Gender-related self-reported mental health inequalities in primary care in England: a cross-sectional analysis using the GP Patient Survey.

BACKGROUND: Transgender, non-binary, and gender diverse people face discrimination and barriers to accessing health care. Existing evidence suggests higher rates of mental health conditions among these groups compared with binary and cisgender groups. However, information is limited by poor gender recording in health records and surveys. We aimed to provide the first national estimates of gender-related inequalities in self-reported mental health conditions and mental health support across 15 gender groups in England. METHODS: We used changes to the 2021 and 2022 nationally representative cross-sectional English General Pracitioner (GP) Patient Surveys and used age-adjusted logistic regression to predict probabilities of two outcomes: first, self-reporting a mental health condition and second, self-reporting unmet mental health needs. We report results for 15 exposure groups: five gender groups (female, male, non-binary, prefer to self-describe, and prefer not to say), within three cisgender or transgender identity groups (cisgender, transgender, or prefer not to say). We explored potential mediation by adding covariates. FINDINGS: Of the 1 520 457 respondents in the estimation sample, 861 017 (51·4%) were female, 645 300 (47·4%) were male, 2600 (0·3%) were non-binary, 2277 (0·2%) self-described their gender, and 9263 (0·7%) preferred not to state their gender. 1 499 852 (98·3%) respondents were cisgender, 7994 (0·7%) were transgender, and 12 611 (1·0%) preferred not to say their cisgender or transgender identity. We found wide gender-related inequalities in the probability of self-reporting a mental health condition, with the highest probabilities among non-binary patients who were transgender (47·21% [95% CI 42·86-51·60]) or preferred not to say their cisgender or transgender identity (32·90% [26·50-40·00]), and among transgender patients who self-described their gender (35·03% [27·39-43·53]). With the exception of non-binary patients in each case, probabilities were lowest among cisgender patient groups (ranging from male at 8·80% [8·69-8·92] to female at 11·97% [11·86-12·07]) and patients who preferred not to say their cisgender or transgender identity (ranging from female 7·15% [6·06-8·42] to prefer to self-describe 10·37% [7·13-14·86]). Inequalities in other health conditions and socioeconomic factors might mediate some of these inequalities. Probabilities of self-reported unmet mental health needs were lowest among cisgender male (15·55% [15·33-15·76]) and female (15·93% [15·76-16·10]) patients with increased probabilities among all other groups, ranging from 19·95% (17·57-22·57) in transgender male patients to 28·64% (26·23-31·17) among patients who preferred not to say their gender or their cisgender or transgender identity. Inequalities in interactions with health-care professionals may mediate much of these inequalities. INTERPRETATION: Together with existing evidence, our findings showed large gender-related inequalities in self-reported mental health outcomes in England. Given the existence of self-reported unmet mental health needs, we suggest that better health care system inclusivity and health-care professional training are needed, alongside broader improvements in the social and legal environment for transgender, non-binary, and gender diverse people. FUNDING: National Institute for Health and Care Research.

Evaluating socioeconomic inequalities in influenza vaccine uptake during the COVID-19 pandemic: A cohort study in Greater Manchester, England.

