Neurodevelopmental Assessments for 139 Children in Swedish Obesity Treatment
by figshare admin karger·Updated 1mo ago
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Description
139 children (mean age 12.7 years, mean BMI SDS 3.1) were recruited from three Swedish obesity clinics. Their motor, executive, perception, memory, language, learning, social, and emotional/behavioral functioning were assessed via an age-normed questionnaire, with scores ≥ the 90th percentile indicating problems. The dataset, authored by figshare admin karger and last updated in 2026, supports the associated research article.
Use Cases
Analyze the prevalence of neurodevelopmental problems across eight functional domains based on questionnaire scores.
Compare rates of neurodevelopmental problems between children with and without formal neurodevelopmental disorder diagnoses.
Investigate the overlap of multiple neurodevelopmental problems within the same individual based on the described assessment.
Study the demographic and clinical characteristics of a pediatric cohort undergoing obesity treatment in Sweden.
Strengths
Includes data for 139 children with specific mean age (12.7 years) and mean BMI SDS (3.1).
Assessments cover eight distinct neurodevelopmental domains using an age-normed instrument.
Clinical relevance is defined by a clear threshold (≥90th percentile) for each domain.
Diagnostic status for neurodevelopmental disorders was collected from patient records for 52.5% of the cohort.
Limitations
Row count is unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
Data may reflect geographic and clinical bias inherent to the three Swedish obesity clinics.
Provenance
Source
figshare admin karger
Collection Method
Children were recruited from three obesity clinics in Sweden and assessed with a questionnaire; neurodevelopmental diagnoses were collected from patient records.
Freshness
Last updated 2026-05-06 05:55:10; freshness should be verified.
Geography
Sweden
The primary data file is a 249.3 KB PDF, which is a tiny dataset; the underlying structured data may require extraction.