Geographic analysis of low birthweight and infant mortality in Michigan using automated zoning methodology

Developing Geographic Areas for Cancer Reporting Using Automated Zone Design

The reporting and analysis of population-based cancer statistics in the United States has traditionally been done for counties. However, counties are not ideal for analysis of cancer rates, due to wide variation in population size, with larger counties having considerable sociodemographic variation within their borders and sparsely populated counties having less reliable estimates of cancer rates that are often suppressed due to confidentiality concerns. There is a need and an opportunity to utilize zone design procedures in the context of cancer surveillance to generate coherent, statistically stable geographic units that are more optimal for cancer reporting and analysis than counties. To achieve this goal, we sought to create areas within each US state that are: 1) similar in population size and large enough to minimize rate suppression; 2) sociodemographically homogeneous; 3) compact; and 4) custom crafted to represent areas that are meaningful to cancer registries and stakeholders. The resulting geographic units reveal the heterogeneity of rates that are hidden when reported at the county-level while substantially reducing the need to suppress data. We believe this effort will facilitate more meaningful comparative analysis of cancer rates for small geographic areas and will advance the understanding of cancer burden in the United States.

Geovisualization and Spatial Analysis of Infant Mortality and Preterm Birth in Ohio, 2008-2015: Opportunities to Enhance Spatial Thinking

OBJECTIVES

Geovisualization and spatial analysis are valuable tools for exploring and evaluating the complex social, economic, and environmental interactions that lead to spatial inequalities in health. The objective of this study was to describe spatial patterns of infant mortality and preterm birth in Ohio by using interactive mapping and spatial analysis.

METHODS

We conducted a retrospective cohort study using Ohio vital statistics records from 2008-2015. We geocoded live births and infant deaths by using residential address at birth. We used multivariable logistic regression to adjust spatial and space-time cluster analyses that examined the geographic clustering of infant mortality and preterm birth and changes in spatial distribution over time.

RESULTS

The overall infant mortality rate in Ohio during the study period was 6.55 per 1000 births; of 1 097 507 births, 10.3% (n = 112 552) were preterm. We found significant geographic clustering of both infant mortality and preterm birth centered on large urban areas. However, when known demographic risk factors were taken into account, urban clusters disappeared and, for preterm birth, new rural clusters appeared.

CONCLUSIONS

Although many public health agencies have the capacity to create maps of health outcomes, complex spatial analysis and geovisualization techniques are still challenging for public health practitioners to use and understand. We found that actively engaging policymakers in reviewing results of the cluster analysis improved understanding of the processes driving spatial patterns of birth outcomes in the state.

City-Specific Spatiotemporal Infant and Neonatal Mortality Clusters: Links with Socioeconomic and Air Pollution Spatial Patterns in France

Infant and neonatal mortality indicators are known to vary geographically, possibly as a result of socioeconomic and environmental inequalities. To better understand how these factors contribute to spatial and temporal patterns, we conducted a French ecological study comparing two time periods between 2002 and 2009 for three (purposefully distinct) Metropolitan Areas (MAs) and the city of Paris, using the French census block of parental residence as the geographic unit of analysis. We identified areas of excess risk and assessed the role of neighborhood deprivation and average nitrogen dioxide concentrations using generalized additive models to generate maps smoothed on longitude and latitude. Comparison of the two time periods indicated that statistically significant areas of elevated infant and neonatal mortality shifted northwards for the city of Paris, are present only in the earlier time period for Lille MA, only in the later time period for Lyon MA, and decrease over time for Marseille MA. These city-specific geographic patterns in neonatal and infant mortality are largely explained by socioeconomic and environmental inequalities. Spatial analysis can be a useful tool for understanding how risk factors contribute to disparities in health outcomes ranging from infant mortality to infectious disease-a leading cause of infant mortality.

Aspectos epidemiológicos da mortalidade por câncer de boca: conhecendo os riscos para possibilitar a detecção precoce das alterações na comunicação

Resumo:OBJETIVOS:caracterizar os aspectos epidemiológicos da mortalidade por câncer de boca, no município de Olinda, no período de 2008 a 2012.MÉTODOS:foi realizado um estudo epidemiológico, de base populacional, do tipo seccional, a partir dos dados do Sistema de Informação de Mortalidade dos óbitos por câncer de boca no período de 2008 a 2012, em residentes de Olinda. Foi calculado o coeficiente de mortalidade específico por câncer de boca, e foram analisadas as variáveis sexo, faixa etária, raça/cor, grau de instrução, estado civil, ocupação, sitio anatômico do câncer e local de ocorrência do óbito, e as diferenças percentuais foram testadas pelo Qui-quadrado corrigido de Yates (α=5%). Foi mensurada a razão de prevalência (α=5%).RESULTADOS:ocorreram 87 óbitos por câncer de boca, perfazendo um coeficiente de mortalidade específico de 21,5/ 100.000 habitantes. Houve predomínio dos óbitos entre homens, não casados, em pretos ou pardos, com ocupação não braçal, escolaridade inferior a 7 anos de estudo, com localização anatômica do tumor em faringe e língua (p<0,005). As maiores razões de prevalência foram encontradas entre os homens (RP=3,43), em trabalhadores braçais (RP= 2,86) e nos casos em que o câncer ocorreu no palato (RP=4,5).CONCLUSÃO:a identificação dos aspectos epidemiológicos que apresentam os maiores riscos para a mortalidade por câncer de boca orientará o planejamento das intervenções em saúde e em Fonoaudiologia.

