Journal of Urban Health-Bulletin of the New York Academy of Medicine最新文献

Latinos have high rates of type 2 diabetes mellitus (T2DM) yet are characterized as having health-promoting social networks. The impacts of COVID-19 on personal networks were complex, especially in urban areas with high proportion of immigrants such as the Bronx in NYC. Our objective was to test the extent to which network characteristics increase vulnerability or resiliency for glycemic control based on data gathered from Mexican-origin Bronx dwellers. We used two-wave panel study analyzing self-reported personal social networks (n=30_participants; 600_{network members}) and HbA1c levels via dried blood spots in 2019, before the COVID-19 pandemic, and in 2021, a time after initial lockdowns and when the pandemic was still ravaging the community of study. Regression models adjusted for individual-level variables including sociodemographic and health indicators (i.e., physical health including COVID-19 and mental health). We found that an increase in the proportion of network members with diabetes predicted an increase in participant's HbA1c levels from 2019 to 2021 (β=0.044, p < 0.05). Also, a greater proportion of network members consuming "an American diet" in 2019 predicted a decrease in participant's HbA1c levels (β=-0.028, p < 0.01), while a greater proportion of network members that encouraged participants' health in 2019 predicted an increase in participant's HbA1c levels (β=0.033, p < 0.05). Our study sheds light on specific social network characteristics relevant to individual diabetes outcomes, including potential longitudinal mechanistic effects that played out at the peak of the COVID-19 crisis.

The 'urban penalty' in health refers to the loss of a presumed survival advantage due to adverse consequences of urban life. This study investigated the levels and trends in neonatal, post-neonatal and under-5 mortality rate and key determinants of child survival using data from Tanzania Demographic and Health Surveys (TDHS) (2004/05, 2010 and 2015/16), AIDS Indicator Survey (AIS), Malaria Indicator survey (MIS) and health facility data in Tanzania mainland. We compared Dar es Salaam results with other urban and rural areas in Tanzania mainland, and between the poorest and richest wealth tertiles within Dar es Salaam. Under-5 mortality declined by 41% between TDHS 2004/05 and 2015/2016 from 132 to 78 deaths per 1000 live births, with a greater decline in rural areas compared to Dar es Salaam and other urban areas. Neonatal mortality rate was consistently higher in Dar es Salaam during the same period, with the widest gap (> 50%) between Dar es Salaam and rural areas in TDHS 2015/2016. Coverage of maternal, new-born and child health interventions as well as living conditions were generally better in Dar es Salaam than elsewhere. Within the city, neonatal mortality was 63 and 44 per 1000 live births in the poorest 33% and richest 33%, respectively. The poorest had higher rates of stunting, more overcrowding, inadequate sanitation and lower coverage of institutional deliveries and C-section rate, compared to richest tertile. Children in Dar es Salaam do not have improved survival chances compared to rural children, despite better living conditions and higher coverage of essential health interventions. This urban penalty is higher among children of the poorest households which could only partly be explained by the available indicators of coverage of services and living conditions. Further research is urgently needed to understand the reasons for the urban penalty, including quality of care, health behaviours and environmental conditions.

Identifying and classifying poor and rich groups in cities depends on several factors. Using data from available nationally representative surveys from 38 sub-Saharan African countries, we aimed to identify, through different poverty classifications, the best classification in urban and large city contexts. Additionally, we characterized the poor and rich groups in terms of living standards and schooling. We relied on absolute and relative measures in the identification process. For absolute ones, we selected people living below the poverty line, socioeconomic deprivation status and the UN-Habitat slum definition. We used different cut-off points for relative measures based on wealth distribution: 30%, 40%, 50%, and 60%. We analyzed all these measures according to the absence of electricity, improved drinking water and sanitation facilities, the proportion of children out-of-school, and any household member aged 10 or more with less than 6 years of education. We used the sample size, the gap between the poorest and richest groups, and the observed agreement between absolute and relative measures to identify the best measure. The best classification was based on 40% of the wealth since it has good discriminatory power between groups and median observed agreement higher than 60% in all selected cities. Using this measure, the median prevalence of absence of improved sanitation facilities was 82% among the poorer, and this indicator presented the highest inequalities. Educational indicators presented the lower prevalence and inequalities. Luanda, Ouagadougou, and N'Djaména were considered the worst performers, while Lagos, Douala, and Nairobi were the best performers. The higher the human development index, the lower the observed inequalities. When analyzing cities using nationally representative surveys, we recommend using the relative measure of 40% of wealth to characterize the poorest group. This classification presented large gaps in the selected outcomes and good agreement with absolute measures.

