Relação entre apoio social e sono de pessoas idosas cuidadoras em vulnerabilidade social / Relationship between social support and sleep of elderly caregivers in social vulnerability / Relación entre apoyo social y sueño de adultos mayores cuidadores con vulnerabilidad social

Objetivo: analisar a relação entre apoio social e qualidade do sono de pessoas idosas que cuidam de outros idosos em ambiente de vulnerabilidade social. Método: estudo transversal realizado com 65 cuidadores entrevistados por meio de instrumento de caracterização, Índice de Katz, Escala de Lawton e Brody, Índice de Qualidade do Sono de Pittsburgh e Escala de Apoio Social do Medical Outcomes Study, com dados analisados com testes de comparação e de correlação. Resultados: a maioria eram mulheres, cônjuges do idoso cuidado e possuíam sono de má qualidade. Observou-se correlação fraca e inversa entre má qualidade do sono e a dimensão interação social positiva (Rho=-0,27; p=0,028). Identificou-se relação significativa entre: apoio material e disfunção diurna (p=0,034); apoio afetivo e eficiência do sono (p=0,026); interação social positiva e qualidade subjetiva do sono (p=0,001) e disfunção diurna (p=0,008). Conclusão: Quanto maior a interação social positiva, melhor é a qualidade do sono.

Objective: to analyze the relationship between social support and sleep quality of elderly individuals who care for other elderly individuals in a socially vulnerable environment. Method: a cross-sectional study conducted with 65 caregivers interviewed using a characterization instrument, Katz Index, Lawton and Brody Scale, Pittsburgh Sleep Quality Index, and Medical Outcomes Study Social Support Scale, with data analyzed using comparison and correlation tests. Results: the majority were women, spouses of the elderly being cared for, and had poor sleep quality. A weak and inverse correlation was observed between poor sleep quality and the positive social interaction dimension (Rho=-0.27; p=0.028). Significant relationships were identified between: material support and daytime dysfunction (p=0.034); emotional support and sleep efficiency (p=0.026); positive social interaction and subjective sleep quality (p=0.001), as well as daytime dysfunction (p=0.008). Conclusion: The higher the positive social interaction, the better the sleep quality.

Objetivo: analizar la relación entre el apoyo social y la calidad del sueño de personas mayores que cuidan de otras personas mayores en entornos socialmente vulnerables. Método: estudio transversal realizado con 65 cuidadores entrevistados mediante un instrumento de caracterización, Índice de Katz, Escala de Lawton y Brody, Índice de Calidad del Sueño de Pittsburgh y Escala de Apoyo Social del Medical Outcomes Study, los datos fueron analizados mediante pruebas de comparación y correlación. Resultados: la mayoría eran mujeres, cónyuges del adulto mayor que recibe el cuidado y tenían mala calidad del sueño. Se observó una correlación débil e inversa entre la mala calidad del sueño y la dimensión de interacción social positiva (Rho=-0,27; p=0,028). Se identificó que había relación significativa entre: apoyo material y disfunción diurna (p=0,034); apoyo afectivo y eficiencia del sueño (p=0,026); interacción social positiva y calidad subjetiva del sueño (p=0,001) y disfunción diurna (p=0,008). Conclusión: Cuanto mayor sea la interacción social positiva, mejor será la calidad del sueño.

Examining the role of social vulnerability, neighborhood characteristics, and geospatial patterns of firearm-related injuries and clinical outcomes in Milwaukee county.

BACKGROUND: Previous work has shown socioenvironmental factors can influence firearm injury. Milwaukee County, Wisconsin is a diverse midwestern county with historic disinvestment in marginalized communities yielding stark segregation along racial and ethnic lines. It is also one of the many U.S. counties burdened by surging firearm injuries. The differences among communities within Milwaukee County provides a unique opportunity to explore the intersection of socioenvironmental factors that may affect clinical outcomes and geospatial patterns of firearm injury. METHODS: The trauma registry from the regional adult level 1 trauma center was queried for patients who sustained a firearm-related injury from 2015 to 2022 (N = 2402). The Social Vulnerability Index (SVI) ranking was derived using patient residence addresses to evaluate its association with traumatic injury clinical outcomes (i.e., in-hospital mortality, length of hospital stay, ICU or ventilator treatment, or injury severity score) and risk screening results for alcohol use disorder (AUD), posttraumatic stress disorder (PTSD), and depression. We evaluated hotspots of firearm injury density over time for patient residences and injury locations and distances between locations. A spatially lagged regression model tested the association between firearm injury density and SVI domains, alcohol outlet types, and park coverage. RESULTS: Most firearm injury patients were younger, male, racial or ethnic minorities from disadvantaged neighborhoods (SVI total; M = 0.86, SD = 0.15). SVI was not associated with any clinical outcomes. Of those screened, 12.9% screened positive for AUD and 44.5% screened at risk for PTSD, depression, or both. Hotspot analysis indicated consistent concentrations of firearm injury density. There were no differences in clinical outcomes between those injured inside or outside the home. Census tracts with lower socioeconomic status, greater off-premises and lower on-premises alcohol outlet density were associated with greater firearm injury density. CONCLUSIONS: In Milwaukee County, firearm injury patients are injured in and often return to the same disadvantaged neighborhoods that may hamper recovery. Results replicate and expand previous work and implicate specific socioenvironmental factors for intervention and prevention of firearm injury.

