Banking on the Neighborhood? Inequalities in Older Adults' Access to Local Banking and Neighborhood Perceptions

OBJECTIVES

Access to local banking represents an understudied dimension of neighborhood-based inequalities that could significantly influence older adults' perceptions of their neighborhood spaces in ways that matter for disparities in well-being. We evaluate disparities in banking access and then examine how local banking access informs older adults' perceptions of neighborhood collective efficacy and danger, above and beyond other neighborhood socioeconomic characteristics.

METHODS

We use nationally representative data from older adults in the United States who were interviewed at Round 3 of the National Social Life, Health, and Aging Project, linked with data on banks in respondents' residential and surrounding census tracts from the National Establishment Time-Series database, in a series of bivariate and multivariable regression analyses.

RESULTS

White older adults and those with higher levels of education have significantly greater local banking access than Black and Hispanic older adults and those with lower levels of education. Higher rates of local banking institutions are associated with significantly lower perceptions of neighborhood danger, but not with perceived collective efficacy. This finding emerges when accounting for neighborhood concentrated disadvantage and physical disorder.

DISCUSSION

Local banks may represent neighborhood investment and the broader economic vitality of a community, as well as the ability of communities to meet older adults' everyday needs in ways that enhance older residents' feelings of safety. Increasing access to local financial institutions may help attenuate neighborhood-based contributors to inequalities in health and well-being among the older adult population.

Measuring Mental Health Service Accessibility for Indigenous Populations: a Systematic Review

Indigenous populations have experienced inequality of accessing mental health services compared with their non-Indigenous counterparts, although the way of measuring mental health service accessibility for Indigenous populations is unclear. This systematic review examines measures of mental health service accessibility for Indigenous people, including the diversity of mental health services that are available to them and the barriers to accessing mental healthcare. Using a systematic search procedure, we identified 27 studies that explored Indigenous populations' mental health service access. Our review shows that 18 studies used interview-based methods to explore how Indigenous people use mental health services, and only nine studies used quantitative methods to measure the uptake of mental health services. While advanced methods for quantifying geographical access to healthcare services are widely available, these methods have not been applied in the current literature to explore the potential access to mental health services by Indigenous populations. This is partially due to limited understanding of how Indigenous populations seek mental healthcare, barriers that prevent Indigenous people from accessing diverse types of mental health services, and scarcity of data that are available to researchers. Future research could focus on developing methods to support spatially explicit measuring of accessibility to mental health services for Indigenous populations.

Bayesian spatiotemporal modelling for disease mapping: an application to preeclampsia and gestational diabetes in Florida, United States

Morbidities generally show patterns of concentration that vary by space and time. Disease mapping models are useful in estimating the spatiotemporal patterns of disease risks and are therefore pivotal for effective disease surveillance, resource allocation, and the development of prevention strategies. This study considers six spatiotemporal Bayesian hierarchical models based on two spatial conditional autoregressive priors. It could serve as a guideline on the development and application of Bayesian hierarchical models to assess the emerging risk trends, risk clustering, and spatial inequality trends, with estimation of covariables' effects on the interested disease risk. The method is applied to the Florida Birth Record data between 2006 and 2015 to study two cardiovascular risk factors: preeclampsia and gestational diabetes. High-risk clusters were detected in North Central Florida for preeclampsia and in Central Florida for gestational diabetes. While the adjusted disease trend was stable, spatial inequality peaked in 2011-2012 for both diseases. Exposure to PM2.5 at first or/and second trimester increased the risk of preeclampsia and gestational diabetes, but the magnitude is less severe compared to previous studies. In conclusion, this study underscores the significance of selecting appropriate disease mapping models in estimating the intricate spatiotemporal patterns of disease risk and suggests the importance of localized interventions to reduce health disparities. The result also identified an opportunity to study potential risk factors of preeclampsia, as the spike of risk in North Central Florida cannot be explained by current covariables.

