Small Area Variation Research Articles

Spatial variation in teens’ crash rate reduction following the implementation of a graduated driver licensing program in Michigan

Motor vehicle crashes are a leading cause of injury, and teen drivers contribute disproportionately to that burden. Graduated Driver Licensing (GDL) programs are effective at reducing teen crash risk, but teen crash rates remain high. Between-state variation in the teen crash rate reduction following GDL implementation has been documented, but this is the first study to examine small-area variation in such a reduction. Fusing together crash data from the Michigan State Police, census data, and organizational data (alcohol outlet, movie theatre, and school locations), we analyzed spatial correlates of teen injury crash, and place-based features that modified the injury crash rate difference following GDL implementation. Specifically, using census-based units, we estimated changes in injury crash rates among teens using negative binomial regression controlling for spatial autocorrelation, and tested whether any measured spatial characteristics modified the crash rate change in the pre versus post GDL periods. There was a substantial reduction in teen crashes after GDL implementation (RR = 0.66, 95%CI: [0.65, 0.67]), and this effect was robust across gender and time-of-day (light/dark). We found evidence that this reduction varied across space; areas with more alcohol outlets corresponded to a larger daytime crash rate reduction post-GDL, while areas near schools corresponded to a smaller daytime crash rate reduction. Concentrations of movie theatres corresponded to larger post-GDL crash rate reductions after dark. Maximizing the substantial successes of GDL programs requires understanding why crash rate reductions were larger in some areas following GDL implementation, and harnessing that understanding to improve its effectiveness across a state, focusing on identifying priorities for improving driver training (e.g., by parents and driver educators), law enforcement, and future policy changes to current GDL laws.

Unwarranted regional variation in vertebroplasty and kyphoplasty in Switzerland: A population-based small area variation analysis.

BackgroundPercutaneous vertebroplasty (VP) and balloon kyphoplasty (BKP) for treating painful osteoporotic vertebral fractures are controversial.ObjectiveWe assessed the regional variation in the use of VP/BKP in Switzerland.MethodsWe conducted a population-based small area variation analysis using patient discharge data for VP/BKP from all Swiss hospitals and Swiss census data for calendar years 2012/13. We derived hospital service areas (HSAs) by analyzing patient flows, assigning regions from which most residents were discharged to the same VP/BKP specific HSA. We calculated age-/sex-standardized mean VP/BKP-rates and measures of regional variation (extremal quotient [EQ], systematic component of variation [SCV]). We estimated the reduction in variation of VP/BKP rates using negative binomial regression, with adjustment for patient demographic and regional socioeconomic factors (socioeconomic status, urbanization, and language region). We considered the residual, unexplained variation most likely to be unwarranted.ResultsOverall, 4955 VP/BKPs were performed in Switzerland in 2012/13. The age-/sex-standardized mean VP/BKP rate was 4.6/10,000 persons and ranged from 1.0 to 10.1 across 26 HSAs. The EQ was 10.2 and the SCV 57.6, indicating a large variation across VP/BKP specific HSAs. After adjustment for demographic and socioeconomic factors, the total reduction in variance was 32.2% only, with the larger part of the variation remaining unexplained.ConclusionsWe found a 10-fold variation in VP/BKP rates across Swiss VP/BKP specific HSAs. As only one third of the variation was explained by differences in patient demographics and regional socioeconomic factors, VP/BKP in the highest-use areas may, at least partially, represent overtreatment.

Hospitalisation of ambulatory care sensitive conditions and access to primary care in Portugal.

