Evidence map›Paper›PMID 26046649›Full record

ArticlePloS one2015

Estimating the Impact of Reducing Under-Nutrition on the Tuberculosis Epidemic in the Central Eastern States of India: A Dynamic Modeling Study.

Olivia Oxlade, Chuan-Chin Huang, Megan Murray

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 14% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
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  7. Article
  8. Article
  9. Factors Associated With Unfavorable Treatment Outcomes Among Persons With Pulmonary Tuberculosis: A Multicentric Prospective Cohort Study From India.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
    Article
  10. Review
  11. Article
  12. Article
  13. Impact of Undernutrition on Tuberculosis Treatment Outcomes in India: A Multicenter, Prospective, Cohort Analysis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  14. Article
  15. Article
  16. Undernutrition is feeding the tuberculosis pandemic: A perspective.Journal of clinical tuberculosis and other mycobacterial diseases · 2022
    Review
  17. Article
  18. Opportunities to prevent and manage undernutrition to amplify efforts to end TB.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
    Article
  19. Article
  20. Review
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

3 authors at 2 institutions in 1 country.

Olivia OxladeDepartment of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.
Chuan-Chin HuangDepartment of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America.
Megan MurrayDepartment of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America; Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts, United States of America; Infectious Disease Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America.
Harvard University · USBrigham and Women's Hospital · US

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

backgroundTuberculosis (TB) and under-nutrition are widespread in many low and middle-income countries. Momentum to prioritize under-nutrition has been growing at an international level, as demonstrated by the "Scaling Up Nutrition" movement. Low body mass index is an important risk factor for developing TB disease. The objective of this study was to project future trends in TB related outcomes under different scenarios for reducing under-nutrition in the adult population in the Central Eastern states of India.

methodsA compartmental TB transmission model stratified by body mass index was parameterized using national and regional data from India. We compared TB related mortality and incidence under several scenarios that represented a range of policies and programs designed to reduce the prevalence of under-nutrition, based on the experience and observed trends in similar countries.

resultsThe modeled nutrition intervention scenarios brought about reductions in TB incidence and TB related mortality in the Central Eastern Indian states ranging from 43% to 71% and 40% to 68% respectively, relative to the scenario of no nutritional intervention. Modest reductions in under-nutrition averted 4.8 (95% UR 0.5, 17.1) million TB cases and 1.6 (95% UR 0.5, 5.2) million TB related deaths over a period of 20 years of intervention, relative to the scenario of no nutritional intervention. Complete elimination of under-nutrition in the Central Eastern states averted 9.4 (95% UR 1.5, 30.6) million TB cases and 3.2 (95% UR 0.7-, 10.1) million TB related deaths, relative to the scenario of no nutritional intervention.

conclusionOur study suggests that intervening on under-nutrition could have a substantial impact on TB incidence and mortality in areas with high prevalence of under-nutrition, even if only small gains in under-nutrition can be achieved. Focusing on under-nutrition may be an effective way to reduce both rates of TB and other diseases associated with under-nutrition.

Indexed as

Models, TheoreticalBody Mass IndexFemaleHumansIncidenceIndiaMalnutritionNutritional StatusRisk FactorsSurvival RateTuberculosis, Pulmonary

Identifiers

PMID26046649
PMCPMC4457886
OpenAlexW1520028340

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.