NHANES Sleep Research as a Cautionary Tale: When Big Data Goes Wrong

The National Health and Nutrition Examination Survey (NHANES) has emerged as one of the premier datasets for population-based health research, and nowhere is this more evident than in the explosive growth of sleep medicine investigations.We conducted a quick bibliometric analysis using PubMed from inception to October 8, 2025, with the search strategy: "(NHANES OR 'National Health and Nutrition Examination Survey') AND (sleep OR 'sleep disorders' OR 'sleep medicine' OR insomnia OR 'sleep apnea' OR 'sleep duration' OR 'sleep quality')" which yielded 3095 papers.From this dataset, we identified 655 papers mentioning NHANES, 1525 papers related to sleep, and 429 studies specifically using NHANES data to investigate sleep and sleep disorders.This analysis reveals a remarkable 1,244% increase in NHANES sleep studies from 2015 to 2024, with research on sleep duration dominating at 32.0% of all investigations, followed by obstructive sleep apnea studies at 16.0%.However, this unprecedented growth demands critical examination, as recent meta-research has raised significant concerns about the quality and methodological rigor of NHANES-based investigations.Figure 1 shows the publication growth trajectory of NHANES sleep research from 2015 to 2025, demonstrating the exponential increase in publications, particularly after 2021. The Formulaic Research ProblemRecently, Suchak et al documented what they termed an "explosion of formulaic research articles" based on NHANES data, including inappropriate study designs and false discoveries. 1 Their systematic analysis revealed concerning patterns: studies consistently failing to account for multifactorial relationships, manuscripts neglecting false discovery rate corrections, and researchers selectively extracting data rather than utilizing comprehensive datasets.Their investigation identified an average of four papers per year between 2014 and 2021, which surged to 190 papers in 2024 alone.Ninety-two percent of recent publications originated from Chinese institutions, compared to just 8% before 2021.These quality concerns remain largely unaddressed in NHANES sleep research.The implications for sleep medicine research are profound, particularly given that our field has embraced NHANES data with exceptional enthusiasm, producing nearly half of all sleep-related NHANES studies in just the past four years.The broader scientific publishing landscape has witnessed similar concerning trends across multiple domains.O'Grady reported that, as Northwestern University metascientist Reese Richardson put it, such free data sources allow almost anyone to take a known research method and swap in new variables to create fresh findings in a kind of "research Mad Libs". 2 This phenomenon extends beyond NHANES to encompass various genetic studies, bibliometric analyses, and other large-scale datasets. 3The timing coincides suspiciously with the widespread availability of artificial intelligence chatbots that can generate readable text from simple prompts. 4This could potentially facilitate the rephrasing of template papers with different variable combinations to avoid plagiarism detection.