Associations between Flood Risk and United States Census Tract-Level Health Outcomes.

Human-induced climate change has led to more frequent and severe flooding throughout the globe. We examined the association between flood risk and the prevalence of coronary heart disease, high blood pressure, asthma, and poor mental health in the UnitedStates, while taking into account different levels of social vulnerability. We aggregated flood risk variables from First Street Foundation by census tract and used principal component analysis to derive a set of five interpretable flood risk factors. The dependent variables were census-tract level disease prevalences generated by the Centers for Disease Control and Prevention. Bayesian spatial conditional autoregressive models were fit on this data to quantify the relationship between flood risk and health outcomes under different stratifications of social vulnerability. We showed that three flood risk principal components had small but significant associations with each of the health outcomes, across the different stratifications of social vulnerability. Our analysis gives the first United States-wide estimates of the associated effects of flood risk on specific health outcomes. We also show that social vulnerability is an important moderator of the relationship between flood risk and health outcomes. Our approach can be extended to other ecological studies that examine the health impacts of climate hazards.

Social Determinants of Health and Limitation of Life-Sustaining Therapy in Neurocritical Care: A CHoRUS Pilot Project.

BACKGROUND: Social determinants of health (SDOH) have been linked to neurocritical care outcomes. We sought to examine the extent to which SDOH explain differences in decisions regarding life-sustaining therapy, a key outcome determinant. We specifically investigated the association of a patient's home geography, individual-level SDOH, and neighborhood-level SDOH with subsequent early limitation of life-sustaining therapy (eLLST) and early withdrawal of life-sustaining therapy (eWLST), adjusting for admission severity. METHODS: We developed unique methods within the Bridge to Artificial Intelligence for Clinical Care (Bridge2AI for Clinical Care) Collaborative Hospital Repository Uniting Standards for Equitable Artificial Intelligence (CHoRUS) program to extract individual-level SDOH from electronic health records and neighborhood-level SDOH from privacy-preserving geomapping. We piloted these methods to a 7 years retrospective cohort of consecutive neuroscience intensive care unit admissions (2016-2022) at two large academic medical centers within an eastern Massachusetts health care system, examining associations between home census tract and subsequent occurrence of eLLST and eWLST. We matched contextual neighborhood-level SDOH information to each census tract using public data sets, quantifying Social Vulnerability Index overall scores and subscores. We examined the association of individual-level SDOH and neighborhood-level SDOH with subsequent eLLST and eWLST through geographic, logistic, and machine learning models, adjusting for admission severity using admission Glasgow Coma Scale scores and disorders of consciousness grades. RESULTS: Among 20,660 neuroscience intensive care unit admissions (18,780 unique patients), eLLST and eWLST varied geographically and were independently associated with individual-level SDOH and neighborhood-level SDOH across diagnoses. Individual-level SDOH factors (age, marital status, and race) were strongly associated with eLLST, predicting eLLST more strongly than admission severity. Individual-level SDOH were more strongly predictive of eLLST than neighborhood-level SDOH. CONCLUSIONS: Across diagnoses, eLLST varied by home geography and was predicted by individual-level SDOH and neighborhood-level SDOH more so than by admission severity. Structured shared decision-making tools may therefore represent tools for health equity. Additionally, these findings provide a major warning: prognostic and artificial intelligence models seeking to predict outcomes such as mortality or emergence from disorders of consciousness may be encoded with self-fulfilling biases of geography and demographics.

The association between social vulnerability and geriatric assessment impairments among older adults with gastrointestinal cancers-The CARE Registry.

