Weather Variability and COPD: A Risk Estimation Identified a Vulnerable Sub-population in Hungary.

BACKGROUND/AIM: Chronic obstructive pulmonary disease (COPD) is a major public health concern, affecting over 200 million people worldwide in 2019. The prevalence of COPD has risen by 40% from 1990 to 2010 and continued to increase by 13% from 2010 to 2019, causing over 3 million deaths globally in 2019, ranking it as the third leading cause of death. This study explored how daily weather changes relate to the number of COPD-related emergency department (ED) visits. MATERIALS AND METHODS: We collected data on daily COPD-related ED visits in 2017 in Pécs along with corresponding meteorological data to analyze this connection. RESULTS: High diurnal temperature range (DTR) and day-to-day variability in dew point were linked to a 4.5% increased risk of more COPD-related ED visits. Notably, DTR had a stronger impact on males, contributing to a 6.3% increase, while dew point variability significantly affected males with an odds ratio (OR) of 1.083. (OR=1.083). Stratifying by age revealed heightened risks for those aged 30-39 (43.5% increase) and 50-59 (7.6% increase). Females aged 30-39 and 50-59 faced elevated risks of 42.7% and 9.1%, respectively, whereas males aged 60-69 showed a 9.8% increase. CONCLUSION: Our findings highlight the influence of weather variations on COPD-related ED visits, with nuanced effects based on age and sex.

Mapping Strategies for Reaching Socioeconomically Disadvantaged Populations in Clinical Trials.

Importance: Socioeconomically disadvantaged patients, such as persons with low income and those with low educational attainment, are less likely to participate in clinical trials than those with higher earnings and higher educational attainment, despite the former being more likely to have chronic medical conditions. Ways to improve the representation of socioeconomically disadvantaged patients in clinical trials deserve attention. Objective: To examine whether current recruitment and enrollment strategies used by US clinical research sites appropriately include patients from socioeconomically disadvantaged backgrounds. Design, Setting, and Participants: This survey study was conducted between April and July 2023. An online survey was distributed among US clinical research sites to explore their use of these strategies and the types of patient sociodemographic and socioeconomic data they collect. The survey was distributed by 13 pharmaceutical companies and 1 clinical research organization. Eight targeted strategies known to increase the recruitment and retention of socioeconomically disadvantaged participants as well as 6 general strategies to recruit and retain clinical trial participants were identified. Data analysis was performed between August and September 2023. Main Outcomes and Measures: Proportions of for-profit vs nonprofit or governmental sites that use recruitment and retention strategies, proportions that have partnerships with community organizations that target socioeconomically disadvantaged groups, and the distribution of sociodemographic and socioeconomic data collected by sites about their patients. A χ2 test of independence was performed to assess the association between research site ownership type and levels of adoption of strategies. Results: A total of 492 responses were collected from 381 clinical research sites in the US (219 for-profit sites [57.5%] and 162 nonprofit or governmental sites [42.5%]). Overall, compared with nonprofit or governmental sites, for-profit sites reported higher use of strategies shown to increase the recruitment and retention of socioeconomically disadvantaged populations, including always or often providing after-hours visits (84 of 173 for-profit sites [48.6%]; 22 of 123 nonprofit or governmental sites [17.9%]) and offering financial compensation (135 of 162 for-profit sites [83.3%]; 60 of 123 nonprofit or governmental sites [48.8%]). Additionally, there was an association between research site ownership type and levels of adoption of these strategies; for example, for-profit sites were more likely to provide after-hours visits (χ2 = 30.33; P < .001) and offer financial compensation (χ2 = 49.35; P < .001). Only 7.2% of for-profit sites (12 of 167) and 13.0% of nonprofit or governmental sites (16 of 123) collected information on the patient's annual income. Conclusions and Relevance: In this survey study, we found an association between a clinical research site's ownership type (for-profit vs nonprofit or governmental) and how often it used strategies to engage socioeconomically diverse populations in clinical research. Regardless of ownership type, most clinical research sites did not collect socioeconomic information from patients. Adoption of strategies to engage socioeconomically diverse populations, particularly by nonprofit or governmental sites, may help minimize barriers to participation for socioeconomically disadvantaged patients.