Our aim is to study the relationship between the incidence of hospitalisations of ambulatory care sensitive conditions (ACSCs) in small geographic areas and characteristics of the primary care delivery system that are associated with access to care such as travel time to the provider, volume of resources and patient-doctor ties. We try to assess the relative importance of access barriers and draw useful implications for healthcare planning policy. This work combines the approach of ACSC rates by Billings etal. (1993) and the Penchansky and Thomas (1981) framework of access, building a tool for analysing variations in small areas and assessing barriers to access for primary health care. We explicitly address and describe some of those barriers through an empirical test of the relevance on ACSC hospitalisation rates of factors that can be grouped in the access dimensions of that framework. We examine data of hospitalisations in public hospitals and characteristics of the public primary care delivery system in small areas of Portugal in 2014, estimating two models by ordinary least squares: one with variables that capture specific aspects of access and one without such variables. We then compared the predictive power of the two models. Although data on specific access barriers are scarce, results show that a model with access variables explains 70% of the variation in ACSC hospitalisation rates, 11 percentage points more than a model without such variables. Our results suggest that increasing resources do not seem to necessarily enhance patient access to care. Other factors, such as reduced travel time and long-term patient-doctor ties, arise as more important in reducing unnecessary hospitalisations. Thus, the solution for increasing the access to primary health care and reducing disparities among small areas seems to lie more in organisational changes than in allocation of resources.

Reflecting on Evidence Based Medicine, Person Centered Medicine and Small Area Variations: how contemporary frameworks for medicine address (or not) the needs of the individual patient

Over the past few decades the medical literature has given much attention to three movements: Evidence Based Medicine (EBM), Person Centered Medicine (PCM) and Small Area Variations (SAV). Each claims to provide a framework for improving the care of individual patients. This paper examines why attention to the individual patient is important in the provision and delivery of healthcare and how each of these movements seek to address individual patient needs. We suggest that EBM, PCM and SAV all suffer from a number of issues that render their use as a framework to address individual patient needs inadequate. In the case of EBM, it is a reliance on (at best) population level study (e.g., clinical trials) that do not necessarily translate to individual patients. PCM appears to recognize the information requirements to care for individual patients, but is unclear on how that information can be obtained. Likewise, SAV is limited in that its methods do not discriminate between warranted and unwarranted variation and its reliance on the EBM approach in assessing what is the correct treatment for patients. This paper concludes that EBM, PCM and SAV are not solving the problem of how to provide care for individual patients. While we do not offer a solution here, it is only when we admit we do not have the answers to this problem that we can begin to look for a solution.

Hospitalizations and amputations for diabetes mellitus-trends and small-area variation in Germany

Hospitalizations and lower limb amputations related to diabetes mellitus (DM) are considered to be potentially avoidable. Appropriate outpatient care of diabetes prevents complications. Rates on potentially avoidable hospitalizations for diabetes are core indicators of the German diabetes surveillance program. International comparisons showed high hospitalization rates in Germany for both indicators. The objective of this analysis is to describe time trends on hospitalizations and inpatient lower limb amputations (major amputations) for DM. Furthermore, we analyze small area variations. Based on the German diagnosis related groups (DRGs) dataset we calculated age-standardized rates covering 2005-2015. Calculations rely on the Organisation for Economic Co-operation and Development (OECD) indicator definitions. Time trends are obtained by linear regression modelling. We also stratified into age groups and analyzed 2015 small-area variations using age-adjusted rates. Crude hospitalization rates were 310admissions per 100,000inhabitants in men (amputation rate: 15.6) and 216 admissions per 100,000inhabitants in women (amputation rate: 7.1) in 2015. Age-adjusted hospitalizations and amputations rates in women decreased over time (10.3 and 1.2cases per 100,000inhabitants and year, respectively). In men, the amputation rate decreased significantly (1.5cases per 100,000inhabitants and year). We found higher rates for men than for women in almost all age categories. In eastern Germany and parts of Bavaria and North Rhine-Westphalia rates are particularly high. Adecrease in hospitalization rates may indicate improvements in ambulatory diabetes care over time. Future studies should consider age-specific differences and small-area variations.