BACKGROUND: Older adults comprise the majority of patients with gastrointestinal (GI) cancer. Geriatric assessments (GAs) are recommended for older adults with cancer in part to detect aging-related impairments (e.g., frailty) associated with early mortality. Social factors like social vulnerability may also influence aging-related impairments. However, the association between social vulnerability and aging outcomes among older adults with cancer is understudied. METHODS: The authors included 908 older adults aged 60 years and older who were recently diagnosed with GI cancer undergoing GA at their first prechemotherapy visit to the University of Alabama at Birmingham oncology clinic. The primary exposure of interest was the social vulnerability index (SVI). Outcomes were frailty (frail vs. robust/prefrail) and total number of GA impairments (range, 0-13). The authors examined the association between SVI and outcomes using Poisson regression with robust variance estimation and generalized estimating equations. RESULTS: The median age at GA was 69 years (interquartile range, 64-75 years), 58.2% of patients were male, 22.6% were non-Hispanic Black, 29.1% had colorectal cancer, 28.2% had pancreatic cancer, and 70.3% had stage III/IV disease. Adjusting for age, sex, cancer type, and disease stage, each decile increase in the SVI was associated with an 8% higher prevalence of frailty (prevalence ratio, 1.08; 95% confidence interval, 1.05-1.11) and a 4% higher average count of total GA impairments (risk ratio, 1.04; 95% confidence interval, 1.02-1.06). The results were attenuated after further adjustment for race and education. CONCLUSIONS: Greater social vulnerability was associated with a higher prevalence of frailty and an increasing average number of GA impairments among older adults with GI cancers before systemic treatment. Intervening on social vulnerability may be a target for improving the risk of frailty and GA impairments, but associations of race and education should be further evaluated.

Food deserts, endometrial cancer survivors, and healthy food access: Is it equitable in rural America? - A geospatial analysis.

OBJECTIVE: To examine endometrial cancer survivors' access to healthy food resources recommended by the Society of Gynecologic Oncology (SGO) in relation to food deserts and social health determinants. METHODS: Participants included women seen for endometrial cancer treatment at an academic medical center in the Deep South from 2015 to 2020 who lived in South Carolina. Demographic and comorbidity data were abstracted from medical records. Food desert data were obtained from the United States Department of Agriculture (USDA). Each patient was assigned a socioeconomic (SES) score (SES-1 = low, SES-5 = high) using census data and a social vulnerability index (SVI) using Center for Disease Control and Prevention (CDC) data for neighborhood adverse health effects. Geospatial techniques assessed patients' driving distance from home to a healthy food resource. RESULTS: Of the 736 endometrial cancer survivors, 31% identified as African American, and 30% lived in low SES (SES-1, SES-2) census blocks. Most survivors had low grade disease (63%) and 76% with stage 1-2 disease. Seventy percent of patients were obese (BMI ≥30 kg/m2). Forty percent of survivors lived in a food desert. Survivors living in a food desert with low SES had significantly higher social vulnerability (p = 0.0001) and lower median income (p = 0.0001). Those with low SES and living in a food desert drove further (p = 0.05, range 0.017-12.0 miles). CONCLUSION: Obesity rates were high in endometrial cancer survivors living in the Deep South. Survivors with higher social vulnerability and lower SES were more likely to live in food deserts with decreased access to healthy food resources.

Investigating the effects of spatial scales on social vulnerability index: A hybrid uncertainty and sensitivity analysis approach combined with remote sensing land cover data.

Investigating the effects of spatial scales on the uncertainty and sensitivity analysis of the social vulnerability index (SoVI) model output is critical, especially for spatial scales finer than the census block group or census block. This study applied the intelligent dasymetric mapping approach to spatially disaggregate the census tract scale SoVI model into a 300-m grids resolution SoVI map in Davidson County, Nashville. Then, uncertainty analysis and variance-based global sensitivity analysis were conducted on two scales of SoVI models: (a) census tract scale; (b) 300-m grids scale. Uncertainty analysis results indicate that the SoVI model has better confidence in identifying places with a higher socially vulnerable status, no matter the spatial scales in which the SoVI is constructed. However, the spatial scale of SoVI does affect the sensitivity analysis results. The sensitivity analysis suggests that for census tract scale SoVI, the indicator transformation and weighting scheme are the two major uncertainty contributors in the SoVI index modeling stages. While for finer spatial scales like the 300-m grid's resolution, the weighting scheme becomes the uttermost dominant uncertainty contributor, absorbing uncertainty contributions from indicator transformation.

Examining social vulnerability to multi-hazards in North-Western Himalayas, India.