Social protection in areas vulnerable to tuberculosis: a mixed methods study in São Luís, Maranhão.

OBJECTIVES: to analyze the risk areas for tuberculosis and the influences of social protection on the development of treatment for the disease in the municipality of São Luís, Maranhão. METHODS: this is explanatory sequential mixed method research. In the quantitative phase, the data were obtained from the Notifiable Diseases Information System from 2010 to 2019, with georeferencing being carried out to identify areas vulnerable to tuberculosis. In the qualitative phase, semi-structured interviews were carried out with individuals who received social benefits. RESULTS: 7,381 cases were geocoded, and, from the purely spatial scanning analysis, it was possible to identify 13 spatial clusters of risk. As for the interviews, there was a positive relationship between patient improvement and receiving benefits. CONCLUSIONS: geographic space and social determinants are relevant for reorienting monitoring actions for the conditions that generate the health-disease process.

Remote Inclusion of Vulnerable Users in mHealth Intervention Design: Retrospective Case Analysis.

BACKGROUND: Mobile health (mHealth) interventions that promote healthy behaviors or mindsets are a promising avenue to reach vulnerable or at-risk groups. In designing such mHealth interventions, authentic representation of intended participants is essential. The COVID-19 pandemic served as a catalyst for innovation in remote user-centered research methods. The capability of such research methods to effectively engage with vulnerable participants requires inquiry into practice to determine the suitability and appropriateness of these methods. OBJECTIVE: In this study, we aimed to explore opportunities and considerations that emerged from involving vulnerable user groups remotely when designing mHealth interventions. Implications and recommendations are presented for researchers and practitioners conducting remote user-centered research with vulnerable populations. METHODS: Remote user-centered research practices from 2 projects involving vulnerable populations in Norway and Australia were examined retrospectively using visual mapping and a reflection-on-action approach. The projects engaged low-income and unemployed groups during the COVID-19 pandemic in user-based evaluation and testing of interactive, web-based mHealth interventions. RESULTS: Opportunities and considerations were identified as (1) reduced barriers to research inclusion; (2) digital literacy transition; (3) contextualized insights: a window into people's lives; (4) seamless enactment of roles; and (5) increased flexibility for researchers and participants. CONCLUSIONS: Our findings support the capability and suitability of remote user methods to engage with users from vulnerable groups. Remote methods facilitate recruitment, ease the burden of research participation, level out power imbalances, and provide a rich and relevant environment for user-centered evaluation of mHealth interventions. There is a potential for a much more agile research practice. Future research should consider the privacy impacts of increased access to participants' environment via webcams and screen share and how technology mediates participants' action in terms of privacy. The development of support procedures and tools for remote testing of mHealth apps with user participants will be crucial to capitalize on efficiency gains and better protect participants' privacy.

Digital Phenotyping of Geriatric Depression Using a Community-Based Digital Mental Health Monitoring Platform for Socially Vulnerable Older Adults and Their Community Caregivers: 6-Week Living Lab Single-Arm Pilot Study.

