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Background The risk of congenital heart disease (CHD) has been found to vary by maternal socioeconomic status (SES) and rural-urban residence. In this study, we examined associations of CHD with two maternal SES indicators and stratified the analysis by maternal rural-urban residence. Methods This was a population-based retrospective cohort study. We included all singleton stillbirths and live hospital births from April 1, 2012 to March 31, 2018 in Ontario, Canada. We linked the BORN Information System and Canadian Institute for Health Information databases. Multivariable logistic regression models were used to examine associations of CHD with material deprivation index (MDI), social deprivation index (SDI), and maternal residence while adjusting for maternal age at birth, assisted reproductive technology, obesity, pre-pregnancy maternal health conditions, mental health illness before and during pregnancy, substance use during pregnancy, and infant’s sex. MDI and SDI were estimated at a dissemination area level in Ontario and were categorized into quintiles (Q1-Q5). Results This cohort study included 798,173 singletons. In maternal urban residence, the p trend (Cochran–Armitage test) was less than 0.0001 for both MDI and SDI; while for rural residence, it was 0.002 and 0.98, respectively. Infants living in the most materially deprived neighbourhoods (MDI Q5) had higher odds of CHD (aOR: 1.21, 95% CI: 1.12–1.29) compared to Q1. Similarly, infants living in the most socially deprived neighbourhoods (SDI Q5) had an 18% increase in the odds of CHD (aOR: 1.18, 95% CI: 1.1–1.26) compared to Q1. Rural infants had a 13% increase in the odds of CHD compared to their urban counterparts. After stratifying by maternal rural-urban residence, we still detected higher odds of CHD with two indices in urban residence but only MDI in rural residence. Conclusion Higher material and social deprivation and rural residence were associated with higher odds of CHD. Health interventions and policies should reinforce the need for optimal care for all families, particularly underprivileged families in both rural and urban regions. Future studies should further investigate the effect of social deprivation on the risk of CHD development.

Describing the relationship between socioeconomic inequalities and cancer survival is important but methodologically challenging. We propose guidelines for addressing these challenges and illustrate their implementation on French population-based data. We analyzed 17 cancers. Socioeconomic deprivation was measured by an ecological measure, the European Deprivation Index (EDI). The Excess Mortality Hazard (EMH), ie, the mortality hazard among cancer patients after accounting for other causes of death, was modeled using a flexible parametric model, allowing for nonlinear and/or time-dependent association between the EDI and the EMH. The model included a cluster-specific random effect to deal with the hierarchical structure of the data. We reported the conventional age-standardized net survival (ASNS) and described the changes of the EMH over the time since diagnosis at different levels of deprivation. We illustrated nonlinear and/or time-dependent associations between the EDI and the EMH by plotting the excess hazard ratio according to EDI values at different times after diagnosis. The median excess hazard ratio quantified the general contextual effect. Lip-oral cavity-pharynx cancer in men showed the widest deprivation gap, with 5-year ASNS at 41% and 29% for deprivation quintiles 1 and 5, respectively, and we found a nonlinear association between the EDI and the EMH. The EDI accounted for a substantial part of the general contextual effect on the EMH. The association between the EDI and the EMH was time dependent in stomach and pancreas cancers in men and in cervix cancer. The methodological guidelines proved efficient in describing the way socioeconomic inequalities influence cancer survival. Their use would allow comparisons between different health care systems.