The enhancing risk from human action and multi-hazard interaction has substantially complicated the hazard-society relationship. The underlying vulnerabilities are crucial in predicting the probable impact to be caused by multi-hazards. Thus, the evaluation of social vulnerability is decisive in inferring the driving factor and preparing for mitigation strategies. The Himalayan landscape is prone to multiple hazards as well as possesses a multitude of vulnerabilities owing to changing human landscape. Thus, an attempt has been made to inquire into the underlying socioeconomic factors enhancing the susceptibility of the region to multi-hazards. The social vulnerability index (SVIent) has been introduced, consisting of 13 indicators and 33 variables. The variables have been standardized using the maximum and minimum normalization method and the relative importance for each indicator has been determined using Shannon entropy methods to compute SVIent. The findings revealed that female population, population above 60 years old, net irrigated area, migrant population, dilapidated house, nonworkers, bank, and nonworkers seeking jobs were found to be relatively significant contributors to the vulnerability. The western part of the study area was classified as the highly vulnerable category (SVI > 0.40628), attributed to high dependence, and higher share of unemployed workers and high poverty. The SVIent was shown to have positive correlation between unemployment, socioeconomic status, migration, dependency, and household structure significant at two-tailed test. The study's impact can be found in influencing the decision of policymakers and stakeholders in framing the mitigation strategies and policy documents.

Socioeconomic Disparities and the Prevalence of Antimicrobial Resistance.

BACKGROUND: The increased prevalence of antimicrobial resistant (AMR) infections is a significant global health threat, resulting in increased morbidity, mortality, and costs. The drivers of AMR are complex and potentially impacted by socioeconomic factors. We investigated the relationships between geographic and socioeconomic factors and AMR. METHODS: We collected select patient bacterial culture results from 2015 to 2020 from electronic health records (EHR) of two expansive healthcare systems within the Dallas-Fort Worth, TX (DFW) metropolitan area. Among individuals with EHR records who resided in the four most populus counties in DFW, culture data were aggregated. Case counts for each organism studied were standardized per 1,000 persons per area population. Using residential addresses, the cultures were geocoded and linked to socioeconomic index values. Spatial autocorrelation tests identified geographic clusters of high and low AMR organism prevalence and correlations with established socioeconomic indices. RESULTS: We found significant clusters of AMR organisms in areas with high levels of deprivation, as measured by the Area Deprivation Index (ADI). We found a significant spatial autocorrelation between ADI and the prevalence of AMR organisms, particularly for AmpC and MRSA with 14% and 13%, respectively, of the variability in prevalence rates being attributable to their relationship with the ADI values of the neighboring locations. CONCLUSIONS: We found that areas with a high ADI are more likely to have higher rates of AMR organisms. Interventions that improve socioeconomic factors such as poverty, unemployment, decreased access to healthcare, crowding, and sanitation in these areas of high prevalence may reduce the spread of AMR.

Effect of Social Vulnerability on Cocaine-Related Mortality Rates in U.S. Counties.

Cocaine-related mortality rates have risen sharply since 2013 and social vulnerability is a crucial indicator for drug-related mortality rates. Therefore, the purpose of this study was to investigate the relationship between social vulnerability and cocaine-related mortality rates in U.S. counties. The Data were collected from the CDC WONDER, CDC's Social Vulnerability Index (CDC's SVI), and American Community Survey (ACS). The Data were analyzed by spatial autoregression models. According to present results, first, counties with social vulnerability (socioeconomic) were positively related to higher rates of cocaine overdose death (spatial lag: B = 0.323, p < .05; spatial error: B = 0.513, p < .01). Second, counties with social vulnerability (minority status & language) were negatively related to higher rates of cocaine overdose death (spatial lag: B = -0.233, p < .05). Third, counties with social vulnerability (housing type & transportation) were positively related to higher rates of cocaine overdose death (spatial lag: B = 0.413, p < .001; spatial error: B = 0.378, p < .001). In conclusion, the spread of cocaine overdose on U.S. counties with social vulnerabilities demonstrated a disproportionate burden of cocaine-related mortality.

Telehealth Infrastructure, Accountable Care Organization, and Medicare Payment for Patients with Alzheimer's Disease and Related Dementia Living in Socially Vulnerable Areas.

