Facilitating youth diabetes studies with the most comprehensive epidemiological dataset available through a public web portal.
Catherine McDonoughYan Chak LiNita VangeepuramBian LiuGaurav PandeyPublished in: medRxiv : the preprint server for health sciences (2023)
The prevalence of type 2 diabetes mellitus (DM) and prediabetes (preDM) is rapidly increasing among youth, posing significant health and economic consequences. To address this growing concern, we created the most comprehensive youth-focused diabetes dataset to date derived from National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018. The dataset, consisting of 15,149 youth aged 12 to 19 years, encompasses preDM/DM relevant variables from sociodemographic, health status, diet, and other lifestyle behavior domains. An interactive web portal, POND (Prediabetes/diabetes in youth ONline Dashboard), was developed to provide public access to the dataset, allowing users to explore variables potentially associated with youth preDM/DM. Leveraging statistical and machine learning methods, we conducted two case studies, revealing established and lesser-known variables linked to youth preDM/DM. This dataset and portal can facilitate future studies to inform prevention and management strategies for youth prediabetes and diabetes.
Keyphrases
- mental health
- physical activity
- young adults
- glycemic control
- type diabetes
- cardiovascular disease
- machine learning
- healthcare
- public health
- emergency department
- social media
- risk assessment
- metabolic syndrome
- risk factors
- insulin resistance
- big data
- climate change
- artificial intelligence
- electronic health record
- deep learning
- adverse drug