BACKGROUND: Despite the increasing need for digital services to support geriatric mental health, the development and implementation of digital mental health care systems for older adults have been hindered by a lack of studies involving socially vulnerable older adult users and their caregivers in natural living environments. OBJECTIVE: This study aims to determine whether digital sensing data on heart rate variability, sleep quality, and physical activity can predict same-day or next-day depressive symptoms among socially vulnerable older adults in their everyday living environments. In addition, this study tested the feasibility of a digital mental health monitoring platform designed to inform older adult users and their community caregivers about day-to-day changes in the health status of older adults. METHODS: A single-arm, nonrandomized living lab pilot study was conducted with socially vulnerable older adults (n=25), their community caregivers (n=16), and a managerial social worker over a 6-week period during and after the COVID-19 pandemic. Depressive symptoms were assessed daily using the 9-item Patient Health Questionnaire via scripted verbal conversations with a mobile chatbot. Digital biomarkers for depression, including heart rate variability, sleep, and physical activity, were measured using a wearable sensor (Fitbit Sense) that was worn continuously, except during charging times. Daily individualized feedback, using traffic signal signs, on the health status of older adult users regarding stress, sleep, physical activity, and health emergency status was displayed on a mobile app for the users and on a web application for their community caregivers. Multilevel modeling was used to examine whether the digital biomarkers predicted same-day or next-day depressive symptoms. Study staff conducted pre- and postsurveys in person at the homes of older adult users to monitor changes in depressive symptoms, sleep quality, and system usability. RESULTS: Among the 31 older adult participants, 25 provided data for the living lab and 24 provided data for the pre-post test analysis. The multilevel modeling results showed that increases in daily sleep fragmentation (P=.003) and sleep efficiency (P=.001) compared with one's average were associated with an increased risk of daily depressive symptoms in older adults. The pre-post test results indicated improvements in depressive symptoms (P=.048) and sleep quality (P=.02), but not in the system usability (P=.18). CONCLUSIONS: The findings suggest that wearable sensors assessing sleep quality may be utilized to predict daily fluctuations in depressive symptoms among socially vulnerable older adults. The results also imply that receiving individualized health feedback and sharing it with community caregivers may help improve the mental health of older adults. However, additional in-person training may be necessary to enhance usability. TRIAL REGISTRATION: ClinicalTrials.gov NCT06270121; https://clinicaltrials.gov/study/NCT06270121.

[Translation into French and republication of: "Management of cancer-associated thromboembolism in vulnerable population"]. / Traduction et republication de : « Prise en charge de la maladie thromboembolique veineuse associée au cancer chez les populations vulnérables ¼.

Although all patients with cancer-associated thrombosis (CAT) have a high morbidity and mortality risk, certain groups of patients are particularly vulnerable. This may expose the patient to an increased risk of thrombotic recurrence or bleeding (or both), as the benefit-risk ratio of anticoagulant treatment may be modified. Treatment thus needs to be chosen with care. Such vulnerable groups include older patients, patients with renal impairment or thrombocytopenia, and underweight and obese patients. However, these patient groups are poorly represented in clinical trials, limiting the available data on which treatment decisions can be based. Meta-analysis of data from randomised clinical trials suggests that the relative treatment effect of direct oral factor Xa inhibitors (DXIs) and low molecular weight heparin (LMWH) with respect to major bleeding could be affected by advanced age. No evidence was obtained for a change in the relative risk-benefit profile of DXIs compared to LMWH in patients with renal impairment or of low body weight. The available, albeit limited, data do not support restricting the use of DXIs in patients with TAC on the basis of renal impairment or low body weight. In older patients, age is not itself a critical factor for choice of treatment, but frailty is such a factor. Patients over 70 years of age with CAT should undergo a systematic frailty evaluation before choosing treatment and modifiable bleeding risk factors should be addressed. In patients with renal impairment, creatine clearance should be assessed and monitored regularly thereafter. In patients with an eGFR less than 30mL/min/1.72m2, the anticoagulant treatment may need to be adapted. Similarly, platelet count should be assessed prior to treatment and monitored regularly. In patients with grade 3-4, thrombocytopenia (less than 50,000platelets/µL) treatment with a LMWH at a reduced dose should be considered. For patients with CAT and low body weight, standard anticoagulant treatment recommendations are appropriate, whereas in obese patients, apixaban may be preferred.

Validation of the Disaster Adaptation and Resilience Scale for Vulnerable Communities in Vietnam's Coastal Regions.

