Evidence map›Paper›PMID 38524862›Full record

ArticleJournal of multidisciplinary healthcare2024

Analysis of Dietary and Nutritional Status of Tuberculosis Patients in Hulunbuir Region.

Jin-Qi Hao, Lan Zhang, Yan-Qin Yu, Ming-Yuan Hao, Ai-Xin Wang, Fu-Min Feng

Open access · goldAbstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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  6. The Vicious Cycle of Malnutrition and Tuberculosis: A Narrative Review.Journal of clinical practice and research · 2024
    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

6 authors at 3 institutions in 1 country.

Jin-Qi HaoSchool of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, 063210, People's Republic of China.
Lan ZhangSchool of Public Health, Baotou Medical College, Baotou, Inner Mongolia, 014040, People's Republic of China.
Yan-Qin YuSchool of Public Health, Baotou Medical College, Baotou, Inner Mongolia, 014040, People's Republic of China.
Ming-Yuan HaoThe Second People's Hospital in Hulunbuir, Zaerdong, 162650, People's Republic of China.
Ai-Xin WangThe Second People's Hospital in Hulunbuir, Zaerdong, 162650, People's Republic of China.
Fu-Min FengSchool of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, 063210, People's Republic of China.
Baotou Medical College · CNNorth China University of Science and Technology · CNXian Yang Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Tuberculosis (TB) is a major public health problem that affects millions of people worldwide. Malnutrition is a common complication of TB and can worsen the disease outcome. The purpose of this study was to investigate the dietary and nutritional status, as well as the dietary structure, of TB patients in Hulunbuir City, Inner Mongolia, China. Additionally, the study aimed to analyze the factors that influence the nutritional status in order to provide a theoretical foundation for the prevention and treatment of TB and related issues. Methods: A cross-sectional study was conducted on 334 randomly selected TB patients from Hulunbuir City Second Hospital. A questionnaire survey was administered to collect information on demographic characteristics, dietary habits, and food intake. Nutritional status was assessed by body mass index (BMI). Dietary diversity score (DDS) was calculated based on the number of food groups consumed in the previous 24 hours. Statistical analysis was performed using SPSS 20.0 software. Descriptive statistics employed rates and composition ratios, and categorical data was represented using frequencies and percentages. The chi-square test was used to analyze the association between nutritional status and other variables, with a significance level set at α=0.05. Multivariable ordinal logistic regression analysis was performed to identify the independent factors affecting the nutritional status of TB patients. Results: The univariate analysis revealed statistically significant differences (P < 0.05) in the nutritional status (as measured by BMI) among tuberculosis patients, considering ethnicity, educational level, smoking, meat-based diet, vegetable consumption, and DDS grading. No statistically significant differences were found regarding gender, age, marital status, occupation, sleep duration, alcohol consumption, and consumption of rice and flour dishes. Statistically significant variables from the univariate analysis were included in a multivariable ordinal logistic regression analysis model. The findings highlighted that educational level (high school or below), smoking, meat-based diet, DDS scores of 1-3, and a primarily vegetable-based diet had independent effects on the nutritional status of tuberculosis patients (all P < 0.05). No significant difference was found in nutritional status between the Han ethnic group and other ethnicities. Conclusion: The study revealed that the dietary and nutritional status of TB patients in Hulunbuir City was suboptimal and influenced by several factors. Smoking, meat-based diet, and low dietary diversity score were the primary risk factors for malnutrition among TB patients. The study suggests that nutritional education and intervention programs should be implemented for TB patients to improve their dietary quality and nutritional status.

Indexed as

dietary diversity scoreinfluencing factorsnutritional statustuberculosis

Identifiers

PMID38524862
PMCPMC10960538
OpenAlexW4392965324

What OpenQuestion holds

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LicenceCC BY-NC
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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.