Neighborhood Socioeconomic Status Research Articles

Cohort profile: the longitudinal National Growth and Health Study (NGHS) of black and white girls from Northern California tracking how behavioural and psychosocial risk factors predict cardiovascular risk and biological ageing in midlife and in offspring

PurposeThe National Heart, Lung and Blood Institute Growth and Health Study (NGHS) prospectively collected anthropometric, biospecimens, clinical, health behaviour and psychosocial measures associated with cardiovascular disease from childhood to young...

Time trends in associations between neighbourhood and school characteristics and mental health problems among Dutch adolescents

We investigated trends in associations between physical and social neighbourhood and school characteristics and adolescent mental health problems between 2005 and 2017. Nationally representative, repeated cross-sectional data collected in the Netherlands among primary (N = 5,871) and secondary school students (N = 20,778) were analysed through cross-classified multilevel models. Hardly any evidence was found for over-time changes in associations between neighbourhood and school characteristics and adolescent mental health problems. Findings showed that for both groups of students, only social characteristics within the two contexts were associated with adolescent mental health problems. For secondary school students, school effects were larger than neighbourhood effects, while the opposite was true for primary school students. Specifically, primary school students residing in more socially fragmented or lower socioeconomic status (SES) neighbourhoods, and lower SES schools, reported more conduct problems and peer relationship problems. For secondary school students, only the SES of the neighbourhood and the school was associated with all four aspects of mental health problems. Remarkably, the direction of the associations between neighbourhood/ school SES and adolescent mental health problems varied across the different mental health outcomes. More research is warranted to replicate our findings.

Association Between Socioeconomic Status and Adherence to Fecal Occult Blood Tests in Colorectal Cancer Screening Programs: Systematic Review and Meta-Analysis of Observational Studies.

Screening adherence is important in reducing colorectal cancer (CRC) incidence and mortality. Disparity in CRC screening adherence was observed in populations of different socioeconomic status (SES), but the direction and strength of the association remained unclear. We aimed to systematically review all the observational studies that have analyzed the association between SES and adherence to organized CRC screening based on fecal occult blood tests. We systematically reviewed the studies in PubMed, Embase, and Web of Science and reference lists of relevant reviews from the inception of the database up until June 7, 2023. Individual SES, neighborhood SES, and small-area SES were included, while any SES aggregated by geographic areas larger than neighbors were excluded. Studies assessing SES with any index or score combining indicators of income, education, deprivation, poverty, occupation, employment, marital status, cohabitation, and others were included. A random effect model meta-analysis was carried out for pooled odds ratios (ORs) and relative risks for adherence related to SES. Overall, 10 studies, with a total of 3,542,379 participants and an overall adherence rate of 64.9%, were included. Compared with low SES, high SES was associated with higher adherence (unadjusted OR 1.73, 95% CI 1.42-2.10; adjusted OR 1.53, 95% CI 1.28-1.82). In the subgroup of nonindividual-level SES, the adjusted association was significant (OR 1.57, 95% CI 1.26-1.95). However, the adjusted association was insignificant in the subgroup of individual-level SES (OR 1.46, 95% CI 0.98-2.17). As for subgroups of the year of print, not only was the unadjusted association significantly stronger in the subgroup of early studies (OR 1.97, 95% CI 1.59-2.44) than in the subgroup of late studies (OR 1.43, 95% CI 1.31-1.56), but also the adjusted one was significantly stronger in the early group (OR 1.86, 95% CI 1.43-2.42) than in the late group (OR 1.26, 95% CI 1.14-1.39), which was consistent and robust. Despite being statistically insignificant, the strength of the association seemed lower in studies that did not adjust for race and ethnicity (OR 1.31, 95% CI 1.21-1.43) than the overall estimate (OR 1.53, 95% CI 1.28-1.82). The higher-SES population had higher adherence to fecal occult blood test-based organized CRC screening. Neighborhood SES, or small-area SES, was more competent than individual SES to be used to assess the association between SES and adherence. The disparity in adherence between the high SES and the low SES narrowed along with the development of interventions and the improvement of organized programs. Race and ethnicity were probably important confounding factors for the association.

