Early predictors of impaired sleep: a study on life course socioeconomic conditions and sleeping problems in older adults

Pandemic policies and sleeping problems in older adults

Sleep quality is fundamental to physical and mental health. Recent research shows that the COVID-19 pandemic has affected individuals' sleep quality. This study aims to investigate whether the containment and health policies (Oxford Coronavirus Government Response Tracker indexes) adopted by European countries and Israel during the pandemic are related to sleep problems in people aged 50 and over. A cross-sectional study was conducted using a logistic regression analysis based on data from the Survey of Health, Ageing and Retirement in Europe, collected in 27 European countries and Israel, in 2021. The results show that containment and health policies affect older adults' sleep, once we neutralise the influence of the sociodemographic, economic, and health characteristics of the individuals and close contact with COVID-19. In fact, the more containment and health policies, the fewer chances of sleep problems. A possible explanation for this is that these policies give people over 50 a sense of safety and security in relation to COVID-19, which may reduce sleep problems.

Intra-generational social mobility and mortality among older men in the Concord Health and Ageing in Men Project: A cohort study

Objectives

We examined associations between intra-generational social mobility (reflected in life-course socioeconomic trajectories) and mortality, among older men.

Methods

Data came from a prospective Australian community-based cohort of older men. Social mobility was defined by socioeconomic indicators from three points in the life-course: educational attainment (late adolescence-early adulthood), occupation (mid-life), and current sources of income (older age). We defined indicators of social mobility trajectory (6 categories; reflecting the direction of social mobility) and social mobility status (2 categories; mobile or non-mobile). We used Cox regression to examine associations with mortality, adjusting for age, country of birth, and living arrangement.

Results

We followed 1568 men (mean age 76.8, SD 5.4) for a mean duration of 9.1 years, with 797 deaths recorded. Moving upward was the predominant social mobility trajectory (36.0%), followed by mixed trajectories (25.1%), downward (15.1%), stable low (12.2%), stable high (7.6%), and stable middle (4.0%). Men with downward (Hazard ratio 1.58, 95% CI 1.13 to 2.19) and stable low socioeconomic trajectories (1.77, 1.25 to 2.50) had higher mortality risks than men with stable high socioeconomic trajectories, while men with upward trajectories had similar risks to those with stable high trajectories. 76.2% of the participants were classified as having mobile status; no associations were evident between binary social mobility status and mortality.

Discussions

These findings suggest cumulative and persistent exposure to disadvantaged socioeconomic conditions across the life-course, rather than social mobility, is associated with increased mortality. For each stage of the life-course, addressing socioeconomic disadvantage may reduce inequities in mortality.

Prevalence of Sleep Disturbances in Latin American Populations and Its Association with Their Socioeconomic Status-A Systematic Review and a Meta-Analysis

BACKGROUND

The worldwide increase in the prevalence and incidence of sleep disturbances represents a major public health issue. Among multiple determinants affecting sleep health, an individual's socioeconomic status (SES) is the most ignored and underestimated throughout the literature. No systematic review on the relation between SES and sleep health has been previously conducted in Latin America.

METHODS

PRISMA guidelines were used.

RESULTS

Twenty articles were included in the final sample (all cross-sectional studies), and twelve among them were rated as fair or poor quality. Among these studies, 80.0% (n = 16) were performed in Brazil, 10.0% (n = 2) were performed in Peru, 5.0% (n = 1) were performed in Chile, and 5.0% (n = 1) were multicentric (11 countries). The combined total number of participants was N = 128.455, comprising 3.7% (n = 4693) children, 16.0% (n = 20,586) adolescents, and 80.3% (n = 103,176) adults. The results show the following: (1) The sleep outcomes analyzed were sleep duration, sleep quality/sleep disturbance, insomnia, excessive daytime sleepiness (EDS), obstructive sleep apnea (OSA)/sleep-disordered breathing (SDB) symptoms, and bruxism. (2) The most used determinants were income, education level, employment status/occupation, wealth/assets, and composite indices. (3) Higher SES was associated with shorter sleep duration. (4) Lower SES was associated with a decrease in sleep quality, less frequent snoring, more prevalent EDS, and sleep bruxism. (5) Lower education was associated with insomnia. (6) Higher education was associated with more sleep bruxism. (7) The pooled prevalence using a meta-analysis of the random effects model was 24.73% (95%CI, 19.98-30.19), with high heterogeneity (I2 = 100%). (8) The prevalence of sleep disturbances decreased with high education (OR, 0.83; 95%CI, [0.69-0.99]; I2 = 79%), while it increased with low income (OR, 1.26; 95%CI, [1.12-1.42]; I2 = 59%), unemployment (OR, 2.84; 95%CI, [2.14-3.76]; I2 = 0%), and being a housewife (OR, 1.72; 95%CI, [1.19-2.48]; I2 = 55%).

