The bidirectional association of 24-h activity rhythms and sleep with depressive symptoms in middle-aged and elderly persons

Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art

Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.

Twenty-four-hour physical activity patterns associated with depressive symptoms: a cross-sectional study using big data-machine learning approach

BACKGROUND

Depression is a global burden with profound personal and economic consequences. Previous studies have reported that the amount of physical activity is associated with depression. However, the relationship between the temporal patterns of physical activity and depressive symptoms is poorly understood. In this exploratory study, we hypothesize that a particular temporal pattern of daily physical activity could be associated with depressive symptoms and might be a better marker than the total amount of physical activity.

METHODS

To address the hypothesis, we investigated the association between depressive symptoms and daily dominant activity behaviors based on 24-h temporal patterns of physical activity. We conducted a cross-sectional study on NHANES 2011-2012 data collected from the noninstitutionalized civilian resident population of the United States. The number of participants that had the whole set of physical activity data collected by the accelerometer is 6613. Among 6613 participants, 4242 participants had complete demography and Patient Health Questionnaire-9 (PHQ-9) questionnaire, a tool to quantify depressive symptoms. The association between activity-count behaviors and depressive symptoms was analyzed using multivariable logistic regression to adjust for confounding factors in sequential models.

RESULTS

We identified four physical activity-count behaviors based on five physical activity-counting patterns classified by unsupervised machine learning. Regarding PHQ-9 scores, we found that evening dominant behavior was positively associated with depressive symptoms compared to morning dominant behavior as the control group.

CONCLUSIONS

Our results might contribute to monitoring and identifying individuals with latent depressive symptoms, emphasizing the importance of nuanced activity patterns and their probability of assessing depressive symptoms effectively.

Factors associated with the fragmentation and stability of the rest-activity rhythm in adults and older adults

This cross-sectional study aimed to identify factors related to the fragmentation and stability of the rest-activity rhythm (RAR) in adults and older adults. It is part of a larger research project investigating aspects concerning sleep duration, quality, and disorders in a representative subsample of the population. Sociodemographic data, lifestyle, health habits and subjective sleep variables were obtained; RAR records were collected by means of actigraphy and analyzed using non-parametric variables (IS, IV, M10, L5, RA, sL5, and sM10). Study participants were 313 individuals with complete actigraphy records. There was a prevalence of older adults (50.2%) and females (51.1%). Females, individuals with 4-8 y of education, and those who used alcohol abusively exhibited lower RAR fragmentation. Higher fragmentation was observed in individuals who napped and those reporting poor sleep quality. Greater rhythm stability was evident in females, older adults, those with 4-8 y of education, and those who had a partner. Smokers demonstrated lower RAR stability. These findings may contribute valuable insights for decision-making aimed at preventing and treating issues related to fragmentation and instability of the rhythm and its possible consequences to health.

The Rotterdam Study. Design update and major findings between 2020 and 2024

The Rotterdam Study is a population-based cohort study, started in 1990 in the district of Ommoord in the city of Rotterdam, the Netherlands, with the aim to describe the prevalence and incidence, unravel the etiology, and identify targets for prediction, prevention or intervention of multifactorial diseases in mid-life and elderly. The study currently includes 17,931 participants (overall response rate 65%), aged 40 years and over, who are examined in-person every 3 to 5 years in a dedicated research facility, and who are followed-up continuously through automated linkage with health care providers, both regionally and nationally. Research within the Rotterdam Study is carried out along two axes. First, research lines are oriented around diseases and clinical conditions, which are reflective of medical specializations. Second, cross-cutting research lines transverse these clinical demarcations allowing for inter- and multidisciplinary research. These research lines generally reflect subdomains within epidemiology. This paper describes recent methodological updates and main findings from each of these research lines. Also, future perspective for coming years highlighted.

The middle-aged and older Chinese adults' health using actigraphy in Taiwan (MOCHA-T): protocol for a multidimensional dataset of health and lifestyle

BACKGROUND AND OBJECTIVES

Older adults keep transforming with Baby Boomers and Gen Xers being the leading older population. Their lifestyle, however, is not well understood. The middle-aged and older Chinese adults' health using actigraphy in Taiwan (MOCHA-T) collected both objective and subjective data to depict the health and lifestyle of this population. The objectives, design, and measures of the MOCHA-T study are introduced, and the caveats and future directions related to the use of the data are presented.

METHODS

People aged 50 and over were recruited from the community, with a subset of women aged 45-49 invited to supplement data on menopause and aging. Four instruments (i.e., self-reported questionnaires, diary, wrist actigraphy recorder, and GPS) were used to collect measures of sociodemographic, health, psychosocial, behavioral, temporal, and spatial data.