OBJECTIVES: This study validated the Vietnamese version of the Disaster Adaptation and Resilience Scale (DARS) for use in vulnerable communities in Vietnam. METHODS: This was a cross-sectional study involving 595 adults from 2 identified communities. The original DARS assessment tool was translated, and the validity and reliability of the Vietnamese version of DARS (V-DARS) were assessed. The internal consistency of the overall scale and its subscales was evaluated using Cronbach's alpha and McDonald's omega reliability coefficients. Confirmatory factor analysis (CFA) was employed to evaluate its construct validity, building upon the factor structure identified in exploratory factor analysis (EFA). Construct validity was assessed based on convergent and discriminant validity. RESULTS: Following the established criteria for EFA, 8 items were removed, resulting in a refined V-DARS structure comprising 35 items distributed across 5 distinct factors. Both alpha and omega reliability coefficients indicated strong internal consistency for the overall scale (α=0.963, ω=0.963) and for each of the 5 sub-scales (all>0.80). The CFA model also retained the 5-factor structure with 35 items. The model fit indices showed acceptable values (RMSEA: 0.072; CFI: 0.912; TLI: 0.904; chi-square test: <0.01). Additionally, the convergent and discriminant validity of the V-DARS were deemed appropriate and satisfactory for explaining the measurement structure. CONCLUSIONS: Our findings suggest that the V-DARS is a valid and reliable scale for use within vulnerable communities in Vietnam to assess adaptive responses to natural disasters. It may also be considered for use in other populations.

Why location matters: associations between county-level characteristics and availability of National Cancer Oncology Research Program and National Cancer Institute sites.

BACKGROUND: The majority of patients with cancer seek care at community oncology sites; however, most clinical trials are available at National Cancer Institute (NCI)-designated sites. Although the NCI National Cancer Oncology Research Program (NCORP) was designed to address this problem, little is known about the county-level characteristics of NCORP site locations. METHODS: This cross-sectional analysis determined the association between availability of NCORP or NCI sites and county-level characteristic theme percentile scores from the Center for Disease Control and Prevention's Social Vulnerability Index themes. Health Resources and Services Administration's Area Health Resource Files were used to determine contiguous counties. We estimated risk ratios and 95% confidence intervals (CIs) using modified Poisson regression models to evaluate the association between county-level characteristics and site availability within singular and singular and contiguous counties. RESULTS: Of 3141 included counties, 14% had an NCORP, 2% had an NCI, and 1% had both sites. Among singular counties, for a standard deviation increase in the racial and ethnic theme score, there was a 22% higher likelihood of NCORP site availability (95% CI = 1.10 to 1.36); for a standard deviation increase in the socioeconomic status theme score, there was a 24% lower likelihood of NCORP site availability (95% CI = 0.67 to 0.87). Associations were of smaller magnitude when including contiguous counties. NCI sites were located in more vulnerable counties. CONCLUSIONS: NCORP sites were more often in racially diverse counties and less often in socioeconomically vulnerable counties. Research is needed to understand how clinical trial representation will increase if NCORP sites strategically increase their locations in more vulnerable counties.

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.

Utilizing social determinants of health to identify most vulnerable neighborhoods-Latent class analysis and GIS map.