Background: Structural social determinants of health have an accumulated negative impact on physical and mental health. Evidence is needed to understand whether emerging health information technology and innovative payment models can help address such structural social determinants for patients with complex health needs, such as Alzheimer's disease and related dementias (ADRD). Objective: This study aimed to test whether telehealth for care coordination and Accountable Care Organization (ACO) enrollment for residents in the most disadvantaged areas, particularly those with ADRD, was associated with reduced Medicare payment. Methods: The study used the merged data set of 2020 Centers for Medicare and Medicaid Services Medicare inpatient claims data, the Medicare Beneficiary Summary File, the Medicare Shared Savings Program ACO, the Center for Medicare and Medicaid Service's Social Vulnerability Index (SVI), and the American Hospital Annual Survey. Our study focused on community-dwelling Medicare fee-for-service beneficiaries aged 65 years and up. Cross-sectional analyses and generalized linear models (GLM) were implemented. Analyses were implemented from November 2023 to February 2024. Results: Medicare fee-for-service beneficiaries residing in SVI Q4 (i.e., the most vulnerable areas) reported significantly higher total Medicare costs and were least likely to be treated in hospitals that provided telehealth post-discharge services or have ACO affiliation. Meanwhile, the proportion of the population with ADRD was the highest in SVI Q4 compared with other SVI levels. The GLM regression results showed that hospital telehealth post-discharge infrastructure, patient ACO affiliation, SVI Q4, and ADRD were significantly associated with higher Medicare payments. However, coefficients of interaction terms among these factors were significantly negative. For example, the average interaction effect of telehealth post-discharge and ACO, SVI Q4, and ADRD on Medicare payment was -$1,766.2 (95% confidence interval: -$2,576.4 to -$976). Conclusions: Our results suggested that the combination of telehealth post-discharge and ACO financial incentives that promote care coordination is promising to reduce the Medicare cost burden among patients with ADRD living in socially vulnerable areas.

High-Risk Areas for Congenital Zika Syndrome in Rio de Janeiro: Spatial Cluster Detection.

Brazil reported 18,282 suspected congenital Zika syndrome (CZS) cases up to 2018 and accounts for 61.4% of the total reported Zika cases in the Americas in the period. To detect high-risk areas for children with CZS in the city of Rio de Janeiro, we used cluster detection and thematic maps. We analyzed data using a Poisson model in Satscan 10.1.3 software. We also analyzed the records of children with CZS from 2015 to 2016 to describe the clinical and epidemiological maternal and child profile, as well as live births in 2016 and the social development index (SDI) by neighborhood. In 2015 and 2016, the incidence rates of CZS were 8.84 and 46.96 per 100,000 live births in the city, respectively. Severe congenital findings such as microcephaly and brain damage, osteoarticular impairment, ocular abnormalities, and hearing loss were observed in 47 children. The spatial distribution of CZS was concentrated in the north and west zones in heterogeneous neighborhoods. The neighborhoods with the highest occurrence of CZS cases were found to have the worst SDIs. Stascan detected three spatial clusters in the north zone, where the SDI is lower. The clusters presented high relative risks for CZS (7.86, 1.46, and 2.08), although they were not statistically significant. Our findings highlight a higher occurrence of CZS in areas with less favorable socioeconomic conditions.

Characteristics of healthcare personnel with SARS-CoV-2 infection: 10 emerging infections program sites in the United States, April 2020-December 2021.

BACKGROUND: Understanding characteristics of healthcare personnel (HCP) with SARS-CoV-2 infection supports the development and prioritization of interventions to protect this important workforce. We report detailed characteristics of HCP who tested positive for SARS-CoV-2 from April 20, 2020 through December 31, 2021. METHODS: CDC collaborated with Emerging Infections Program sites in 10 states to interview HCP with SARS-CoV-2 infection (case-HCP) about their demographics, underlying medical conditions, healthcare roles, exposures, personal protective equipment (PPE) use, and COVID-19 vaccination status. We grouped case-HCP by healthcare role. To describe residential social vulnerability, we merged geocoded HCP residential addresses with CDC/ATSDR Social Vulnerability Index (SVI) values at the census tract level. We defined highest and lowest SVI quartiles as high and low social vulnerability, respectively. RESULTS: Our analysis included 7,531 case-HCP. Most case-HCP with roles as certified nursing assistant (CNA) (444, 61.3%), medical assistant (252, 65.3%), or home healthcare worker (HHW) (225, 59.5%) reported their race and ethnicity as either non-Hispanic Black or Hispanic. More than one third of HHWs (166, 45.2%), CNAs (283, 41.7%), and medical assistants (138, 37.9%) reported a residential address in the high social vulnerability category. The proportion of case-HCP who reported using recommended PPE at all times when caring for patients with COVID-19 was lowest among HHWs compared with other roles. CONCLUSIONS: To mitigate SARS-CoV-2 infection risk in healthcare settings, infection prevention, and control interventions should be specific to HCP roles and educational backgrounds. Additional interventions are needed to address high social vulnerability among HHWs, CNAs, and medical assistants.