RESULTS

A total of 242 participants who returned the informed consent and questionnaires were recruited in the MOCHA-T study. Among them, 94.6%, 95.0%, and 25.2% also completed the diary, actigraphy, and GPS data, respectively. There was almost no difference in sociodemographic characteristics between those with and without a completed diary, actigraphy, and GPS data, except for age group and educational level for those who returned completed actigraphy data.

CONCLUSION

The MOCHA-T study is a multidimensional dataset that allows researchers to describe the health, behaviors, and lifestyle patterns, and their interactions with the environment of the newer generation of middle-aged and older adults in Taiwan. It can be compared with other countries with actigraphy and GPS-based lifestyle data of middle-aged and older adults in the future.

Sleep Quality is Associated with Axial Length Elongation in Myopic Children Receiving Orthokeratology: A Retrospective Study

Purpose

To identify potential demographic and lifestyle factors associated with progression of myopia with orthokeratology (ortho-k) treatment via follow-up of axial length (AL).

Methods

In this retrospective observational study, demographics, ocular parameters, near-work distance, outdoor activities, and sleep quality were analyzed in 134 children with myopia aged 8~15 years using ortho-k and a follow-up for one year.

Results

Compared with the slow progression group, the participants in the fast progression group were younger in age (10.55 ±1.70 years vs 9.90 ±1.18 years, P = 0.009), demonstrated higher spherical equivalent (SE) value (-2.52 ±0.63 diopters (D) vs -3.05 ±0.89 D, P < 0.001), shorter near-work distance (P = 0.010), and poorer sleep quality (Pittsburgh sleep quality index [PSQI], 4.79 ±1.29 vs 3.81 ±1.38, P < 0.001) in the one-year follow-up. Furthermore, multivariate linear regression analyses showed that baseline age (B =-0.020, P = 0.020), SE (B = 0.0517, P < 0.001), and total PSQI (B=0.026, P = 0.001) were associated with axial elongation. Advanced logistic regression analyses demonstrated that shorter average near-work distance (P = 0.034), higher SE value (P = 0.023), and poorer sleep quality (P = 0.003) were associated with fast axial elongation.

Conclusion

Sleep quality is one of the key factors associated with axial elongation in children with myopia after using ortho-k for one year. Further studies are required to confirm this observation and expand its practical applications.

Rest-Activity Rhythm Characteristics Associated With Depression Symptoms in Stroke Survivors

OBJECTIVE

To examine which 24-hour rest-activity rhythm (RAR) characteristics are associated with depression symptoms in stroke survivors.

DESIGN

Cross-sectional observational study examining associations of RAR characteristics with the presence of depression symptoms adjusting for age, sex, race, and medical comorbidity.

SETTING

Community setting.

PARTICIPANTS

Stroke survivors: (1) recruited locally (N women=35, N men=28) and (2) a nationally representative probability sample (the National Health and Nutrition Examination Survey [NHANES]; N women=156, N men=124).

INTERVENTIONS

None.

MEASUREMENTS

Objective RAR characteristics derived from accelerometer recordings including activity onset/offset times and non-parametric measures of RAR strength (relative amplitude), stability (interdaily stability), and fragmentation (intradaily variability). The presence of depression symptoms was categorized using Patient Health Questionnaire scores.

RESULTS

In both samples, the only RAR characteristic associated with depression symptoms was intradaily variability (fragmentation): local sample, odds ratio=1.96 [95% confidence interval=1.05-3.63]; NHANES sample, odds ratio=1.34, [95% confidence interval=1.01-1.78]). In the NHANES sample, which included both mild and moderate/severe depression, the association between 24-hour sleep-wake fragmentation and depression symptoms was driven by moderate-to-severe cases.

CONCLUSIONS

Stroke survivors with higher levels of RAR fragmentation were more likely to have depression symptoms in both samples. These findings have implications, given prior studies in general samples linking RAR fragmentation with future depression and dementia risk. Research is needed to establish the potential consequences, mechanisms, and modifiability of RAR fragmentation in stroke survivors.

Association of 24-Hour Activity Pattern Phenotypes With Depression Symptoms and Cognitive Performance in Aging

Importance

Evidence regarding the nature and prevalence of 24-hour activity pattern phenotypes in older adults, especially those related to depression symptoms and cognition, is needed to guide the development of targeted mechanism research and behavioral interventions.

Objectives

To identify subgroups of older adults with similar 24-hour activity rhythm characteristics and characterize associated depression symptoms and cognitive performance.

