Area-level Data Research Articles

Relationships between health outcomes in older populations and urban green infrastructure size, quality and proximity

BackgroundThere is a growing body of literature supporting positive associations between natural environments and better health. The type, quality and quantity of green and blue space (‘green-space’) in proximity to the home might be particularly important for less mobile populations, such as for some older people. However, considerations of measurement and definition of green-space, beyond single aggregated metrics, are rare. This constitutes a major source of uncertainty in current understanding of public health benefits derived from natural environments. We aimed to improve our understanding of how such benefits are conferred to different demographic groups through a comprehensive evaluation of the physical and spatial characteristics of urban green infrastructure.MethodsWe employed a green infrastructure (GI) approach combining a high-resolution spatial dataset of land-cover and function with area-level demographic and socio-economic data. This allowed for a comprehensive characterization of a densely populated, polycentric city-region. We produced multiple GI attributes including, for example, urban vegetation health. We used a series of step-wise multi-level regression analyses to test associations between population chronic morbidity and the functional, physical and spatial components of GI across an urban socio-demographic gradient.ResultsGI attributes demonstrated associations with health in all socio-demographic contexts even where associations between health and overall green cover were non-significant. Associations varied by urban socio-demographic group. For areas characterised by having higher proportions of older people (‘older neighbourhoods’), associations with better health were exhibited by land-cover diversity, informal greenery and patch size in high income areas and by proximity to public parks and recreation land in low income areas. Quality of GI was a significant predictor of good health in areas of low income and low GI cover. Proximity of publicly accessible GI was also significant.ConclusionsThe influence of urban GI on population health is mediated by green-space form, quantity, accessibility, and vegetation health. People in urban neighbourhoods that are characterised by lower income and older age populations are disproportionately healthy if their neighbourhoods contain accessible, good quality public green-space. This has implications for strategies to decrease health inequalities and inform international initiatives, such as the World Health Organisation’s Age-Friendly Cities programme.

Association Between Socioeconomic and Demographic Characteristics and Non-fatal Alcohol-Related Injury in Maringá, Brazil.

Background: Previous research has corroborated a high burden of alcohol-related injury in Brazil and the presence of socioeconomic disparities among the injured. Yet, individual-level data is scarce. To fill this gap, we examined the association between demographic and socioeconomic characteristics with non-fatal alcohol-related injury in Maringá, Brazil.Methods: We used household survey data collected during a 2015 cross-sectional study. We conducted univariate and multivariate analyses to evaluate associations of demographic (age, gender, race) and socioeconomic characteristics (employment, education, income) with non-fatal alcohol-related injury.Results: Of the 995 participants who reported injuries, 62 (6.26%) were alcohol-related. Fifty-three (85%) alcohol-related injuries were reported by males. Multivariate analysis indicated being male (OR = 5.98 95% CI = 3.02, 13.28), 15–29 years of age (OR = 3.62 95% CI = 1.72, 7.71), and identifying as Black (OR = 2.38 95% CI = 1.09, 4.95) were all significantly associated with increased likelihood of reporting an alcohol-related injury, whereas unemployment was significantly associated with decreased likelihood of reporting an alcohol-related injury (OR = 0.41 95% CI = 0.18, 0.88).Conclusion: Our findings suggest that in Maringá, being male, between the ages of 15 and 29, employed, or identifying as Black were characteristics associated with a higher risk for non-fatal alcohol-related injury. Individual level data, such as ours, should be considered in combination with area-level and country-level data when developing evidence-based public-health policies.

Trends in Sociodemographic Disparities in Colorectal Cancer Staging and Survival: A SEER-Medicare Analysis.