Variations in osteoporosis medication utilization. A population-based ecological cross-sectional study in the region of Valencia, Spain

Little is known about the contextual variability in osteoporosis medication utilization. Our aims were 1) to describe variations in utilization and spending on osteoporotic medication between the Primary Care Health Zones (PHZ) of the Valencia region, Spain, 2) to analyze observed variations using Small Area Variation Analysis methods, and 3) to quantify the influence of the specialized care level on variations in utilization. We conducted a population-based cross-sectional ecological study of expenditure and utilization of five therapeutic groups marketed as osteoporosis treatments in Spain in 2009. The unit of analysis was the PHZ (in total 240) nested in the 23 Hospital Healthcare Departments (HHD) of the region of Valencia, covering a population of about 4.9 million inhabitants. Drug utilization was measured by dispensed Defined Daily Dose per 1000 women aged 50 years old and over and day (DID) per PHZ and cost was measured by the annual osteoporosis drug cost per woman aged 50 and older as well as the average price of DDD (Defined Daily Dose) in each PHZ. We calculated Indirect Standardized Drug Utilization Ratios (ISR) and we used Spearman’s correlation to analyze associations between the ISRs of the different therapies. The average osteoporosis drug consumption was 119.1 DID, ranging from 77.6 to 171.3 DID (2.2 times higher) between PHZs in the 5th and 95th percentiles. Annual expenditure also showed a two-fold variation among PHZs. Average prices of the DDD by therapeutic group showed very low or no variation, although they differed substantially among therapeutic groups. Regarding the standardized consumption of osteoporotic drugs, HHDs explained a substantial part (39%) of the variance among PHZs. In conclusion, there is considerable variability in the volume and choice of anti-osteoporotic treatments between PHZs. with HHDs explaining an important proportion of the variation in utilization. Interventions aimed at reducing variation to improve appropriate care should take into account both the PHZ and HHD levels of care.

Neighborhood characteristics and violence behind closed doors: The spatial overlap of child maltreatment and intimate partner violence.

In this study, we analyze first whether there is a common spatial distribution of child maltreatment (CM) and intimate partner violence (IPV), and second, whether the risks of CM and IPV are influenced by the same neighborhood characteristics, and if these risks spatially overlap. To this end we used geocoded data of CM referrals (N = 588) and IPV incidents (N = 1450) in the city of Valencia (Spain). As neighborhood proxies, we used 552 census block groups. Neighborhood characteristics analyzed at the aggregated level (census block groups) were: Neighborhood concentrated disadvantage (neighborhood economic status, neighborhood education level, and policing activity), immigrant concentration, and residential instability. A Bayesian joint modeling approach was used to examine the spatial distribution of CM and IPV, and a Bayesian random-effects modeling approach was used to analyze the influence of neighborhood-level characteristics on small-area variations of CM and IPV risks. For CM, 98% of the total between-area variation in risk was captured by a shared spatial component, while for IPV the shared component was 77%. The risks of CM and IPV were higher in neighborhoods characterized by lower levels of economic status and education, and higher levels of policing activity, immigrant concentration, and residential instability. The correlation between the log relative risk of CM and IPV was .85. Most census block groups had either low or high risks in both outcomes (with only 10.5% of the areas with mismatched risks). These results show that certain neighborhood characteristics are associated with an increase in the risk of family violence, regardless of whether this violence is against children or against intimate partners. Identifying these high-risk areas can inform a more integrated community-level response to both types of family violence. Future research should consider a community-level approach to address both types of family violence, as opposed to individual-level intervention addressing each type of violence separately.

An exploratory analysis of spatial variations in organ donation registration rates in Wales prior to the implementation of the Human Transplantation (Wales) Act 2013

Spatial variations in rates of registered organ donors have not been studied in the UK at detailed spatial scales despite some evidence of national and regional differences. By drawing on the findings from the existing literature, this study examines associations between small-area variations in rates of new registrants to the UK organ donor register (ODR) within Wales and key demographic factors. Using map-based visualisations and statistical regression methods, spatial patterns in new registrants to the ODR are identified within Wales, a country which moved to an opt-out system of consent for organ donation following the Human Transplantation (Wales) Act 2013. By identifying the underlying factors associated with trends in rates of new ODR sign-up, this study aims to highlight the types of approaches that could be used to help to inform future targeted interventions aimed at improving registration rates.

