Does coffee disrupt sleep? Large population study suggests the impact may be minimal

By Pooja Toshniwal PahariaReviewed by Susha Cheriyedath, M.Sc.Mar 11 2026

A large population study of middle-aged adults suggests that habitual coffee drinking may have far less impact on sleep and daytime fatigue than commonly believed, raising new questions about long-term caffeine adaptation in the brain.

Study: Habitual coffee consumption poorly correlates with sleep quality and daytime sleepiness: A cross-sectional study. Image Credit: Jacob Lund / Shutterstock

A recent population-level study published in the journal PLOS ONE suggests that regular coffee drinking may not meaningfully disrupt sleep in middle-aged adults. Analyzing a large Swedish cohort, researchers found little to no association between habitual caffeine intake, sleep quality, and daytime sleepiness. The findings suggest that long-term caffeine exposure may reflect possible adaptive changes in the brain’s adenosine system, as proposed by the authors, potentially blunting coffee’s usual alertness effects. However, larger studies and age-group comparisons are still needed to clarify how aging and biological adaptation influence the long-term relationship between coffee, sleep, and daytime fatigue.

Coffee’s reputation as a sleep disruptor faces renewed scrutiny

Coffee is one of the world’s most widely consumed beverages, making caffeine its most commonly used psychoactive ingredient. Known for promoting alertness, caffeine acts on the central nervous system (CNS) by blocking adenosine receptors that regulate sleep–wake balance. While short-term caffeine intake is known to disrupt sleep, its long-term effects remain less clear.

Emerging genetic research further shows that individual responses to caffeine vary. Genome-wide association studies (GWAS) link key variants to caffeine metabolism pathways. Notably, genes involved in the cytochrome P450 (CYP450) system and their regulators influence caffeine processing efficiency, shaping tolerance and physiological effects. In this study, these genetic markers were also used to help validate the reliability of self-reported coffee consumption.

Large Swedish cohort study examines coffee intake and sleep health

In this cross-sectional study, researchers examined the association between habitual coffee consumption and sleep health among 25,381 adults aged 50–64 years enrolled in the Swedish Cardiopulmonary Bioimage Study (SCAPIS).

The team assessed the frequency of coffee intake across multiple questionnaire categories, which were later grouped into four levels (none, low, moderate, and high) using food frequency questionnaires (FFQs). In addition, they evaluated sleep habits using a modified version of the Basic Nordic Sleep Questionnaire. They also measured daytime sleepiness (DS) using the Epworth Sleepiness Scale (ESS).

The indicators of sleep quality included trouble falling asleep, sleep duration, nocturnal awakenings, early waking, reflux after bedtime, loud snoring, and overall sleep quality. Researchers analyzed these indicators individually and as a composite sleep score.

Further, the team conducted GWAS to identify established genetic variants linked to coffee intake and to validate self-reported coffee consumption. They used regression models to estimate the odds ratios adjusted for confounders identified using directed acyclic graph (DAG) analysis.

In addition, the researchers used quasi-Poisson generalized linear models to assess sleep and sleepiness scores using coffee intake as the primary predictor. Sensitivity analyses tested dose–response patterns using four modeling approaches. These included categorical, continuous, and non-linear spline models to test linear and non-linear associations between coffee consumption and sleep outcomes.

Study reveals minimal links between coffee intake and sleep quality

The cohort included slightly more women (51%; n=12,990) than men. Most participants reported drinking coffee at least once daily (88%; n=22,257). Researchers identified key confounding factors for DS, including age, sex, body mass index (BMI), physical activity, stress, smoking, tea intake, sleep medication use, and nighttime sleep duration. Overweight or obese male smokers consumed coffee more frequently than their peers.

GWAS identified 66 single-nucleotide polymorphisms (SNPs) associated with coffee intake. Variants of the aryl hydrocarbon receptor (AHR), calcineurin binding protein 1 (CABIN1), and sushi domain-containing protein 2 (SUSD2) genes showed negative associations with higher intake. On the contrary, variants near CYP1A1/CYP1A2 showed positive associations, supporting the reliability of questionnaire data.

Participants generally reported good sleep quality (mean sleep score, 8.6), and only 16% experienced excessive DS. Overall, coffee intake showed very weak associations with sleep quality and DS. While several associations were statistically significant, their practical impact on sleep was very small.

Interestingly, compared with non-drinkers, low coffee intake was associated with poorer sleep quality, greater difficulty falling asleep, and more frequent nighttime awakenings (odds ratios of 1.16 to 1.17). In contrast, high intake was linked to improved sleep quality (odds ratio, 0.83), less trouble falling asleep (odds ratio, 0.86), fewer early awakenings (odds ratio, 0.78), and less reflux after bedtime (odds ratio, 0.82).

Those with higher coffee intake had slightly fewer nighttime awakenings, although the finding was not statistically significant (odds ratio, 0.92). Nevertheless, all intake levels were associated with louder snoring (odds ratio, 1.15-1.25). Overall, coffee drinkers reported slightly less DS, but higher intake did not consistently translate into greater benefits.

Findings suggest a possible long-term biological adaptation to caffeine

The study findings challenge the common view that regular coffee consumption meaningfully disrupts sleep. Associations with sleep quality and daytime sleepiness were negligible, and statistically significant results translated into minimal real-world differences. BMI appeared to modify these effects, indicating individuals with higher adiposity may be more susceptible to caffeine-related sleep disruption and could benefit from personalized intake guidance. The weak links may also reflect long-term biological adaptation, a hypothesis proposed by the authors, as sustained caffeine exposure may recalibrate brain adenosine signaling, particularly in older adults.

Genetic analyses confirmed known markers near AHR and CYP1A1/CYP1A2 and identified additional signals near CABIN1 and SUSD2, highlighting potential new biological pathways linking caffeine and sleep. However, the authors note that these findings are exploratory and require further investigation to determine their biological relevance. Future studies should use objective measures of caffeine intake and capture detailed information on consumption sources and timing. Longitudinal, age-comparative designs will also help clarify long-term effects and individual susceptibility.