INTRODUCTION:Race, ethnicity, and socioeconomic status are known to influence staging and survival in colorectal cancer (CRC). It is unclear how these relationships are affected by geographic factors and changes in insurance coverage for CRC screening. We examined the temporal trends in the association between sociodemographic and geographic factors and staging and survival among Medicare beneficiaries.METHODS:We identified patients 65 years or older with CRC using the 1991–2010 Surveillance, Epidemiology, and End Results–Medicare database and extracted area-level sociogeographic data. We constructed multinomial logistic regression models and the Cox proportional hazards models to assess factors associated with CRC stage and survival in 4 periods with evolving reimbursement and screening practices: (i) 1991–1997, (ii) 1998–June 2001, (iii) July 2001–2005, and (iv) 2006–2010.RESULTS:We observed 327,504 cases and 102,421 CRC deaths. Blacks were 24%–39% more likely to present with distant disease than whites. High-income areas had 7%–12% reduction in distant disease. Compared with whites, blacks had 16%–21% increased mortality, Asians had 32% lower mortality from 1991 to 1997 but only 13% lower mortality from 2006 to 2010, and Hispanics had 20% reduced mortality only from 1991 to 1997. High-education areas had 9%–12% lower mortality, and high-income areas had 5%–6% lower mortality after Medicare began coverage for screening colonoscopy. No consistent temporal trends were observed for the associations between geographic factors and CRC survival.DISCUSSION:Disparities in CRC staging and survival persisted over time for blacks and residents from areas of low socioeconomic status. Over time, staging and survival benefits have decreased for Asians and disappeared for Hispanics.

Area-Level Variation in Children's Unmet Need for Community-Based Mental Health Services: Findings from the 2014 Ontario Child Health Study.

There is limited empirical evidence documenting the magnitude and correlates of area-level variability in unmet need for children's mental health services. Research is needed that identifies area-level characteristics that can inform strategies for reducing unmet need in the population. The study purpose is to: (1) estimate area-level variation in children's unmet need for mental health services (using Service Areas as defined by the Ontario Ministry of Children and Youth Services), and (2) identify area-level service arrangements, and geographic and population characteristics associated with unmet need. Using individual-level general population data, area-level government administrative data and Census data from Ontario, Canada, we use multilevel regression models to analyze unmet need for mental health services among children (level 1) nested within Service Areas (level 2). The study finds that 1.64% of the reliable variance in unmet need for mental health services is attributable to between-area differences. Across areas, we find that Service Areas with more agencies had a lower likelihood of unmet need for mental health services. Compared to other Service Areas, Toronto had much lower likelihood of unmet need compared to the rest of Ontario. Rural areas, areas with unsatisfactory public transport, and areas with higher levels of socio-economic disadvantage had a higher likelihood of unmet need for mental health services. These findings identify challenges in service provision that researchers, policymakers and administrators in children's mental health services need to better understand. Policy implications and potential Service Area strategies that could address equitable access to mental health services are discussed.

Cost-effectiveness of offering an area-level financial incentive on breast feeding: a within-cluster randomised controlled trial analysis

ObjectiveTo provide the first estimate of the cost-effectiveness of financial incentive for breastfeeding intervention compared with usual care.DesignWithin-cluster (‘ward’-level) randomised controlled trial cost-effectiveness analysis (trial registration number ISRCTN44898617).SettingFive local authority...

Prices and Illicit Trade of Cigarettes in the European Union: A Cross-sectional Analysis.

Within the context of the World Health Organization Framework Convention on Tobacco Control Protocol to Eliminate Illicit Trade in Tobacco Products and the impending revision of the European Union (EU) directive on tobacco excise rules we assessed whether cigarettes price is linked to being offered illicit cigarettes. We combined data being offered illicit cigarettes from the 2015 Special Eurobarometer Survey on Illicit Tobacco (N = 27,672) with area-level data on Gross Domestic Product, unemployment, perceived corruption, and sharing a border with a non-European Economic Area (non-EEA) state. We used the 2015 Weighted Average Price of cigarettes (WAP), which reflects the average price of a cigarette pack in each Member State. We assessed associations between prices and illicit trade using three-level ordered regression models. About 19.6% of respondents reported ever being offered illicit cigarettes, 6.4% repeatedly. In fully adjusted models WAP was not associated with being more likely to have been offered illicit market cigarettes more often (adjusted odds ratio = 1.02, 95% confidence interval: 0.91; 1.15). Sharing a border with a non-EEA Member State was associated with increased likelihood of reporting being offered illicit cigarettes more often (1.73, 1.26; 2.39). This study found no significant association between cigarette prices and reporting being offered illicit cigarettes; sharing a border with a non-EEA Member State was linked to illicit trade. This study adds to evidence that increasing prices of cigarettes are not associated with illicit trade and that the focus should remain on securing supply chains, including through features such as independent traceability systems. After adjusting for individual and regional factors, we did not identify an association between prices of cigarettes and likelihood of reporting being offered illicit cigarettes in the EU. Sharing a border with a non-EEA state, however, was associated with increased likelihood of reporting being offered illicit cigarettes more often. This study adds to evidence that increasing taxes and prices of cigarettes are not a driver of illicit trade and that policies should maintain their focus on securing the supply chain.