The place of charity in a public health service: Inequality and persistence in charitable support for NHS trusts in england

The British National Health Service (NHS) relies for the great bulk of its funding on direct taxation, but the contribution of charitable sources of income to the NHS is not well-understood. The few studies of charitable giving to the NHS to date have concentrated on aggregate levels of income and expenditure. However, to date there has been limited collective understanding about the extent to which different kinds of NHS Trusts benefit from charitable funding and about the persistence of inequalities between trusts in their access to these resources. This paper presents novel analyses of the distribution of NHS Trusts in terms of the proportion of their income that comes from charitable sources. We build a unique linked longitudinal dataset which follows through time the population of NHS Trusts, and the population of associated NHS charities, in England since 2000. The analysis illustrates intermediate levels of charitable support for acute hospital trusts compared with the much lower levels of charitable support for ambulance, community and mental health Trusts and, conversely, much higher levels of charitable support for Trusts providing specialist care. These results represent rare quantitative evidence relevant to theoretical discussions about the uneven nature of the voluntary sector's response to healthcare need. They provide important evidence for a key feature (and arguably weakness) of voluntary initiative, namely philanthropic particularism - the tendency for charitable support to focus on a restricted range of causes. We also show that this 'philanthropic particularism' - reflected in the very sizeable differences in charitable income between different sectors of NHS trusts - is becoming more marked over time, while spatial disparities, notably between elite institutions in London and other locations, are also substantial. The paper reflects on the implications of these inequalities for policy and planning within a public health care system.

China's enhanced urban wastewater treatment increases greenhouse gas emissions and regional inequality

Sustainable water pollution control requires understanding of historical trajectories and spatial characteristics of greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs), which remains inadequately studied. Here, we establish plant-level monthly operational emissions inventories of China's WWTPs in 2009-2019. We show that urban wastewater treatment has been enhanced with 80% more chemical oxygen demand being removed annually. However, this progress is associated with 180% more GHG emissions at the national level, up to 58.3 Mt CO₂ eq in 2019. We found significant seasonality in GHG emissions. Increasing sludge yield and electricity intensity became primary drivers after 2015 because of stricter standards, causing GHG emissions increase 12.9 and 8.3% until 2019. GHG emissions from urban wastewater treatment show high spatial difference at province, city and plant levels, with different sludge disposal and energy mix approaches combined with different influent and effluent conditions in WWTPs across China. Stricter effluent standard resulted in similar GHG emissions growth pattern in cities. We argue WWTPs focus on resource recovery in developed areas and higher operational efficiency in developing areas.

Spatiotemporal investigation of the digital divide, the case study of Iranian Provinces

Many communities and territories in developing countries experience significant gaps in access to and use of information and communication technology (ICT), which is viewed as a major impediment to socioeconomic and health-related vulnerabilities. Geographic considerations, on the other hand, as well as variations in motivation for ICT usage and technology adoption within and across nations, as well as between cultures, have exacerbated the digital divide. This paper investigates disparities in access to and utilization of ICT in 31 Iranian provinces from 2011 to 2020. The research discovers evidence that family income and the number of R&D centers affected the formation of the digital divide, albeit the degree of the split has fluctuated through time and space. This study discovered that digital inequality is associated with social exclusion throughout Iranian regions, and it went on to try to better understand the underlying issues and potential solutions. In this regard, some policy avenues are suggested for government action, particularly for marginalized socioeconomic groups, such as the provision of infrastructure, training and skill augmentation, and the easing of digital services supplied by the government or private sector.

Stunting, double orphanhood and unequal access to public services in democratic South Africa

