical records., Setting and Participants: Electronic health records from a large secondary mental healthcare provider in south London, accessed through the Clinical Record Interactive Search platform. The text mining application was run over the free-text fields in the electronic health records of 341 720 patients (all aged ≥16 years)., Outcomes: Precision and recall estimates of the application performance; occupation retrieval using the application compared with structured fields; most common patient occupations; and analysis of key sociodemographic and clinical indicators for occupation recording., Results: Using the structured fields alone, only 14% of patients had occupation recorded. By implementing the text mining application in addition to the structured fields, occupations were identified in 57% of patients. The application performed on gold-standard human-annotated clinical text at a precision level of 0.79 and recall level of 0.77. The most common patient occupations recorded were 'student' and 'unemployed'. Patients with more service contact were more likely to have an occupation recorded, as were patients of a male gender, older age and those living in areas of lower deprivation., Conclusion: This is the first time a natural language processing application has been used to successfully derive patient-level occupations from the free-text of electronic mental health records, performing with good levels of precision and recall, and applied at scale. This may be used to inform clinical studies relating to the broader social determinants of health using electronic health records., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Inequalities in older adults' health rarely consider life-course aspects of socioeconomic status (SES). We examined the association between lifelong SES and old-age health trajectories, and explored the role of lifestyle factors and depressive symptoms in this association. We followed 2760 adults aged 60+ from the Swedish National Study on Care and Aging, Kungsholmen. SES groups were derived using latent class analysis incorporating seven socioeconomic measures spanning childhood, midlife, and late life. We measured health using the Health Assessment Tool, which combines gait speed, cognition, multimorbidity, and disability. Linear mixed models were used to estimate health trajectories. Four SES groups were identified: High (34.9%), Middle (40.2%), Low (21.2%), and Mixed (3.8%). The Mixed group reported greater financial difficulties in childhood and older age, but varying SES attainment in midlife. Baseline health scores indicated that Mixed SES experienced substantial cognitive and physical deficits 12 years earlier than the High SES group. Compared to the High SES group, the Mixed SES group had the fastest health deterioration (β×time=-0.07, 95% CI:-0.11,-0.02); other groups followed a gradient (High>Middle>Low). Lifestyle factors and depressive symptoms attenuated the gradient but did not explain Mixed group's health disadvantage. Life-long SES measures are crucial for understanding older adults' health inequalities.

Background: Restrictions in the eligibility requirements for disability benefits have been introduced in many countries, on the assumption that this will increase work incentives for people with chronic illness and disabilities. Evidence to support this assumption is unclear, but there is a danger that removal of social protection without increased employment would increase the risk of poverty among disabled people. This paper presents a systematic review of the evidence on the employment effects of changes to eligibility criteria across OECD countries., Methods: Systematic review of all empirical studies from OECD countries from 1990 to June 2018 investigating the effect of changes in eligibility requirements and income replacement level of disability benefits on the employment of disabled people. Studies were narratively synthesised, and meta-analysis was performed using meta-regression on all separate results. The systematic review protocol was registered with the Prospective Register for Systematic Reviews (Registration code: PROSPERO 2018 CRD42018103930)., Results: Seventeen studies met inclusion criteria from seven countries. Eight investigated an expansion of eligibility criteria and nine a restriction. There were 36 separate results included from the 17 studies. Fourteen examined an expansion of eligibility; six found significantly reduced employment, eight no significant effect and one increased employment. Twenty-two results examined a restriction in eligibility for benefits; three found significantly increased employment, 18 no significant effect and one reduced employment. Meta-regression of all studies produced a relative risk of employment of 1.06 (95% CI 0.999 to 1.014; I2 77%)., Conclusions: There was no firm evidence that changes in eligibility affected employment of disabled people. Restricting eligibility therefore has the potential to lead to a growing number of people out of employment with health problems who are not eligible for adequate social protection, increasing their risk of poverty. Policymakers and researchers need to address the lack of robust evidence for assessing the employment impact of these types of welfare reforms as well as the potential wider poverty impacts., Competing Interests: The authors have declared that no competing interests exist.