OBJECTIVES: Public Health officials are often challenged to effectively allocate limited resources. Social determinants of health (SDOH) may cluster in areas to cause unique profiles related to various adverse life events. The authors use the framework of unintended teen pregnancies to illustrate how to identify the most vulnerable neighborhoods. METHODS: This study used data from the U.S. American Community Survey, Princeton Eviction Lab, and Connecticut Office of Vital Records. Census tracts are small statistical subdivisions of a county. Latent class analysis (LCA) was employed to separate the 832 Connecticut census tracts into four distinct latent classes based on SDOH, and GIS mapping was utilized to visualize the distribution of the most vulnerable neighborhoods. GEE Poisson regression model was used to assess whether latent classes were related to the outcome. Data were analyzed in May 2021. RESULTS: LCA's results showed that class 1 (non-minority non-disadvantaged tracts) had the least diversity and lowest poverty of the four classes. Compared to class 1, class 2 (minority non-disadvantaged tracts) had more households with no health insurance and with single parents; and class 3 (non-minority disadvantaged tracts) had more households with no vehicle available, that had moved from another place in the past year, were low income, and living in renter-occupied housing. Class 4 (minority disadvantaged tracts) had the lowest socioeconomic characteristics. CONCLUSIONS: LCA can identify unique profiles for neighborhoods vulnerable to adverse events, setting up the potential for differential intervention strategies for communities with varying risk profiles. Our approach may be generalizable to other areas or other programs. KEY MESSAGES: What is already known on this topic Public health practitioners struggle to develop interventions that are universally effective. The teen birth rates vary tremendously by race and ethnicity. Unplanned teen pregnancy rates are related to multiple social determinants and behaviors. Latent class analysis has been applied successfully to address public health problems. What this study adds While it is the pregnancy that is not planned rather than the birth, access to pregnancy intention data is not available resulting in a dependency on teen birth data for developing public health strategies. Using teen birth rates to identify at-risk neighborhoods will not directly represent the teens at risk for pregnancy but rather those who delivered a live birth. Since teen birth rates often fluctuate due to small numbers, especially for small neighborhoods, LCA may avoid some of the limitations associated with direct rate comparisons. The authors illustrate how practitioners can use publicly available SDOH from the Census Bureau to identify distinct SDOH profiles for teen births at the census tract level. How this study might affect research, practice or policy These profiles of classes that are at heightened risk potentially can be used to tailor intervention plans for reducing unintended teen pregnancy. The approach may be adapted to other programs and other states to prioritize the allocation of limited resources.

Residential mobility and persistently depressed voting among disadvantaged adults in a large housing experiment.

This study examines the impact of residential mobility on electoral participation among the poor by matching data from Moving to Opportunity, a US-based multicity housing-mobility experiment, with nationwide individual voter data. Nearly all participants in the experiment were Black and Hispanic families who originally lived in high-poverty public housing developments. Notably, the study finds that receiving a housing voucher to move to a low-poverty neighborhood decreased adult participants' voter participation for nearly two decades-a negative impact equal to or outpacing that of the most effective get-out-the-vote campaigns in absolute magnitude. This finding has important implications for understanding residential mobility as a long-run depressant of voter turnout among extremely low-income adults.

Mental and social wellbeing trajectory during the pandemic for vulnerable populations.

Objectives: We investigated changes over time in mental and social wellbeing indicators for vulnerable population subgroups during the pandemic. These groups were younger people, people with disabilities, low-income groups, unemployed, culturally, and linguistically diverse communities (CaLD), and Aboriginal and Torres Strait Islander peoples. Methods: A series of four repeated population representative surveys were conducted in June 2020, September 2020, January 2022, and June 2022. Questions included items on psychological distress, financial hardship, social connection, and life satisfaction. Results: For most groups, social connection and life satisfaction improved in 2022 relative to 2020. Psychological distress and financial hardship showed the opposite pattern, with some groups having worse results in 2022 relative to 2020. People without any vulnerability had better mental health and social wellbeing outcomes at each time point relative to the vulnerable population subgroups. Conclusion: Pandemic-related policies had differential effects over time and for different population groups. Future policies and research need to closely monitor how they impact population subgroups, and the overall results clearly demonstrate the inequity in mental health and social wellbeing outcomes for vulnerable population cohorts.

Area Vulnerability and Disparities in Therapy for Patients With Metastatic Renal Cell Carcinoma.

