Evidence map›Paper›PMID 27473140›Full record

ArticleBMC public health2016

Trends in socioeconomic inequalities in mortality in small areas of 33 Spanish cities.

Marc Marí-Dell'Olmo, Mercè Gotsens, Laia Palència, Maica Rodríguez-Sanz, Miguel A Martinez-Beneito, Mónica Ballesta, Montse Calvo, Lluís Cirera, Antonio Daponte, Felicitas Domínguez-Berjón and 8 more

Abstract read
In one paragraph

Article in BMC public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death.International journal of environmental research and public health · 2021
    Article
  3. Article
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  8. Article
  9. Tackling Health Inequalities Using Urban HEART in the Sustainable Development Goals Era.Journal of urban health : bulletin of the New York Academy of Medicine · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Marc Marí-Dell'OlmoCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. mmari@aspb.cat.
Mercè GotsensCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Laia PalènciaCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Maica Rodríguez-SanzCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Miguel A Martinez-BeneitoCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Mónica BallestaCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Montse CalvoEstudios e investigación Sanitaria, Departamento de Sanidad y Consumo, Gobierno Vasco, Vitoria-Gasteiz, Spain.
Lluís CireraCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Antonio DaponteCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Felicitas Domínguez-BerjónSubdirección de Promoción de la Salud y Prevención, Consejería de Sanidad, Comunidad de Madrid, Spain.
Ana GandarillasSubdirección de Promoción de la Salud y Prevención, Consejería de Sanidad, Comunidad de Madrid, Spain.
Natividad Izco GoñiRegistro de Mortalidad, Consejería de Salud y Servicios Sociales, La Rioja, Spain.
Carmen MartosInstituto Aragonés de Ciencias de la Salud, Zaragoza, Spain.
Conchi Moreno-IribasInstituto de Salud Pública de Navarra, Departamento de Salud, Gobierno de Navarra, Pamplona, Navarra, Spain.
Andreu NolascoUnidad de Investigación en Análisis de la Mortalidad y Estadísticas Sanitarias, Universidad de Alicante, San Vicente del Raspeig, Spain.
Diego SalmerónCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Margarita TaracidoCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
Carme BorrellCIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn Spain, several ecological studies have analyzed trends in socioeconomic inequalities in mortality from all causes in urban areas over time. However, the results of these studies are quite heterogeneous finding, in general, that inequalities decreased, or remained stable. Therefore, the objectives of this study are: (1) to identify trends in geographical inequalities in all-cause mortality in the census tracts of 33 Spanish cities between the two periods 1996-1998 and 2005-2007; (2) to analyse trends in the relationship between these geographical inequalities and socioeconomic deprivation; and (3) to obtain an overall measure which summarises the relationship found in each one of the cities and to analyse its variation over time.

methodsEcological study of trends with 2 cross-sectional cuts, corresponding to two periods of analysis: 1996-1998 and 2005-2007. Units of analysis were census tracts of the 33 Spanish cities. A deprivation index calculated for each census tracts in all cities was included as a covariate. A Bayesian hierarchical model was used to estimate smoothed Standardized Mortality Ratios (sSMR) by each census tract and period. The geographical distribution of these sSMR was represented using maps of septiles. In addition, two different Bayesian hierarchical models were used to measure the association between all-cause mortality and the deprivation index in each city and period, and by sex: (1) including the association as a fixed effect for each city; (2) including the association as random effects. In both models the data spatial structure can be controlled within each city. The association in each city was measured using relative risks (RR) and their 95 % credible intervals (95 % CI).

resultsFor most cities and in both sexes, mortality rates decline over time. For women, the mortality and deprivation patterns are similar in the first period, while in the second they are different for most cities. For men, RRs remain stable over time in 29 cities, in 3 diminish and in 1 increase. For women, in 30 cities, a non-significant change over time in RR is observed. However, in 4 cities RR diminishes. In overall terms, inequalities decrease (with a probability of 0.9) in both men (RR = 1.13, 95 % CI = 1.12-1.15 in the 1st period; RR = 1.11, 95 % CI = 1.09-1.13 in the 2nd period) and women (RR = 1.07, 95 % CI = 1.05-1.08 in the 1st period; RR = 1.04, 95 % CI = 1.02-1.06 in the 2nd period).

conclusionsIn the future, it is important to conduct further trend studies, allowing to monitoring trends in socioeconomic inequalities in mortality and to identify (among other things) temporal factors that may influence these inequalities.

Indexed as

Health Status DisparitiesAdolescentAdultAgedAged, 80 and overBayes TheoremCensusesChildChild, PreschoolCitiesCross-Sectional StudiesDemographyFemaleHumansInfantInfant, NewbornBayesian methodsDisease mappingGeographical inequalitiesInequalities in mortalityMortalityMultilevel analysisSmall areasSocioeconomic inequalitiesTrendsUrban areas

Identifiers

PMID27473140
PMCPMC4966571

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.