Associations between area-level deprivation, rural residence, physician density, screening policy and late-stage colorectal cancer in Canada

BackgroundImportant social disparities in colorectal screening exist in Canada. Few studies have assessed disparities further along the cancer control continuum. Here we assess the associations between social and material deprivation, physician density, rural residence, and the absence of provincial mail-based screening programs and colorectal cancer (CRC) stage at diagnosis. MethodsColorectal cancer cases and stage data (“local or regional” if stage 0, I, or II, “late” if stage III or IV) were obtained through the Canadian Cancer Registry (2011–2015, N = 54,745). Cases were linked to 2006 Canadian Census Dissemination Area-level data on rural/urban status, exposure to a provincial mail-based screening program, and social and material deprivation (Pampalon Index quintile groups); and to Scott’s Medical Database 2011 physician density data (<7 vs. ≥ 7/10,000). Age, sex, and predictor-adjusted Generalized estimating equation (GEE) Poisson models were used to determine independent associations between predictors and late-stage at diagnosis. ResultsHalf of CRC cases are diagnosed at stage III or IV (51 %), with younger age groups experiencing higher late-stage prevalence (57 % among those aged 18–49). The covariate-adjusted late-stage prevalence was 2-percentage points higher in most materially- and socially-deprived areas (95 % CI: 1 %, 4 %, in both, respectively) and in provinces with no mail-based screening programs (95 % CI: 1 %, 2 %). No significant differences were observed according to rural residence or physician density. ConclusionsSocial disparities in late-stage CRC diagnosis are modest. Continued surveillance of these disparities may be warranted as provinces continue to promote early cancer detection through screening, and stage distributions may change overtime.

Inequalities in exposure to the air pollutants PM2.5 and NO2 in Australia

Vulnerable subpopulations may be exposed to higher levels of outdoor air pollution than the rest of the population. Due to the potential for this to exacerbate their existing health burden, concerns about disparities in subpopulations’ air pollution exposure have motivated international public health researchers to examine this topic. In Australia, such research is lacking to date, despite heterogeneity in air pollution at multiple spatial scales across the continent. This study aimed to investigate disparities in exposure to two health-relevant outdoor air pollutants: particulate matter <2.5 μm (PM2.5) and nitrogen dioxide (NO2). We used national land-use regression models to estimate annual average concentrations of PM2.5 and NO2, and area-level census data on ethnicity, age and socio-economic status (SES) to calculate the bivariate associations between each census-derived variable with the concentration of air pollutants. We also used multivariable models including specific measures of SES as covariates to assess to what extent associations were explained by SES. Associations were calculated separately for rural and urban areas using generalised additive models which accounted for spatial autocorrelation. Bivariate results showed significant nonlinear associations (p < 0.001) between vulnerable subpopulations and pollutant concentration. These associations suggested that areas with greater socio-economic disadvantage, a higher proportion of ethnic minorities, and elderly people are exposed to higher concentrations of PM2.5 and NO2, although differences in the magnitude of exposure were small overall. Our multivariable models showed that the associations between ethnic minorities and pollutant concentration appear to be substantially affected by area-level SES. Our results suggested that these vulnerable subpopulations are inequitably exposed to PM2.5 and NO2. While the magnitude of differences in exposure were generally small, the predicted differences in exposure among vulnerable subpopulations could contribute to a potentially avertable health burden at a population-level.