BACKGROUND: There are known socioeconomic inequalities in annual seasonal influenza (flu) vaccine uptake. The Coronavirus Disease 2019 (COVID-19) pandemic was associated with multiple factors that may have affected flu vaccine uptake, including widespread disruption to healthcare services, changes to flu vaccination eligibility and delivery, and increased public awareness and debate about vaccination due to high-profile COVID-19 vaccination campaigns. However, to the best of our knowledge, no existing studies have investigated the consequences for inequalities in flu vaccine uptake, so we aimed to investigate whether socioeconomic inequalities in flu vaccine uptake have widened since the onset of the COVID-19 pandemic. METHODS AND FINDINGS: We used deidentified data from electronic health records for a large city region (Greater Manchester, population 2.8 million), focusing on 3 age groups eligible for National Health Service (NHS) flu vaccination: preschool children (age 2 to 3 years), primary school children (age 4 to 9 years), and older adults (age 65 years plus). The sample population varied between 418,790 (2015/16) and 758,483 (2021/22) across each vaccination season. We estimated age-adjusted neighbourhood-level income deprivation-related inequalities in flu vaccine uptake using Cox proportional hazards models and the slope index of inequality (SII), comparing 7 flu vaccination seasons (2015/16 to 2021/22). Among older adults, the SII (i.e., the gap in uptake between the least and most income-deprived areas) doubled over the 7 seasons from 8.48 (95% CI [7.91,9.04]) percentage points to 16.91 (95% CI [16.46,17.36]) percentage points, with approximately 80% of this increase occurring during the pandemic. Before the pandemic, income-related uptake gaps were wider among children, ranging from 15.59 (95% CI [14.52,16.67]) percentage points to 20.07 (95% CI [18.94,21.20]) percentage points across age groups and vaccination seasons. Among preschool children, the uptake gap increased in 2020/21 to 25.25 (95% CI [24.04,26.45]) percentage points, before decreasing to 20.86 (95% CI [19.65,22.05]) percentage points in 2021/22. Among primary school children, inequalities increased in both pandemic years to reach 30.27 (95% CI [29.58,30.95]) percentage points in 2021/22. Although vaccine uptake increased during the pandemic, disproportionately larger increases in uptake in less deprived areas created wider inequalities in all age groups. The main limitation of our approach is the use of a local dataset, which may limit generalisability to other geographical settings. CONCLUSIONS: The COVID-19 pandemic led to increased inequalities in flu vaccine uptake, likely due to changes in demand for vaccination, new delivery models, and disruptions to healthcare and schooling. It will be important to investigate the causes of these increased inequalities and to examine whether these increased inequalities also occurred in the uptake of other routine vaccinations. These new wider inequalities in flu vaccine uptake may exacerbate inequalities in flu-related morbidity and mortality.

Correction: Ethnic inequalities in COVID-19 vaccine uptake and comparison to seasonal influenza vaccine uptake in Greater Manchester, UK: A cohort study.

[This corrects the article DOI: 10.1371/journal.pmed.1003932.].

Ethnic inequalities in COVID-19 vaccine uptake and comparison to seasonal influenza vaccine uptake in Greater Manchester, UK: A cohort study.

BACKGROUND: COVID-19 vaccine uptake is lower amongst most minority ethnic groups compared to the White British group in England, despite higher COVID-19 mortality rates. Here, we add to existing evidence by estimating inequalities for 16 minority ethnic groups, examining ethnic inequalities within population subgroups, and comparing the magnitudes of ethnic inequalities in COVID-19 vaccine uptake to those for routine seasonal influenza vaccine uptake. METHODS AND FINDINGS: We conducted a retrospective cohort study using the Greater Manchester Care Record, which contains de-identified electronic health record data for the population of Greater Manchester, England. We used Cox proportional hazards models to estimate ethnic inequalities in time to COVID-19 vaccination amongst people eligible for vaccination on health or age (50+ years) criteria between 1 December 2020 and 18 April 2021 (138 days of follow-up). We included vaccination with any approved COVID-19 vaccine, and analysed first-dose vaccination only. We compared inequalities between COVID-19 and influenza vaccine uptake adjusting by age group and clinical risk, and used subgroup analysis to identify populations where inequalities were widest. The majority of individuals (871,231; 79.24%) were White British. The largest minority ethnic groups were Pakistani (50,268; 4.75%), 'other White background' (43,195; 3.93%), 'other ethnic group' (34,568; 3.14%), and Black African (18,802; 1.71%). In total, 83.64% (919,636/1,099,503) of eligible individuals received a COVID-19 vaccine. Uptake was lower compared to the White British group for 15 of 16 minority ethnic groups, with particularly wide inequalities amongst the groups 'other Black background' (hazard ratio [HR] 0.42, 95% CI 0.40 to 0.44), Black African (HR 0.43, 95% CI 0.42 to 0.44), Arab (HR 0.43, 95% CI 0.40 to 0.48), and Black Caribbean (HR 0.43, 95% CI 0.42 to 0.45). In total, 55.71% (419,314/752,715) of eligible individuals took up influenza vaccination. Compared to the White British group, inequalities in influenza vaccine uptake were widest amongst the groups 'White and Black Caribbean' (HR 0.63, 95% CI 0.58 to 0.68) and 'White and Black African' (HR 0.67, 95% CI 0.63 to 0.72). In contrast, uptake was slightly higher than the White British group amongst the groups 'other ethnic group' (HR 1.11, 95% CI 1.09 to 1.12) and Bangladeshi (HR 1.08, 95% CI 1.05 to 1.11). Overall, ethnic inequalities in vaccine uptake were wider for COVID-19 than influenza vaccination for 15 of 16 minority ethnic groups. COVID-19 vaccine uptake inequalities also existed amongst individuals who previously took up influenza vaccination. Ethnic inequalities in COVID-19 vaccine uptake were concentrated amongst older and extremely clinically vulnerable adults, and the most income-deprived. A limitation of this study is the focus on uptake of the first dose of COVID-19 vaccination, rather than full COVID-19 vaccination. CONCLUSIONS: Ethnic inequalities in COVID-19 vaccine uptake exceeded those for influenza vaccine uptake, existed amongst those recently vaccinated against influenza, and were widest amongst those with greatest COVID-19 risk. This suggests the COVID-19 vaccination programme has created additional and different inequalities beyond pre-existing health inequalities. We suggest that further research and policy action is needed to understand and remove barriers to vaccine uptake, and to build trust and confidence amongst minority ethnic communities.

