Journal of Epidemiology and Community Health最新文献

Background: Community resilience is a relevant concept in public health, but its empirical relationship with health outcomes remains underexplored. This study examines whether a Community Resilience Index (CRI) is associated with population health outcomes in England, and whether it offers explanatory added value beyond the Index of Multiple Deprivation (IMD).

Methods: The CRI comprises 44 indicators reflecting community-level resilience to chronic stressors. Associations between CRI scores and five health outcomes, deaths of despair, cardiovascular disease (CVD) mortality, COVID-19 mortality, excess all-cause mortality during two waves of COVID-19 and self-rated health were assessed at local authority district level. IMD was adjusted to remove health-related indicators. Linear regression models assessed the explanatory power of the CRI and IMD, using likelihood ratio tests to compare model fit. Interaction and stratified analyses explored effect modification by IMD.

Results: Higher CRI scores were associated with lower Deaths of Despair and CVD mortality, and higher self-rated health; these associations remained significant after adjusting for IMD. CRI was not significantly associated with COVID-19 outcomes. IMD remained the stronger predictor of health outcomes, but CRI significantly improved model fit. The interaction between CRI and IMD was significant for deaths of despair and self-rated health. Stratified analyses showed the CRI-deaths of despair association was strongest in more deprived areas.

Conclusions: Community resilience is associated with health outcomes in England. While not a substitute for deprivation-based measures, resilience indices offer complementary insight into structural and social factors shaping health. Resilience-building efforts may be particularly impactful in areas of greatest disadvantage.

Background: In the USA, HIV remains a pressing public health challenge (~37 400 new diagnoses in 2018) and pronounced racialised inequities persist. In 2018, Black and Latine people represented 43% and 26% of new diagnoses but only 13% and 18% of the population, respectively. Antiracist laws may help mitigate these inequities, yet research investigating specific laws is lacking. This study aimed to examine associations between state minimum wage laws and new HIV diagnosis rates by racialised group and sex/gender.

Methods: We linked data on inflation-adjusted state minimum wage and state-level new HIV diagnosis rates among US adults aged 13-59 years. We fit two-way fixed-effects models to examine associations between changes in minimum wage and changes in new HIV diagnosis rates per 100 000 people from 2010 to 2019 by racialised group (Black/Latine/White) and sex/gender (women/men). Additional analyses tested for effect heterogeneity by racialised group and by sex/gender within racialised group.

Results: Findings show an inverse association between state minimum wage and new HIV diagnosis rates across all racialised and sex/gender groups, except White women. Among Black adults, a 1 US Dollar ($) increase in state minimum wage was associated with a 5.81 per 100 000 decrease in new HIV diagnosis rate, followed by Latine (2.81/100 000) and White adults (1.50/100 000). The inverse association was larger among Latine (4.73/100 000) and White men (2.88/100 000) than Latine (0.98/100 000) and White women (0.07/100 000), respectively. There was no evidence of effect heterogeneity comparing Black men to Black women.

Conclusions: State minimum wage laws may represent a critical policy intervention to address racialised HIV inequities.

Disadvantaged groups are often defined by characteristics such as income or ethnicity. Reducing health disparities by directly manipulating such exposures may be infeasible. Instead, interventions can target mediators between these exposures and health outcomes. Indirect effects estimated using mediation analysis, interventional effects or the interventional disparity measure can quantify the expected impact of such disparity-reducing interventions. They capture the impact of changing the mediator distribution evaluated among the total population. This means keeping individuals in their exposure group but hypothetically assigning them the mediator distribution of another group. However, when indirect effects are intended to inform about disparity-reducing interventions implemented among disadvantaged groups, estimating effects in the total population does not quantify the effect among those targeted. Instead, we propose evaluating the interventional disparity indirect effect directly among the disadvantaged individuals. We introduce the estimand and illustrate it using a register-based study examining a potential intervention improving medication initiation in low-income heart failure patients. We compare the expected change in 1-year mortality in a hypothetical world where low-income patients were as likely to initiate medication as high-income patients. We included 1700 patients and assessed intervention effects in low-income patients and the total population, respectively. Under the intervention, the 1-year mortality declined from 10.3% to 9.3% (95% CI 8.6% to 10.1%) among low-income patients but 6.6% to 6.2% (95% CI 6.0% to 6.5%) in the total population. In disparity research, evaluating intervention effects in the total population, rather than among disadvantaged groups, may impact the effect size. Therefore, when guiding future disparity-targeted interventions, measuring effects within disadvantaged groups is important.

Background: While C-section (CS) deliveries exhibit significant socioeconomic inequalities in low- and middle-income countries (LMICs), the extent and underlying drivers of these inequalities remain poorly understood. This study assesses these inequalities and identifies key contributing factors.