Orphans who lack household or community support face significant socio-economic disadvantages. In particular, they are at greater risk of malnutrition and stunting in developing countries. Children who have no living parents, also called double orphans, are most likely to require support from extended families or public institutions. This paper explores how WASH infrastructure, and public health and social services relate to stunting. It is one of the first studies to analyse these factors with a specific focus on double orphans, who tend to live in under-serviced areas with high stunting rates and poor access to public resources. We collate a cross sectional spatial dataset with local child stunting rates from 2013, rates of double orphanhood, private household resources, and public services from 2011 for South Africa, a country where the HIV/AIDS pandemic has led to high rates of double orphanhood. We estimate spatial econometric models that account for unobserved regional shocks and measurement bias, but which do not address other biases. Our results show that high stunting rates, particularly in areas with high proportions of double orphans, overlap strongly with poor provision of WASH and the availability of household resources. By contrast, other softer services accessed outside the home, such as access to health, social welfare and early childhood development facilities are not correlated with stunting in the same way. WASH is more strongly related to reduced stunting when infrastructure covers larger geographic areas and with the combined use of services from adjacent areas. This occurs because of economies of scale in provision and preventing transmission of disease across regions. Policy makers can explore the option to reduce stunting by expanding geographic networks of WASH service delivery into under-serviced areas where double orphans tend to locate.

Measuring COVID-19 vaccination coverage: an enhanced age-adjusted two-step floating catchment area model

BACKGROUND

There are only limited studies on access to COVID-19 vaccines and identifying the most appropriate health centres for performing vaccination in metropolitan areas. This study aimed to measure potential spatial access to COVID-19 vaccination centres in Mashhad, the second-most populous city in Iran.

METHODS

The 2021 age structure of the urban census tracts was integrated into the enhanced two-step floating catchment area model to improve accuracy. The model was developed based on three different access scenarios: only public hospitals, only public healthcare centres and both (either hospitals or healthcare centres) as potential vaccination facilities. The weighted decision-matrix and analytic hierarchy process, based on four criteria (i.e. service area, accessibility index, capacity of vaccination centres and distance to main roads), were used to choose potential vaccination centres looking for the highest suitability for residents. Global Moran's index (GMI) was used to measure the spatial autocorrelation of the accessibility index in different scenarios and the proposed model.

RESULTS

There were 26 public hospitals and 271 public healthcare centres in the study area. Although the exclusive use of public healthcare centres for vaccination can provide the highest accessibility in the eastern and north-eastern parts of the study area, our findings indicate that including both public hospitals and public healthcare centres provide high accessibility to vaccination in central urban part. Therefore, a combination of public hospitals and public healthcare centres is recommended for efficient vaccination coverage. The value of GMI for the proposed model (accessibility to selected vaccination centres) was calculated as 0.53 (Z = 162.42, P < 0.01). Both GMI and Z-score values decreased in the proposed model, suggesting an enhancement in accessibility to COVID-19 vaccination services.

CONCLUSIONS

The periphery and poor areas of the city had the least access to COVID-19 vaccination centres. Measuring spatial access to COVID-19 vaccination centres can provide valuable insights for urban public health decision-makers. Our model, coupled with geographical information systems, provides more efficient vaccination coverage by identifying the most suitable healthcare centres, which is of special importance when only few centres are available.

Happy but Unequal: Differences in Subjective Well-Being across Individuals and Space in Colombia

Despite being on average a relatively happy country, Colombia has a high level of inequality in subjective well-being (SWB). Using Gallup World Poll data for the period from 2010 to 2018, this paper tests the direction and strength of association of a range of objective and subjective factors with SWB and explains differences in SWB across individuals and space. The perceived welfare of the average Colombian is mainly influenced by conditions and expectations related to economic opportunities and education. However, quantile regressions, reveal substantial differences in the domains that matter to those at the bottom and top of the experienced welfare distribution. Standard-of-living improvements, housing affordability, and civic engagement matter more to the most fortunate top 20%, while having education, a job, sufficient income, economic security, and digital connectivity are much more strongly associated with the well-being of the bottom 20%. The life domains that matter more to the unhappiest respondents also explain the majority of the spatial differences in perceived welfare between residents in urban and rural areas as well as core and peripheral regions. Policy actions aimed at closing the gaps in these areas have the potential to increase well-being and reduce inequality in Colombia.