Comparing Individual and Community-level Characteristics of People with Ground Beef-associated Salmonellosis and Other Ground Beef Eaters: A Case-control Analysis.

Salmonella is estimated to be the leading bacterial cause of U.S. domestically acquired foodborne illness. Large outbreaks of Salmonella attributed to ground beef have been reported in recent years. The demographic and sociodemographic characteristics of infected individuals linked to these outbreaks are poorly understood. We employed a retrospective case-control design; case-patients were people with laboratory-confirmed Salmonella infections linked to ground beef-associated outbreaks between 2012 and 2019, and controls were respondents to the 2018-2019 FoodNet Population Survey who reported eating ground beef and denied recent gastrointestinal illness. We used county-level CDC/ATSDR Social Vulnerability Index (SVI) to compare case-patient and controls. Case-patient status was regressed on county-level social vulnerability and individual-level demographic characteristics. We identified 376 case-patients and 1,321 controls in the FoodNet sites. Being a case-patient was associated with increased overall county-level social vulnerability (OR: 1.21 [95% CI: 1.07-1.36]) and socioeconomic vulnerability (OR: 1.24 [1.05-1.47]) when adjusted for individual-level demographics. Case-patient status was not strongly associated with the other SVI themes of household composition and disability, minority status and language, and housing type and transportation. Data on individual-level factors such as income, poverty, unemployment, and education could facilitate further analyses to understand this relationship.

Wildfires and climate justice: future wildfire events predicted to disproportionally impact socioeconomically vulnerable communities in North Carolina.

Wildfire events are becoming increasingly common across many areas of the United States, including North Carolina (NC). Wildfires can cause immediate damage to properties, and wildfire smoke conditions can harm the overall health of exposed communities. It is critical to identify communities at increased risk of wildfire events, particularly in areas with that have sociodemographic disparities and low socioeconomic status (SES) that may exacerbate incurred impacts of wildfire events. This study set out to: (1) characterize the distribution of wildfire risk across NC; (2) implement integrative cluster analyses to identify regions that contain communities with increased vulnerability to the impacts of wildfire events due to sociodemographic characteristics; (3) provide summary-level statistics of populations with highest wildfire risk, highlighting SES and housing cost factors; and (4) disseminate wildfire risk information via our online web application, ENVIROSCAN. Wildfire hazard potential (WHP) indices were organized at the census tract-level, and distributions were analyzed for spatial autocorrelation via global and local Moran's tests. Sociodemographic characteristics were analyzed via k-means analysis to identify clusters with distinct SES patterns to characterize regions of similar sociodemographic/socioeconomic disparities. These SES groupings were overlayed with housing and wildfire risk profiles to establish patterns of risk across NC. Resulting geospatial analyses identified areas largely in Southeastern NC with high risk of wildfires that were significantly correlated with neighboring regions with high WHP, highlighting adjacent regions of high risk for future wildfire events. Cluster-based analysis of SES factors resulted in three groups of regions categorized through distinct SES profiling; two of these clusters (Clusters 2 and 3) contained indicators of high SES vulnerability. Cluster 2 contained a higher percentage of younger (<5 years), non-white, Hispanic and/or Latino residents; while Cluster 3 had the highest mean WHP and was characterized by a higher percentage of non-white residents, poverty, and less than a high school education. Counties of particular SES and WHP-combined vulnerability include those with majority non-white residents, tribal communities, and below poverty level households largely located in Southeastern NC. WHP values per census tract were dispersed to the public via the ENVIROSCAN application, alongside other environmentally-relevant data.

Pen needle use patterns in an insured population with diabetes: US retrospective claims analysis.

