Evidence map›Paper›PMID 33191528›Full record

ArticleThe International journal of eating disorders2021

Screen-detected disordered eating and related traits in a large population sample of females in mainland China: China Health and Nutrition Survey.

Shuyang Yao, Ruyue Zhang, Laura M Thornton, Christine M Peat, Baiyu Qi, Shufa Du, Huijun Wang, Bing Zhang, Cynthia M Bulik

Abstract read
In one paragraph

Article in The International journal of eating disorders, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed, 1 synthesis or guideline 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.

Shuyang YaoDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0001-9669-4470
Ruyue ZhangDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0001-5747-9428
Laura M ThorntonDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0001-9384-7988
Christine M PeatDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Baiyu QiDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Shufa DuDepartment of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Huijun WangNational Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, PR China.
Bing ZhangNational Institute for Nutrition and Health, Chinese Center for Diseases Control and Prevention, Beijing, PR China.
Cynthia M BulikDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0001-7772-3264

Funding

UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SUSAN M. SMITH · 1999 to 2026
$31.6M
MONITORING SOCIAL CHANGE: HEALTH, REPRODUCTION, AGINGR01HD030880 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 1994 to 2024
$27.0M
POPULATION STUDIEST32HD007168 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELIZABETH A FRANKENBERG · 1985 to 2026
$13.8M
Carolina Population CenterR24HD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MORGAN, SAMUEL PHILIP · 2005 to 2014
$10.0M
Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
Eating Disorders Genetics Initiative (EDGI)R01MH120170 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BULIK, CYNTHIA M · 2019 to 2023
$7.2M
Monitoring Social Change: Dynamics Of Aging And Cognitive FunctionR01AG065357 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 2020 to 2024
$3.6M
Predicting Binge and Purge Episodes from Passive and Active Apple Watch Data Using a Dynamical Systems ApproachR01MH119084 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BULIK, CYNTHIA M, BUTNER, JONATHAN · 2019 to 2022
$2.8M
CHILD HEALTH EFFECTS OF RAPID SOCIO-DEMOGRAPHIC CHANGER01HD038700 · NICHD · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · PI POPKIN, BARRY M · 2000 to 2004
$1.5M
Nutrition-Related NCD Prevention Training in ChinaD43TW009077 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI POPKIN, BARRY M · 2011 to 2015
$1.1M
Nutrition-Related NCD Prevention Training in ChinaD43TW007709 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI POPKIN, BARRY M · 2006 to 2010
$723k
Breaking the Cycle of Risk: Intervention for Mothers with Eating DisordersR34MH080750 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BULIK, CYNTHIA M · 2008 to 2010
$657k
FIC NIH HHS D43 TW007709FIC NIH HHS D43 TW009077NIA NIH HHS R01 AG065357NICHD NIH HHS P2C HD050924NICHD NIH HHS R01 HD030880NICHD NIH HHS R01 HD038700NICHD NIH HHS R24 HD050924NICHD NIH HHS T32 HD007168NIDDK NIH HHS P30 DK056350NIMH NIH HHS R01 MH119084NIMH NIH HHS R01 MH120170NIMH NIH HHS R34 MH080750
6 · The paper itself

Abstract

objectiveWe describe the prevalence and sociodemographic factors associated with screen-detected disordered eating and related traits in a population-based sample of women in China. We also explored prevalence trends over time.

methodA total of 4,218 females aged 12-50 were sampled from 15 provinces as part of the China Health and Nutrition Survey (CHNS) in 2015. The SCOFF questionnaire screened for disordered eating and the selected questions from the Eating Disorders Examination-Questionnaire measured dietary restraint, shape concerns, and weight concerns. Body mass index (BMI) was measured and sociodemographic factors captured urban/rural residence, age, ethnicity, income, education, marital status, and occupational status. We calculated the prevalence of screen-detected disordered eating and related traits broadly and across several dimensions and compared prevalence estimates to 2009 and 2011 reports.

resultsWe detected 296 individuals who screened positive for disordered eating on the SCOFF (prevalence = 7.04%). Positive screens were associated with urban residence (p = .002) and higher education levels (p < .001). Scores on restraint, shape concerns, and weight concerns were all higher for individuals in urban versus village locations (all p's < .001), and with higher BMI (p < .001) for shape and weight concerns. The prevalence of screen-detected disordered eating increased numerically across 2009, 2011, and 2015. DISCUSSION: The prevalence of screen-detected disordered eating in mainland China was comparable to other populations worldwide obtained from a recent meta-analysis. The distribution of disordered eating and related traits varied by several sociodemographic factors, which include age, BMI, urban/rural residence, education, and income, suggesting important directions for case detection and intervention in China.

Indexed as

Feeding and Eating DisordersMass ScreeningAdolescentAdultChildChinaFemaleHealth SurveysHumansMiddle AgedRisk FactorsYoung Adultbody mass indexCHNSeating disordersepidemiologywomen's health

Identifiers

PMID33191528
PMCPMC7855662

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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.