Development of a measure of multiple physical environmental deprivation. After United Kingdom and New Zealand, Portugal

Ribeiro, Ana Isabel; Pina, Maria de Fátima de; Mitchell, Richard

doi:10.1093/eurpub/cku242

Cited by 17 publications

(12 citation statements)

References 18 publications

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“…Yet, as we considered most POST items, it is unlikely those choices are driving our main results. Similarly, although dichotomization prior to index computation is a rather common procedure [ 80 , 81 , 82 ], this methodological approach is also arguable and might lead to some loss of information. Nevertheless, as most of POST items were originally dichotomous, we considered that this approach did not compromise our findings or conclusions.…”

Section: Discussionmentioning

confidence: 99%

Socioeconomic Inequalities in Green Space Quality and Accessibility—Evidence from a Southern European City

Hoffimann

Barros

Ribeiro

2017

IJERPH

226

112

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Background: The provision of green spaces is an important health promotion strategy to encourage physical activity and to improve population health. Green space provision has to be based on the principle of equity. This study investigated the presence of socioeconomic inequalities in geographic accessibility and quality of green spaces across Porto neighbourhoods (Portugal). Methods: Accessibility was evaluated using a Geographic Information System and all the green spaces were audited using the Public Open Space Tool. Kendall’s tau-b correlation coefficients and ordinal regression were used to test whether socioeconomic differences in green space quality and accessibility were statistically significant. Results: Although the majority of the neighbourhoods had an accessible green space, mean distance to green space increased with neighbourhood deprivation. Additionally, green spaces in the more deprived neighbourhoods presented significantly more safety concerns, signs of damage, lack of equipment to engage in active leisure activities, and had significantly less amenities such as seating, toilets, cafés, etc. Conclusions: Residents from low socioeconomic positions seem to suffer from a double jeopardy; they lack both individual and community resources. Our results have important planning implications and might contribute to understanding why deprived communities have lower physical activity levels and poorer health.

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Section: Discussionmentioning

confidence: 99%

Socioeconomic Inequalities in Green Space Quality and Accessibility—Evidence from a Southern European City

Hoffimann

Barros

Ribeiro

2017

IJERPH

226

112

View full text Add to dashboard Cite

show abstract

“…Both simple regression and Bayesian sparse spatial multilevel models were utilized to evaluate the relationship between lead exposure and both gonorrhea and chlamydia, accounting for other non-chemical stressors such as index of concentrated disadvantage [57]. Negative binomial regression models were used to examine associations between mortality and environmental factors including air pollution and drinking water quality with consideration to socioeconomic deprivation [62]. …”

Section: Resultsmentioning

confidence: 99%

Cumulative Risk and Impact Modeling on Environmental Chemical and Social Stressors

Huang

Wang

Morello‐Frosch

et al. 2018

Curr Envir Health Rpt

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There has been an increase in literature that evaluates combined effects of exposures to environmental chemicals and social stressors on health using regression models; very few studies applied other data mining and machine learning techniques to this problem. The majority of studies we identified used regression models to evaluate combined effects of multiple environmental and social stressors. With proper study design and appropriate modeling assumptions, additional data mining methods may be useful to examine combined effects of environmental and social stressors.

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“…Yet, several other studies have found that, compared to other aspects, namely socioeconomic conditions and access to healthcare, the physical environment play a less important role (Hood et al, 2016 ). Moreover, some investigations have shown that the exposure to harmful physical environments may be more strongly associated with specific causes of death, namely cancer, and not so strongly with overall mortality (Ribeiro et al, 2015 ). Regrettably, in our study we were not able to differentiate the causes of death.…”

Section: Discussionmentioning

confidence: 99%

“… Average the punctuations of the items to obtain a global dissatisfaction score and then average according to domain to obtain dissatisfaction scores by domain for each city. This method of generating punctuations and scores has been employed elsewhere (Ribeiro et al, 2015 ; Hoffimann et al, 2017 ) and allow to generate a measure of dissatisfaction based on rank position of each city in the sample distribution. …”

Section: Methodsmentioning

confidence: 99%

Residents' Dissatisfaction and All-Cause Mortality. Evidence from 74 European Cities

2018

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Background: About 2/3 of the Europeans reside in cities. Thus, we must expand our knowledge on how city characteristics affect health and well-being. Perceptions about cities' resources and functioning might be related with health, as they capture subjective experiences of the residents. We characterized the health status of 74 European cities, using all-cause mortality as indicator, and investigated the association of mortality with residents' dissatisfaction with key domains of urban living.Methods: We considered 74 European cities from 29 countries. Aggregated data on residents' dissatisfaction was obtained from the Flash Eurobarometer, Quality of life in European cities (2004–2015). For each city a global dissatisfaction score and a dissatisfaction score by domain (environment, social, economic, healthcare, and infrastructures/services) were calculated. Data on mortality and population was obtained from the Eurostat. Standardized Mortality Ratios, SMR, and 95% Confidence Intervals (95% CI) were calculated. The association between dissatisfaction scores and SMR was estimated using Generalized Linear Models.Results: SMR varied markedly (range: 73.2–146.5), being highest in Eastern Europe and lowest in the South and Western European cities. Residents' dissatisfaction levels also varied greatly. We found a significant association between city SMR and residents' dissatisfaction with healthcare (β = 0.334; IC 95% 0.030–0.639) and social environment (β = 0.239; IC 95% 0.015–0.464). No significant association was found with the dissatisfaction scores related with the physical and economic environment and the infrastructures/services.Conclusions: We found a significant association between city levels of mortality and residents' dissatisfaction with certain urban features, suggesting subjective assessments can be also used to comprehend urban health.

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Development of a measure of multiple physical environmental deprivation. After United Kingdom and New Zealand, Portugal

Abstract: The methods used to create UK and NZ indexes have good transferability to Portugal. MEDIx might contribute to untangle the complex pathways that link health, socioeconomic and physical environment.

Cited by 17 publications

References 18 publications

Socioeconomic Inequalities in Green Space Quality and Accessibility—Evidence from a Southern European City

Socioeconomic Inequalities in Green Space Quality and Accessibility—Evidence from a Southern European City

Cumulative Risk and Impact Modeling on Environmental Chemical and Social Stressors

Residents' Dissatisfaction and All-Cause Mortality. Evidence from 74 European Cities

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