BACKGROUND: People with diabetes who inject insulin with pen devices may reuse the pen needles (PNs), a practice that can cause PN tip deformity, breakage, and contamination, and that is associated with lipohypertrophy and injection-related pain. OBJECTIVE: This retrospective study aimed to estimate the extent of PN reuse among people with diabetes in two insured populations in the United States. METHODS: Using claims data for Commercial Fully Insured (CFI) and Medicare Advantage (MA) populations from 1-Oct-2018 to 31-Dec-2022, we identified adults with type 1 or type 2 diabetes (T1D/T2D) who had ≥1 claim for PNs and ≥2 claims for insulin from 1-Jan-2019 to 31-Dec-2021, with continuous medical/pharmacy eligibility for 3 months before first claim and 1 year after (follow-up). Those receiving hospice or palliative care or using mail-order prescriptions were excluded. We compared actual annual fill rate of PNs with expected fill rate (assuming single use) according to prescribed insulin regimen. Whether the annual actual-to-expected ratio for PN numbers equaled 1 was evaluated using sign tests with 2-sided p-values. RESULTS: Median annual actual-to-expected ratios ranged from 0.41 (T1D basal+prandial cohort) to 0.82 (T2D basal cohort; all p<0.001) in the CFI population (N=10,854), and from 0.55 (TID basal+prandial) to 1.10 (T2D basal and basal+prandial; p=0.382 to <0.001) in the MA population (N=32,495); medians were 0.34 and 0.55 for four expected T2D basal+prandial injections/day in CFI and MA populations, respectively (p<0.001). Annual actual-to-expected ratios were <1 for 62% and 47% of CFI and MA populations, respectively. An estimated 2-27% and 0-17%, respectively, depending on insulin regimen, had inadequate supplies of PNs suggesting that PNs could have been used ≥5 times. CONCLUSIONS: These findings highlight the need for educating people with diabetes about reasons for avoiding PN reuse and the key role that pharmacists can play in providing this information and adequate supplies of PNs.

The Impact of Social Vulnerability on Structural and Functional Glaucoma Severity, Worsening, and Variability.

PURPOSE: To determine the associations between social vulnerability index (SVI) and baseline severity, worsening, and variability of glaucoma, as assessed by visual field (VF) and OCT. DESIGN: Retrospective longitudinal cohort study. PARTICIPANTS: Adults with glaucoma or glaucoma suspect status in 1 or both eyes. Visual fields were derived from 7897 eyes from 4482 patients, while OCTs were derived from 6271 eyes from 3976 patients. All eyes had a minimum of 5 tests over follow-up using either the Humphrey Field Analyzer or the Cirrus HD-OCT. METHODS: Social vulnerability index, which measures neighborhood-level environmental factors, was linked to patients' addresses at the census tract level. Rates of change in mean deviation (MD) and retinal nerve fiber layer (RNFL) thickness were computed using linear regression. The slope of the regression line was used to assess worsening, while the standard deviation of residuals was used as a measure of variability. Multivariable linear mixed-effects models were used to investigate the impact of SVI on baseline, worsening, and variability in both MD and RNFL. We further explored the interaction effect of mean intraocular pressure (IOP) and SVI on worsening in MD and RNFL. MAIN OUTCOME MEASURES: Glaucoma severity defined based on baseline MD and RNFL thickness. Worsening defined as MD and RNFL slope. Variability defined as the standard deviation of the residuals obtained from MD and RNFL slopes. RESULTS: Increased (worse) SVI was significantly associated with worse baseline MD (ß = -1.07 dB, 95% confidence interval [CI]: [-1.54, -0.60]), thicker baseline RNFL (ß = 2.46 µm, 95% CI: [0.75, 4.17]), greater rates of RNFL loss (ß = -0.12 µm, 95% CI: [-0.23, -0.02]), and greater VF variability (ß = 0.16 dB, 95% CI: [0.07, 0.24]). Having worse SVI was associated with worse RNFL loss with increases in IOP (ßinteraction = -0.07, 95% CI: [-0.12, -0.02]). CONCLUSIONS: Increased SVI score is associated with worse functional (VF) loss at baseline, higher rates of structural (OCT) worsening over time, higher VF variability, and a greater effect of IOP on RNFL loss. Further studies are needed to enhance our understanding of these relationships and establish their cause. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The Impact of Social Vulnerability on Alcohol Consumption and Mortality: A 20-year Age, Sex-stratified Analysis from the Taiwan Longitudinal Study of Aging.