Methods: The most recent nationally representative samples of live births (n=652 539) from the Demographic and Health Surveys, conducted between 2014 and 2024 in 44 LMICs, were used to calculate the CS delivery rates. The Wagstaff (WI) and Erreygers (EI) indices were used to measure the relative and absolute socioeconomic inequalities in CS delivery. Meta-regression analyses were performed to identify the proximate determinants of the observed socioeconomic inequalities in CS delivery across the selected LMICs.

Results: CS delivery rates varied across LMICs, with a median of 6.25% (IQR=16.18). The WI and EI indicated that CS deliveries were concentrated among high socioeconomic backgrounds, with only one country exhibiting no inequality. The pooled estimates (WI: 0.32, 95% CI 0.28 to 0.36 and EI: 0.11, 95% CI 0.09 to 0.14) further demonstrate the concentration of CS among the rich in LMICs. Meta-regression analyses indicated that inequalities in education and antenatal care were significantly and positively associated with the concentration of CS deliveries among wealthier women.

Conclusion: CS delivery concentration among wealthier women remains a health concern in LMICs. Given the positive link between higher education and antenatal care with CS deliveries, country-specific policies promoting health education and targeted messaging during antenatal care visits on the adverse health effects of unnecessary CS deliveries may help reduce socioeconomic inequalities in CS delivery.

Background: Housing is a critical social determinant of health for migrant and refugee populations in high-income countries; however, the causal pathways linking housing affordability to health outcomes remain underexplored. This study aimed to examine the relationship between housing affordability stress and both mental and general health, and to assess the role of economic deprivation as a mediator of this relationship.

Methods: This study uses data from the five waves (2013-2018) of the Building a New Life in Australia study, which followed 2399 humanitarian migrants who arrived in Australia or were granted a permanent protection visa in 2013. Causal mediation analyses using marginal structural models were conducted to decompose the total effect of housing affordability stress on mental and general health into the natural direct effect and natural indirect effect mediated through economic deprivation.

Results: The total effect of housing affordability stress on mental health was 1.56 (95% CI 1.26 to 1.92). Economic deprivation mediated 37% (95% CI 19.5% to 68.8%) of the total effect, and 79.6% (95% CI 60.3% to 113.9%) of the total effect could potentially be eliminated by intervening on economic deprivation. For self-rated general health, the total effect of housing affordability stress was 1.43 (95% CI 1.15 to 1.74). Economic deprivation accounted for 27.7% (95% CI 5.3% to 62.6%) of the total effect, and 65.9% (95% CI 29.9% to 101.9%) of the total effect could potentially be eliminated by intervening on economic deprivation.

Conclusions: The findings demonstrate that housing affordability stress leads to elevated psychological distress and poor self-rated general health among humanitarian migrants. A substantial portion of this impact occurs through economic deprivation, which could be attenuated by targeting economic deprivation as a key intervention point during early years of resettlement.

Background: Prehospital delays remain critical barriers to timely acute coronary syndrome (ACS) care, particularly for patients referred from resource-constrained primary healthcare to hospitals with percutaneous coronary intervention (PCI) capabilities. This study evaluated the associations between China Chest Pain Unit (CPU) programme, with prehospital delays, management and in-hospital outcomes for ACS patients.

Methods: This retrospective cohort study used registry data from the Chinese Cardiovascular Association Database. We included patients diagnosed with ACS who were referred from primary healthcare facilities to chest pain centres (CPCs). The CPU-referral group received standardised triage and referral protocols; the non-CPU-referral group received routine referral. All patients were treated at CPCs. Primary outcomes included in-hospital heart failure, in-hospital mortality, door-in-door-out (DIDO) time and time from onset to CPC door. Secondary outcomes included time from onset to first medical contact, door-to-balloon time, discharge medication use, length of stay and total hospital expenditure. Propensity score matching and generalised linear mixed models were used to evaluate the associations.

Results: A cohort consisting of 8834 patients was constructed by propensity score matching among 119 723 eligible referred ACS patients (5000 CPU-referrals and 114 723 non-CPU-referrals). CPU referral was associated with lower odds of in-hospital heart failure (OR 0.16, 95% CI 0.08 to 0.30) and in-hospital mortality (OR 0.68, 95% CI 0.50 to 0.92), shorter DIDO time (β=-0.33, 95% CI -0.40 to -0.25) and shorter times from onset to arrival at the CPC door (β=-0.19, 95% CI -0.27 to -0.11). CPU referral was also associated with shorter time to first medical contact and door-to-balloon time, improved adherence to guideline-recommended discharge medications, reduced length of stay and lower total hospital expenditure.

Conclusions: The regionalised quality improvement programme for CPUs was associated with reduced prehospital delays, lower in-hospital heart failure and mortality, better care quality and lower costs among referred ACS patients.

Background: Suicide is a leading cause of death among young adults in South Korea. We investigated the association between triglyceride-glucose (TyG) index and suicide mortality in young adults.

Methods: This nationwide study analysed data from 6 667 138 individuals aged 20-39 using the National Health Insurance Database. Participants were grouped into TyG index quartiles. The primary outcome was suicide mortality.