Importance: Area-level measures of sociodemographic disadvantage may be associated with racial and ethnic disparities with respect to receipt of treatment for metastatic renal cell carcinoma (mRCC) but have not been investigated previously, to our knowledge. Objective: To assess the association between area-level measures of social vulnerability and racial and ethnic disparities in the treatment of US Medicare beneficiaries with mRCC from 2015 through 2019. Design, Setting, and Participants: This retrospective cohort study included Medicare beneficiaries older than 65 years who were diagnosed with mRCC from January 2015 through December 2019 and were enrolled in fee-for-service Medicare Parts A, B, and D from 1 year before through 1 year after presumed diagnosis or until death. Data were analyzed from November 22, 2022, through January 26, 2024. Exposures: Five different county-level measures of disadvantage and 4 zip code-level measures of vulnerability or deprivation and segregation were used to dichotomize whether an individual resided in the most vulnerable quartile according to each metric. Patient-level factors included age, race and ethnicity, sex, diagnosis year, comorbidities, frailty, Medicare and Medicaid dual enrollment eligibility, and Medicare Part D low-income subsidy (LIS). Main Outcomes and Measures: The main outcomes were receipt and type of systemic therapy (oral anticancer agent or immunotherapy from 2 months before to 1 year after diagnosis of mRCC) as a function of patient and area-level characteristics. Multivariable regression analyses were used to adjust for patient factors, and odds ratios (ORs) from logistic regression and relative risk ratios (RRRs) from multinomial logistic regression are reported. Results: The sample included 15 407 patients (mean [SD] age, 75.6 [6.8] years), of whom 9360 (60.8%) were men; 6931 (45.0%), older than 75 years; 93 (0.6%), American Indian or Alaska Native; 257 (1.7%), Asian or Pacific Islander; 757 (4.9%), Hispanic; 1017 (6.6%), non-Hispanic Black; 12 966 (84.2%), non-Hispanic White; 121 (0.8%), other; and 196 (1.3%), unknown. Overall, 8317 patients (54.0%) received some type of systemic therapy. After adjusting for individual factors, no county or zip code-level measures of social vulnerability, deprivation, or segregation were associated with disparities in treatment. In contrast, patient-level factors, including female sex (OR, 0.78; 95% CI, 0.73-0.84) and LIS (OR, 0.48; 95% CI, 0.36-0.65), were associated with lack of treatment, with particularly limited access to immunotherapy for patients with LIS (RRR, 0.25; 95% CI, 0.14-0.43). Associations between individual-level factors and treatment in multivariable analysis were not mediated by the addition of area-level metrics. Disparities by race and ethnicity were consistently and only observed within the most vulnerable areas, as indicated by the top quartile of each vulnerability deprivation index. Conclusions and Relevance: In this cohort study of older Medicare patients diagnosed with mRCC, individual-level demographics, including race and ethnicity, sex, and income, were associated with receipt of systemic therapy, whereas area-level measures were not. However, individual-level racial and ethnic disparities were largely limited to socially vulnerable areas, suggesting that efforts to improve racial and ethnic disparities may be most effective when targeted to socially vulnerable areas.

Higher consumption of ultra-processed foods is associated with obesity and abdominal obesity in socially vulnerable Brazilian women.

This study aimed to assess the consumption of ultra-processed foods (UPF) and identify their association with obesity and abdominal obesity in adult women of reproductive age living in situations of social vulnerability in Maceió, Northeastern Brazil. This was a cross-sectional study carried out between October 2020 and May 2021. An anthropometric evaluation was carried out to assess obesity and abdominal obesity. A dietary assessment was also conducted using a 24-h food recall to determine the calorie intake from UPF. To estimate intra-individual variability in food consumption, the probabilistic Multiple Source Method was used. These data in the form of tertiles were used to analyse the association between the consumption of UPF and obesity and abdominal obesity. Logistic regressions were used to analyse the association. A directed acyclic graph (DAG) was created for this analysis. This study included 1702 women of which 53.7% were 31 years old or older, and 74.2% lived in poverty. It identified that 36.5% and 38.1% of the women had obesity and abdominal obesity, respectively, and that an average of 33.8% of calories consumed came from UPF. In the analysis of association guided by the DAG, it was observed that women with a high-calorie intake from UPF had a 1.3 times higher probability of being obese. It was also observed that women with a moderate and high-calorie intake from UPF were 1.4 and 1.3 times more likely, respectively, to have abdominal obesity. Thus, it can be concluded that socially vulnerable women in Brazil have a relatively high consumption of UPF and that this condition increases the probability of obesity in this population group.