Exploring the Impact of Socioeconomic Status and Environmental Characteristics on Child and Adolescent Mental Health in Disadvantaged Urban Communities in West Java

This quantitative study investigates the complex interactions that exist between neighborhood features, children's and adolescents' mental health, and socioeconomic status (SES) in underprivileged urban neighborhoods in West Java. 340 individuals in a broad sample offered insights into neighborhood characteristics, SES indicators, demographic variances, and mental health outcomes. The results highlight the critical role that economic differences play by revealing a strong negative connection between SES and mental health. Furthermore, neighborhood features—in particular, social cohesiveness and safety perceptions—have been shown to have a significant impact on mental health outcomes. These neighborhood characteristics, according to mediation analyses, moderate the association between SES and mental health, providing detailed insights into the underlying mechanisms. The results help provide a more comprehensive picture of young people's mental health in urban environments, which helps shape targeted treatments and policies for vulnerable groups.

Associations of the neighbourhood built and natural environment with cardiometabolic health indicators: A cross-sectional analysis of environmental moderators and behavioural mediators

BackgroundMost studies examining the effects of neighbourhood urban design on cardiometabolic health focused solely on the built or natural environment. Also, they did not consider the roles of neighbourhood socio-economic status (SES) and ambient air pollution in the observed associations, and the extent to which these associations were mediated by physical activity and sedentary behaviours. MethodsWe used data from the AusDiab3 study (N = 4141), a national cohort study of Australian adults to address the above-mentioned knowledge gaps. Spatial data were used to compute indices of neighbourhood walkability (population density, intersection density, non-commercial land use mix, commercial land use), natural environment (parkland and blue spaces) and air pollution (annual average concentrations of nitrogen dioxide (NO2) and fine particulate matter <2.5 μm in diameter (PM2.5)). Census indices were used to define neighbourhood SES. Clinical assessments collected data on adiposity, blood pressure, blood glucose and blood lipids. Generalised additive mixed models were used to estimate associations. ResultsNeighbourhood walkability showed indirect beneficial associations with most indicators of cardiometabolic health via resistance training, walking and sitting for different purposes; indirect detrimental associations with the same indicators via vigorous gardening; and direct detrimental associations with blood pressure. The neighbourhood natural environment had beneficial indirect associations with most cardiometabolic health indicators via resistance training and leisure-time sitting, and beneficial direct associations with adiposity and blood lipids. Neighbourhood SES and air pollution moderated only a few associations of the neighbourhood environment with physical activity, blood lipids and blood pressure. ConclusionsWithin a low-density and low-pollution context, denser, walkable neighbourhoods with good access to nature may benefit residents’ cardiometabolic health by facilitating the adoption of an active lifestyle. Possible disadvantages of living in denser neighbourhoods for older populations are having limited opportunities for gardening, higher levels of noise and less healthy dietary patterns associated with eating out.

Neighborhood socioeconomic status and race are associated with incidence disparities in oral cavity cancers

ObjectivesTo determine the association between neighborhood socioeconomic status (nSES), race and incidence rate trends of oral cavity cancer (OCC). Materials and methodsWe used data from the SEER (Surveillance, Epidemiology, and End Results) 18 Census Tract-level SES and Rurality Database (2006–2018) database of the National Cancer Institute to create cohorts of OCC patients between 2006 and 2018. Annual incidence rates were calculated and trends in rates were estimated using joinpoints regression. ResultsThe incidence of OCC is the highest among low nSES White Americans (2.86 per 100 000 persons) and the lowest among high nSES Black Americans (1.17 per 100 000 persons). Incidence has significantly increased among Asian Americans (annual percent change [APC]: low nSES-2.4, high nSES-2.6) and White Americans (APC: low nSES-1.4, high nSES-1.6). Significant increases in the incidence of oral tongue cancer in these groups primarily drive this increase. Other increases were noted in alveolar ridge cancer among White Americans and hard palate cancer among Asian Americans. OCC incidence decreased significantly in Hispanic Americans of high nSES (APC: −2.5) and Black Americans of low nSES (APC: −2.7). Floor of mouth cancer incidence decreased among most groups. ConclusionDespite the overall decreasing incidence of OCC, these trends are inconsistent among all OCC subsites. Differences are seen by race, nSES, and subsite, indicating intersectional barriers that extend beyond nSES and race and ethnicity alone. Further research on risk factors and developing interventions targeting vulnerable groups is needed.