Shiga toxigenic Escherichia coli incidence is related to small area variation in cattle density in a region in Ireland

Shiga toxigenic Escherichia coli (STEC) are pathogenic E. coli that cause infectious diarrhoea. In some cases infection may be complicated by renal failure and death. The incidence of human infection with STEC in Ireland is the highest in Europe. The objective of the study was to examine the spatial incidence of human STEC infection in a region of Ireland with significantly higher rates of STEC incidence than the national average and to identify possible risk factors of STEC incidence at area level. Anonymised laboratory records (n = 379) from 2009 to 2015 were obtained from laboratories serving three counties in the West of Ireland. Data included location and sample date. Population and electoral division (ED) data were obtained from the Irish 2011 Census of Population. STEC incidence was calculated for each ED (n = 498) and used to map hotspots/coldspots using the Getis-Ord Gi* spatial statistic and significant spatial clustering using the Anselin's Local Moran's I statistic. Multivariable regression analysis was used to consider the importance of a number of potential predictors of STEC incidence. Incidence rates for the seven-year period ranged from 0 to 10.9 cases per 1000. A number of areas with significant local clustering of STEC incidence as well as variation in the spatial distribution of the two main serogroups associated with disease in the region i.e. O26 and O157 were identified. Cattle density was found to be a statistically significant predictor of STEC in the region. GIS analysis of routine data indicates that cattle density is associated STEC infection in this high incidence region. This finding points to the importance of agricultural practices for human health and the importance of a “one-health” approach to public policy in relation to agriculture, health and environment.

Forecasting Daily Streamflow for Basins with Different Physical Characteristics through Data-Driven Methods

Modelling streamflow is essential for activities, such as flood control, drought mitigation, and water resources utilization and management. Artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machines (SVM) are techniques that are frequently used in hydrology to specifically model streamflow. This study compares the accuracy of ANN, ANFIS, and SVM in forecasting the daily streamflow with the traditional approach known as autoregressive (AR) model for basins with different physical characteristics. The accuracies of the models are compared for three basins, that is, 1801, 1805, and 1822, at the Seyhan River Basin in Turkey. The comparison was performed by using coefficient of efficiency, index of agreement, and root-mean-square error. Results indicate that ANN and ANFIS are more accurate than AR and SVM for all the basins. ANN and ANFIS perform similarly, while ANN outperformed ANFIS. Among the models used, the ANN demonstrates the highest performance in forecasting the peak flood values. This study also finds that physical characteristics, such as small area, high slope, and high elevation variation, and streamflow variance deteriorate the accuracy of the methods.

Variation in Antiosteoporotic Drug Prescribing and Spending Across Spain. A Population-Based Ecological Cross-Sectional Study.

Introduction: Evidence has shown that utilization of antiosteoporotic medications does not correspond with risk, and studies on other therapies have shown that adequacy of pharmaceutical prescribing might vary between regions. Nevertheless, very few studies have addressed the variability in osteoporotic drug consumption. We aimed to describe variations in pharmaceutical utilization and spending on osteoporotic drugs between Health Areas (HA) in Spain.Methods: Population-based cross-sectional ecological study of expenditure and utilization of the five therapeutic groups marketed for osteoporosis treatment in Spain in 2009. Small area variation analysis (SAVA) methods were used. The units of analysis were the 168 HA of 13 Spanish regions, including 7.2 million women aged 50 years and older. The main outcomes were the defined daily dose (DDD) per 1000 inhabitants and day (DDD/1000/Day) dispensed according to the pharmaceutical claims reimbursed, and the expenditure on antiosteoporotics at retail price per woman ≥50 years old and per year.Results: The average osteoporosis drug consumption was 116.8 DDD/1000W/Day, ranging from 78.5 to 158.7 DDD/1000W/Day between the HAs in the 5th and 95th percentiles. Seventy-five percent of the antiosteoporotics consumed was bisphosphonates, followed by raloxifene, strontium ranelate, calcitonins, and parathyroid hormones including teriparatide. Regarding variability by therapeutic groups, biphosphonates showed the lowest variation, while calcitonins and parathyroid hormones showed the highest variation. The annual expenditure on antiosteoporotics was €426.5 million, translating into an expenditure of €59.2 for each woman ≥50 years old and varying between €38.1 and €83.3 between HAs in the 5th and 95th percentiles. Biphosphonates, despite accounting for 79% of utilization, only represented 63% of total expenditure, while parathyroid hormones with only 1.6% of utilization accounted for 15% of the pharmaceutical spending.Conclusion: This study highlights a marked geographical variation in the prescription of antiosteoporotics, being more pronounced in the case of costly drugs such as parathyroid hormones. The differences in rates of prescribing explained almost all of the variance in drug spending, suggesting that the difference in prescription volume between territories, and not the price of the drugs, is the main source of variation in this setting. Data on geographical variation of prescription can help guide policy proposals for targeting areas with inadequate antiosteoporotic drug use.