OBJECTIVE: This study aimed to use the Social Vulnerability Index (SVI) to encapsulate the complex and multidimensional nature of social determinants and their influence on alcohol intake and mortality in middle-aged and older individuals. DESIGN: Cohort study. SETTING AND PARTICIPANTS: Data were obtained from the Taiwan Longitudinal Study on Aging (TLSA), with 3945 study participants aged 50 years and older. METHODS: The TLSA questionnaire defined SVI (51 items including living conditions, social support, socially oriented activities of daily living, social engagement and leisure, empowerment of life, satisfaction about life, and socioeconomic status) and alcohol intake (behavior as well as type and frequency of alcohol intake). Multivariate Cox proportional hazard models were used to estimate the association between alcohol intake and mortality, stratified by sex and SVI groups. RESULTS: Men with high social vulnerability and high alcohol intake exhibit an elevated mortality risk [adjusted hazard ratio (aHR), 1.51; 95% CI, 1.01-2.24], whereas notably, women in similar social circumstances but with moderate alcohol intake face a quintupled mortality risk (>35 g/wk; aHR, 5.67; 95% CI, 2.37-13.61). The impact of alcohol and social vulnerability on mortality was more pronounced in men younger than 65. Among them, those with high social vulnerability and moderate (35-140 g/wk; aHR, 2.83; 95% CI, 1.50-5.36) to high (>140 g/wk; aHR, 2.24; 95% CI, 1.15-4.35) alcohol intake was associated with an increased risk of mortality. CONCLUSIONS AND IMPLICATIONS: Various factors throughout the life course of both men and women significantly impact the risk of all-cause mortality due to alcohol intake, underscoring the importance of social vulnerability as a determinant of both alcohol intake behavior and mortality risk.

Slow-wave brain connectivity predicts executive functioning and group belonging in socially vulnerable individuals.

Important efforts have been made to describe the neural and cognitive features of healthy and clinical populations. However, the neural and cognitive features of socially vulnerable individuals remain largely unexplored, despite their proneness to developing neurocognitive disorders. Socially vulnerable individuals can be characterised as socially deprived, having a low socioeconomic status, suffering from chronic social stress, and exhibiting poor social adaptation. While it is known that such individuals are likely to perform worse than their peers on executive function tasks, studies on healthy but socially vulnerable groups are lacking. In the current study, we explore whether neural power and connectivity signatures can characterise executive function performance in healthy but socially vulnerable individuals, shedding light on the impairing effects that chronic stress and social disadvantages have on cognition. We measured resting-state electroencephalography and executive functioning in 38 socially vulnerable participants and 38 matched control participants. Our findings indicate that while neural power was uninformative, lower delta and theta phase synchrony are associated with worse executive function performance in all participants, whereas delta phase synchrony is higher in the socially vulnerable group compared to the control group. Finally, we found that delta phase synchrony and years of schooling are the best predictors for belonging to the socially vulnerable group. Overall, these findings suggest that exposure to chronic stress due to socioeconomic factors and a lack of education are associated with changes in slow-wave neural connectivity and executive functioning.

Psychosocial risk profiles to address future health emergencies: a country study during the COVID-19 lockdown period in Colombia.

Introduction: The different strategies used worldwide to curb the COVID-19 pandemic between 2020 and 2021 had a negative psychosocial impact, which was disproportionately higher for socially and economically vulnerable groups. This article seeks to identify the psychosocial impact of the confinement period during the COVID-19 pandemic for the Colombian population by identifying profiles that predict the levels of different mental health indicators (feelings of fear, positive emotions or feelings during free time, and work impact) and based on them, characterize the risk factors and protection that allows us to propose guidelines for prevention or recovery from future health emergencies. Methods: This is an observational, cross-sectional, retrospective ex post facto study. Multistage cluster probabilistic sampling and binary logistic regression analysis were used to predict extreme levels of various mental health indicators based on psychosocial indicators of the COVID-19 confinement period and to identify risk and protection factors. Results: A relationship was established between the combination of some of the different psychosocial factors evaluated (this combination being the predictive profile identified) with each of the three main variables: feeling of fear (n = 8,247; R = 0.32; p = 0.00; Poverall = 62.4%; 𝜔overall = 0.25; 1-𝛽overall = 1.00), positive emotions or feelings during free time (n = 6,853; R = 0.25; p = 0.00; Poverall = 59.1%; 𝜔overall = 0.18; 1-𝛽overall = 1.00) and labour impact (n = 4,573; R = 0.47; p = 0.63; Poverall = 70.4%; 𝜔overall = 0.41; 1-𝛽overall = 1.00), with social vulnerability determined by sociodemographic factors that were common in all profiles (sex, age, ethnicity and socioeconomic level) and conditions associated with job insecurity (unemployed, loss of health insurance and significant changes to job's requirements) and place of residence (city). Conclusion: For future health emergencies, it is necessary to (i) mitigate the socio-employment impact from emergency containment measures in a scaled and differentiated manner at the local level, (ii) propose prevention and recovery actions through psychosocial and mental health care accessible to the entire population, especially vulnerable groups, (iii) Design and implement work, educational and recreational adaptation programs that can be integrated into confinement processes.