Associations between air pollution, residential greenness, and glycated hemoglobin (HbA1c) in three prospective cohorts of U.S. adults

BackgroundWhile studies suggest impacts of individual environmental exposures on type 2 diabetes (T2D) risk, mechanisms remain poorly characterized. Glycated hemoglobin (HbA1c) is a biomarker of glycemia and diagnostic criterion for prediabetes and T2D. We explored associations between multiple environmental exposures and HbA1c in non-diabetic adults. MethodsHbA1c was assessed once in 12,315 women and men in three U.S.-based prospective cohorts: the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study (HPFS). Residential greenness within 270 m and 1,230 m (normalized difference vegetation index, NDVI) was obtained from Landsat. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated from nationwide spatiotemporal models. Three-month and one-year averages prior to blood draw were assigned to participants’ addresses. We assessed associations between single exposure, multi-exposure, and component scores from Principal Components Analysis (PCA) and HbA1c. Fully-adjusted models built on basic models of age and year at blood draw, BMI, alcohol use, and neighborhood socioeconomic status (nSES) to include diet quality, race, family history, smoking status, postmenopausal hormone use, population density, and season. We assessed interactions between environmental exposures, and effect modification by population density, nSES, and sex. ResultsBased on HbA1c, 19% of participants had prediabetes. In single exposure fully-adjusted models, an IQR (0.14) higher 1-year 1,230 m NDVI was associated with a 0.27% (95% CI: 0.05%, 0.49%) lower HbA1c. In basic component score models, a SD increase in Component 1 (high loadings for 1-year NDVI) was associated with a 0.19% (95% CI: 0.04%, 0.34%) lower HbA1c. CI's crossed the null in multi-exposure and fully-adjusted component score models. There was little evidence of associations between air pollution and HbA1c, and no evidence of effect modification. ConclusionsAmong non-diabetic adults, environmental exposures were not consistently associated with HbA1c. More work is needed to elucidate biological pathways between the environment and prediabetes.

How far I’ll go: Social infrastructure accessibility and proximity in urban neighborhoods

Recent studies have shown that social infrastructure – community spaces, places of worship, social businesses, and parks – help build social ties, mitigate political polarization, and improve our health. This exploratory study examines why some areas in American cities see greater access to social infrastructure than others, applying geospatial models and city block analyses to the case of Boston. We hypothesize that neighborhoods of color and lower-income neighborhoods might see lower levels of access to social infrastructure, which have significant implications for the health and resilience of these neighborhoods. Using analyses of proximity on a large-N dataset of (1) all social infrastructure sites in Boston and (2) every building in Boston, we measure the distance between every building and social infrastructure site in the city, and model the associations of neighborhood demographics, socioeconomic status, and urban design factors on median distance from social infrastructure. Finally, we demonstrate findings using hyperlocal case studies of 3 iconic city blocks in Boston, examining Back Bay, Nubian Square, and Mount Bowdoin. We find evidence of strong race- and income-related gaps in access to social infrastructure, consistent even after extended controls for demographics and physical infrastructure traits, highlighting major inequities in social policy.

Understanding the role of environmental and socioeconomic factors in the geographic variation of breast cancer risk in the US-wide Sister Study

ObjectiveTo describe the geographic pattern of breast cancer incidence in a nationwide prospective cohort and investigate whether environmental exposures and/or neighborhood socioeconomic status explain observed geographic disparities. MethodsUsing accelerated failure time models with a spatial random effect term, we mapped the health region-level association between residential location and breast cancer incidence for 44,707 participants in the Sister Study after controlling for established individual-level breast cancer risk factors. We performed a variable selection process to select environmental exposures [i.e., ambient nitrogen dioxide (NO2) and fine particulate matter (PM2.5), PM2.5 chemical composition, outdoor light at night (LAN), ambient noise, ultraviolet radiation, and greenspace] and neighborhood-level factors [i.e., population density and area deprivation index (ADI)] that predicted breast cancer incidence and quantified the spatial variation explained by the selected factors. We also considered whether the geographic pattern and predictors were similar when restricting to estrogen receptor-positive (ER+) tumors. ResultsWe observed a spatial patterning in the incidence of overall breast cancer (Moran's I = 16.7, p < 0.05) and ER+ breast cancer (Moran's I = 13.2, p < 0.05), with a lower risk observed in the South and Southeast and a greater risk in the Northwest and certain areas of the Midwest and Northeast. NO2, LAN, and ADI explained 21.4% of the spatial variation in overall breast cancer incidence whereas NO2, PM2.5 chemical composition, LAN, greenspace, and ADI together explained 63.3% of the spatial variation in ER+ breast cancer incidence. ConclusionsOur findings provide additional evidence for a role of environmental exposures in breast cancer incidence and suggest that geographic-based risk factors may vary according to breast cancer subtype. Our findings support the need for additional research to quantify the relative contributions of geographic-based risk factors for breast cancer.

