Evidence map›Paper›PMID 34817704›Full record

ArticleArchives of osteoporosis2021

Assessing the roles of demographic, social, economic, environmental, health-related, and political factors on risk of osteoporosis diagnosis among older adults.

Margaret Gough Courtney, Yadira Quintero, K Godde

Open access · greenAbstract read
In one paragraph

Article in Archives of osteoporosis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
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

10 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Health Insurance Coverage as a Social Determinant of Osteoporosis Diagnosis in a Population-Based Cohort Study of Older American Adults.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2023
    Article
  10. 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

3 authors at 1 institution in 1 country.

Margaret Gough CourtneyUniversity of La Verne, La Verne, CA, USA.
Yadira QuinteroUniversity of La Verne, La Verne, CA, USA.
K GoddeUniversity of La Verne, La Verne, CA, USA. kgodde@laverne.edu.
University of La Verne · US

Funding

THE GLOBAL BURDEN OF DISEASE 2000 IN AGING POPULATIONSP01AG017625 · NIA · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI MURRAY, CHRISTOPHER J.L. · 2000 to 2004
$9.4M
Adding Contextual Data to the Health and Retirement StudyR21AG045625 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI AILSHIRE, JENNIFER A, CRIMMINS, EILEEN M · 2013 to 2014
$447k
A Model of Accelerated Aging: Social, Political, Economic, Environmental, and Biological Factors' Effects on Osteoporosis, High Sensitivity C-Reactive Protein, and Telomere LengthR15AG063330 · NIA · UNIVERSITY OF LA VERNE · PI BROUSSARD, CHRISTINE ANN · 2020 to 2020
$390k
NIA NIH HHS P01 AG017625NIA NIH HHS R15 AG063330NIA NIH HHS R15AG063330NIA NIH HHS R21 AG045625
6 · The paper itself

Abstract

Chronic stress from social/environmental pressures has been proposed to affect bone health through increased inflammation. We demonstrate that inflammation from prolonged stress does not cause changes to bone health through inflammation but instead impacts access to health care, social inequalities, and overall health, which in turn impact bone health. PURPOSE: The study provides a comprehensive assessment of how determinants of health across demographic, psychological, mobility-related, health, environmental, and economic domains are associated with the diagnosis of osteoporosis and tests three hypotheses: (1) a diverse set of variables across domains will predict osteoporosis, (2) chronic inflammation as a result of stress (represented by high-sensitivity C-reactive protein) will not be associated with osteoporosis, and (3) the model developed will have high accuracy in predicting osteoporosis.

methodsLogistic regression and Cox proportional hazards models of osteoporosis diagnosis were estimated using data from 14,792 and 13,169 participants (depending on model) in the 2012-2016 waves of the Health and Retirement Study, including the Biomarker Study, the Contextual Data Resource, and validated measures of childhood socioeconomic status. Predictive accuracy was assessed using k-Nearest Neighbors Discriminant Analysis.

resultsDemographic, environmental, and health-related factors were associated with osteoporosis diagnosis, and predictive accuracy of the models was good. High-sensitivity C-reactive protein was not associated with osteoporosis diagnosis.

conclusionSocial determinants identified indicate access to health care, inequalities in the greater social environment (e.g., access to resources), and overall health (i.e., underlying medical conditions) are key components for developing osteoporosis and indicate underlying health inequities in this sample. There is a need to further address the interplay between primary health care and social determinants of health.

Indexed as

Health InequitiesOsteoporosisAgedEnvironmental HealthHumansPoliticsSocioeconomic FactorsAgingBiomarkersBone healthLongitudinal analysisSocial determinants of health

Identifiers

PMID34817704
PMCPMC8722370
OpenAlexW3215168595

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.