Evidence map›Paper›PMID 32051421›Full record

ArticleScientific reports2020

Application of single-level and multi-level modeling approach to examine geographic and socioeconomic variation in underweight, overweight and obesity in Nepal: findings from NDHS 2016.

Nipun Shrestha, Shiva Raj Mishra, Saruna Ghimire, Bishal Gyawali, Pranil Man Singh Pradhan, Dan Schwarz

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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

  1. Pooled it
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  3. Review
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  7. Review
  8. Prevalence and Correlates of Underweight among Women of Reproductive Age in Nepal: A Cross-Sectional Study.International journal of environmental research and public health · 2022
    Article
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  14. Socioeconomic Vulnerability Index and Obesity among Korean Adults.International journal of environmental research and public health · 2021
    Article
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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

6 authors.

Nipun Shrestha *Institute for Health and Sport (IHeS), Victoria University, Melbourne, Australia.ORCID http://orcid.org/0000-0003-3542-8130
Shiva Raj Mishra *Nepal Development Society, Chitwan, Nepal. shivarajmishra@gmail.com.
Saruna GhimireDepartment of Sociology and Gerontology and Scripps Gerontology Center, Miami University, Oxford, OH, USA.
Bishal GyawaliSection of Global Health, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.ORCID http://orcid.org/0000-0002-8315-1925
Pranil Man Singh PradhanDepartment of Community Medicine and Public Health, Institute of Medicine, Tribhuvan University, Kathmandu, Nepal.ORCID http://orcid.org/0000-0002-0066-8583
Dan SchwarzNyaya Health Nepal, Kathmandu, Nepal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nepal's dual burden of undernutrition and over nutrition warrants further exploration of the population level differences in nutritional status. The study aimed to explore, for the first time in Nepal, potential geographic and socioeconomic variation in underweight and overweight and/or obesity prevalence in the country, adjusted for cluster and sample weight. Data came from 14,937 participants, including 6,172 men and 8,765 women, 15 years or older who participated in the 2016 Nepal Demography and Health Survey (NDHS). Single-level and multilevel multi-nominal logistic regression models and Lorenz curves were used to explore the inequalities in weight status. Urban residents had higher odds of being overweight and/or obese (OR: 1.89, 95% CI: 1.62-2.20) and lower odds of being underweight (OR: 0.81, 95% CI: 0.70-0.93) than rural residents. Participants from Provinces 2, and 7 were less likely to be overweight/obese and more likely to be underweight (referent: province-1). Participants from higher wealth quintile households were associated with higher odds of being overweight and/or obese (P-trend < 0.001) and lower odds of being underweight (P-trend < 0.001). Urban females at the highest wealth quintile were more vulnerable to overweight and/or obesity as 49% of them were overweight and/or obese and nearly 39% at the lowest wealth quintile were underweight.

Indexed as

AdolescentAdultBody WeightFemaleHealth SurveysHumansMaleMiddle AgedNepalObesityOverweightPrevalenceRural PopulationSocioeconomic FactorsThinnessUrban Population

Identifiers

PMID32051421
PMCPMC7016110

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Registered trials

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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.