Ecological deprivation indices belong to essential instruments for monitoring and understanding health inequalities. Our aim was to develop the SI-EDI, a newly derived European Deprivation Index for Slovenia. We intend to provide researchers and policy-makers in our country with a relevant tool for measuring and reducing the socioeconomic inequalities in health, and even at a broader level. Data from the European survey on Income and Living Conditions and Slovenian national census for the year 2011 were used in the SI-EDI construction. The concept of relative deprivation was used where deprivation refers to unmet need(s), which is caused by lack of all kinds of resources, not only material. The SI-EDI was constructed for 210 Slovenian municipalities. Its geographical distribution was compared to the distribution of two existing deprivation scores previously applied in health inequality research in Slovenia. There were 36% of adults recognized as deprived in Slovenia in 2011. SI-EDI was calculated using 10 census variables that were associated with individual deprivation. A clear east-to-west gradient was detected with the most deprived municipalities in the eastern part of the country. The two existing deprivation scores correlate significantly with the SI-EDI. A new deprivation index, the SI-EDI, is grounded on the internationally established scientific concept, can be replicated over time and, crucially, provides an account of the socioeconomic and cultural particularities of the Slovenian population. The SI-EDI could be used by the stakeholders and the governmental and nongovernmental sectors in Slovenia, with the goal of better understanding health inequalities in Slovenia.

Neighborhood adversity’s impact on postoperative/adjuvant therapy delivery and overall survival (OS) is poorly described in patients with localized pancreatic cancer (PC). Area Deprivation Index (ADI) is a validated measure classifying neighborhood adversity. Higher ADI signifies increasing adversity. The 2013 national ADI scores were obtained from patients who completed preoperative/neoadjuvant therapy and surgery. Patients were categorized as having high (>50%) or low (≤50%) ADI. Of the 224 patients, 163 (73%) had low ADI and 61 (27%) had high ADI. Adjuvant therapy was delivered to 129 (58%) patients, including 62% (101/163) with low ADI and 46% (28/61) with high ADI (p = 0.03). Patients with high ADI had 55% (95%CI 0.23–0.86; p = 0.02) decreased odds of receiving adjuvant therapy, independent of other factors. The median OS was 45 months for 129 patients who received adjuvant therapy and 31 months for 94 patients who did not receive adjuvant therapy (p = 0.03). Patients with high ADI are less likely to receive adjuvant therapy for localized PC. Future studies should address impediments to care in patients from higher ADI neighborhoods. [Display omitted] •Area Deprivation Index (ADI) is validated to stratify patients by ZIP code adversity.•Patients with localized pancreatic cancer were stratified as having high or low ADI.•Patients with higher/disadvantaged ADI were less likely to receive adjuvant therapy.•Patients with lower/advantaged ADI had a survival benefit from adjuvant therapy.

Background Persons with low socioeconomic status may be disproportionately at risk for multimorbidity. Methods Adults aged ≥20 years on 4/1/2015 from 7 counties in Minnesota were identified using the Rochester Epidemiology Project (population-based sample). A composite measure of neighborhood socioeconomic disadvantage, the area deprivation index (ADI), was estimated at the census block group level ( n  = 251). The prevalence of 21 chronic conditions was obtained to calculate the proportion of persons with multimorbidity (≥2 chronic conditions) and severe multimorbidity (≥5 chronic conditions). Hierarchical logistic regression was used to estimate the association of ADI with multimorbidity and severe multimorbidity using odds ratios (OR). Results Among 198,941 persons (46.7% male, 30.6% aged ≥60 years), the age- and sex-standardized (to the United States 2010 census) median prevalence (Q1, Q3) was 23.4% (21.3%, 25.9%) for multimorbidity and 4.8% (4.0%, 5.7%) for severe multimorbidity. Compared with persons in the lowest quintile of ADI, persons in the highest quintile had a 50% increased risk of multimorbidity (OR 1.50, 95% CI 1.39–1.62) and a 67% increased risk of severe multimorbidity (OR 1.67, 95% CI 1.51–1.86) after adjusting for age, sex, race, and ethnicity. Associations were stronger after further adjustment for individual level of education; persons in the highest quintile had a 78% increased risk of multimorbidity (OR 1.78, 95% CI 1.62–1.96) and a 92% increased risk of severe multimorbidity (OR 1.92, 95% CI 1.72–2.13). There was evidence of interactions between ADI and age, between ADI and sex, and between ADI and education. After age 70 years, no difference in the risk of multimorbidity was observed across quintiles of ADI. The pattern of increasing multimorbidity with increasing ADI was more pronounced in women. Finally, there was less variability across quintiles of ADI for the most highly educated group. Conclusions Higher ADI was associated with increased risk of multimorbidity, and the associations were strengthened after adjustment for individual level of education, suggesting that neighborhood context plays a role in health above and beyond individual measures of socioeconomic status. Furthermore, associations were more pronounced in younger persons and women, highlighting the importance of interventions to prevent chronic conditions in younger women, in particular.