A Multiscale Spatially Varying Coefficient Model for Regional Analysis of Topsoil Geochemistry

A motivating example for this paper is to study a topsoil geochemical process across a large region. In regional environmental health studies, ambient levels of toxic substances in topsoil are commonly used as surrogates for personal exposure to toxic substances. However, toxicity levels in topsoil are usually sparsely measured at a limited number of point locations. Consequently, topsoil measurements only provide highly localized regional information and cannot be representative of the surrounding area. Instead, it is standard practice to use point-referenced measurements of stream sediments, because they are widely available across a region and are correlated with topsoil measurements at nearby locations. For more effective regional modeling of topsoil geochemistry, we develop a spatially varying coefficient model that integrates point-level topsoil and point-referenced area-level stream sediment data. The proposed model incorporates two spatial characteristics: the local spatial autocorrelation in the latent topsoil process and the spatially varying relationship between the latent topsoil and stream sediment processes. The former is modeled indirectly via a conditional autoregressive model for the stream sediment process, and the latter is modeled by spatially varying coefficients that follow a multivariate Gaussian process. We apply the proposed model to a real dataset of arsenic concentration and demonstrate better performance than competing models.

A Spatial Analysis of Health Disparities Associated with Antibiotic Resistant Infections in Children Living in Atlanta (2002-2010).

Background:Antibiotic resistant bacteria like community-onset methicillin resistant Staphylococcus aureus (CO-MRSA) have continued to cause infections in children at alarming rates and are associated with health disparities. Geospatial analyses of individual and area level data can enhance disease surveillance and identify socio-demographic and geographic indicators to explain CO-MRSA disease transmission patterns and risks.Methods:A case control epidemiology approach was undertaken to compare children with CO-MRSA to a noninfectious condition (unintentional traumatic brain injury (uTBI)). In order to better understand the impact of place based risks in developing these types of infections, data from electronic health records (EHR) were obtained from CO-MRSA cases and compared to EHR data from controls (uTBI). US Census data was used to determine area level data. Multi-level statistical models were performed using risk factors determined a priori and geospatial analyses were conducted and mapped.Results:From 2002–2010, 4,613 with CO-MRSA and 34,758 with uTBI were seen from two pediatric hospitals in Atlanta, Georgia. Hispanic children had reduced odds of infection; females and public health insurance were more likely to have CO-MRSA. Spatial analyses indicate significant ‘hot spots’ for CO-MRSA and the overall spatial cluster locations, differed between CO-MRSA cases and uTBI controls.Conclusions:Differences exist in race, age, and type of health insurance between CO-MRSA cases compared to noninfectious control group. Geographic clustering of cases is distinct from controls, suggesting placed based factors impact risk for CO-MRSA infection.

A Prediction Model for Uncontrolled Type 2 Diabetes Mellitus Incorporating Area-level Social Determinants of Health.

Social determinants of health (SDH) at the area level are understood to influence the likelihood of having poor glycemic control for patients with type 2 diabetes mellitus (T2DM). To develop a model for predicting whether a person with T2DM has uncontrolled diabetes (hemoglobin A1c ≥9%), incorporating individual and area-level (census tract) covariates. Development and validation of machine learning models. Total of N=1,015,808 privately insured persons in claims data with T2DM. C-statistic, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. A standard logistic regression model selecting among the available individual-level covariates and area-level SDH covariates (at the census tract level) performed poorly, with a C-statistic of 0.685, sensitivity of 25.6%, specificity of 90.1%, positive predictive value of 56.9%, negative predictive value of 70.4%, and accuracy of 68.4% on a 25% held-out validation subset of the data. By contrast, machine learning models improved upon risk prediction, with the highest performance from a random forest algorithm with a C-statistic of 0.928, sensitivity of 68.5%, specificity of 94.6%, positive predictive value of 69.8%, negative predictive value of 94.3%, and accuracy of 90.6%. SDH variables alone explained 16.9% of variation in uncontrolled diabetes. A predictive model developed through a machine learning approach may assist health care organizations to identify which area-level SDH data to monitor for prediction of diabetes control, for potential use in risk-adjustment and targeting.

Neighborhood Environment and Health of Injured Urban Black Men.

