Evidence map›Paper›PMID 38956083›Full record

ArticleScientific reports2024

Age-appropriate BMI cut-offs for malnutrition among older adults in India.

Akancha Singh, Aparajita Chattopadhyay

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Comparison of Body Mass Index Range Criteria and Their Association with Nutrition-Related Risk: A Cross-Sectional Study in Polish Older Adults.Medical science monitor : international medical journal of experimental and clinical research · 2025
    Article
  4. 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

2 authors.

Akancha SinghInternational Institute for Population Sciences, Mumbai, 400088, Maharashtra, India. aksin176@gmail.com.ORCID 0000-0002-6381-228X
Aparajita ChattopadhyayDepartment of Population and Development, and Associate Head, Centre for Demography of Gender (CDG), International Institute for Population Sciences, Mumbai, 400088, Maharashtra, India.ORCID 0000-0002-1722-4268

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing prevalence of obesity in India, body mass index (BMI) has garnered importance as a disease predictor. The current World Health Organization (WHO) body mass index (BMI) cut-offs may not accurately portray these health risks in older adults aged 60 years and above. This study aims to define age-appropriate cut-offs for older adults (60-74 years and 75 years and above) and compare the performance of these cut-offs with the WHO BMI cut-offs using cardio-metabolic conditions as outcomes. Using baseline data from the Longitudinal Ageing Study in India (LASI), classification and regression tree (CART) cross-sectional analysis was conducted to obtain age-appropriate BMI cut-offs based on cardio-metabolic conditions as outcomes. Logistic regression models were estimated to compare the association of the two sets of cut-offs with cardio-metabolic outcomes. The area under the receiver operating characteristic curve (AUC), sensitivity and specificity were estimated. Agreement with waist circumference, an alternate measure of adiposity, was conducted. For older adults aged 60-74 years and 75 years and above, the cut-off for underweight reduced from < 18.5 to < 17.4 and < 13.3 respectively. The thresholds for overweight and obese increased for older adults aged 60-74 years old from >  = 25 to > 28.8 and >  = 30 to > 33.7 respectively. For older adults aged 75 years and above, the thresholds decreased for both categories. The largest improvement in AUC was observed in older adults aged 75 years and above. The newly derived cut-offs also demonstrated higher sensitivity and specificity among all age-sex stratifications. There is a need to adopt greater rigidity in defining overweight/obesity among older adults aged 75 years and above, as opposed to older adults aged 60-74 years old among whom the thresholds need to be less conservative. Further stratification in the low risk category could also improve BMI classification among older adults. These age-specific thresholds may act as improved alternatives of the current WHO BMI thresholds and improve classification among older adults in India.

Indexed as

Body Mass IndexMalnutritionAgedAged, 80 and overAge FactorsCross-Sectional StudiesFemaleHumansIndiaLongitudinal StudiesMaleMiddle AgedObesityOverweightROC CurveThinnessBMICART analysisCut-offDecision treeIndiaOlder adults

Identifiers

PMID38956083
PMCPMC11219785

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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.