Think about the last time you had a bad night of sleep: maybe you snapped at someone you care about over something tiny or felt overwhelmed by emails that would not normally faze you. Then, after a few nights of better sleep, those same situations often felt manageable again.
Poor sleep is increasingly recognised as a key factor in mental health. For example, people with insomnia are 10 times more likely to develop depression, and 17 times more likely to develop anxiety (Taylor et al., 2005).
Sleep problems also appear more prevalent in females and older adults (Leblanc et al., 2015; Taylor et al., 2005). It is therefore important to understand how sleep patterns differ by age and sex across the lifespan, and how these patterns are associated with mood and wellbeing.
To do this, the current study aimed to provide normative reference values for sleep patterns in daily life using objective sleep-tracking data from over 77,000 individuals aged 44-82 years. Specifically, the study quantified age and sex-related differences in sleep duration, timing (onset and wake time) and daytime activity; compared objectively recorded sleep with self-reported sleep; and assessed how these sleep measures were related to mood symptoms.
Sleep is closely tied to mental health, but how it varies by age and sex across later life remains unclear.
Methods
Participants were drawn from the UK biobank, a large cohort of over 500,000 adults across the UK. In 2014-2015, a subset was randomly invited to wear wrist-worn accelerometers for seven days to measure physical activity, from which sleep metrics were derived. In 2017, these participants completed an online mental health questionnaire based on the WHO Composite International Diagnostic Interview (Wittchen, 1994), including items on sleep, depression and anhedonia (i.e., lack of pleasure).
Means and standard deviations were used to describe the effects of age, sex and day of the week on sleep measures. Differences between self-reported sleep duration groups (6-9 hours) were tested using one-way ANOVA and binary self-report groups for recent symptoms of depression and anhedonia (i.e. Yes vs No) were compared using two sample t-tests.
Results
After rigorous quality control, 77,093 participants remained. To allow independent replication, the sample was split into discovery (N=38,546) and a replication (N=38,547) dataset, matched by sex and grouped into seven age groups spanning 44-82 years. Analyses were conducted in the discovery dataset and then replicated in the replication dataset.
Sleep patterns differ by age and sex
- Males showed shorter sleep durations than females across most age groups, particularly those under 60.
- This was driven by later sleep onset and earlier wake times, resulting (on average) in about 17 minutes less sleep compared to females.
- In participants in their 70s, the gap between males and females diminished, with similar sleep durations and wake times, potentially coinciding with reduced occupational and societal influences.
- Participants tended to wake later in their 60s, reflecting possible biological changes in sleep-wake regulation or lifestyle changes after retirement.
Sleep patterns differ between weekend and weekdays
- Participants under 60 went to bed later, woke up later and slept about 50 minutes longer at weekends.
- Males show less variation in sleep onset between weekends and weekdays, suggesting their later bedtimes may not be solely driven by work schedules.
- For older participants (>65 years), weekend and weekday sleep were similar.
Wake activity and daily activity patterns differ by age and sex
- Wake activity (i.e., actions that occur during transition from sleep to alertness such as morning routines) declined with age, with a steeper reduction in males.
- Participants under 60 were more active at weekends and older participants showed lower but more stable activity across the week.
- Across the sample, activity was higher in the morning and lower in the evenings, with morning and afternoon activity higher at weekends.
Objective sleep and activity differ in relation to self-reported sleep
- Self-reported sleep duration predicted objectively measured sleep duration, but subjective differences between “short” and “long” sleepers were larger than objective differences.
- Self-reports of “waking too early” were associated with earlier objective wake times but not shorter total sleep duration.
- Endorsing “too much sleep” was linked to later sleep onset and wake times and lower wake activity, but not to longer total sleep duration.
Objective sleep and activity differ in relation to self-reported mood
- Recent symptoms of depression and anhedonia were associated with lower daily wake activity.
- Older females (>54 years) with recent depressive symptoms tended to show reduced sleep duration.
- Men reporting recent depressive symptoms also showed later sleep onset.
Sleep varies systematically by age, sex, and lifestyle, with differences in timing, duration, activity, and mood revealing a complex and shifting picture across later life.
Conclusions
The findings from this large-scale study provide comprehensive normative reference for how objective sleep measures (both duration and timing) vary with age and sex, and how they relate to self-reported sleep and mood. The results show replicable demographic differences, highlighting non-linear interactions between age and sex.