Inequality in oral anticoagulation use and clinical outcomes in atrial fibrillation: a Danish nationwide perspective.

To explore the potential of small-area variation analysis as a tool for identifying unwarranted variation in oral anticoagulation (OAC) use and clinical outcomes in patients with atrial fibrillation (AF) and thereby identify locations with opportunity for improvement in AF care. Based on Danish health care registries, we conducted a nationwide historical cohort study including first-time AF patients with a CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75, diabetes, thromboembolism, vascular disease, age 65-74, and sex category) score ≥ 2 between 2007 and 2014 (n = 94482). For each administrative region and municipality, we assessed OAC initiation and persistence as well as the risk of ischaemic stroke, haemorrhagic stroke, and other major bleeding, respectively. In addition, potential temporal changes were examined for all outcomes. Initiation of OAC varied among regions from 49.5% to 62.4%. In patients initiating OAC, the proportion of patients still receiving OAC after 1 year varied from 73.9% to 79.3%. Oral anticoagulation use increased in all regions during the study period, particularly after 2010, but regional variation in OAC initiation persisted. Generally, the regions and municipalities with the highest initiation of OAC also had the highest OAC persistence. The risk of ischaemic stroke and other major bleeding was lower in these regions and municipalities. We found no significant difference between regions in risk of haemorrhagic stroke. Substantial geographical variation in OAC use and clinical outcomes occurs in Denmark demonstrating the potential of small-area variation analysis as a tool for identifying unwarranted variation in AF care and clinical outcomes. Our findings demonstrate the need for additional initiatives to ensure uniform high-quality care for AF patients.

Small-area variations in overweight and obesity in an urban area of Nigeria: The role of fast food outlets

Abstract Overweight and obesity are two related health issues of epidemic proportions. In Nigeria, these health conditions have been emerging only recently. The extant literature shows inter-city variations in the prevalence of overweight and obesity in Nigeria. However, they say little about intra-city variations of these health problems in Nigerian urban centres. Thus, the focus of the study was to determine the small-area variations in the prevalence of overweight and obesity in an urban area of Nigeria and its association with socio-economic, environmental, dietary and lifestyle risk factors. With the aid of a questionnaire, information on the demographic, socio-economic, lifestyle, household and neighbourhood characteristics of respondents was obtained from respondents. Overweight and obesity were computed based on the self-reported height and weight of respondents, using the Body Mass Index (BMI) formula. A simple linear regression model was estimated to determine the individual and collective effects of risk factors. Findings showed that there were noticeable spatial variations in the prevalence of overweight and obesity which result from the varying contextual and compositional characteristics among the political wards of the Ibadan North LGA. Physical proximity to fast food outlets was the only significant factor driving the spatial pattern of obesity (b = 0.645; R2 = 0.416). The paper suggests that government and health officials should formulate area-specific obesity prevention and control plans to curb this growing epidemic in Nigeria.

