ArticleJournal of primary care & community health
The Impact of Biological and Social Factors on Mortality in Older Adults Living in Rural Communities.
Article in Journal of primary care & community health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Enhancing the Utility of Sleep-Related Symptoms as Predictors of Poor Cardiovascular Health: A Population Study in Middle-Aged and Older Adults Residing Near the Equator.Journal of primary care & community healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInformation on factors that increase mortality in remote settings is limited. This study aims to estimate the independent and joint role of several factors on mortality risk among older adults living in rural Ecuador.
methodsParticipants were selected from community-dwelling older adults who were included in previous studies targeting mortality risk factors in the study population. Generalized structural equation modeling (GSEM) was utilized to evaluate prior causal assumptions, to redraw causal links, and to introduce latent variables that may help to explain how the independently significant variables are associated with mortality.
resultsThe study included 590 individuals (mean age: 67.9 ± 7.3 years; 57% women), followed for a median of 8.2 years. Mortality rate was 3.4 per 100 person-years. Prior work on separate multivariate Poisson and Cox models was used to build a tentative causal construct. A GSEM containing all variables showed that age, symptoms of depression, high social risk, high fasting glucose, a history of overt stroke, and neck circumference were directly associated with mortality. Two latent variables were introduced, 1 representing the impact of biological factors and another, the impact of social factors on mortality. The social variable significantly influenced the biological variable which carried most of the direct effect on mortality.
conclusionsSeveral factors contributed to mortality risk in the study population, the most significant being biological factors which are highly influenced by social factors. High social risk interact with biological variables and play an important role in mortality risk.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.