Who is most vulnerable? Factors associated with presenting to antenatal care without a male partner in Northern Tanzania.

OBJECTIVE: Male engagement in pregnancy care can be beneficial for maternal and child health outcomes. In Tanzania, pregnant women are strongly encouraged to present to their first antenatal care (ANC) appointment with a male partner, where they jointly test for HIV. For some, this presents a barrier to ANC attendance. The objectives of this study were to identify factors associated with presenting to ANC with a male partner using a cross-sectional design and to assess whether women presenting without partners had significantly delayed presentation. METHODS: Pregnant women (n = 1007) attending a first ANC appointment in Moshi, Tanzania were surveyed. Questions captured sociodemographic characteristics and measures of psychosocial constructs. RESULTS: Just over half (54%) of women presented to care with a male partner. Women were more likely to present with a male partner if they were younger than 25 years old, married, Muslim, attending ANC for their first pregnancy, and testing for HIV for the first time. Women presenting to ANC with a male partner were significantly more likely to attend ANC earlier in their pregnancy than those presenting without male partners. CONCLUSION: Policy change allowing women to present to care with other supportive family members could promote earlier presentation to first ANC. Unmarried women may be at a disadvantage in presenting to ANC when policies mandate attendance with a male partner. Male partners of multiparous women should be encouraged to provide pregnancy support even after first pregnancies, and a wholistic emphasis (beyond HIV testing) on first ANC could encourage male engagement beyond the initial appointment.

Dementia, dementia's risk factors and premorbid brain structure are concentrated in disadvantaged areas: National register and birth-cohort geographic analyses.

INTRODUCTION: Dementia risk may be elevated in socioeconomically disadvantaged neighborhoods. Reasons for this remain unclear, and this elevation has yet to be shown at a national population level. METHODS: We tested whether dementia was more prevalent in disadvantaged neighborhoods across the New Zealand population (N = 1.41 million analytic sample) over a 20-year observation. We then tested whether premorbid dementia risk factors and MRI-measured brain-structure antecedents were more prevalent among midlife residents of disadvantaged neighborhoods in a population-representative NZ-birth-cohort (N = 938 analytic sample). RESULTS: People residing in disadvantaged neighborhoods were at greater risk of dementia (HR per-quintile-disadvantage-increase = 1.09, 95% confidence interval [CI]:1.08-1.10) and, decades before clinical endpoints typically emerge, evidenced elevated dementia-risk scores (CAIDE, LIBRA, Lancet, ANU-ADRI, DunedinARB; ß's 0.31-0.39) and displayed dementia-associated brain structural deficits and cognitive difficulties/decline. DISCUSSION: Disadvantaged neighborhoods have more residents with dementia, and decades before dementia is diagnosed, residents have more dementia-risk factors and brain-structure antecedents. Whether or not neighborhoods causally influence risk, they may offer scalable opportunities for primary dementia prevention.

An Application of Social Vulnerability Index to Infant Mortality Rates in Ohio Using Geospatial Analysis- A Cross-Sectional Study.

BACKGROUND: Ohio ranks 43rd in the nation in infant mortality rates (IMR); with IMR among non-Hispanic black infants is three times higher than white infants. OBJECTIVE: To identify the social factors determining the vulnerability of Ohio counties to IMR and visualize the spatial association between relative social vulnerability and IMR at county and census tract levels. METHODS: The social vulnerability index (SVICDC) is a measure of the relative social vulnerability of a geographic unit. Five out of 15 social variables in the SVICDC were utilized to create a customized index for IMR (SVIIMR) in Ohio. The bivariate descriptive maps and spatial lag model were applied to visualize the quantitative relationship between SVIIMR and IMR, accounting for the spatial autocorrelation in the data. RESULTS: Southeastern counties in Ohio displayed highest IMRs and highest overall SVIIMR; specifically, highest vulnerability to poverty, no high school diploma, and mobile housing. In contrast, extreme northwestern counties exhibited high IMRs but lower overall SVIIMR. Spatial regression showed five clusters where vulnerability to low per capita income in one county significantly impacted IMR (p = 0.001) in the neighboring counties within each cluster. At the census tract-level within Lucas county, the Toledo city area (compared to the remaining county) had higher overlap between high IMR and SVIIMR. CONCLUSION: The application of SVI using geospatial techniques could identify priority areas, where social factors are increasing the vulnerability to infant mortality rates, for potential interventions that could reduce disparities through strategic and equitable policies.