Results: During a median follow-up duration of 10.7 years, 41 004 (0.6%) suicidal deaths occurred. The cumulative event rates for suicide mortality were highest among participants in TyG index quartile 4. Multivariable Cox analysis showed significant increases in the risks of suicide mortality in participants with TyG index quartile 4 compared with those in the low quartiles (adjusted HR 1.17, 95% CI 1.11 to 1.23, vs quartile 1; adjusted HR 1.15, 95% CI 1.10 to 1.20, vs quartile 1-3). The association between the TyG index and the risks of suicide mortality was positive and quasi-linear. Subgroup analysis showed a consistent trend of increasing HRs for suicide mortality with higher TyG index quartiles, with significant interactions between TyG index, sex and depression.

Conclusion: TyG index can be useful in identifying young individuals at an increased risk of suicide mortality.

Background: Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) is a leading quantitative approach for intersectionality-informed health research, but most applications analyse binary or cross-sectional outcomes, ignoring event timing. We applied a multilevel survival (shared frailty) model within the MAIHDA framework to examine intersectional disparities in time-to-diagnosis of hypertension.

Methods: Using 2019 Korean Community Health Survey data (n=228 632), we defined intersectional strata by sex, education, income and residential area. Three survival specifications were implemented: accelerated failure time (AFT), parametric proportional hazards (PHs) and semi-parametric Cox PH models, each with stratum-level random intercepts (shared frailty terms). Between-stratum variance was summarised with the variance partition coefficient (VPC) where estimable and proportional change in variance quantified fixed-effect contributions. Stratum-specific random effects were compared across model types to assess ranking stability.

Results: Between-stratum variance was small overall (AFT VPC: 1.8%), but several strata deviated markedly from the grand mean. Strata with low education and low income were diagnosed earlier than average, while high-education, low-income strata were diagnosed later. Geographic context modified these effects. Time-to-diagnosis patterns often diverged from prevalence patterns. Across models, random effect estimates and ranks were highly correlated (Spearman's ρ>0.97), though some middle-ranked strata shifted by up to six positions.

Conclusions: Applying a multilevel survival (shared frailty) model within MAIHDA enables examination of when disparities emerge, not just whether they exist. This approach retains MAIHDA's interpretability while leveraging time-to-event data, offering advantages in settings with incomplete follow-up or irregular observation windows.

Background: Many studies have detected a negative relationship between income inequality and general measures of health. However, data limitations have prevented a full understanding of whose health is impacted and in what ways.

Methods: In this study, we combined area-level census data with individual-level health claims data to estimate the cross-sectional association between county-level income inequality and healthcare utilisation across a range of member characteristics.

Results: We found that a 1 SD increase in the Gini coefficient was associated with about 5% higher medical and pharmacy costs and a 0.2 percentage-point increase in the probability of a hospital visit within the year. Income inequality was associated with higher medical costs primarily among adults with commercial insurance, more emergency department visits among children and Medicaid members, and more hospital visits among older adults, including Medicare members. By examining diagnoses attached to claims, we found that income inequality was associated with detrimental impacts on mental health, as indicated by higher spending for anxiety and depression and more emergency department visits for substance-use disorders.

Conclusions: Income inequality was associated with worse health across a wide range of members by age, income and insurance type, and can be considered as a risk factor by policymakers and health systems.

Background: During preconception counselling, pregnant women who smoke are advised to quit smoking. While the adverse effects of paternal smoking on pregnancy and perinatal outcomes have been increasingly recognised, the health benefits of paternal smoking cessation prior to conception remain understudied.

Methods: The current study involved non-smoking reproductive-aged Chinese women who participated two times in the National Free Prepregnancy Checkups Project during 2010-2018. A total of 158 986 pregnancies were included, with husbands reporting smoking at the preconception examination stage during their first participation. The primary exposure was paternal smoking cessation before pregnancy. And the primary outcome was spontaneous abortion (SAB) recorded in the second participation. Inverse-probability-weighted (IPW) logistic regression was used to estimate ORs and their 95% CIs of SAB with paternal smoking cessation before pregnancy. Instrumental variable (IV) analyses were further used to estimate the association.

Results: Compared with continued paternal smoking, paternal smoking cessation before pregnancy was associated with a reduced risk of SAB (IPW-adjusted OR 0.86 (95% CI 0.81 to 0.91); IV-estimated OR 0.79 (95% CI 0.76 to 0.82)). Additionally, a decrease in paternal smoking was also associated with a lower risk of SAB. Notably, the risk of SAB was still higher than that of those without paternal smoking in IV analysis (OR 1.21 (95% CI 1.26 to 1.32)).

Conclusions: Paternal smoking cessation prior to conception is linked to a reduced risk of SAB. However, the risk of SAB among women with paternal smoking cessation was still higher than that among those without paternal smoking. Preconception counselling should advise fathers who smoke to quit.