SAT127 What’s Cookin’: Attitudes Towards A Healthy, Budget-friendly Meal Planning Tool In Patients With Type 2 Diabetes

Abstract Disclosure: R. Abramczyk: None. S. Sadiq: None. C. Vaz: None. Background: Eating home-cooked meals has been associated with reduced risk of developing type 2 diabetes (T2DM). Additionally, nutrition counseling can aid weight loss and improve glucose levels. However, these interventions may be less effective in underserved patients as food prices can be a barrier to healthy food access. We performed a preliminary assessment of a quality improvement nutritional intervention at a university-based clinic in a medically underserved area. Aim: This analysis aimed to measure patients’ perceived levels of confidence in shopping for and preparing healthy, DM-friendly meals and interest in receiving a sample grocery list with matching recipes. Methods: Patients with T2DM seen in fellows’ clinic over 3 months were offered surveys that measured confidence levels in shopping for and preparing a healthy, DM-friendly diet. Participants were subsequently offered an ADA-compliant, Supplemental Nutritional Assistance Program-friendly sample grocery list and weekly meal plan. Results: 50 patients completed surveys. 70% were &amp;gt;50 years and 70% identified as African American. 98% shop for food at a supermarket, with 12% also utilizing smaller grocery and corner stores. 8% were not confident in shopping for healthy, DM-friendly foods. 30% were somewhat confident, 46% were confident, and 16% were extremely confident in shopping for DM-friendly foods. 82% of participants either did their own meal prep at home or had someone else at home who cooked. 16% were not confident in cooking DM-friendly foods, whereas 26% were somewhat confident, 50% were confident, and 8% were extremely confident. 92% were interested in receiving a 1-week shopping list for healthy groceries with corresponding recipes. Conclusion: While many patients in a low socioeconomic status neighborhood reported feeling confident shopping for healthy, DM-friendly foods, fewer felt confident in preparing and cooking these foods. Most patients were interested in a budget friendly shopping list and meal planning tool to assist in both shopping for and cooking foods that will assist in achieving improved DM control. A follow up phase study will evaluate the rate of utilization and other patient behavioral factors in response to this intervention. Further research is needed to develop and evaluate the impact that tools such as this may have on changes in behavior towards shopping for and cooking healthy, DM-friendly foods at home and its effects on glycemic control. Presentation: Saturday, June 17, 2023

Change in Neighborhood Socioeconomic Status and Adherence to the Cancer Prevention Lifestyle Guidelines in Hispanic/Latino Adults: Results from the HCHS/SOL Study.

This study provides new evidence on the link between neighborhood gentrification, changing income inequality and adoption and maintenance of cancer preventive behaviors in an understudied population in cancer research. We observed that while neighborhood deprivation may deter from healthy lifestyle behaviors, positive changes in neighborhood SES via the process of gentrification, may not influence lifestyle guideline adherence among Hispanic/Latino adults.

Stress, depression, and risk of dementia – a cohort study in the total population between 18 and 65 years old in Region Stockholm