Ethnic inequalities in health-related quality of life among older adults in England: secondary analysis of a national cross-sectional survey.

BACKGROUND: The population of older adults (ie, those aged ≥55 years) in England is becoming increasingly ethnically diverse. Previous reports indicate that ethnic inequalities in health exist among older adults, but information is limited by the paucity of data from small minority ethnic groups. This study aimed to analyse inequalities in health-related quality of life (HRQoL) and five determinants of health in older adults across all ethnic groups in England. METHODS: In this cross-sectional study, we analysed data from five waves (July 1, 2014, to April 7, 2017) of the nationally representative English General Practice Patient Survey (GPPS). Study participants were adults aged 55 years or older who were registered with general practices in England. We used regression models (age-adjusted and stratified by gender) to estimate the association between ethnicity and HRQoL, measured by use of the EQ-5D-5L index and its domains (mobility, self-care, usual activities, pain or discomfort, and anxiety or depression). We also estimated associations between ethnicity and five determinants of health (presence of long-term conditions or multimorbidity, experience of primary care, degree of support from local services, patient self-confidence in managing own health, and degree of area-level social deprivation). We examined robustness to differential handling of missing data, alternative EQ-5D-5L value sets, and differences in area-level social deprivation. FINDINGS: There were 1 416 793 GPPS respondents aged 55 years and older. 1 394 361 (98·4%) respondents had complete data on ethnicity and gender and were included in our analysis. Of these, 152 710 (11·0%) self-identified as belonging to minority ethnic groups. HRQoL was worse for men or women, or both, in 15 (88·2%) of 17 minority ethnic groups than the White British ethnic group. In both men and women, inequalities were widest for Gypsy or Irish Traveller (linear regression coefficient -0·192 [95% CI -0·318 to -0·066] in men; -0·264 [-0·354 to -0·173] in women), Bangladeshi (-0·111 [-0·136 to -0·087] in men; -0·209 [-0·235 to -0·184] in women), Pakistani (-0·084 [-0·096 to -0·073] in men; -0·206 [-0·219 to -0·193] in women), and Arab (-0·061 [-0·086 to -0·035] in men; -0·145 [-0·180 to -0·110] in women) ethnic groups, with magnitudes generally greater for women than men. Differentials tended to be widest for the self-care EQ-5D-5L domain. Ethnic inequalities in HRQoL were accompanied by increased prevalence of long-term conditions or multimorbidity, poor experiences of primary care, insufficient support from local services, low patient self-confidence in managing their own health, and high area-level social deprivation, compared with the White British group. INTERPRETATION: We found evidence of wide ethnic inequalities in HRQoL and five determinants of health for older adults in England. Outcomes varied between minority ethnic groups, highlighting heterogeneity in the direction and magnitude of associations. We recommend further research to understand the drivers of inequalities, together with policy changes to improve equity of socioeconomic opportunity and access to services for older adults from minority ethnic groups. FUNDING: University of Manchester and National Institute for Health Research.