The US is facing a severe affordable rental housing crisis that contributes to multiple forms of housing insecurity including homelessness, crowded and poor quality housing conditions, unstable housing arrangements, and cost burdens. A considerable body of evidence finds that housing insecurity is an important determinant of health. However, the existing literature may fall short of conceptualizing and measuring the full impact of housing insecurity on population health and on racial health equity. In this paper, we seek to expand the conceptualization of housing as a determinant of population health equity by considering housing insecurity as a manifestation of structural racism that intersects with other manifestations and impacts of structural racism to affect, not only the health of housing insecure individuals, but also the health of the networks and communities in which these individuals live. First, we situate the current housing crisis within larger systems of structural racism. We extend prior work documenting the confluence of ways that racist policies and practices have created unequal burdens of housing insecurity to also discuss the ways that the meanings and impacts of housing insecurity may be shaped by racism. Next, we consider how the health impacts of this unequal burden of housing insecurity can extend beyond individual households to affect networks and communities. Ultimately, we provide a multilevel framework that can inform research, policy, and practice to address housing and health equity.

Transgender and gender-diverse communities are disproportionately incarcerated in the USA. Incarcerated gender minority populations are detained within carceral systems constructed around a cisgender (gender identity matches sex assigned at birth) binary (only male and female identities recognized) understanding of gender. This leads to marginalizing experiences while perpetuating the extreme vulnerability individuals experience in the community. In order to address this cruel and unusual experience, carceral systems should undergo "whole-setting" reforms to protect and affirm transgender and gender-diverse populations. This includes ensuring access to gender-affirming clinical care that aligns with community health standards recommended by medical professional associations. Implementing gender-affirming reforms reduces security issues and will likely improve health outcomes providing mutual benefit for both correctional staff and gender minority populations. Given the current divisive political and social environment for gender minority populations in the USA, evidence-based person-centered reforms in corrections are needed now more than ever.

Access to and utilization of consumer credit remains an understudied social determinant of health. We examined associations between a novel, small-area, multidimensional credit insecurity index (CII), and the prevalence of self-reported frequent mental distress across US cities in 2020. The census tract-level CII was developed by the Federal Reserve Bank of New York using Census population information and a nationally representative sample of anonymized Equifax credit report data. The CII was calculated for tracts in 766 cities displayed on the City Health Dashboard at the time of analysis, predominantly representing cities with over 50,000 residents. The CII combined data on tract-level participation in the formal credit economy with information on the percent of individuals without revolving credit, percent with high credit utilization, and percent with deep subprime credit scores. Tracts were classified as credit-assured, credit-likely, mid-tier, at-risk, or credit-insecure. We used linear regression to examine associations between the CII and a modeled tract-level measure of frequent mental distress, obtained from the CDC PLACES project. Regression models were adjusted for neighborhood economic and demographic characteristics. We examined effect modification by US region by including two-way interaction terms in regression models. In adjusted models, credit-insecure tracts had a modestly higher prevalence of frequent mental distress (prevalence difference = 0.38 percentage points; 95% CI = 0.32, 0.44), compared to credit-assured tracts. Associations were most pronounced in the Midwest. Local factors impacting credit access and utilization are often modifiable. The CII, a novel indicator of community financial well-being, may be an independent predictor of neighborhood health in US cities and could illuminate policy targets to improve access to desirable credit products and downstream health outcomes.