BackgroundChronic stress and depression are potential risk factors for mild cognitive impairment and dementia, including Alzheimer disease. The aim was to investigate whether any such risk is additive.MethodsCohort study including 1 362 548 people (665 997 women, 696 551 men) with records in the Region Stockholm administrative healthcare database (VAL).Exposure was a recorded ICD-10 diagnosis of chronic stress, depression, or both, recorded in 2012 or 2013. Outcome was a diagnosis of Alzheimer disease, other dementia, or mild cognitive impairment recorded from 2014 through 2022. Odds ratios with 99% confidence intervals (CI) adjusted for age, sex, neighborhood socioeconomic status, diabetes, and cardiovascular disorders were calculated.ResultsDuring the exposure period, 4 346 patients were diagnosed with chronic stress, 40 101 with depression, and 1 898 with both. The average age at baseline was around 40 years in all groups. In the fully adjusted model, the odds ratio of Alzheimer disease was 2.45 (99% CI 1.22–4.91) in patients with chronic stress, 2.32 (99% CI 1.85–2.90) in patients with depression, and 4.00 (99% CI 1.67–9.58) in patients with chronic stress and depression. The odds ratio of mild cognitive impairment was 1.87 (99% CI 1.20–2.91) in patients with chronic stress, 2.85 (99% CI 2.53–3.22) in patients with depression, and 3.87 (99% CI 2.39–6.27) in patients with both. When other dementia was analyzed, the odds ratio was significant only in patients with depression, 2.39 (99% CI 1.92–2.96).ConclusionsDocumented chronic stress increased the risk of mild cognitive impairment and Alzheimer disease. The same was seen with depression. The novel finding is the potential additive effect of chronic stress to depression, on risk of MCI and AD.

Survival outcomes for lung neuroendocrine tumors in California differ by sociodemographic factors.

Lung neuroendocrine tumors (NETs) have few known predictors of survival. We investigated associations of sociodemographic, clinicopathologic, and treatment factors with overall survival (OS) and lung cancer-specific survival (LCSS) for incident lung NET cases (typical or atypical histology) in the California Cancer Registry (CCR) from 1992 to 2019. OS was estimated with the Kaplan-Meier method and compared by sociodemographic and disease factors univariately with the log-rank test. We used sequential Cox proportional hazards regression for multivariable OS analysis. LCSS was estimated using Fine-Gray competing risks regression. There were 6038 lung NET diagnoses (5569 typical, 469 atypical carcinoid); most were women (70%) and non-Hispanic White (73%). In our multivariable model, sociodemographic factors were independently associated with OS, with better survival for women (hazard ratio (HR) 0.62, 95% confidence interval (CI) 0.57-0.68, P < 0.001), married (HR 0.76, 95% CI 0.70-0.84, P < 0.001), and residents of high socioeconomic status (SES) neighborhoods (HRQ5vsQ1 0.73, 95% CI 0.62-0.85, P < 0.001). Compared to cases with private insurance, OS was worse for cases with Medicare (HR 1.24, 95% CI 1.10-1.40, P < 0.001) or Medicaid/other public insurance (HR 1.45, 95% CI 1.24-1.68, P < 0.001). In our univariate model, non-Hispanic Black Californians had worse OS than other racial/ethnic groups, but differences attenuated after adjusting for stage at diagnosis. In our LCSS models, we found similar associations between sex and marital status on survival, but no differences in outcomes by SES or insurance. By race/ethnicity, American Indian cases had worse LCSS. In summary, beyond disease-related and treatment variables, sociodemographic factors were independently associated with survival in lung NETs.

Association of Childbirth With Medical Debt.

We evaluated the association between childbirth and having medical debt in collections and examined differences by neighborhood socioeconomic status. Among a statewide cohort of commercially insured pregnant (n=14,560) and postpartum (n=12,157) adults, having medical debt in collections was more likely among postpartum individuals compared with pregnant individuals (adjusted odds ratio [aOR] 1.36, 95% CI 1.27-1.46) and those in lowest-income neighborhoods compared with all others (aOR 2.18, 95% CI 2.02-2.35). Postpartum individuals in lowest-income neighborhoods had the highest predicted probabilities of having medical debt in collections (28.9%, 95% CI 27.5-30.3%), followed by pregnant individuals in lowest-income neighborhoods (23.2%, 95% CI 22.0-24.4%), followed by all other postpartum and pregnant people (16.1%, 95% CI 15.4-16.8% and 12.5%, 95% CI 11.9-13.0%, respectively). Our findings suggest that current peripartum out-of-pocket costs are objectively more than many commercially insured families can afford, leading to medical debt. Policies to reduce maternal-infant health care spending among commercially insured individuals may mitigate financial hardship and improve birth equity.