Urban black males are at disproportionately high risk of poor health outcomes; thus, we need to measure neighborhood environments appropriately in order to understand aspects of neighborhoods that influence their mental and physical health. We explored associations between physical and mental health of injured, urban black men with objectively measured and perceived neighborhood characteristics. In 2017-2018, we analyzed data from 486 black, adult males in Philadelphia admitted to a trauma center with injury between January 2013 and February 2017. Area-level measures of social, economic, and built environments were obtained from multiple sources. At enrollment, participants answered questions about neighborhood environment and self-reported physical and mental health 30days before injury. We conducted factor analysis to identify neighborhood characteristics, then estimated odds of poor physical or mental health, accounting for spatial correlation of participants. Poor physical and mental health was reported by 12% and 22% of participants, respectively. In participants' neighborhoods, 29% of adults lived in poverty. Individually, 73% of men reported abandoned buildings, and 31% reported not feeling safe walking around their neighborhood. Physical health was associated with neighborhood poverty and disconnectedness. Mental health was associated with neighborhood economics and individual perceptions of social disorder and safety. Individual-level factors were not correlated with area-level factors. We found both area-level and individual-level measures were associated with health, perhaps operating through different mechanisms, but individual experiences may not be easily extrapolated from area-level data. By identifying important components of neighborhood environments, we may better understand how neighborhoods contribute to health in vulnerable populations.

Estimating Occupational Heat Exposure From Personal Sampling of Public Works Employees in Birmingham, Alabama.

This study investigated whether using thermometers clipped on workers' shoes would result in different heat exposure estimation and work-rest schedules compared with using area-level meteorological data alone. Alabama workers (n = 51) were individually monitored using thermometers on shoes. Wet bulb globe temperature (WBGT) was estimated using thermometer temperatures (WBGT [personal]) or nearby weather station temperatures (WBGT [WS]). Work-rest schedules were determined from WBGT, clothing, and hourly metabolic rates estimated from self-reported tasks and bodyweight. The percent of hours exceeding the threshold limit value (TLV, ACGIH, Cincinnati, OH) were estimated at 47.8% using WBGT (personal) versus 42.1% using WBGT (WS). For work-rest recommendations, more hours fell into the most protective schedule (0 to 15 min work/45 to 60 min rest) using WBGT (personal) versus WBGT (WS) (17.4% vs 14.4%). Temperatures from wearable thermometers, together with meteorological data, can serve as an additional method to identify occupational heat stress exposure and recommend work-rest schedules.

Area-level income disparities in colorectal screening in Canada: evidence to inform future surveillance.

Participation in colorectal screening remains low even in countries with universal health coverage. Area-level determinants of low screening participation in Canada remain poorly understood. We assessed the association between area-level income and two indicators of colorectal screening (having never been screened, having not been screened recently) by linking census-derived local area-level income data with self-reported screening data from urban-dwelling respondents to the Canadian Community Health Survey (50-75 years of age, cycles 2005 and 2007, n = 18,362) who reported no known risk factors for colorectal cancer. Generalized estimating equation Poisson models estimated the prevalence ratios and differences for having never been screened and having not been screened recently, adjusting for individual-level income, education, marital status, having a regular physician, age, and sex. About 53% of the study population had never been screened. Among individuals who had ever been screened, 35% had been screened recently. Adjusting for covariates, lower area-level income was associated with having never been screened [covariate-adjusted prevalence ratios: 1.24 for quartile 1; 95% confidence limits (cl): 1.16, 1.34; 1.25 for quartile 2; 95% cl: 1.15, 1.33; 1.15 for quartile 3; 95% cl: 1.08, 1.23]. Among individuals who had been screened in their lifetime, area-level income was not associated with having not been screened recently. Lower area-level income is associated with having never been screened for colorectal cancer even after adjusting for individual socioeconomic factors. Those findings highlight the potential importance of socioeconomic contexts for colorectal screening initiation and merit attention in both future research and surveillance efforts.

No Man is an Island: The Impact of Neighborhood Disadvantage on Mortality.

This study’s purpose is to determine if neighborhood disadvantage, air quality, economic distress, and violent crime are associated with mortality among term life insurance policyholders, after adjusting for individual demographics, health, and socioeconomic characteristics. We used a sample of approximately 38,000 term life policyholders, from a large national life insurance company, who purchased a policy from 2002 to 2010. We linked this data to area-level data on neighborhood disadvantage, economic distress, violent crime, and air pollution. The hazard of dying for policyholders increased by 9.8% (CI: 6.0–13.7%) as neighborhood disadvantage increased by one standard deviation. Area-level poverty and mortgage delinquency were important predictors of mortality, even after controlling for individual personal income and occupational status. County level pollution and violent crime rates were positively, but not statistically significantly, associated with the hazard of dying. Our study provides evidence that neighborhood disadvantage and economic stress impact individual mortality independently from individual socioeconomic characteristics. Future studies should investigate pathways by which these area-level factors influence mortality. Public policies that reduce poverty rates and address economic distress can benefit everyone’s health.