Rare copy number variants (CNVs) are associated with risk of neurodevelopmental disorders characterised by varying degrees of cognitive impairment, including schizophrenia, autism spectrum disorder and intellectual disability. However, the effects of many individual CNVs in carriers without neurodevelopmental disorders are not yet fully understood, and little is known about the effects of reciprocal copy number changes of known pathogenic loci.AimsWe aimed to analyse the effect of CNV carrier status on cognitive performance and measures of occupational and social outcomes in unaffected individuals from the UK Biobank. We called CNVs in the full UK Biobank sample and analysed data from 420 247 individuals who passed CNV quality control, reported White British or Irish ancestry and were not diagnosed with neurodevelopmental disorders. We analysed 33 pathogenic CNVs, including their reciprocal deletions/duplications, for association with seven cognitive tests and four general measures of functioning: academic qualifications, occupation, household income and Townsend Deprivation Index. Most CNVs (24 out of 33) were associated with reduced performance on at least one cognitive test or measure of functioning. The changes on the cognitive tests were modest (average reduction of 0.13 s.d.) but varied markedly between CNVs. All 12 schizophrenia-associated CNVs were associated with significant impairments on measures of functioning. CNVs implicated in neurodevelopmental disorders, including schizophrenia, are associated with cognitive deficits, even among unaffected individuals. These deficits may be subtle but CNV carriers have significant disadvantages in educational attainment and ability to earn income in adult life.Declaration of interestNone.

The aims of this study were to compare the NZ Indices of Multiple Deprivation (IMD) with the NZDep index of socioeconomic deprivation in terms of their: (1) theoretical and methodological approaches; (2) use of small areas; (3) rankings of small areas; and (4) relationships with various health and social outcomes. Literature sources were reviewed for aim 1. The data sources for aims 2-4, all contained within Statistics New Zealand's Integrated Data Infrastructure, were: (1) 2013 Census, (2) health data sets, (3) Police database, and (4) 2014 General Social Survey. Outcomes were smoking, mortality, respiratory disease, crime, self-assessed health status. Spearman's rho was used as a measure of correlation. Deciles were treated as categorical in the stepwise logistic regressions. The key finding is that there is a range of theoretical and methodological differences between the indexes. Despite these differences, the indexes behave in a similar, but not identical, manner in their ranking of small areas and in their associations with health and social outcomes. In conclusion, for practical purposes for many applications the two indexes give similar results when analysing very large data sets, although there are some important caveats related to this conclusion for both large and small data sets.

The coronavirus disease 2019 (COVID-19) has had a rapid and sustained negative impact on sleep and mental health in the United States with disproportionate morbidity and mortality among socioeconomically deprived populations. We used multivariable and logistic regression to evaluate the associations among sleep duration, mental health, and socioeconomic deprivation (social deprivation index) in 14,676 Ohio residents from 1101 zip code tabulation areas from the 2020 Behavioral Risk Factor Surveillance System (BRFSS) survey. Higher socioeconomic deprivation was associated with shorter sleep and poorer mental health after adjusting for covariates (age, sex, race, education, income, and body mass index) in the multivariable linear regression models. Those in the highest socioeconomically deprived areas had 1.6 and 1.5 times higher odds of short sleep (duration < 6 h) and poor mental health (>14 poor mental health days), respectively, in the logistic regression models. Previous researchers have focused on limited socio-environmental factors such as crowding and income. We examined the role of a composite area based measure of socioeconomic deprivation in sleep duration and mental health during the first year of COVID-19. Our results suggest the need for a broader framework to understand the associations among socioeconomic deprivation, sleep duration, and mental health during a catastrophic event.

