Evidence map›Paper›PMID 28977369›Full record

ArticleThe Gerontologist2018

A Cross-National Study of the Gender Gap in Health Among Older Adults in India and China: Similarities and Disparities.

Anna Oksuzyan, Prashant Kumar Singh, Kaare Christensen, Domantas Jasilionis

Abstract read
In one paragraph

Article in The Gerontologist, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. The landscape of dementia in India: Prevalence, risk factors, and opportunities ahead.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors.

Anna OksuzyanMax Planck Institute for Demographic Research, Rostock, Germany.
Prashant Kumar SinghDepartment of Policy Studies, TERI University, New Delhi, India.
Kaare ChristensenEpidemiology, Biostatistics, and Biodemography Unit, Odense.
Domantas JasilionisMax Planck Institute for Demographic Research, Rostock, Germany.

Funding

STATISTICAL DATA ENCLAVE COREP30AG012836 · NIA · UNIVERSITY OF PENNSYLVANIA · PI KOHLER, HANS-PETER · 1999 to 2024
$14.0M
STALLARD Admin Supp: Predicting Future Care Needs and Costs for Individual Medicare Enrollees with Incident Suspected Alzheimer's DiseaseP30AG034424 · NIA · DUKE UNIVERSITY · PI Tyson Brown · 2009 to 2026
$12.2M
THE RANGE OF MALE-FEMALE MORTALITY DIFFERENCESP01AG031719 · NIA · DUKE UNIVERSITY · PI VAUPEL, JAMES W. · 2009 to 2020
$10.2M
Biodemography of Disease and Death in MoscowR01AG026786 · NIA · DUKE UNIVERSITY · PI VAUPEL, JAMES W. · 2006 to 2010
$1.9M
Explanations of Racial Disparities in Active LifeR03HD050374 · NICHD · PRINCETON UNIVERSITY · PI LYNCH, SCOTT M · 2005 to 2006
$156k
NIA NIH HHS P01 AG031719NIA NIH HHS P30 AG012836NIA NIH HHS P30 AG034424NIA NIH HHS R01 AG026786NICHD NIH HHS R03 HD050374
6 · The paper itself

Abstract

Background and Objectives: The present cross-sectional study examines gender differences in three major health measures among older adults in India and in China, and investigates whether these differences can be explained by major sociodemographic and health risk characteristics. Research Design and Methods: The study included 7,150 individuals in India and 13,367 individuals in China aged 50-plus who participated in the WHO Study on Global AGEing and Adult Health in 2007-2010. Logistic regression models for self-reported health (SRH) and ordinary least square regression models for grip strength and cognitive function were used to investigate gender differences in health. Results: A consistent female disadvantage was found in India and in China for all three health measures. Compared to their male counterparts, women in the Indian and the Chinese samples had, respectively, 38% (95% confidence interval [CI]: 1.22, 1.56) and 36% (95% CI: 1.25, 1.48) higher risk of reporting poor SRH, 9.56 kg (95% CI: 9.91, 9.22) and 11.95 kg (95% CI: 12.29, 11.62) lower grip strength, and 3.64 (95% CI: 3.96, 3.32) and 1.99 (95% CI: 2.28, 1.71) lower cognitive scores. The magnitude of the female disadvantage in poor SRH and in grip strength changed very little when adjustments were made for marital status, education, place of residence, smoking status, height, and number of chronic conditions; but these characteristics accounted for about 50% of the gender gap in cognitive function. Discussion and Implications: In these study populations, major sociodemographic and health risk characteristics accounted for very small parts of the gender differences in health, except in cognition.

Indexed as

Cross-Cultural ComparisonHealth Status DisparitiesAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHealthcare DisparitiesHealth SurveysHumansIndiaMaleMiddle AgedSelf ReportSex FactorsSocioeconomic Factors

Identifiers

PMID28977369
PMCPMC6455934

What OpenQuestion holds

Textmetadata
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.