Evidence map›Paper›PMID 35215409›Full record

ArticleNutrients2022

Multilevel Analysis of the Nutritional and Health Status among Children and Adolescents in Eastern China.

Ting Tian, Yuanyuan Wang, Wei Xie, Jingxian Zhang, Yunlong Ni, Xianzhen Peng, Guiju Sun, Yue Dai, Yonglin Zhou

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 28% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 3 institutions in 1 country.

Ting TianInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Yuanyuan WangInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Wei XieInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Jingxian ZhangInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Yunlong NiInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Xianzhen PengDepartment of Public Health and Preventive Medicine, Kangda College of Nanjing Medical University, Lianyungang 222000, China.
Guiju SunDepartment of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China.ORCID 0000-0001-5969-2185
Yue DaiInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Yonglin ZhouInstitute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.
Jiangsu Provincial Center for Disease Control and Prevention · CNKangda College of Nanjing Medical UniversitySoutheast University · CN

Funding

National Key R&D Program of China 2016YFC1305201National Natural Science Foundation of China No.81872618Philosophy and Social Science Research Projects in Universities of Jiangsu Province No. 2020SJA2439
6 · The paper itself

Abstract

We aimed to identify multiple nutritional health problems and the relevant factors among children and adolescents aged 7-17 years. This study was part of the China Nutrition and Health Surveillance of Children and Lactating Mothers in 2016-2017, conducted in Jiangsu Province in eastern China. After sampling, 3025 school-age children and adolescents were enrolled into this study. Demographic information collections and anthropometric measurements were conducted by trained local Center for Disease Control and Prevention (CDC) staff. Venous blood in the amount of 6 mL was drawn from each participant in the morning and used for testing biochemical and nutritional indicators. Multivariate logistic regression analysis and Poisson regression analysis were used for overnutrition- and undernutrition-related disorders to test relevant personal, parental, and household factors. The prevalence of wasting, overweight, and obesity was 5.5%, 14.8%, and 12.7%, respectively. Metabolic syndrome (MetS) was prevalent among 5.1% of participants. Among the study participants, 29.5% had hyperuricemia. The overall prevalence of high low-density lipoprotein (LDL) and high total cholesterol (TC) of all participants was 4.8% and 7.4%, respectively. 0.9% of the participants had vitamin A deficiency (VAD) and 14.6% had marginal vitamin A deficiency; 25.1% had vitamin D deficiency (VDD) and 54.5% had inadequate vitamin D levels. Anemia was present in 4.0% of all participants. The prevalence of zinc deficiency was 4.8%. Demographic characteristics, behavioral characteristics, parents' characteristics, and family characteristics were associated with these multiple malnutrition disorders. The double burdens of malnutrition, which includes overnutrition- and undernutrition-related diseases, were prevalent among the school-age children and adolescents in Jiangsu Province in eastern China. There were various factors related to different nutritional problems. Thus, health education focusing on behavior intervention and nutrition education are necessary in containing nutritional problems among children.

Indexed as

LactationMalnutritionAdolescentChildChinaFemaleHumansMultilevel AnalysisNutritional StatusPrevalencechildren and adolescentsmalnutritionnutritional statusovernutrition

Identifiers

PMID35215409
PMCPMC8877382
OpenAlexW4212885247

What Socratic 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 Socratic graph.