Evidence map›Paper›PMID 31384099›Full record

ArticleClinical pediatric endocrinology : case reports and clinical investigations : official journal of the Japanese Society for Pediatric Endocrinology2019

Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children's Health.

Yasuaki Saijo, Yoshiya Ito, Eiji Yoshioka, Yukihiro Sato, Machiko Minatoya, Atsuko Araki, Chihiro Miyashita, Reiko Kishi

Open access · diamondAbstract read
In one paragraph

Article in Clinical pediatric endocrinology : case reports and clinical investigations : official journal of the Japanese Society for Pediatric Endocrinology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. A point system to predict the future risk of obesity in 10-year-old children.Environmental health and preventive medicine · 2023
    Article
  3. Article
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

8 authors at 5 institutions in 1 country.

Yasuaki SaijoDepartment of Social Medicine, Asahikawa Medical University, Sapporo, Japan.
Yoshiya ItoFaculty of Nursing, Japanese Red Cross Hokkaido College of Nursing, Sapporo, Japan.
Eiji YoshiokaDepartment of Social Medicine, Asahikawa Medical University, Sapporo, Japan.
Yukihiro SatoDepartment of Social Medicine, Asahikawa Medical University, Sapporo, Japan.
Machiko MinatoyaCenter for Environmental and Health Sciences, Hokkaido University, Sapporo, Japan.
Atsuko ArakiCenter for Environmental and Health Sciences, Hokkaido University, Sapporo, Japan.
Chihiro MiyashitaCenter for Environmental and Health Sciences, Hokkaido University, Sapporo, Japan.
Reiko KishiCenter for Environmental and Health Sciences, Hokkaido University, Sapporo, Japan.
Asahikawa Medical University · JPHokkaido University · JPHealth Sciences University of Hokkaido · JPJapanese Red Cross College of Nursing · JPSapporo University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to construct a childhood obesity risk index based on predictors identified in pregnant women and 1-yr-old infants. The primary outcome was an identified obesity index of > 20% at 6-8 yr of age. Of a total sample size of 6,846 mother-child pairs, 80% and 20% were randomly allocated to the derivation and validation cohorts, respectively. For the derivation cohort, univariate and multivariate logistic regression analyses of data were conducted to identify the final predictors to determine the childhood obesity risk score algorithm. These included pre-pregnancy body mass index (BMI), child's gender, smoking during pregnancy, education, and obesity index at one yr of age. The β coefficients for categories of predictor variables were each divided by the smallest value among them. The quotient was rounded off to the integer and assigned to the risk score, and a value of zero was assigned to reference categories. A total risk score was calculated for each individual. A cutoff point ≥ 16 had 22.2% and 21.8% positive predictive values in the derivation and validation cohorts, respectively. In conclusion, the childhood obesity risk score algorithm was constructed based on generic predictors that can be easily obtained from maternal and child health handbooks.

Indexed as

body mass indexchildhoodobesitypregnancyrisk score

Identifiers

PMID31384099
PMCPMC6646240
OpenAlexW2964212726

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.