Design, Setting, and Participants

From January to March 2022, a cross-sectional analysis of the 2011-2014 National Health and Nutrition Examination and Survey (NHANES) accelerometer study was conducted. The NHANES used a multistage probability sample that was designed to be representative of noninstitutionalized adults in the US. The main analysis included participants 65 years or older who had accelerometer and depression measures weighted to represent approximately 32 million older adults.

Exposures

Latent profile analysis identified subgroups with similar 24-hour activity pattern characteristics as measured using extended-cosine and nonparametric methods.

Main Outcomes and Measures

Covariate-adjusted sample-weighted regressions assessed associations of subgroup membership with (1) depression symptoms defined as 9-Item Patient Health Questionnaire (PHQ-9) scores of 10 or greater (PHQ-9) and (2) having at least psychometric mild cognitive impairment (p-MCI) defined as scoring less than 1 SD below the mean on a composite cognitive performance score.

Results

The actual clustering sample size was 1800 (weighted: mean [SD] age, 72.9 [7.3] years; 57% female participants). Clustering identified 4 subgroups: (1) 677 earlier rising/robust (37.6%), (2) 587 shorter active period/less modelable (32.6%), (3) 177 shorter active period/very weak (9.8%), and (4) 359 later settling/very weak (20.0%). The prevalence of a PHQ-9 score of 10 or greater differed significantly across groups (cluster 1, 3.5%; cluster 2, 4.7%; cluster 3, 7.5%; cluster 4, 9.0%; χ2 P = .004). The prevalence of having at least p-MCI differed significantly across groups (cluster 1, 7.2%; cluster 2, 12.0%; cluster 3, 21.0%; cluster 4, 18.0%; χ2 P < .001). Five of 9 depression symptoms differed significantly across subgroups.

Conclusions and Relevance

In this cross-sectional study, findings indicate that approximately 1 in 5 older adults in the US may be classified in a subgroup with weak activity patterns and later settling, and approximately 1 in 10 may be classified in a subgroup with weak patterns and shorter active duration. Future research is needed to investigate the biologic processes related to these behavioral phenotypes, including why earlier and robust activity patterns appear protective, and whether modifying disrupted patterns improves outcomes.

Light up: an intervention study of the effect of environmental dynamic lighting on sleep-wake rhythm, mood and behaviour in older adults with intellectual disabilities

BACKGROUND

Evidence-based interventions to improve the sleep-wake rhythm, mood and behaviour in older adults with intellectual disabilities (ID) are limited. Increasing light exposure has been shown to be effective in improving the sleep-wake rhythm, mood, and behaviour in other populations. The current study investigates the effect of installing environmental dynamic lighting in common living rooms of care facilities on sleep-wake rhythm, mood, and behaviour in older adults with ID.

METHODS

A non-randomised, non-concurrent, multiple baseline study was performed from October 2017 to May 2018. Fifty-four participants [mean (SD) age of 63.42 (8.6) years, 65% female] in six care facilities were included. All participants had three baseline measurements (Weeks 1, 5 and 9). Dynamic lighting was installed in Week 10, after which three intervention measurements took place (Weeks 12, 17 and 24). Sleep characteristics and the sleep-wake rhythm were assessed using actigraphy (GENEActiv). Mood was measured with the Anxiety, Depression and Mood Scale (ADAMS) and behaviour with the Aberrant Behaviour Checklist (ABC).

RESULTS

Mixed-effect regression analysis showed a worsening of the primary outcome interdaily stability (P = 0.001). This could be attributed to one care facility, whereas interdaily stability did not change in the other care facilities (P = 0.74). Dynamic lighting led to earlier mid-sleep (P = 0.003) and sleep onset (P < .0001) and improved mood as indicated by lower scores on the ADAMS depression (-0.64 SD, P < 0.001) and social avoidance (-0.47 SD, P = 0.004) subscales. The prevalence of screening above cut-off for depression decreased from 23 to 9.8% (OR = .16, P = 0.003). For behaviour, a decrease was seen in hyperactivity (-0.43 SD, P < 0.001), lethargy (-0.35 SD, P = 0.008) and irritability (-0.33 SD, P < .001) as measured with the ABC. No adverse effects were reported.

CONCLUSION

Installing dynamic lighting in common living areas for older adults with ID improved the mood and behaviour of the residents up to 14 weeks after placement. Integrated dynamic lighting is a promising, undemanding and potentially effective addition to improve mood and behaviour in care organisations for people with ID, but does not seem to do so by improving sleep or sleep-wake rhythms.