Ethnic differences in depression and anxiety among adults with atopic eczema: Population-based matched cohort studies within UK primary care

BACKGROUND

Evidence demonstrates that individuals with atopic eczema (eczema) have increased depression and anxiety; however, the role of ethnicity in these associations is poorly understood. We aimed to investigate whether associations between eczema and depression or anxiety differed between adults from white and minority ethnic groups in the UK.

METHODS

We used UK Clinical Practice Research Datalink GOLD to conduct matched cohort studies of adults (≥18 years) with ethnicity recorded in primary care electronic health records (April 2006-January 2020). We matched (age, sex, practice) adults with eczema to up to five adults without. We used stratified Cox regression with an interaction between eczema and ethnicity, to estimate hazard ratios (HRs) for associations between eczema and incident depression and anxiety in individuals from white ethnic groups and a pooled minority ethnic group (adults from Black, South Asian, Mixed and Other groups).

RESULTS

We identified separate cohorts for depression (215,073 with eczema matched to 646,539 without) and anxiety (242,598 with eczema matched to 774,113 without). After adjusting for matching variables and potential confounders (age, sex, practice, deprivation, calendar period), we found strong evidence (p < 0.01) of ethnic differences in associations between eczema and depression (minority ethnic groups: HR = 1.33, 95% CI = 1.22,1.45; white ethnic groups: HR = 1.15, 95% CI = 1.12,1.17) and anxiety (minority ethnic groups: HR = 1.41, 95% CI = 1.28,1.55; white ethnic groups: HR = 1.17, 95% CI = 1.14,1.19).

CONCLUSIONS

Adults with eczema from minority ethnic groups appear to be at increased depression and anxiety risk compared with their white counterparts. Culturally adapted mental health promotion and prevention strategies should be considered in individuals with eczema from minority ethnic groups.

Genetically predicted androgenic profiles and adverse cardiac markers: a sex-specific Mendelian randomization study

AIMS

Observational evidence suggests associations between sex hormone levels and heart failure (HF). We used sex-specific genetic variants associated with androgenic sex hormone profiles to investigate the causal relevance of androgenic sex hormone profiles on cardiac structure and function and HF using Mendelian randomization (MR).

METHODS AND RESULTS

Sex-specific uncorrelated genome-wide significant (P < 5 × 10-8 ) variants predicting sex hormone-binding globulin (SHBG), total testosterone, and bioavailable testosterone were extracted from summary statistics of genome-wide association study (GWAS) on 425 097 participants in the UK Biobank. Sex-specific gene-outcome association estimates were computed for left ventricular ejection fraction (LVEF), left ventricular end-diastolic and end-systolic volumes (LVEDV and LVESV, respectively), left ventricular stroke volume (LVSV), cardiac index, and cardiac output in 11 528 female and 14 356 male UK Biobank Imaging Study participants and for incident or prevalent HF in an external cohort of 47 309 cases and 930 014 controls. Inverse-variance weighted MR was the primary analysis method. In females, higher genetically predicted bioavailable testosterone was associated with lower LVEDV [β per nmol/L = -0.11 (-0.19 to -0.03), P = 0.006], lower LVESV [β = -0.09 (-0.17 to -0.01), P = 0.022], lower LVSV [β = -0.11 (-0.18 to -0.03), P = 0.005], lower cardiac output [β = -0.08 (-0.16 to 0.00), P = 0.046], and lower cardiac index [β = -0.08 (-0.16 to -0.01), P = 0.034] and a higher risk of HF [odds ratio 1.10 (1.01-1.19), P = 0.026] on external validation analysis in larger scale, sex-adjusted GWAS data. Higher genetically predicted SHBG was associated with higher LVEDV [β per nmol/L = 0.17 (0.08-0.25), P = 2 × 10-4 ], higher LVESV [β = 0.13 (0.05-0.22), P = 0.003], and higher LVSV [β = 0.18 (0.08-0.28), P = 2 × 10-4 ]. In males, higher genetically predicted total and bioavailable testosterone was associated with lower LVESV [β = -0.07 (-0.12 to -0.02), P = 0.007] and LVEF [β = -0.11 (-0.18 to -0.04), P = 0.003], respectively.

CONCLUSIONS

This study supports a causal effect of pro-androgenic sex hormone profiles in females on adverse markers of left ventricular structure and function typically associated with HF with preserved ejection fraction and with HF. There was weaker evidence of association in males.

Image-Based Biological Heart Age Estimation Reveals Differential Aging Patterns Across Cardiac Chambers

BACKGROUND

Biological heart age estimation can provide insights into cardiac aging. However, existing studies do not consider differential aging across cardiac regions.

PURPOSE

To estimate biological age of the left ventricle (LV), right ventricle (RV), myocardium, left atrium, and right atrium using magnetic resonance imaging radiomics phenotypes and to investigate determinants of aging by cardiac region.

STUDY TYPE

Cross-sectional.

POPULATION

A total of 18,117 healthy UK Biobank participants including 8338 men (mean age = 64.2 ± 7.5) and 9779 women (mean age = 63.0 ± 7.4).

FIELD STRENGTH/SEQUENCE

A 1.5 T/balanced steady-state free precession.

ASSESSMENT

An automated algorithm was used to segment the five cardiac regions, from which radiomic features were extracted. Bayesian ridge regression was used to estimate biological age of each cardiac region with radiomics features as predictors and chronological age as the output. The "age gap" was the difference between biological and chronological age. Linear regression was used to calculate associations of age gap from each cardiac region with socioeconomic, lifestyle, body composition, blood pressure and arterial stiffness, blood biomarkers, mental well-being, multiorgan health, and sex hormone exposures (n = 49).

STATISTICAL TEST

Multiple testing correction with false discovery method (threshold = 5%).

RESULTS

The largest model error was with RV and the smallest with LV age (mean absolute error in men: 5.26 vs. 4.96 years). There were 172 statistically significant age gap associations. Greater visceral adiposity was the strongest correlate of larger age gaps, for example, myocardial age gap in women (Beta = 0.85, P = 1.69 × 10-26 ). Poor mental health associated with large age gaps, for example, "disinterested" episodes and myocardial age gap in men (Beta = 0.25, P = 0.001), as did a history of dental problems (eg LV in men Beta = 0.19, P = 0.02). Higher bone mineral density was the strongest associate of smaller age gaps, for example, myocardial age gap in men (Beta = -1.52, P = 7.44 × 10-6 ).

DATA CONCLUSION

This work demonstrates image-based heart age estimation as a novel method for understanding cardiac aging.

EVIDENCE LEVEL

1.

TECHNICAL EFFICACY

Stage 1.