Spatial variation in cancer incidence and survival over time across Queensland, Australia

Interpreting changes over time in small-area variation in cancer survival, in light of changes in cancer incidence, aids understanding progress in cancer control, yet few space–time analyses have considered both measures. Bayesian space–time hierarchical models were applied to Queensland Cancer Registry data to examine geographical changes in cancer incidence and relative survival over time for the five most common cancers (colorectal, melanoma, lung, breast, prostate) diagnosed during 1997–2004 and 2005–2012 across 516 Queensland residential small-areas. Large variation in both cancer incidence and survival was observed. Survival improvements were fairly consistent across the state, although small for lung cancer. Incidence changes varied by location and cancer type, ranging from lung and colorectal cancers remaining relatively constant over time, to prostate cancer dramatically increasing across the entire state. Reducing disparities in cancer-related outcomes remains a health priority, and space–time modelling of different measures provides an important mechanism by which to monitor progress.

Integrating national surveys to estimate small area variations in poor health and limiting long-term illness in Great Britain

ObjectivesThis study aims to address, for the first time, the challenges of constructing small area estimates of health status using linked national surveys. The study also seeks to assess the...

Small-Area Variation of Fertility Rates

Alike most of the Western world, the Danish fertility rate declined throughout the 20th century simultaneous to economic growth. This development, which conflicts with economic intuition, has been denoted the fertility paradox, and several studies have been devoted to resolve it. The present study analyzes the geographic variation across Danish municipalities in the fertility rate during the years 1982 to 2004. Several factors commonly believed to explain the variation in the fertility rate is found to be exerted to considerable regional variation. A model linking the fertility rate to several economic determinants is established and further modified to capture geographic small-area variation. Specifically, a positive correlation between regional levels of income and fertility is found, which contradicts the fertility paradox. Thus, the necessity of separating small-area and dynamic variation, aiming at obtain a proper interpretation of the link between fertility and its determinants, is demonstrated.

Asymptotic random extremal ratio and product based on generalized order statistics and its dual

ABSTRACTThe extremal ratio has been used in several fields, most notably in industrial quality control, life testing, small-area variation analysis, and the classical heterogeneity of variance situation. In many biological, agricultural, military activity problems and in some quality control problems, it is almost impossible to have a fixed sample size, because some observations are always lost for various reasons. Therefore, the sample size itself is considered frequently to be an random variable (rv). Generalized order statistics (GOS) have been introduced as a unifying theme for several models of ascendingly ordered rvs. The concept of dual generalized order statistics (DGOS) is introduced to enable a common approach to descendingly ordered rvs. In this article, the limit dfs are obtained for the extremal ratio and product with random indices under non random normalization based on GOS and DGOS. Moreover, this article considers the conditions under which the cases of random and non random indices give the same asymptotic results. Some illustrative examples are obtained, which lend further support to our theoretical results.

Small area variation in the utilization of common medical tests and consultations in Ontario, Canada

ABSTRACT
 ObjectiveEvidence of regional variation in the utilization of medical tests and procedures has raised concern surrounding the potential overuse of unnecessary care. Such overuse is detrimental as it may lead to overdiagnosis, and the resulting overtreatment of indolent disease, inefficient use of resources, and rising healthcare costs. The purpose of this study was to explore small area variation in rates of commonly used laboratory, imaging, and cardiac tests and specialist consultations, and to identify factors associated with rate variations.
 ApproachThis is a population-based cross-sectional study in Ontario, Canada using linked, administrative databases from the Institute for Clinical Evaluative Sciences (ICES). The study population was all adults aged 40 to 75 as of January 1, 2008. We measured the age- and sex-standardized rates of 36 laboratory, imaging and cardiac tests and specialist consultations across 97 health regions in 2008 using physician and laboratory billing data. The list of tests and consultations was chosen through discussion with primary care physicians to identify procedures that are commonly used and potentially overused in primary care settings. We compared the small area rates to the Ontario rate. We calculated small area variation statistics, including the extremal quotient (EQ), coefficient of variation (CV) and systematic component of variance (SCV), for each test and consult. We used multivariable regression models to identify factors associated with health area utilization rates.
 ResultsAt minimum, a 10-fold difference was observed in the rates of each test and consult across the 97 health regions in Ontario, with the extremal quotients ranging from 13.6 to 54.9. When ranked in highest to lowest variation using the SCV, the tests and procedures with the greatest small area variation were limb computed tomography (EQ=49.6, CV=23.3, SCV=38.9), ferritin blood tests (EQ=42.7, CV=33.4, SCV=36.8) and vitamin B12 blood tests (EQ=40.9, CV=35.9, SCV=36.0). The test with the smallest variation was knee imaging (EQ=13.6, CV=2.1, SCV=1.7).
 ConclusionWe observed substantial variation across Ontario in the utilization of 36 medical tests and consultations. These findings may indicate problems with access to care in areas with low utilization, or overuse of potentially inappropriate or unnecessary medical care in areas with high utilization. Ongoing analyses are exploring determinants of area-level utilization to better understand the observed rate variations.

