Evidence map›Paper›PMID 39441596›Full record

ArticleJAMA network open2024

Prevalence, Phenotypes, and Comorbidities of Polycystic Ovary Syndrome Among Indian Women.

Mohd Ashraf Ganie, Subhankar Chowdhury, Neena Malhotra, Rakesh Sahay, Prasanta Kumar Bhattacharya, Sarita Agrawal, P K Jabbar, Vanita Suri, Roya Rozati, Vishnubhatla Sreenivas and 8 more

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Visceral adiposity and insulin resistance in polycystic ovarian syndrome - A cross-sectional, observational study.European journal of obstetrics & gynecology and reproductive biology: X · 2026
    Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Targeted metabolomics and fatty acid profiling in lean and obese polycystic ovarian syndrome patients: A pilot study.European journal of obstetrics & gynecology and reproductive biology: X · 2026
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Living with PCOS: A Narrative of its Biology, Diagnosis, and Evolving Treatment.Endocrine, metabolic & immune disorders drug targets · 2026
    Review
  18. Review
  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

18 authors.

Mohd Ashraf GanieDepartment of Endocrinology, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, India.
Subhankar ChowdhuryDepartment of Endocrinology Metabolism, Institute of Postgraduate Medical Education Research, Kolkata, India.
Neena MalhotraDepartment of Obstetrics and Gynaecology, All India Institute of Medical Sciences, New Delhi, India.
Rakesh SahayDepartment of Endocrinology, Osmania Medical College, Hyderabad, India.
Prasanta Kumar BhattacharyaDepartment of General Medicine, North-Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, India.
Sarita AgrawalDepartment of Obstetrics and Gynaecology, All India Institute of Medical Sciences, Raipur, India.
P K JabbarDepartment of Endocrinology, Government Medical College, Thiruvananthapuram, India.
Vanita SuriDepartment of Obstetrics and Gynaecology, Postgraduate Institute of Medical Education and Research, Chandigarh, India.
Roya RozatiDepartment of Obstetrics and Gynaecology, Maternal Health, Research Trust, Hyderabad, India.
Vishnubhatla SreenivasDepartment of Biostatistics, All India Institute of Medical Sciences, New Delhi, India.
Mohammad Salem BabaDepartment of Endocrinology, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, India.
Imtiyaz Ahmad WaniDepartment of Endocrinology, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, India.
Haroon RashidDepartment of Endocrinology, Sher-i-Kashmir Institute of Medical Sciences, Srinagar, India.
Abhilash NairDepartment of Endocrinology, Government Medical College, Thiruvananthapuram, India.
Amlin ShuklaReproductive Biology and Maternal Health, Child Health, Indian Council of Medical Research, New Delhi, India.
Taruna AroraReproductive Biology and Maternal Health, Child Health, Indian Council of Medical Research, New Delhi, India.
Bharati KulkarniReproductive Biology and Maternal Health, Child Health, Indian Council of Medical Research, New Delhi, India.
PCOS Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The prevalence of polycystic ovary syndrome (PCOS) varies across the globe. Indian studies on PCOS are limited by poor design, small sizes, regional representations, and varying methods. Objectives: To estimate the nationwide prevalence of PCOS in India, examine the phenotypic spectrum, and assess the magnitude of comorbidities associated with PCOS. Design, Setting, and Participants: This cross-sectional study recruited 9824 women aged 18 to 40 years from November 1, 2018, to July 31, 2022, across 5 zones of the country. A prevalidated questionnaire dichotomized women into screen-positive and screen-negative groups. Relevant clinical, hormonal, and sonographic assessments categorized women as either women with criteria-based PCOS (ie, National Institutes of Health [NIH] 1990 criteria, Rotterdam 2003 criteria, or Androgen Excess and Polycystic Ovary Syndrome Society [AE-PCOS] criteria), women with partial phenotypes (hyperandrogenism, oligomenorrhea, or polycystic morphology labeled as pre-PCOS), or healthy women, in addition to quantitating various comorbidities. Main Outcomes and Measures: The prevalence and phenotypes of PCOS among women of reproductive age and the burden of comorbidities associated with PCOS. Results: A total of 8993 women (mean [SD] age, 29.5 [6.2] years) were enrolled in this study; 196 women were already diagnosed with PCOS, 2251 were categorized as screen positive, and 6546 were categorized as screen negative. The mean (SD) age of screen-positive women (28.1 [6.4] years) was lower than that of screen-negative women (29.7 [6.1] years) (P < .001), and the mean (SD) age at menarche was higher in the former group (13.2 [1.3] vs 13.1 [1.2] years; P < .001). The national prevalence of PCOS was 7.2% (95% CI, 4.8%-10.8%) by NIH 1990 criteria, 19.6% (95% CI, 12.7%-29.2%) by Rotterdam 2003 criteria, and 13.6% (95% CI, 8.4%-21.6%) by AE-PCOS criteria. Overall, PCOS phenotypes C (501 [40.8%]) and D (301 [24.6%]) were the most common, and 492 women (pre-PCOS subgroup) had oligomenorrhea (n = 75), hyperandrogenism (n = 257), or polycystic ovarian morphology (n = 160) only. Among women with PCOS (n = 1224), obesity was present in 529 (43.2%), dyslipidemia in 1126 (91.9%), nonalcoholic fatty liver disease in 403 (32.9%), metabolic syndrome in 305 (24.9%), impaired glucose tolerance in 111 (9.1%), diabetes in 41 (3.3%), and hypertension in 101 (8.3%). The pre-PCOS subgroup (n = 492) displayed similar metabolic aberrations (dyslipidemia: 390 [79.3%]; metabolic syndrome: 78 [15.9%]; nonalcoholic fatty liver disease: 163 [33.1%]; impaired glucose tolerance: 62 [12.6%]; diabetes: 7 [1.4%]; and hypertension: 26 [5.3%]). Conclusions and Relevance: In this cross-sectional study of reproductive-age women recruited across India, the prevalence of PCOS was high, with phenotype C being predominant. Most of these women had metabolic abnormalities. These findings are crucial for developing preventive and therapeutic strategies, potentially integrating PCOS management into national health programs.

Indexed as

ComorbidityPhenotypePolycystic Ovary SyndromeAdolescentAdultCross-Sectional StudiesFemaleHumansHyperandrogenismIndiaPrevalenceYoung Adult

Identifiers

PMID39441596
PMCPMC11581580

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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.