Objective measures of sleep also have nuanced associations with subjective reports of sleep and mood. These findings underscore the importance of demographic context when interpreting sleep patterns and the need to use both objective and subjective measures of sleep. Future longitudinal work is needed to clarify the mechanisms underlying these variations in sleep and their implications for mental health.
Sleep is not one-size-fits-all, and understanding its links with mood requires combining objective measures with subjective experience across age and sex.
Strengths and limitations
A major strength of this study is the use of a large UK biobank sample (N > 77,000) combined with objective sleep measures, addressing a common limitation of reliance on self-reported data often seen in cohort studies. Self-reported sleep quality often differs from objective measures (Buysse et al., 2008), making multimodal assessment important. Indeed, this study found that estimates of short vs long sleep were considerably larger than objectively measured differences, highlighting the value of including both measures when examining sleep-mood associations.
However, UK biobank participants are not fully representative of the general population. Fry et al. (2017) found participants were more likely to be older, female, from less deprived areas, and had fewer self-reported health conditions, with these authors suggesting evidence of a “healthy volunteer” selection bias. Additionally, the sample was limited to adults aged 44+ years, precluding generalisation to younger ages. Sleep problems are particularly prevalent in adolescents, with ~69-73% of adolescents not getting enough sleep (Eaton et al., 2010; Wheaton, 2018). The sleep-mental health association is also particularly important in adolescents (Patel et al., 2007), yet the study lacks objective normative sleep data for this age group.
Furthermore, mental health assessment was limited. First, only depression and anhedonia were measured. Other important mental health outcomes such as anxiety, which has also been associated with sleep disturbances (Chen et al., 2017; Chinvararak et al., 2025), was not assessed. Second, depression and anhedonia were dichotomised (“Yes” for any symptom endorsement; “No” otherwise), losing nuance and preventing the examination of associations between objective sleep measures and symptom severity. Finally, the cross-sectional design of the study precludes causal inference so we cannot determine whether recent depression symptoms cause lower daily wake activity or vice versa.
This study benefits from a large UK Biobank sample and objective sleep measures, but is constrained by selection bias, restricted age range, limited mental health assessment, and cross-sectional design.
Implications for practice
The findings reveal complex changes in sleep onset, wake times, and sleep duration across age and sex. First, males exhibited shorter sleep duration than females, particularly in middle-aged groups. This may reflect cultural attitudes where men view sleep as an “unfortunate necessity” competing with work responsibilities, reinforced by “hustle culture” messaging (e.g., “I’ll sleep when I’m dead”). These findings therefore suggest the need for public health interventions emphasising sleep importance, particularly in occupational contexts. Notably, these sex differences diminished in older adults, suggesting work responsibilities may indeed play a role.
Relatedly, individuals under 60 obtained approximately 50 minutes more sleep on weekends. This pattern aligns with social jetlag, where individuals accumulate sleep debt during the week and compensate by sleeping longer on weekends (Wittmann et al., 2006). While this discrepancy raises concerns about chronic sleep deprivation, recent UK biobank data found that weekend catch-up sleep was unrelated to mortality or cardiovascular disease (Chaput et al., 2024).
Self-reported estimates of short versus long sleep were considerably larger than objective measures, highlighting the importance of integrating both modalities to capture complementary aspects of sleep behaviour with distinct age and health trajectories.
Recent depression symptoms were associated with both later sleep onset and shorter sleep duration, corroborating prior research on self-reported sleep and depression (Joo et al., 2022). Depression was also associated with reduced wake activity. These findings further emphasise the potential efficacy of lifestyle interventions for depression incorporating exercise and sleep hygiene components (Firth et al., 2020).
Given robust variation in sleep patterns between groups and individuals, further work is needed to disentangle biological or other factors underpinning these differences. Future studies could combine objective sleep data with genotyping and/or neuroimaging to identify genetic and neural markers of sleep pattern variation across age and sex.
Sleep should be treated as a modifiable health behaviour in both clinical and workplace settings, with interventions targeting sleep habits, mental health, and daily activity across different age and sex groups.
Statement of interests
Emma Sullivan has no conflicts of interests to report.
Editor
Edited by Éimear Foley. AI tools assisted with language refinement and formatting during the editorial phase.
Links
Primary paper
Rahimi-Eichi, Habiballah, Baker, Justin T., Fjell, Anders M., & Buckner, Randy L. (2025). Age- and sex-related differences in sleep patterns and their relations to self-reported sleep and mood. SLEEP Advances, 6(4), zpaf079. https://doi.org/10.1093/sleepadvances/zpaf079
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