Socioeconomic inequalities in mortality in Barcelona: A study based on census tracts (MEDEA Project)

Cano-Serral, Gemma; Azlor, Enric; Rodríguez-Sanz, Maica; Pasarín, M. Isabel; Martı́nez, José Miguel; Puigpinós, Rosa; Muntañer, Carles; Borrell, Carme

doi:10.1016/j.healthplace.2008.04.004

Cited by 20 publications

(17 citation statements)

References 36 publications

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“…Some studies have found that the smaller the geographical unit is, the more likely the population is to be homogenous, and that such units are therefore more appropriate for detecting health differences (Havard et al. 2007; Cano‐Serral et al. 2009).…”

Section: Discussionmentioning

confidence: 99%

Spatial analysis and privation index to identify urban areas with a high risk of lymphatic filariasis

Bonfim

Alves

Costa

et al. 2011

Tropical Med Int Health

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Summaryobjective To evaluate composite living conditions as indicators of urban areas with a higher risk of filariasis transmission.methods This was an ecological study in the municipality of Jaboatã o dos Guararapes, in Brazil. The analysis units were census tracts. The study was divided into three phases. First, data gathered during an epidemiological investigation were analysed. Secondly, living condition indicators were drawn up and the relationship between these indicators and microfilaremia prevalence rates was analysed. Thirdly, positive cases were georeferenced with a view to identifying spatial concentration using kernel intensity estimates. Two composite living condition indicators were calculated: a socio-environmental risk index (in the form of scores) and a social deprivation index (through principal-component factor analysis).results Of 23 673 individuals examined, 1.4% had microfilaremia. According to the two indicators, greater prevalence was found in the high-risk strata, and this association was confirmed by the kernel intensity estimates.conclusions Classification of census tracts into risk strata showed the relevance of socio-economic factors and environmental conditions in identifying priority areas in urban spaces for interventions by the surveillance services and in planning filariasis control. Spatial analysis also proved to be an important tool for building up a territorially based surveillance system. These indicators, used in association with spatial analysis, are an instrument to be used by the Global Programme to Eliminate Lymphatic Filariasis.keywords lymphatic filariasis, spatial analysis, socio-economic factors, risk index, control programs

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Section: Discussionmentioning

confidence: 99%

Spatial analysis and privation index to identify urban areas with a high risk of lymphatic filariasis

Bonfim

Alves

Costa

et al. 2011

Tropical Med Int Health

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“…This is a cross-sectional ecological study which forms part of the MEDEA project (Socio-economic and environmental inequalities in mortality in small areas of Spanish cities: http://www.proyectomedea.org/) (Barceló et al, 2008;Borrell et al, 2010;Cano-Serral et al, 2009;Domínguez-Berjón et al, 2008). The units of analysis are the census tracts of 10 Spanish cities (Alicante, Barcelona, Bilbao, Castellón, Córdoba, Madrid, Málaga, Sevilla, Valencia and Zaragoza) as defined in the 2001 Spanish Population and Housing Census.…”

Section: Designmentioning

confidence: 99%

“…For example, this is the case of Rome and some cities in England and Wales (Michelozzi et al, 1999;Middleton et al, 2006Middleton et al, , 2008. Studies in Spain have related socio-economic deprivation in small areas with total mortality (Cano-Serral et al, 2009;Domínguez-Berjón et al, 2005;Esnaola et al, 2006;Nolasco et al, 2004Nolasco et al, , 2009Ocaña-Riola et al, 2008), but none have analyse injuries mortality in small urban areas. Thus, the aim of the present study is to analyse socioeconomic inequalities in mortality due to injuries in small areas of Spanish cities.…”

Section: Introductionmentioning

confidence: 99%

Socio-economic inequalities in mortality due to injuries in small areas of ten cities in Spain (MEDEA Project)

Gotsens

Marí-Dell’Olmo

Martínez-Beneito³

et al. 2011

Accident Analysis & Prevention

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“…People from a lower economic class are at higher risk of cardiovascular disease (CVD) risk factors, morbidity and early death [14-16]. Both in Sweden and other countries, there is evidence on geographical inequalities in mortality and morbidity due to differences in social and material deprivation and the association between poor living conditions and health may differ by geographical context and socioeconomic conditions [17,18]. Owing to extensive epidemiological studies on cardiovascular disease (CVD) in Northern Sweden in 1980, it became apparent that Västerbotten county had developed the highest CVD mortality in Sweden [19].…”

Section: Introductionmentioning

confidence: 99%

Socioeconomic inequalities and body mass index in Västerbotten County, Sweden: a longitudinal study of life course influences over two decades

Padyab

Norberg

2014

International Journal for Equity in Health

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IntroductionLife course socioeconomic inequalities in heart disease, stroke and all-cause mortality are well studied in Sweden. However, few studies have sought to explain the mechanism for such associations mainly due to lack of longitudinal data with multiple measures of socioeconomic status (SES) across the life course. Given the population health concern about how socioeconomic inequality is related to poorer health, we aim to tackle obesity as one of the prime suspects that could explain the association between SES inequality and cardiovascular disease and consequently premature death. The aim of this study is to test which life course model best describes the association between socioeconomic disadvantage and obesity among 60 year old inhabitants of Västerbotten County in Northern Sweden.MethodsA birth cohort consisting of 3340 individuals born between 1930 and 1932 was studied. Body mass index (BMI) at the age of 60 and information on socioeconomic status at three stages of life (ages 40, 50, and 60 years) was collected. Independent samples t-test was used to compare BMI between advantaged and disadvantaged groups and one-way ANOVA was used to compare BMI among eight SES trajectories. We applied a structured modeling approach to examine three different hypothesized life course SES models (accumulation, critical period, and social mobility) in relation to BMI.ResultsWe found sex differences in the way that late adulthood socioeconomic disadvantage is associated with BMI among inhabitants of Northern Sweden. Our study suggests that social adversity in all stages of late adulthood is a particularly important indicator for addressing the social gradients in BMI among women in Northern Sweden and that unhealthy behaviors in terms of smoking and physical inactivity are insufficient to explain the relationships between social and lifestyle inequalities and BMI.ConclusionIn order for local authorities to develop informed preventive efforts, we suggest further research to identify modifiable risk factors across the life course which could explain this health inequality.

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Socioeconomic inequalities in mortality in Barcelona: A study based on census tracts (MEDEA Project)

Cited by 20 publications

References 36 publications

Spatial analysis and privation index to identify urban areas with a high risk of lymphatic filariasis

Spatial analysis and privation index to identify urban areas with a high risk of lymphatic filariasis

Socio-economic inequalities in mortality due to injuries in small areas of ten cities in Spain (MEDEA Project)

Socioeconomic inequalities and body mass index in Västerbotten County, Sweden: a longitudinal study of life course influences over two decades

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