Multiscale Contextual Poverty in the Netherlands: Within and Between-Municipality Inequality

Contextual poverty refers to high proportions of people with a low income in a certain (residential) space, and it can affect individual socioeconomic outcomes as well as decisions to move into or out of the neighbourhood. Contextual poverty is a multiscale phenomenon: Poverty levels at the regional scale reflect regional economic development, while meso-scale concentrations of poverty within cities are related to city-specific social, economic and housing characteristics. Within cities, poverty can also concentrate at micro spatial scales, which are often neglected, largely due to a lack of data. Exposure to poverty at lower spatial scales, such as housing blocks and streets, is important because it can influence individuals through social mechanisms such as role models or social networks. This paper is based on the premise that sociospatial context is necessarily multiscalar, and therefore contextual poverty is a multiscale problem which can be better understood through the inequality within and between places at different spatial scales. The question is how to compare different spatial contexts if we know that they include various spatial scales. Our measure of contextual poverty embraces 101 spatial scales and compares different locations within and between municipalities in the Netherlands. We found that the national inequality primarily came from the concentrations of poverty in areas of a few kilometres, located in cities, which have different spatial patterns of contextual poverty, such as multicentre, core-periphery and east-west. In addition to the inequality between municipalities, there are considerable within-municipality inequalities, particularly among micro-areas of a few hundred metres.

Examining spatial inequality in COVID-19 positivity rates across New York City ZIP codes

We aim to understand the spatial inequality in Coronavirus disease 2019 (COVID-19) positivity rates across New York City (NYC) ZIP codes. Applying Bayesian spatial negative binomial models to a ZIP-code level dataset (N = 177) as of May 31st, 2020, we find that (1) the racial/ethnic minority groups are associated with COVID-19 positivity rates; (2) the percentages of remote workers are negatively associated with positivity rates, whereas older population and household size show a positive association; and (3) while ZIP codes in the Bronx and Queens have higher COVID-19 positivity rates, the strongest spatial effects are clustered in Brooklyn and Manhattan.

Urban inequalities in the 21st century economy

In the last decade or so, inequality studies have assumed renewed prominence across the social sciences. In this introduction to a special issue of Applied Geography, we set out to articulate the importance of urban spatial context in broader present-day inequality debates. We argue that the information-based economy is emphatically urban-based and that it has forged new spatial inequalities in and between cities and among urban populations. Income gaps have widened, inter-city disparities have grown, suburbs have been re-sorted into a wide array on the basis of class and race or ethnicity, and many central cities have assumed a renewed importance within metropolitan areas. We argue that attention to urban spatial dimensions at various scales is critical to understanding current inequality trends, from intra-urban to regional and global scales. Contributions to this special issue from North America, Europe, South America, and China suggest that deepening urban inequalities are pervasive across the globe.

Has Income Segregation Really Increased? Bias and Bias Correction in Sample-Based Segregation Estimates

Several recent studies have concluded that residential segregation by income in the United States has increased in the decades since 1970, including a significant increase after 2000. Income segregation measures, however, are biased upward when based on sample data. This is a potential concern because the sampling rate of the American Community Survey (ACS)-from which post-2000 income segregation estimates are constructed-was lower than that of the earlier decennial censuses. Thus, the apparent increase in income segregation post-2000 may simply reflect larger upward bias in the estimates from the ACS, and the estimated trend may therefore be inaccurate. In this study, we first derive formulas describing the approximate sampling bias in two measures of segregation. Next, using Monte Carlo simulations, we show that the bias-corrected estimators eliminate virtually all of the bias in segregation estimates in most cases of practical interest, although the correction fails to eliminate bias in some cases when the population is unevenly distributed among geographic units and the average within-unit samples are very small. We then use the bias-corrected estimators to produce unbiased estimates of the trends in income segregation over the last four decades in large U.S. metropolitan areas. Using these corrected estimates, we replicate the central analyses in four prior studies on income segregation. We find that the primary conclusions from these studies remain unchanged, although the true increase in income segregation among families after 2000 was only half as large as that reported in earlier work. Despite this revision, our replications confirm that income segregation has increased sharply in recent decades among families with children and that income inequality is a strong and consistent predictor of income segregation.