Multimorbidity and depression are complex multifactorial conditions with major implications for older individuals, their families, and healthcare providers. In this scoping review, we aimed to 1) review findings from longitudinal epidemiological studies investigating the association between multimorbidity and depression; 2) identify potential mechanisms linking multimorbidity and depression; 3) discuss challenges to advance the research field. Overall, evidence emerging from longitudinal studies supports a bidirectional association between the two conditions, although studies are methodologically heterogeneous in terms of design, inclusion criteria, measurement of multimorbidity and depression, and length of follow-up. A variety of biological, psychosocial, and care-related drivers may regulate the transition from multimorbidity to depression, and the other way around, although these mechanisms are yet to be explicitly verified. Further research is required to unravel the intricate interplay between multimorbidity, depression, their common drivers, and precipitating factors underlying the relationship between the two conditions. Understanding these processes will inform strategies aimed at promoting mental and physical health during aging., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Keeping older workers in employment is critical for societies facing the challenge of an ageing population. This study examined the association between types of health conditions and differentials in the probability of employment by level of education among men and women between 60-69 years of age in Canada, Denmark, Sweden and England., Methods: Data were drawn from the Canadian Community Health Survey, Survey of Health, Ageing and Retirement in Europe and English Longitudinal Study of Ageing. We combined country data, applied logistic regression, adjusted for educational level, and stratified the analysis by sex to calculate the odds ratio (OR) of employment (>15 hours work per week) for persons with physical health conditions, mental health conditions (depression) and physical-mental health comorbidity., Results: The odds of employment among men and women with physical-mental health comorbidity were lower compared to those with no/other conditions (men: OR 0.32, 95% CI: 0.25-0.42, women: OR 0.38 95% CI: 0.30-0.48). Women with low education had lower odds of employment compared to their counterparts with high education (OR 0.66, 95% CI: 0.57-0.76). The odds of employment at older ages was lower in Canada, Denmark and England compared with Sweden (e.g. English men: OR 0.48 95% CI 0.40-0.58; English women OR 0.33 95% CI 0.27-0.41)., Conclusions: The odds of employment beyond age 60 is lower for groups with low education, particularly women, and those with physical-mental health co-morbidities. As such, policies to extend working lives should not be 'one size fits all' but instead consider subgroups, in particular, these groups that we have shown to be most vulnerable on the labour market., Competing Interests: The authors have declared that no competing interests exists.

Objectives: Comorbidity is prevalent in older working ages and might affect employment exits. This study aimed to 1) assess the associations between comorbidity and different employment exit routes, and 2) examine such associations by gender., Methods: We used data from employed adults aged 50-62 in the Stockholm Public Health Survey 2002 and 2006, linked to longitudinal administrative income records (N = 10,416). The morbidity measure combined Limiting Longstanding Illness and Common Mental Disorder-captured by the General Health Questionnaire-12 (≥4)-into a categorical variable: 1) No Limiting Longstanding Illness, no Common Mental Disorder, 2) Limiting Longstanding Illness only, 3) Common Mental Disorder only, and 4) comorbid Limiting Longstanding Illness+Common Mental Disorder. Employment status was followed up until 2010, treating early retirement, disability pension and unemployment as employment exits. Competing risk regression analysed the associations between morbidity and employment exit routes, stratifying by gender., Results: Compared to No Limiting Longstanding Illness, no Common Mental Disorder, comorbid Limiting Longstanding Illness+Common Mental Disorder was associated with early retirement in men (subdistribution hazard ratio = 1.73, 95% confidence intervals: 1.08-2.76), but not in women. For men and women, strong associations for disability pension were observed with Limiting Longstanding Illness only (subdistribution hazard ratio = 11.43, 95% confidence intervals: 9.40-13.89) and Limiting Longstanding Illness+Common Mental Disorder (subdistribution hazard ratio = 14.25, 95% confidence intervals: 10.91-18.61), and to a lesser extent Common Mental Disorder only (subdistribution hazard ratio = 2.00, 95% confidence intervals: 1.31-3.05). Women were more likely to exit through disability pension than men (subdistribution hazard ratio = 1.96, 95% confidence intervals: 1.60-2.39). Common Mental Disorder only was the only morbidity category associated with unemployment (subdistribution hazard ratio = 1.70, 95% confidence intervals: 1.36-2.15)., Conclusions: Strong associations were observed between specific morbidity categories with different employment exit routes, which differed by gender. Initiatives to extend working lives should consider older workers' varied health needs to prevent inequalities in older age., Competing Interests: The authors have declared that no competing interests exist.