We sought to investigate temporal trends in telehealth availability among outpatient mental health treatment facilities and differences in the pace of telehealth growth by state urbanicity and rurality. We used the National Mental Health Services Survey (2015-2020) to identify outpatient mental health treatment facilities in the US (N = 28,989 facilities; 2015 n = 5,018; 2020 n = 4,889). We used logistic regression to model telehealth, predicted by time, state rurality (1 to 10% rural, 10 to < 20%, 20 to < 30%, or [Formula: see text] 30%), and their interaction, and adjusted for relevant covariates. We estimated the predicted probability of telehealth based on our model. We estimated effects with and without data from 2020 to assess whether the rapid and widespread adoption of telehealth during the COVID-19 pandemic changed the rural/urban trajectories of telehealth availability. We found that telehealth grew fastest in more urban states (year*rurality interaction p < 0.0001). Between 2015 and 2020, the predicted probability of telehealth in more urban states increased by 51 percentage points (from 9 to 61%), whereas telehealth in more rural states increased by 38 percentage points (from 23 to 61%). Predicted telehealth also varied widely by state, ranging from more than 75% of facilities (RI, OR) to below 20% (VT, KY). Health systems and new technological innovations must consider the unique challenges faced by urban populations and how best practices may be adapted to meet the growing urban demand. We framed our findings around the need for policies that minimize barriers to telehealth.

We used the 2021 Policing in America Survey to examine experiences with police and perceptions of policing in Cook County, IL, and Dallas County, TX. Substantial portions of residents believe that local police use force during at least half of arrests (Cook 45.8%, Dallas 52.2%) and report dissatisfaction with local policing efforts (Cook 49.0%, Dallas 48.5%). Black and Hispanic residents in both communities were more likely than white, non-Hispanic residents to have frequent use of force expectations and dissatisfaction with police. Several other indicators of experiences with and perceptions of police also varied by race and ethnicity. We combined individual-level survey data with neighborhood-level data from the American Community Survey in multilevel logistic regression models to examine differences between groups for primary outcomes. Some findings were consistent for both counties. Black residents (Cook aOR = 3.63; Dallas aOR = 5.07) and those who had witnessed police misconduct were more likely to have frequent use of force expectations (Cook aOR = 6.44; Dallas aOR = 14.91). Differences between Black, Hispanic, and white residents were not associated with dissatisfaction in the adjusted models. Negative experiences with police (Cook aOR = 10.73; Dallas aOR = 12.11), witnessing misconduct (Cook aOR = 3.87; Dallas aOR = 3.55), and feeling unsafe in one's neighborhood (Cook aOR = 4.56; Dallas aOR = 3.49) were independently associated with greater odds of dissatisfaction. Inequities in exposure to unsafe neighborhoods, witnessing misconduct, and negative interactions with police are key drivers of variation in expectations and perceptions of police. Optimizing transparency and assurances of procedural justice are needed to reduce fear and increase satisfaction with police in the USA.

This article uses ethnographic and qualitative research to explore the health implications and social responses of a low-income neighborhood in Southeast England, to more than a decade of austerity policies and declining institutional and welfare support. Findings examine how cuts to public services and welfare programs alongside changes to the area's social structure shape resident's perceptions of health risks and threats. Residents pointed to poor levels of mental health that were exacerbated by financial insecurity, the closure of community facilities and difficulties accessing support and professional help. An increase in social disorder and sense of danger within the vicinity were attributed to changes in the area's social composition and a reduction of policing in the neighborhood, which were an additional cause of anxiety for residents. Many people felt their neighborhood was treated inequitably with regard to law-and-order, health provision and other services designed to address health problems and risks and dangers in their social environment. This institutional vacuum generates unmet health needs facilitating informal practices and methods for managing health, such as through self-provision or using alternative, and more readily available, sources of medical advice and treatment. The demise of older forms of social control and surveillance that ran parallel with closure of the area's communal spaces had been partly compensated by social media usage, while informal methods of policing were a growing presence in the neighborhood in reaction to rising lawlessness and the ineffectiveness of police and local authorities.