Estimating areas of common risk in low birth weight and infant mortality in Namibia: a joint spatial analysis at sub-regional level

There is lots of literature documenting a positive association between low birth weight (LBW) and infant mortality (IM), however, little is known how the risk of LBW and IM are geographically co-distributed. We fitted joint spatial models of LBW and IM, and used data from Namibia, to examine their geographical variability. We used a Bayesian approach to measure and rank areas according to specific and shared risk of LBW and IM. Our findings show some degree of similarities in the spatial pattern of LBW and IM, with high risk in the central and north-eastern parts of the country. Results suggest a need for comprehensive programming of maternal and newborn interventions that reach areas of spatially concentrated risk of LBW and IM. It further presents an opportunity for generating hypotheses for further research aimed at improving child health, especially in higher risk constituencies thus identified.

Análise espacial da mortalidade infantil e adequação das informações vitais: uma proposta para definição de áreas prioritárias

Estudo ecológico que objetivou analisar a relação entre o comportamento espacial da mortalidade infantil e a adequação das informações vitais. Para avaliar a adequação das informações sobre nascimentos (Sinasc) e óbitos (SIM) do Ministério da Saúde foi utilizado um método, já validado, que é constituído por cinco indicadores calculados por município, segundo o porte populacional. Os municípios foram classificados em: informações vitais consolidadas, em fase de consolidação ou não consolidadas. Na análise espacial, foram gerados os Polígonos de Voronoi para minimizar os problemas de proximidade entre os municípios, e o índice de Moran local para identificação dos agregados espaciais de mortalidade infantil. Identificou-se que 76,6% dos municípios apresentaram informações vitais consolidadas. Houve formação de cluster para a mortalidade infantil em 34 municípios, formando três agregados espaciais. Verificou-se associação entre a adequação das informações vitais e o comportamento espacial da mortalidade infantil. As técnicas de geoestatística foram preditivas na identificação de agregados espaciais com informações vitais consolidadas. A proposta contribuirá para a melhoria da qualidade da informação e o planejamento de ações visando à redução da mortalidade infantil.

Geographic analysis of infant mortality in New Zealand, 1995-2008: an ethnicity perspective

OBJECTIVE

To detect spatial clusters of high infant mortality rates in New Zealand for Māori and non-Māori populations and verify if these clusters are stable over a certain time period (1995-2008) and similar between the two populations.

METHOD

We applied the Kulldorff's spatial scan statistics on data collected by New Zealand Ministry of Health (1995 to 2008) at the territorial local authorities (TLA) level. Kappa coefficient was used to assess the concordance between clusters obtained for Māori and non-Māori populations. T-test analyses were conducted to identify associations between spatial clusters and two predictors (population density and deprivation score).

RESULTS

There are some significant spatial clusters of infant mortality in New Zealand for both Māori and Non-Māori. The concordance of the cluster locations between the two populations is strong (kappa=0.77). Unsurprisingly, infant mortality clusters for both Māori and Non-Māori are associated with the deprivation score. The population density predictor is only significantly and positively associated with clusters obtained for the non-Māori population. After controlling for deprivation the presence of spatial clusters is all but eliminated.

CONCLUSIONS

Infant mortality patterns are geographically similar for both Māori and Non-Māori. However, there are differences geographically between the two populations after accounting for deprivation.

IMPLICATIONS

Health services that can affect infant mortality should be aware of the geographical differences across NZ. Deprivation is an important factor in explaining infant mortality rates and policies that ameliorate its effects should be pursued, as it is the major determinant of the geographical pattern of infant mortality in NZ.

Blood donation clusters in Québec, Canada (2003-2008): spatial variations according to sex and age

BACKGROUND AND OBJECTIVES

The detection of spatial clusters of blood donation rate is an important issue, especially for targeting spatial units with significantly low rates, where it could be possible to increase the numbers of donors. The objective of this study is to detect spatial clusters of high or low blood donation rate in Québec according to sex and age of the donors.

MATERIALS AND METHODS

Blood donation data were obtained from Héma-Québec over a period of 5 years. We aggregated these data for each of 101 municipalités regionales de comté (i.e. counties) for men, women and four age groups. To detect spatial high/low donation rate areas, we used the Kulldorff's scan statistics. Kappa coefficient was used to assess discordance between clusters obtained for the different groups (18-29, 30-39, 40-49, 50-59, 60-69 years old). T-test analyses were conducted to identify significant associations between spatial clusters and socio-economic variables.

RESULTS

The results indicate the presence of several geographical areas with high or low blood donation rates for each group. The size, the location and the socio-demographic profiles of low/high clusters vary according to sex and age categories.

