Geostatistical predictive modeling for asthma and chronic obstructive pulmonary disease using socioeconomic and environmental determinants

Kumarihamy, R. M. K.; Tripathi, Nimisha

doi:10.1007/s10661-019-7417-0

Cited by 13 publications

(7 citation statements)

References 87 publications

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“…A cross-sectional study conducted in Jiading District from 2001 to 2010 found that arterial road density was significantly associated with the mortality of COPD (26). Proximity to roads (0-200 m) and road density are predictors for COPD morbidity in Kandy (27). A cohort study performed by Cakmak et al in Canada found that exposure to higher road density and proximity to major traffic roads were related to increased COPD mortality (28).…”

Section: Discussionmentioning

confidence: 99%

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Peng¹,

Zhang

Yu³

et al. 2021

Front. Public Health

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Background: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent.Methods: This study included mortality analysis and a case-control design by using the data extracted from the Mortality Registration System in Jiading District, Shanghai. Traditional logistic regression, geographically weighted logistic regression (GWLR), and spatial scan statistical analysis were performed to explore the geographic variation of COPD mortality and the possible influencing factors.Results: Traditional logistic regression showed that extreme lower temperature in the month prior to death, shorter distance to highway, lower GDP level were associated with increased COPD mortality. GWRL model further demonstrated obvious geographical discrepancies for the above associations. We additionally identified a significant cluster of low COPD mortality (OR = 0.36, P = 0.002) in the southwest region of Jiading District with a radius of 3.55 km by using the Bernoulli model. The geographical variation in age-standardized mortality rate for COPD in Jiading District was explained to a certain degree by these factors.Conclusion: The risk of COPD mortality in Jiading District showed obvious geographical variation, which were partially explained by the geographical variations in effects of the extreme low temperature in the month prior to death, residential proximity to highway, and GDP level.

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Section: Discussionmentioning

confidence: 99%

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Peng¹,

Zhang

Yu³

et al. 2021

Front. Public Health

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“…The studies on asthma and COPD conducted by Kauhl et al (2018), Kumarihamy et al (2019), andGuo et al (2021) reveal similar associations, con rming the suitability of GWR-like models opposed to global alternatives.…”

Section: Discussionmentioning

confidence: 82%

“…However, not all GWR approaches work equally well. In the study by Guo et al (2021) the geographical and temporal weighted regression (GTWR) outperformed the "traditional" GWR approaches (Kumarihamy et al, 2019;Kauhl et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…GWR models can assess underlying patterns of association, translated into a set of local regression outputs. These methods have been used recently in the eld of health geography, and previous studies on respiratory diseases, particularly asthma and COPD, have demonstrated their suitability for studying the spatial behavior of their prevalence using a DH approach (Kauhl et al, 2018;Kumarihamy et al, 2019;Guo et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

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Spatial Patterns in the Association between the Prevalence of Asthma and Chronic Obstructive Pulmonary Disease: Socioeconomic and Climate Indicators in a Mediterranean Region

Bentué

Mimbrero

González

et al. 2021

Preprint

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The World Health Organization endorses the study of diseases from the perspective of the Determinants of Health (DH). DH are known as the circumstances in which people are born and raised, the environment in which they grow up and age and their lifestyle. The aim of this study is to analyze the spatial behavior of the prevalence of chronic obstructive pulmonary disease (COPD) and asthma in 2017 in Aragon, a Mediterranean region in Spain, using a DH approach. The methodological process entailed building a spatial database collating sociodemographic and climate indicators, and then evaluating the spatial variability of the relationships between DH indicators and disease prevalence by combining the Principal Component Analysis (PCA), Geographically Weighted Regression (GWR) models and cartographic design techniques. GWR evidences both global and spatially varying relationships, although each prevalence behaves differently. Asthma seems closely tied to local climate patterns whereas COPD is largely influenced by the built environment. Consequently, the socioeconomic and climatic contrasts characterizing the study area translate into several DH scenarios leading to situations vulnerable to the prevalence of asthma and COPD. This differential DH behavior detected by local regression models is relevant to guiding and refining public health decision-making.

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“…These authors also found that along with the level of exposure to PM2.5, the impacts varied by age, race/ethnicity, and insurance, which contributed to asthma health disparities among children. Mudiyanselage and Tripathi (2019) employed different methodologies to examine the associations between asthma/COPD morbidity and their determinants. By analyzing individually and in combination, they explored the potential risk factors per meteorological factors, direct and indirect factors of air pollution, socioeconomic factors, and characteristics of the physical environment.…”

Section: Healthcare Pattern and Disparitiesmentioning

confidence: 99%

Geospatial technology in environmental health applications

Faruque

2019

Environ Monit Assess

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The associations of environmental factors with human health and well-being now can be more precisely analyzed than before. Several multidisciplinary achievements advanced our understanding of the continuum of Benvironment and health outcomes.^Investments in multidisciplinary initiatives led to the development of many new tools that can pinpoint environmental factors, human exposure, and health outcomes on a wide range of scales-from global to even an individual. As environmental factors and human interactions cannot be completely examined without accounting for their spatial components and relationships, the improvements in geospatial data quality, technology, and analytical tools are playing a critical role to advance our understanding of environmental factors affecting human health and well-being. However, at the same time, researchers must be aware of the limitations of spatial data and tools, while conducting their studies. This special issue covers a wide range of geospatial health-related topics and methods including the climate change, neglected tropical diseases, vector-borne diseases, smartphone technology, healthcare utilization, health disparities, air quality assessment, asthma, water quality assessment, antimicrobial resistance, and machine learning. After intense reviews and revisions, the following 23 papers were selected for publication. While in many instances, the topics and methodologies of the papers significantly overlap, a brief discussion about the papers is provided below under loosely aggregated categorizations. Research topics Climate Extreme weather and related phenomena appear to be rising in frequency and intensity which pose growing health risks to human populations. Liss and Naumova (2019) conducted spatio-temporal analyses to examine the association between hospitalizations due to heat stroke in older adults in the United States with respect to heatwave sequence, time of arrival, and regional climate. Analyzing 16 years of daily hospitalization records, the authors found substantial differences in heat-related hospitalizations and response to heatwaves in different climate regions of the USA. As heatwaves are one of the major manifestations of the growing events of extreme weather, the authors suggested that the findings of this study could be useful for prevention as well as for decision support framework for heat-related medical care, which would be more essentials in the coming years. Wrable and her colleagues (Wrable et al. 2019) analyzed 8 years of monthly reported schistosomiasis to

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Geostatistical predictive modeling for asthma and chronic obstructive pulmonary disease using socioeconomic and environmental determinants

Cited by 13 publications

References 87 publications

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Spatial Patterns in the Association between the Prevalence of Asthma and Chronic Obstructive Pulmonary Disease: Socioeconomic and Climate Indicators in a Mediterranean Region

Geospatial technology in environmental health applications

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