Introduction: We describe the California Healthy Places Index (HPI) and its performance relative to other indexes for measuring community well-being at the census-tract level. The HPI arose from a need identified by health departments and community organizations for an index rooted in the social determinants of health for place-based policy making and program targeting. The index was geographically granular, validated against life expectancy at birth, and linked to policy actions. Materials and Methods: Guided by literature, public health experts, and a positive asset frame, we developed a composite index of community well-being for California from publicly available census-tract data on place-based factors linked to health. The 25 HPI indicators spanned 8 domains; weights were derived from their empirical association with tract-level life expectancy using weighted quantile sums methods. Results: The HPI’s domains were aligned with the social determinants of health and policy action areas of economic resources, education, housing, transportation, clean environment, neighborhood conditions, social resources, and health care access. The overall HPI score was the sum of weighted domain scores, of which economy and education were highly influential (50% of total weights). The HPI was strongly associated with life expectancy at birth (r = 0.58). Compared with the HPI, a pollution-oriented index did not capture one-third of the most disadvantaged quartile of census tracts (representing 3 million Californians). Overlap of the HPI’s most disadvantaged quartile of census tracts was greater for indexes of economic deprivation. We visualized the HPI percentile ranking as a web-based mapping tool that presented the HPI at multiple geographies and that linked indicators to an action-oriented policy guide. Practice Implications: The framing of indexes and specifications such as domain weighting have substantial consequences for prioritizing disadvantaged populations. The HPI provides a model for tools and new methods that help prioritize investments and identify multisectoral opportunities for policy action.

Emergency General Surgery (EGS) has high complication and mortality rates and social factors have been associated with outcomes in national datasets. Social deprivation index (SDI) is a validated geographic area demographic index used to quantify variations in healthcare. We sought to examine the association of SDI with mortality of high-risk EGS procedures at a regional level across a large integrated healthcare system. This is a retrospective cohort study of adult patients with ICD10 codes for EGS diagnoses who underwent high-risk procedures (small bowel resection, colectomy, gastroduodenal repair or resection, or combined procedures) in a large integrated healthcare system from 2017 to 2021. Our primary exposure was SDI. Primary outcome was inpatient mortality. Secondary outcomes were return to OR (RTOR), venous thromboembolism (VTE), and extended length of stay (≥75th percentile by procedure) (ELOS). Outcomes were analyzed by SDI and adjusted for age, race, Elixhauser Comorbidity Index, insurance, procedure, and initial shock index using multivariable logistic regression. Facilities were also analyzed by the SDI distribution of their EGS population. A total of 9441 hospital encounters were identified with 2765 high-risk procedure hospital encounters across nine hospitals. Overall inpatient mortality in the study cohort was 8.6 ​%. EGS patients undergoing high-risk procedures from the most disadvantaged areas had higher mortality rates and were more likely to require RTOR than those from the least disadvantaged areas after adjustment for covariates (OR 2.1, p ​= ​0.01; OR 1.9, p ​= ​0.001). SDI is associated with higher mortality and RTOR in EGS patients undergoing high-risk procedures. This study highlights the importance of local or regional area descriptions of population deprivation which may lead to geographically targeted interventions and prevention strategies. •Emergency general surgery patients from disadvantaged areas had higher mortality rates than patients from less disadvantaged areas•Emergency general surgery patients from disadvantaged areas were more likely to require return to the OR than patients from less disadvantage areas•Facilities within a large healthcare system had different proportions of patients from disadvantaged areas•Geographic targeting of interventions to communities at risk may improve surgical outcomes