Purpose: Life events have been associated with a variety of mental health conditions including depression. There is a scarcity of research in South Asia exploring the aetiology of independent and dependent life events and their relationship with depression symptoms. This study aimed, in a Sri Lankan population, to identify the socio-demographic correlates and genetic and environmental influences on independent and dependent life events and their relationship with depression., Methods: Questionnaire data came from the Colombo Twin and Singleton Follow-up Study, CoTaSS-2 (N = 3969), a population study of Sri Lankan twins and singletons. Lifetime-ever independent and dependent life events were measured using a questionnaire and depressive symptoms using the Revised Beck's Depression Inventory. Structural Equation Model-fitting analyses explored the genetic and environmental influences on life events and depression., Results: Living in a rural environment and financial hardship were associated with greater reporting of independent and dependent life events. Sex differences were evident in the aetiology of life events and depression symptoms. Independent and dependent life events, but not depression symptoms, were heritable in males. Independent life events and depression symptoms, but not dependent life events, were heritable in females. Non-shared environmental influences explained phenotypic associations between independent life events and depression symptoms in both males and females. Genetic and non-shared environmental influences explained the phenotypic associations between dependent life events and depression symptoms in males. Only non-shared environment explained the covariation between dependent life events and depression symptoms in females., Conclusions: Socio-demographic correlates of independent and dependent life events were similar to those reported in Western populations. Life events were associated with increased depression symptoms. Contrary to research in Western populations, we found that non-shared environmental, rather than genetic, influences explained much of the covariation between life events and depression symptoms. This suggests that whilst independent LEs may be heritable, the relationship is unlikely to be confounded by genetic influences and has significant implications for possible interventions for depression.

Objective: Results from twin studies examining the genetic overlap between type 2 diabetes and depression are currently inconclusive. This question has not been addressed in non-Western populations. We aimed to examine whether there are common genetic factors between type 2 diabetes and depression in a Sri Lankan population using genetic model-fitting analysis., Method: The Colombo Twin and Singleton Study-Phase 2 consists of 2019 singletons, and 842 monozygotic and 578 dizygotic twin pairs. The primary outcomes were self-reported type 2 diabetes diagnosis and Beck Depression Inventory scores. Standard bivariate twin models were fitted to estimate the genetic and environmental (co)variance of type 2 diabetes and depression., Results: In the best-fitting model, the phenotypic correlation between type 2 diabetes and depression was significant in female individuals only (r = 0.15 [0.08-0.21]). This association was primarily attributed to a significant genetic correlation between the traits (rA = 0.53 [0.19-0.98])., Conclusions: In female individuals, but not male individuals, we found a significant genetic overlap between type 2 diabetes and depression in the context of a modest phenotypic correlation.

Objective: There is inconsistent evidence about the association between inflammatory disorders and depression and anxiety onset in a primary care context. The study aimed to evaluate the risk of depression and anxiety within multisystem and organ-specific inflammatory disorders., Methods: This is a prospective cohort study with primary care patients from the UK Clinical Practice Research Datalink diagnosed with an inflammatory disorder between 1 January 2001 and 31 December 2016. These patients were matched on age, gender, practice and index date with patients without an inflammatory disorder. The study exposures were seven chronic inflammatory disorders. Clinical diagnosis of depression and anxiety represented the outcome measures of interest., Results: Among 538 707 participants, the incidence of depression ranged from 14 per 1000 person-years (severe psoriasis) to 9 per 1000 person-years (systemic vasculitis), substantively higher compared with their comparison group (5-7 per 1000 person-years). HRs of multiple depression and anxiety events were 16% higher within inflammatory disorders (HR, 1.16, 95% CI 1.12 to 1.21, p<0.001) compared with the matched comparison group. The incidence of depression and anxiety was strongly associated with the age at inflammatory disorder onset. The overall HR estimate for depression was 1.90 (95% CI 1.66 to 2.17, p<0.001) within early-onset disorder (<40 years of age) and 0.93 (95% CI 0.90 to 1.09, p=0.80) within late-onset disorder (≥60 years of age)., Conclusions: Primary care patients with inflammatory disorders have elevated rates of depression and anxiety incidence, particularly those patients with early-onset inflammatory disorders. This finding may reflect the impact of the underlying disease on patients' quality of life, although the precise mechanisms require further investigation., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Discrimination is a well-established stressor that is substantially associated with poor health and a known contributor to health inequalities. However, the role of discrimination in health service use is less explored. This study will take an intersectional approach to investigate differences in health service use and examine the role of discrimination experiences., Methods: Data on health service use were assessed in a diverse inner London sample of 1052 participants in the South East London Community Health (SELCoH) Study. Latent class analysis (LCA) was used to define classes of intersectional social status using multiple indicators of socioeconomic status (SES), ethnicity and migration status. Adjusted associations between intersectional social status and discrimination experiences with health service use indicators are presented., Results: Using latent class analysis allowed us to identify an intersectional social status characterized by multiple disadvantage that was associated with decreased secondary physical health service use and a class characterized by both privilege and disadvantage that was associated with increased health service use for mental disorder after controlling for age, gender and health status. Anticipated discrimination was also associated with increased service use for mental disorder in adjusted models. There was no evidence to suggest that discrimination experiences were acting as a barrier to health service use., Conclusions: This study highlights the complex ways in which discrimination experiences may increase the need for health services whilst also highlighting differences in health service use at the intersection of ethnicity, migration status and SES. Findings from this study illustrate the importance of measuring multiple levels of discrimination and taking an intersectional approach for health service use research.