Strangers in a strange land: Mapping household and neighbourhood associations with improved wellbeing outcomes in Accra, Ghana

Urban poverty is not limited to informal settlements, rather it extends throughout cities, with the poor and affluent often living in close proximity. Using a novel dataset derived from the full Ghanaian Census, we investigate how neighbourhood versus household socio-economic status (SES) relates to a set of household development outcomes (related to housing quality, energy, water and sanitation, and information technology) in Accra, Ghana. We then assess “stranger” households' outcomes within neighbourhoods: do poor households fare better in affluent neighbourhoods, and are affluent households negatively impacted by being in poor neighbourhoods? Through a simple generalized linear model we estimate the variance components associated with household and neighbourhood status for our outcome measures. Household SES is more closely associated with 13 of the 16 outcomes assessed compared to the neighbourhood average SES. For 9 outcomes poor households in affluent areas fair better, and the affluent in poor areas are worse off. For two outcomes, poor households have worse outcomes in affluent areas, and the affluent have better outcomes in poor areas, on average. For three outcomes “stranger” households do worse in strange neighbourhoods. We discuss implications for mixed development and how to direct resources through households versus location-based targets.

Neighborhood Deprivation and Neural Tube Defects.

Individual measures of socioeconomic status (SES) have been associated with an increased risk of neural tube defects (NTDs); however, the association between neighborhood SES and NTD risk is unknown. Using data from the National Birth Defects Prevention Study (NBDPS) from 1997 to 2011, we investigated the association between measures of census tract SES and NTD risk. The study population included 10,028 controls and 1829 NTD cases. We linked maternal addresses to census tract SES measures and used these measures to calculate the neighborhood deprivation index. We used generalized estimating equations to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) estimating the impact of quartiles of census tract deprivation on NTDs adjusting for maternal race-ethnicity, maternal education, and maternal age at delivery. Quartiles of higher neighborhood deprivation were associated with NTDs when compared with the least deprived quartile (Q2: aOR = 1.2; 95% CI = 1.0, 1.4; Q3: aOR = 1.3, 95% CI = 1.1, 1.5; Q4 (highest): aOR = 1.2; 95% CI = 1.0, 1.4). Results for spina bifida were similar; however, estimates for anencephaly and encephalocele were attenuated. Associations differed by maternal race-ethnicity. Our findings suggest that residing in a census tract with more socioeconomic deprivation is associated with an increased risk for NTDs, specifically spina bifida.

Implementation of an integrated community approach in deprived neighbourhoods: a theory-based process evaluation using the Consolidated Framework for Implementation Research (CFIR).

We investigated the implementation process of an Integrated Community Approach (ICA) applied in four low socio-economic status neighbourhoods in Maastricht, the Netherlands. The ICA is a Population Health Management initiative and aims to improve population health, quality of care, professional's satisfaction and decrease costs of care. This study addresses the facilitators and barriers for implementing the ICA from a stakeholder perspective, including steering group members, professionals and citizens. We conducted a mixed-methods study using a triangulation of methods to investigate the implementation from 1 December 2016 to 31 December 2020. The Consolidated Framework for Implementation Research guided data collection and data-analysis for evaluating the implementation process. In total, 77 interviews, 97 observations, seven focus groups, 65 collected documents and two surveys with open-ended questions were conducted. Facilitators for implementation were the use of citizen science to bring residents' needs into sharp focus, the integration of the ideology of Positive Health into the working routines of the professionals and leadership at the steering group level to overcome barriers in the ICA. The existing accounting and financial infrastructure obstructed combining budgets at neighbourhood level. Engaging citizens and professionals at an early stage is an important facilitator for implementation. The use of a shared vision on health also worked as a facilitator since it created a shared language among professionals, which is important in Population Health Management initiatives where multiple professionals are expected to collaborate. NTR 6543; registration date, 25 July 2017.

Neighbourhood and household level socio-economic status and its association with air pollution exposure in Indian cities

Neighbourhood and household level socio-economic status and its association with air pollution exposure in Indian cities

Mapping wild vascular plant species diversity in urban areas in California using crowdsourcing data by regression kriging: Examining socioeconomic disparities

