ArticleAnnals of epidemiology2019
Not so implausible: impact of longitudinal assessment of implausible anthropometric measures on obesity prevalence and weight change in children and adolescents.
Article in Annals of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed, 26 citations in OpenAlex.
- Exclusive Breastfeeding and Growth Trajectories Until 5 Years of Age Among Children Monitored in Primary Health Care in Brazil.American journal of human biology : the official journal of the Human Biology Council · 2026Article
- Malnutrition among men in Ghana: socio-demographic factors and rural-urban differences.Journal of health, population, and nutrition · 2026Article
- Classification of childhood obesity using longitudinal clinical body mass index and its validation.International journal of obesity (2005) · 2025Observational
- Should gestational weight gain charts exclude individuals with excess postpartum weight retention?Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2024Article
- Safety of low weight gain or weight loss in pregnancies with class 1, 2, and 3 obesity: a population-based cohort study.Lancet (London, England) · 2024Article
- Detecting potential outliers in longitudinal data with time-dependent covariates.European journal of clinical nutrition · 2024Article
- Identifying biologically implausible values in big longitudinal data: an example applied to child growth data from the Brazilian food and nutrition surveillance system.BMC medical research methodology · 2024Article
- Associations between collagen X biomarker and linear growth velocity in a pediatric chronic kidney disease cohort.Pediatric nephrology (Berlin, Germany) · 2023Article
- Maternal and child nutrition programme of investigation within the 100 Million Brazilian Cohort: study protocol.BMJ open · 2023Article
- Data quality control in longitudinal epidemiologic studies: conditional studentized residuals from linear mixed effects models for outlier detection in the setting of pediatric chronic kidney disease.Annals of epidemiology · 2023Article
- Identification of robust deep neural network models of longitudinal clinical measurements.NPJ digital medicine · 2022Article
- Differences in Classification Standards For the Prevalence of Overweight and Obesity in Children. A Systematic Review and Meta-Analysis.Clinical epidemiology · 2022Review
- Is it time to stop sweeping data cleaning under the carpet? A novel algorithm for outlier management in growth data.PloS one · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
purposeImplausible anthropometric measures are typically identified using population outlier definitions, conflating implausible and extreme measures. We determined the impact of a longitudinal outlier approach on prevalence of body mass index (BMI) categories and mean change in anthropometric measures in pediatric electronic health record data.
methodsWe examined 996,131 observations from 147,375 children (10-18 years) in the ADVANCE Clinical Data Research Network, a national network of community health centers. Sex-stratified, mixed effects, linear spline regression modeled weight, height, and BMI as a function of age. Longitudinal outliers were defined as observations with studentized residual greater than |6|; population outliers were defined by Centers for Disease Control-defined z-score thresholds.
resultsAt least 99.7% of anthropometric measures were not extreme by longitudinal or population definitions (agreement ≥ 0.995). BMI category prevalence after excluding longitudinal or population outliers differed by less than 0.1%. Among children greater than 85th percentile at baseline, annual mean changes in anthropometric measures were larger in data that excluded longitudinal (girls: 1.24 inches, 12.39 pounds, 1.53 kg/m
conclusionsLongitudinal outlier methods may reduce underestimation of anthropometric change in children with elevated baseline values.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.