DISCUSSION

This meta-analysis shows that lower SES (education, income, and work) was associated with sleep disturbances in Latin America. Therefore, sleep disturbance management should be addressed with a multidimensional approach, and a significant investment in targeted public health programs to reduce sleep disparities and support research should be made by the government before the situation becomes uncontrollable.

Socioeconomic status and sleep health: a narrative synthesis of 3 decades of empirical research

STUDY OBJECTIVES

This review aims to assess the association between socioeconomic status (SES) and sleep health in the general population and the mediating effects of lifestyle and mental and physical health in this relationship.

METHODS

Observational studies testing the independent association between objective or subjective SES indicators and behavioral/physiological or clinical sleep health variables in the general population were included. PubMed/MEDLINE was searched for reports published from January 1990 to December 2019. The direction of effect was used as the primary effect measure, testing the hypothesis that low SES is associated with poor sleep health outcomes. Results are presented in the form of direction effect plots and synthesized as binomial proportions.

RESULTS

Overall, 336 studies were identified. A high proportion of effects at the expected direction was noted for measures of sleep continuity (100% for sleep latency, 50-100% for awakenings, 66.7-100% for sleep efficiency), symptoms of disturbed sleep (75-94.1% for insomnia, 66.7-100% for sleep-disordered breathing, 60-100% for hypersomnia), and general sleep satisfaction (62.5-100%), while the effect on sleep duration was inconsistent and depended on the specific SES variable (92.3% for subjective SES, 31.7% for employment status). Lifestyle habits, chronic illnesses, and psychological factors were identified as key mediators of the SES-sleep relationship.

CONCLUSIONS

Unhealthy behaviors, increased stress levels, and limited access to health care in low-SES individuals may explain the SES-sleep health gradient. However, the cross-sectional design of most studies and the high heterogeneity in employed measures of SES and sleep limit the quality of evidence. Further research is warranted due to important implications for health issues and policy changes.

CITATION

Papadopoulos D, Etindele Sosso FA. Socioeconomic status and sleep health: a narrative synthesis of 3 decades of empirical research. J Clin Sleep Med. 2023;19(3):605-620.

Physical inactivity amplifies the negative association between sleep quality and depressive symptoms

Poor sleep quality and physical inactivity are known risk factors for depressive symptoms. Yet, whether these factors differently contribute to depressive symptoms and whether they interact with one another remains unclear. Here, we examined how sleep quality and physical activity influence depressive symptoms in 79,274 adults 50 years of age or older (52.4% women) from the Survey of Health, Aging and Retirement in Europe (SHARE) study. Sleep quality (poor vs. good), physical activity (inactive vs. active), and depressive symptoms (0 to 12 score) were repeatedly collected (7 waves of data collection) between 2004 and 2017. Results showed that sleep quality and physical activity were associated with depressive symptoms. Specifically, participants with poorer sleep quality reported more depressive symptoms than participants with better sleep quality (b = 1.85, 95% CI = 1.83-1.86, p < .001). Likewise, compared to physically active participants, physically inactive participants reported more depressive symptoms (b = 0.44, 95% CI = 0.42-0.45, p < .001). Moreover, sleep quality and physical activity showed an interactive association with depressive symptoms (b = 0.17, 95% CI = 0.13-0.20, p < .001). The negative association between poor sleep quality and higher depressive symptoms was stronger in physically inactive than active participants. These findings suggest that, in adults 50 years of age or older, both poor sleep quality and physical inactivity are related to an increase in depressive symptoms. Moreover, the detrimental association between poor sleep quality and depressive symptoms is amplified in physically inactive individuals.