Biodiversity is crucial for human health, but previous methods of measuring biodiversity require intensive resources and have other limitations. Crowdsourced datasets from citizen scientists offer a cost-effective solution for characterizing biodiversity on a large spatial scale. This study has two aims: 1) to generate fine-resolution plant species diversity maps in California urban areas using crowdsourced data and extrapolation methods; and 2) to examine their associations with sociodemographic factors and identify subpopulations with low biodiversity exposure. We used iNaturalist observations from 2019 to 2022 to calculate species diversity metrics by exploring the sampling completeness in a 5 × 5-km2 grid and then computing species diversity metrics for grid cells with at least 80 % sample completeness (841 out of 4755 grid cells). A generalized additive model with ordinary kriging (GAM OK) provided moderately reliable estimates, with correlations of 0.64–0.66 between observed and extrapolated metrics, relative mean absolute errors of 21 %–23 %, and relative root mean squared errors of 27 %–30 % for grid cells with ≥80 % sample completeness from 10-fold cross-validation. GAM OK was further applied to extrapolate species diversity metrics from saturated grid cells (N = 841) to the remaining grid cells with <80 % sample completeness (N = 3914) and generate diversity maps that cover the grid. Further, generalized linear mixed models were used to examine the associations between species diversity and sociodemographic indicators at census tract level. The wild vascular plant species diversity metrics were inversely associated with neighborhood socioeconomic status (i.e., unemployment, linguistic isolation, educational attainment, and poverty rate). Minority populations (i.e., African American, Asian American, and Hispanic) and children had significantly lower diversity exposure in their neighborhoods. Crowdsourcing data offers a cost-effective solution for characterizing large-scale biodiversity in urban areas.

Visit and Between-Visit Interaction Frequency Before and After COVID-19 Telehealth Implementation

Telehealth implementation associated with the COVID-19 public health emergency (PHE) affected patient-clinical team interactions in numerous ways. Yet, studies have narrowly examined billed patient-clinician visits rather than including visits with other team members (eg, pharmacists) or between-visit interactions. To evaluate rates of change over time in visits (in-person, telehealth) and between-visit interactions (telephone calls, patient portal messages) overall and by key patient characteristics. This retrospective cohort study included adults with diabetes receiving primary care at urban academic (University of California San Francisco [UCSF]) and safety-net (San Francisco Health Network [SFHN]) health care systems. Encounters from April 2019 to March 2021 were analyzed. Telehealth implementation over 3 periods: pre-PHE (April 2019 to March 2020), strict shelter-in-place (April to June 2020), and hybrid-PHE (July 2020 to March 2021). The main outcomes were rates of change in monthly mean number of total encounters, visits with any health care team member, visits with billing clinicians, and between-visit interactions. Key patient-level characteristics were age, race and ethnicity, language, and neighborhood socioeconomic status (nSES). Of 15 148 patients (4976 UCSF; 8975 SFHN) included, 2464 (16%) were 75 years or older, 7734 (51%) were female patients, 9823 (65%) self-identified as racially or ethnically minoritized, 6223 (41%) had a non-English language preference, and 4618 (31%) lived in the lowest nSES quintile. After accounting for changes to care delivery through an interrupted time-series analysis, total encounters increased in the hybrid-PHE period (UCSF: 2.3% per patient/mo; 95% CI, 1.6%-2.9% per patient/mo; SFHN: 1.8% per patient/mo, 95% CI, 1.3%-2.2% per patient/mo), associated primarily with growth in between-visit interactions (UCSF: 3.1% per patient/mo, 95% CI, 2.3%-3.8% per patient/mo; SFHN: 2.9% per patient/mo, 95% CI, 2.3%-3.4% per patient/mo). In contrast, rates of visits were stable during the hybrid-PHE period. Although there were fewer differences in visit use by key patient-level characteristics during the hybrid-PHE period, pre-PHE differences in between-visit interactions persisted during the hybrid-PHE period at SFHN. Asian and Chinese-speaking patients at SFHN had fewer monthly mean between-visit interactions compared with White patients (0.46 [95% CI, 0.42-0.50] vs 0.59 [95% CI, 0.53-0.66] between-visit interactions/patient/mo; P < .001) and English-speaking patients (0.52 [95% CI, 0.47-0.58] vs 0.61 [95% CI, 0.56-0.66] between-visit interactions/patient/mo; P = .03). In this study, pre-PHE growth in overall patient-clinician encounters persisted after PHE-related telehealth implementation, driven in both periods by between-visit interactions. Differential utilization based on patient characteristics was observed, which may indicate disparities. The implications for health care team workload and patient outcomes are unknown, particularly regarding between-visit interactions. Therefore, to comprehensively understand care utilization for patients with chronic diseases, research should expand beyond billed visits.