CONCLUSION

The Kulldorff's scan statistics are an efficient tool to assess the blood donation performance across a country or even a specific region over a period of several years. In terms of strategic planning and monitoring, it can be used as a fully operational tool to target areas with significantly low rates (for all donors or specific demographic groups) in future blood donation campaigns.

Analysis of geographical disparities in temporal trends of health outcomes using space-time joinpoint regression

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.

How to choose geographical units in ecological studies: proposal and application to campylobacteriosis

In spatial epidemiology, the choice of an appropriate geographical unit of analysis is a key decision that will influence most aspects of the study. In this study, we proposed and applied a set of measurable criteria applicable for orienting the choice of geographical unit. Nine criteria were selected, covering many aspects such as biological relevance, communicability of results, ease of data access, distribution of exposure variables, cases and population, and shape of unit. These criteria were then applied to compare various geographical units derived from administrative, health services, and natural frameworks that could be used for the study of the spatial distribution of campylobacteriosis in the province of Quebec, Canada. In this study, municipality was the geographical unit that performed the best according to our assessment and given the specific objectives and time period of the study. Future research areas for optimizing the choice of geographical unit are discussed.

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: a multiscale joinpoint regression analysis

BACKGROUND

Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry.

METHODS

Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities.

RESULTS

State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males.

CONCLUSIONS

Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes.

Análise da distribuição espacial da mortalidade neonatal e de fatores associados, em Salvador, Bahia, Brasil, no período 2000-2006

Realizou-se estudo de agregados espaciais visando a identificar padrões na distribuição espacial da mortalidade neonatal, bem como fatores associados, em Salvador, Bahia, Brasil, 2000-2006. Foram construídos mapas temáticos e usadas técnicas para apreciação formal de dependência espacial. Mediante modelos de regressão linear múltipla (espacial e não espacial) verificou-se a relação entre distribuição espacial dessa mortalidade e fatores selecionados. Evidenciou-se autocorrelação espacial para a mortalidade neonatal (I = 0,17; p = 0,0100), não havendo, portanto, aleatoriedade em sua distribuição. Foi delineado um padrão espacial em que os maiores riscos (> 9,0/1.000 nascidos vivos) concentraram-se em áreas do centro e subúrbio, onde reside a população de menor condição socioeconômica, mostrando-se esta distribuição associada aos fatores de risco analisados. A proporção de nascidos vivos com baixo peso foi a única variável significativamente associada à mortalidade neonatal. Possivelmente, as condições de vida da população contribuíram para a desigual distribuição espacial da mortalidade neonatal nesse município.

The socio-spatial neighborhood estimation method: an approach to operationalizing the neighborhood concept

The literature on neighborhoods and health highlights the difficulty of operationalizing "neighborhood" in a conceptually and empirically valid manner. Most studies, however, continue to define neighborhoods using less theoretically relevant boundaries, risking erroneous inferences from poor measurement. We review an innovative methodology to address this problem, called the socio-spatial neighborhood estimation method (SNEM). To estimate neighborhood boundaries, researchers used a theoretically informed combination of qualitative GIS and on-the-ground observations in Texas City, Texas. Using data from a large sample, we assessed the SNEM-generated neighborhood units by comparing intra-class correlation coefficients (ICCs) and multi-level model parameter estimates of SNEM-based measures against those for census block groups and regular grid cells. ICCs and criterion-related validity evidence using SF-36 outcome measures indicate that the SNEM approach to operationalization could improve inferences based on neighborhoods and health research.

Spatial patterns of diabetes related health problems for vulnerable populations in Los Angeles

Background

Rates for Diabetes Mellitus continue to rise in most urban areas of the United States, with a disproportionate burden suffered by minorities and low income populations. This paper presents an approach that utilizes address level data to understand the geography of this disease by analyzing patients seeking diabetes care through an emergency department in a Los Angeles County hospital. The most vulnerable frequently use an emergency room as a common care access point, and such care is especially costly. A fine scale GIS analysis reveals hotspots of diabetes related health problems and provides output useful in a clinic setting. Indeed these results were used to support the work of a progressive diabetes clinic to guide management and intervention strategies.

Results

Hotspots of diabetes related health problems, including neurological and kidney issues were mapped for vulnerable populations in a central section of Los Angeles County. The resulting spatial grid of rates and significance were overlaid with new patient residential addresses attending an area clinic. In this way neighbourhood diabetes health characteristics are added to each patient's individual health record. Of the 29 patients, 4 were within statistically significant hotspots for at least one of the conditions being investigated.

Conclusions

Although exploratory in nature, this approach demonstrates a novel method to conduct GIS based investigations of urban diabetes while providing support to a progressive diabetes clinic looking for novel means of managing and intervention. In so doing, this analysis adds to a relatively small literature on fine scale GIS facilitated diabetes research. Similar data should be available for most hospitals, and with due consideration for preserving spatial confidentiality, analysis outputs such as those presented here should become more commonly employed in other investigations of chronic diseases.