Evidence map›Paper›PMID 38567220›Full record

ArticleCureus2024

BMI and Polycystic Ovary Syndrome: Demographic Trends in Weight and Health.

Ipsita Mohapatra, Subha R Samantaray

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
5.9field-weighted citation impact, top 4% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  9. Observational
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

2 authors at 2 institutions in 1 country.

Ipsita MohapatraObstetrics and Gynecology, All India Institute of Medical Sciences, Kalyani, IND.
Subha R SamantarayObstetrics and Gynecology, Prathima Institute of Medical Sciences, Karimnagar, IND.
All India Institute of Medical Sciences · INInstitute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Polycystic ovary syndrome (PCOS) is a common endocrine disorder that affects women in adolescence and reproductive age. The distribution of PCOS across different body mass index (BMI) categories can vary, and research has shown associations between PCOS and weight status. This study tries to evaluate the distribution of PCOS in relation to BMI in women attending the PCOS clinic in a tertiary hospital in eastern India. Methodology This hospital-based cross-sectional study was carried out in the gynecology outpatient department of a tertiary care center. The study population included all the women in the age group between 15 and 45 years diagnosed as having PCOS using the Rotterdam definition. The various physical, clinical, and biochemical parameters were measured in the study population and compared among the obese and lean PCOS patients. Results and discussion A total of 143 women were included in the study. The mean age of the study population was 26.8 years. Among these, the underweight and normal weight patients were categorized as lean PCOS patients, 35 in number (24.5%), and overweight and obese patients were categorized as obese PCOS patients, 108 in number (75.5%). All the physical parameter measures like age (mean = 28.05, SD = 5.722), height (mean = 153.384, SD = 6.679), weight (mean = 68.182, SD = 11.501), waist circumference (mean = 95.135, SD = 10.291), hip circumference (mean = 101.47, SD = 9.320), waist-to-hip ratio (mean = 0.940, SD = 0.0831), and neck circumference (mean = 34.85, SD = 2.445) were significantly higher in the obese group as compared to the lean group. Menstrual irregularity was significantly more common in the obese PCOS patients as compared to the lean PCOS group (p = 0.02). There was a significant difference (p < 0.05) between the obese and lean PCOS patients when the biochemical parameters like fasting insulin, fasting glucose, and homeostatic model assessment of insulin resistance (HOMA-IR) were compared. There is a strong link between obesity, insulin resistance, and PCOS. Obesity can exacerbate insulin resistance, a common feature of PCOS, leading to increased levels of insulin and androgens. Conclusion The demographic distribution of PCOS in relation to BMI is essential for tailoring interventions and treatments.

Indexed as

insulin resistancelean pcoslifestyle modification (lsm)obese pcosobesitypolycystic ovary syndromepolycystic ovary syndrome (pcos)

Identifiers

PMID38567220
PMCPMC10986768
OpenAlexW4392343691

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.