Nucleocapsid and Spike Protein-Based Anti-SARS-CoV-2 Assay Performance in the Minority and Rural Coronavirus Insights Study: Characteristics of Socioeconomically Disadvantaged Populations with Health Disparities.

BACKGROUND: COVID-19 has had a devastating impact on Black, Hispanic, and other underserved, disadvantaged populations. Here anti-SARS-CoV-2 tests are characterized in disadvantaged patients to examine equivalence in US populations. METHODS: Underserved participant adults (age > 18 years) were enrolled before the availability of SARS-CoV-2 vaccines in Federal Qualified Health Centers in California, Florida, Louisiana, Illinois, and Ohio and contributed samples to the Minority and Rural Coronavirus Insights Study (MRCIS). A subset coined the MRCIS SARS-CoV-2 Antibody Cohort of 2365 participants was tested with the Roche Anti-SARS-CoV-2 assay (Cobas e601). Five hundred ninety-five of these were also tested with the Ortho Clinical Diagnostics VITROS Anti-SARS-CoV-2 IgG assay (VITROS-5600); 1770 were also tested with the Abbott ARCHITECT SARS-CoV-2 IgG assay (ARCHITECT-2000). Assay-specific cutoffs classified negative/positive results. RESULTS: Eight point four percent (199/2365) of the MRCIS SARS-CoV-2 Antibody Cohort was SARS-CoV-2 RNA positive at enrollment. Agreement between the Ortho/Roche and the Abbott/Roche antibody testing did not vary by enrollment RNA status. The Ortho (anti-spike protein) vs Roche (anti-nucleocapsid protein) comparison agreed substantially: kappa = 0.63 (95% CI: 0.57-0.69); overall agreement, 83%. However, agreement was even better for the Abbott vs Roche assays (both anti-nucleocapsid protein tests): kappa = 0.85 (95% CI: 0.81-0.87); overall agreement, 95%. Anti-SARS-CoV-2 comparisons stratified by demographic criteria demonstrated no significant variability in agreement by sex, race/ethnicity, or age. CONCLUSIONS: Analytical agreement is 96.4% for anti-spike-protein vs anti-nucleocapsid-protein comparisons. Physiologically, seroreversion of anti-nucleocapsid reactivity after infection occurred in the disadvantaged population similarly to general populations. No anti-SARS-CoV-2 assays included demonstrated a clinically significant difference due to the demographics of the disadvantaged MRCIS SARS-CoV-2 Antibody Cohort.

Low Levels of Lifetime Pap Test Receipt Among Vulnerable Guatemalans.

Low and middle-income countries, such as Guatemala, shoulder a disproportionate share of cervical cancer, a preventable disease in high income countries. Tangible obstacles, such as lack of access to health care, cultural differences, and insufficient infrastructure, and facilitators, such as being Ladino, married, and educated, have been identified in the literature related to cervical cancer prevention. The aim of this survey was to explore barriers and facilitators to cervical cancer prevention, comparing rural Indigenous and urban Ladino populations. We surveyed 139 women in two health clinics. Participants answered questions about demographic information, cervical cancer knowledge, and health care behaviors. We analyzed survey data with four bivariate models. Our results suggest vulnerable populations, such as rural Indigenous women who are single, illiterate, and lack education, face higher cervical cancer risk. Partnerships should be formed with health promotors and lay midwives to educate and encourage vulnerable populations to prevent cervical cancer.