Sleep Variables in Health Research: From Systematic Omission to Methodological Integration — A Narrative Review and Proposal

For decades, sample characterization in health and physiological research has relied on a “triad of convenience”: demographics, anthropometrics, and socioeconomic status. While these parameters offer a baseline description, they systematically omit a critical biological variable sustaining human homeostasis: sleep. This baseline omission introduces significant residual confounding, creating a “Table 1 Fallacy” where matched cohorts appear identical but remain physiologically heterogeneous due to unmeasured sleep-wake variance, including duration, quality, and circadian alignment. Sleep occupies a unique position among neglected baseline variables because it simultaneously coordinates neuroendocrine secretion, immune priming, autonomic regulation, and metabolic clearance within each circadian cycle, mechanistic roles that differentiate it from other lifestyle factors currently absent from reporting guidelines. Compelling evidence demonstrates that sleep duration, quality, and chronotype directly modulate peripheral insulin sensitivity, hormonal balance, immune readiness, and cardiovascular function. Failing to account for these metrics can lead to the misclassification of participants as “non-responders” in clinical trials, masking true primary intervention effects or creating an illusion of treatment efficacy. To restore reproducibility and scientific rigor, we contend that sleep reporting must transition from a voluntary act to a methodological mandate in studies where sleep represents a biologically plausible source of confounding. We propose a high-yield, low-cost Minimal Sleep Set (MSS) utilizing validated screening tools to systematically control for sleep-wake variance, ensuring that the human biological state is as clearly defined as the intervention itself.