Pathways to ethnic differences in obesity: The role of migration, culture and socio-economic position in the UK.

Previous research has identified ethnic differences in abdominal obesity but has not fully explored the pathways that explain these ethnic differences, which may relate to individual and contextual characteristics. This research identifies ethnic differences in waist circumference for eight ethnic groups in England, before and after accounting for a range of individual-level and area-level factors. Three key pathways to obesity are explored: migration status, cultural characteristics, and socio-economic characteristics.Data come from four years of the Health Survey for England (1998, 1999, 2003 and 2004) and linked area-level data from the 2001 Census. The total sample size is 27,946. Multi-level modelling methods are used to account for individual-level and area-level factors.The results show that migration status has a strong association with ethnic differences in waist circumference – in particular, waist circumference increases with length of time since migration to the UK. Cultural characteristics and socio-economic characteristics are also associated with ethnic differences in waist circumference, but not to the same extent as migration status. The strong association between migration status and waist circumference is partly attenuated by cultural characteristics and partly by socio-economic inequality. However, there is still a strong association between migrant status and waist circumference that remains unexplained.

Spatial distributions of common and rare species in a widespread group of stream insects

The phenomenon of rarity is understudied in freshwater systems compared with terrestrial systems. We examined whether spatial distributions of rare species of black flies (Diptera: Simuliidae) differed from those of common species. We used mean pairwise distance between stream sites as a proxy for dispersal ability to describe spatial distributions. From a master database of 1445 North American stream-site collections, in which all immature black flies were identified to species, we created one database of 12 ecoregion-level data sets (476 sites) and a second database of 5 larger area-level data sets (504 sites) to address the following questions: 1) Does the spatial distribution (clumped, random, or overdispersed) differ between common and rare species? 2) Does the mean distance among sites occupied by rare species differ from that for common species? 3) Is species frequency (species occurrences/sites in a data set) related to distance among occupied sites? 4) Does the classification of an individual species as common, rare, or vagrant vary with location? We found that 1) spatial distribution patterns were generally the same for common and rare species, 2) mean distances among stream sites typically did not differ between common and rare species, 3) species frequency was rarely related to distance among occupied sites, and 4) species classified as common, rare, or vagrant in one ecoregion data set were often classified differently in other data sets, indicating the importance of location in determining the status of a species. The results suggest that rare species have dispersal abilities similar to those of common species.

The role of service factors on variations in place of death: an observational study

Background Previous studies have revealed that there is significant geographical variation in place of death in (PoD) England, with sociodemographic and clinical characteristics explaining ≤ 25% of this variation. Service factors, mostly modifiable, may account for some of the unexplained variation, but their role had never been evaluated systematically. Methods A national population-based observational study in England, using National Death Registration Database (2014) linked to area-level service data from public domains, categorised by commissioning, type and capacity, location and workforce of the services, and the service use. The relationship between the service variables and PoD was evaluated using beta regression at the area level and using generalised linear mixed models at the patient level. The relative contribution of service factors at the area level was assessed using the per cent of variance explained, measured by R2. The total impact of service factors was evaluated by the area under the receiver operating characteristic curve (AUC). The independent effect of service variables was measured at the individual level by odds ratios (ORs). Results Among the 431,735 adult deaths, hospitals were the most common PoD (47.3%), followed by care homes (23.1%), homes (22.5%) and hospices (6.1%). One-third (30.3%) of the deaths were due to cancer and two-thirds (69.7%) were due to non-cancer causes. Almost all service categories studied were associated with some of the area-level variation in PoD. Service type and capacity had the strongest link among all service categories, explaining 14.2–73.8% of the variation; service location explained 10.8–34.1% of the variation. The contribution of other service categories to PoD was inconsistent. At the individual level, service variables appeared to be more useful in predicting death in hospice than in hospital or care home, with most AUCs in the fair performance range (0.603–0.691). The independent effect of service variables on PoD was small overall, but consistent. Distance to the nearest care facility was negatively associated with death in that facility. At the Clinical Commissioning Group level, the number of hospices per 10,000 adults was associated with a higher chance of hospice death in non-cancer causes (OR 30.88, 99% confidence interval 3.46 to 275.44), but a lower chance of hospice death in cancer causes. There was evidence for an interaction effect between the service variables and sociodemographic variables on PoD. Limitations This study was limited by data availability, particularly those specific to palliative and end-of-life care; therefore, the findings should be interpreted with caution. Data limitations were partly due to the lack of attention and investment in this area. Conclusion A link was found between service factors and PoD. Hospice capacity was associated with hospice death in non-cancer cases. Distance to the nearest care facility was negatively correlated with the probability of a patient dying there. Effect size of the service factors was overall small, but the interactive effect between service factors and sociodemographic variables suggests that high-quality end-of-life care needs to be built on service-level configuration tailored to individuals’ circumstances. Future work A large data gap was identified and data collection is required nationally on services relevant to palliative and end-of-life care. Future research is needed to verify the identified links between service factors and PoD. Funding The National Institute for Health Research Health Services and Delivery Research programme.