Disparities in Potentially Preventable Hospitalizations: Near-National Estimates for Hispanics.

To obtain near-national rates of potentially preventable hospitalization (PPH)-a marker of barriers to outpatient care access-for Hispanics; to examine their differences from other race-ethnic groups and by Hispanic national origin; and to identify key mediating factors. Data from all-payer inpatient discharge databases for 15 states accounting for 85 percent of Hispanics nationally. Combining counts of inpatient discharges with census population for adults aged 18 and older, we estimated age-sex-adjusted PPH rates. We examined county-level variation in race-ethnic disparities in these rates to identify the mediating role of area-level indicators of chronic condition prevalence, socioeconomic status (SES), health care access, acculturation, and provider availability. Age-sex-adjusted PPH rates were 13 percent higher among Hispanics (1,375 per 100,000 adults) and 111 percent higher among blacks (2,578) compared to whites (1,221). Among Hispanics, these rates were relatively higher in areas with predominantly Puerto Rican and Cuban Americans than in areas with Hispanics of other nationalities. Small area variation in chronic condition prevalence and SES fully accounted for the higher rates among Hispanics, but only partially among blacks. Hispanics and blacks face higher barriers to outpatient care access; the higher barriers among Hispanics (but not blacks) seem mediated by SES, lack of insurance, cost barriers, and limited provider availability.

A study on modeling nitrogen dioxide concentrations using land-use regression and conventionally used exposure assessment methods

The land-use regression (LUR) approach to estimate the levels of ambient air pollutants is becoming popular due to its high validity in predicting small-area variations. However, only a few studies have been conducted in Asian countries, and much less research has been conducted on comparing the performances and applied estimates of different exposure assessments including LUR. The main objectives of the current study were to conduct nitrogen dioxide (NO2) exposure assessment with four methods including LUR in the Republic of Korea, to compare the model performances, and to estimate the empirical NO2 exposures of a cohort.The study population was defined as the year 2010 participants of a government-supported cohort established for bio-monitoring in Ulsan, Republic of Korea. The annual ambient NO2 exposures of the 969 study participants were estimated with LUR, nearest station, inverse distance weighting, and ordinary kriging. Modeling was based on the annual NO2 average, traffic-related data, land-use data, and altitude of the 13 regularly monitored stations.The final LUR model indicated that area of transportation, distance to residential area, and area of wetland were important predictors of NO2. The LUR model explained 85.8% of the variation observed in the 13 monitoring stations of the year 2009. The LUR model outperformed the others based on leave-one out cross-validation comparing the correlations and root-mean square error. All NO2 estimates ranged from 11.3–18.0 ppb, with that of LUR having the widest range. The NO2 exposure levels of the residents differed by demographics. However, the average was below the national annual guidelines of the Republic of Korea (30 ppb).The LUR models showed high performances in an industrial city in the Republic of Korea, despite the small sample size and limited data. Our findings suggest that the LUR method may be useful in similar settings in Asian countries where the target region is small and availability of data is low.