Evidence map›Paper›PMID 30526556›Full record

ArticleBMC public health2018

Social determinants, health status and 10-year mortality among 10,906 older adults from the English longitudinal study of aging: the ATHLOS project.

Natasa Kollia, Francisco Félix Caballero, Albert Sánchez-Niubó, Stefanos Tyrovolas, José Luis Ayuso-Mateos, Josep Maria Haro, Somnath Chatterji, Demosthenes B Panagiotakos

Abstract read
In one paragraph

Article in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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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

8 authors.

Natasa KolliaDepartment of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 70 Eleftheriou Venizelou Ave, 176 61, Attica, Athens, Greece.
Francisco Félix CaballeroDepartment of Preventive Medicine, Public Health and Microbiology, Universidad Autónoma de Madrid, Madrid, Spain.
Albert Sánchez-NiubóInstituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Monforte de Lemos 3-5. Pabellón 11, 28029, Madrid, Spain.
Stefanos TyrovolasDepartment of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 70 Eleftheriou Venizelou Ave, 176 61, Attica, Athens, Greece.
José Luis Ayuso-MateosInstituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Monforte de Lemos 3-5. Pabellón 11, 28029, Madrid, Spain.
Josep Maria HaroInstituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Monforte de Lemos 3-5. Pabellón 11, 28029, Madrid, Spain.
Somnath ChatterjiDepartment of Health Metrics and Measurement, World Health Organization, Geneva, Switzerland.
Demosthenes B PanagiotakosDepartment of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 70 Eleftheriou Venizelou Ave, 176 61, Attica, Athens, Greece. dbpanag@hua.gr.ORCID http://orcid.org/0000-0001-8583-153X

Funding

European Union's Horizon 2020 635316World Health Organization 001
6 · The paper itself

Abstract

backgroundIn either rich or poor countries, people's health widely depends on the social conditions in which they live and work - the social determinants of health. The aim of the present work was to explore the association of educational and financial status with healthy aging and mortality.

methodsData from the English Longitudinal Study of Aging (ELSA) were studied (n = 10,906 participants, 64 ± 11 years, 55% women). A set of 45 self-reported health items and measured tests were used to generate a latent health metric reflecting levels of functioning referred to as health metric (higher values indicated better health status). Overall mortality after 10-years of follow-up (2002-2012) was recorded.

resultsBoth education and household wealth over time were positively associated with the health metric (p < 0.001) and negatively with overall mortality (p < 0.001). Lifestyle behaviors (i.e., physical activity, smoking habits and alcohol consumption) mediated the effect of education and household wealth on the health metric and the latter mediated their effect on overall mortality.

conclusionsIn conclusion, reducing socioeconomic disparities in health by improving the access to education and by providing financial opportunities should be among the priorities in improving the health of older adults.

Indexed as

Health Status DisparitiesSocial Determinants of HealthAgedEnglandFemaleHumansLongitudinal StudiesMaleMiddle AgedMortalitySocioeconomic FactorsEducationFinancial statusHealthHealthy agingMortalitySocial determinantsSocioeconomic

Identifiers

PMID30526556
PMCPMC6288914

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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.