The association of neighborhood-level social class and tobacco consumption with adverse lung cancer characteristics in Maryland.

INTRODUCTIONAlthough both active tobacco use and passive tobacco exposure are well-established as being risk factors for lung cancer, it is challenging to measure tobacco-related exposures at the population level, while considering other factors (gender, race, socioeconomic status) that may modify the relationship between tobacco and lung cancer. Moreover, research to date has focused primarily on relationships between tobacco and endpoints of lung cancer incidence or mortality. Tobacco’s role in disease progression, through association with important disease characteristics such as tumor histological type and grade, and stage of disease at diagnosis, has been less well examined.METHODSThis research examines associations between area-level tobacco use and social class, as well as individual gender, race and age, and three adverse disease characteristics (tumor type, grade and stage) among incident cases of lung cancer reported to the Maryland Cancer Registry in 2000. Cases were geocoded by residential address. Multi-level logistic regression models included Census block group-level estimates of per capita tobacco spending, from Consumer Expenditure Survey data, and a 4-item social class index, from Census estimates of rates of high school graduation, employment, white collar occupation, and per capita income.RESULTSAnalyses of 3223 cases found no significant differences by race, however, results differed by gender. Lower block-group social class and higher tobacco spending were associated with squamous and small cell histological types and poorly differentiated or undifferentiated tumor grade. However, for later stage at diagnosis (SEER stages 2–7), both higher social class and greater tobacco spending were protective, especially for women, suggesting women in high tobacco use communities may benefit from early detection.CONCLUSIONSResults support using area-level behavioral data as tools for identifying high risk communities suitable for more resource-intensive research or interventions. Findings also suggest that area-level social resources are consistent drivers of lung cancer disparities, and merit continued research attention.

Individual- and area-level socioeconomic inequalities in diabetes mellitus in Saskatchewan between 2007 and 2012: a cross-sectional analysis.

Improving our understanding of social inequalities may improve prevention and treatment efforts for diabetes mellitus. We examined the association between individual- and area-level socioeconomic measures and physician-diagnosed diabetes in Saskatchewan over time. In this cross-sectional study, we linked health administrative data with individual-level socioeconomic data from the Canadian Community Health Survey and area-level data from the 2006 Canadian census. We used general linear mixed-models regression to analyze the effect of each factor, controlling for geographic and demographic measures. Area-level deprivation was associated with medically diagnosed type 2 diabetes mellitus after adjustment for the individual-level factors of age, sex, household income and education. Individuals residing in areas ranked in the least deprived quintile had a lower likelihood of diabetes than those in the most deprived quintile (odds ratio 0.40, 95% confidence interval 0.18-0.88). However, this disparity existed only in urban areas. This result may reflect less pronounced health inequalities in rural areas, greater socioeconomic heterogeneity, larger geographic units or some combination of these factors. Individual- and area-level socioeconomic factors were associated with the likelihood of medically diagnosed diabetes; however, the strength of this association varied between urban and rural communities. Acknowledgement of area-level deprivation as a modifiable risk factor related to the prevalence of diabetes is important in the development of effective interventions for urban, but not rural, areas.