Living on the Edge: Neighborhood Boundaries and the Spatial Dynamics of Violent Crime

Neighborhood boundaries are a defining aspect of highly segregated urban areas. Yet, few studies examine the particular challenges and spatial processes that occur at the bordering region between two neighborhoods. Extending the growing literature on spatial interdependence, this article argues that neighborhood boundaries-defined as sharp changes in the racial or socioeconomic composition of neighborhoods-are a salient feature of the spatial structure with implications for violent crime and other outcomes. Boundaries lack the social control and cohesion of adjacent homogeneous areas, are contested between groups provoking intergroup conflict, and create opportunities for criminal behavior. This article presents evidence linking racial neighborhood boundaries to increased violent crime. The findings illustrate the importance of neighborhood boundaries for our understanding of spatial dimensions of population dynamics above and beyond the characteristics of neighborhoods.

National and subnational mortality and disability-adjusted life years (DALYs) attributable to 17 occupational risk factors in Iran, 1990-2015

We estimated age-sex specific and cause-specific mortality, years of life lost due to premature mortality (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) attributable to 17 individual occupational risks in Iran at the national and subnational levels in 1990-2015 based on the Global Burden of Disease Study 2015 (GBD 2015). The burden of disease attributable to occupational risk factors was calculated using the comparative risk assessment methodology based on 10 outcomes and 21 risk-outcome pairs. The temporal changes in the attributable burden of disease were decomposed into the contribution of population growth, population ageing, risk-deleted DALY rate, and risk exposure. National DALYs attributable to occupational risks at the national level in 1990, 2005, and 2015 were 138,210 (95% uncertainty interval 64,429-223,028), 193,243 (91,645-310,281), and 228,310 (106,782-371,709), respectively indicating a total increase of 65% (65-67) during the study period. Between 1990 and 2015, the share of the attributable DALYs for women rose by 55% (51-58) from 13% (12-14) to 20% (19-21). The proportion of YLLs in national DALYs attributable to occupational risks during the study period slightly decreased from 24% in 1990 to 23% in 2015. The five occupational risks with the highest contributions in the national attributable DALYs in 2015 were ergonomic factors (107,490), noise (52,122), exposure to particulate matter, gases, and fumes (26,847), asthmagens (19,347), and exposure to asbestos (7842). From 1990 to 2015, the increase in total DALYs attributable to occupational carcinogens (112%) was higher than that for other occupational risks. During the study period, changes in risk deleted DALY rate and risk exposure led to decreases in total DALYs attributable to occupational risks by 14% and 30%, respectively. Based on the Gini coefficient, spatial inequality in DALY rate attributable to occupational risks at the provincial level decreased during 1990-2015. A comprehensive plan for management of exposure to occupational risks, especially occupational carcinogens can cause an important effect for control of the increasing trend of occupational health losses.

Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences

Background

‘Place’ matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk.

Methods

We conducted a 12-year (2004–2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage—neighborhood economic status, neighborhood education level, and levels of policing activity—, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations.

Results

Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed.

Conclusions

A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more localized prevention and intervention strategies. This new approach can also contribute to an improved epidemiological surveillance system to detect ecological variations in risk, and to assess the effectiveness of the initiatives to reduce this risk.

Quantifying the Spatial Inequality and Temporal Trends in Maternal Smoking Rates in Glasgow

Maternal smoking is well known to adversely affect birth outcomes, and there is considerable spatial variation in the rates of maternal smoking in the city of Glasgow, Scotland. This spatial variation is a partial driver of health inequalities between rich and poor communities, and it is of interest to determine the extent to which these inequalities have changed over time. Therefore in this paper we develop a Bayesian hierarchical model for estimating the spatio-temporal pattern in smoking incidence across Glasgow between 2000 and 2013, which can identify the changing geographical extent of clusters of areas exhibiting elevated maternal smoking incidences that partially drive health inequalities. Additionally, we provide freely available software via the R package CARBayesST to allow others to implement the model we have developed. The study period includes the introduction of a ban on smoking in public places in 2006, and the results show an average decline of around 11% in maternal smoking rates over the study period.