Towards A Socioeconomic Model of Sleep Health among the Canadian Population: A Systematic Review of the Relationship between Age, Income, Employment, Education, Social Class, Socioeconomic Status and Sleep Disparities

A better understanding of the contribution of the socioeconomic status (SES) in sleep health could guide the development of population-based interventions aiming to reduce “the silent public health issue” that are sleep disturbances. PRISMA was employed to identify relevant studies having examined the association between social class, social capital, education, income/assets, occupation/employment status, neighborhood deprivation and sleep health. Sixteen cross-sectional and three longitudinal studies were selected, having sampled 226,029 participants aged from 2 months to 85 years old. Findings showed that: (1) sleep health disparities among children and adolescent are strongly correlated to parental socioeconomic indicators; (2) poor parental income, poor family SES and poor parental education are associated with higher sleep disturbances among children and adolescents; (3) lower education is a predictor of increased sleep disturbances for adults; (4) low SES is associated with high sleep disturbances in adults and old people and; (5) low income and full-time employment was significantly associated with short sleep among adults and old people. In conclusion, sleep health should be an important public health target. Such intervention would be beneficial for populational health, for all taxpayers and public administrations, which would see a reduction in absenteeism and productivity losses attributable to sleep-related health problems in the global economy.

Childhood deprivations predict late-life cognitive impairment among older adults in India

Large population-based studies on the associations of childhood factors with late-life cognition are lacking in many low and middle income countries including India. In this study, we assessed the prevalence of late-life cognitive impairment and examined the associations of childhood socioeconomic status (SES) and health conditions with cognitive impairment among older adults in India. Data for this study were derived from the Longitudinal Ageing Study in India conducted in 2017-18. The effective sample size was 31,464 older adults aged 60 years and above. Cognitive functioning was measured through five global domains (memory, orientation, arithmetic function, executive function, and object naming). The overall score ranged between 0 and 43, and the score was reversed indicating cognitive impairment. Descriptive statistics along with mean scores of cognitive impairment were presented. Additionally, moderated multivariable linear regression models were employed to examine the association between explanatory variables, including childhood SES and health conditions and late-life cognitive impairment. The mean score of cognitive functioning among the study participants was 21.72 (CI 2.64-21.80). About 15% of older adults had poor health conditions, and 44% had lower financial status during their childhood. Older adults who had a fair health during their childhood were more likely to suffer from cognitive impairment in comparison to older adults who had good health during their childhood (Coef: 0.60; CI 0.39, 0.81). In comparison to older adults who had good childhood financial status, those who had poor childhood financial status were more likely to suffer from cognitive impairment (Coef: 0.81; CI 0.56, 1.07). Older adults who had fair childhood health status and poor childhood financial status were more likely to suffer from cognitive impairment in comparison to older adults who had good childhood health and good financial status (Coef: 1.26; CI 0.86, 1.66). Social policies such as improving educational and financial resources in disadvantaged communities and socioeconomically poor children and their families, would help to enhance a better cognitive ageing and a healthy and dignified life in old age.

Better Subjective Sleep Quality Partly Explains the Association Between Self-Reported Physical Activity and Better Cognitive Function

Background: Physical activity has been associated with better cognitive function and better sleep quality. Yet, whether the beneficial effect of physical activity on cognitive function can be explained by an indirect pathway involving better sleep quality is unclear. Objective: To investigate whether sleep quality mediates the association between physical activity and cognitive function in adults 50 years of age or older. Methods: 86,541 community-dwelling European adults were included in the study. Physical activity and sleep quality were self-reported. Indicators of cognitive function (immediate recall, delayed recall, verbal fluency) were assessed using objective tests. All measures were collected six times between 2004 and 2017. The mediation was tested using multilevel mediation analyses. Results: Results showed that self-reported physical activity was associated with better self-reported sleep quality, which was associated with better performance in all three indicators of cognitive function, demonstrating an indirect effect of physical activity on cognitive function through sleep quality. The mediating effect of sleep quality accounted for 0.41%, 1.46%, and 8.88% of the total association of physical activity with verbal fluency, immediate recall, and delayed recall, respectively. Conclusion: These findings suggest that self-reported sleep quality partly mediates the association between self-reported physical activity and cognitive function. These results need to be confirmed by device-based data of physical activity and sleep quality.

Influence of socioeconomic status on objective sleep measurement: A systematic review and meta-analysis of actigraphy studies

Social inequities have many health effects; one of these is a potential relationship to sleep disturbances. Socioeconomic status (SES) is an important factor that contributes to social inequities. SES is a marker of living conditions and habits that influence health by way of different processes, including stress-related mechanisms. However, a systematic review of the relationship between SES and objectively measured sleep parameters has not been conducted. Therefore, a systematic review and meta-analysis were performed to examine the relationship between SES and sleep parameters measured with actigraphy in the general population. Nineteen articles were identified and included from a keyword search in Medline/PubMed, Web of Science, and SCOPUS, following PRISMA guidelines. For an article to be included, it had to have a measure of SES and also, an actigraphy-based measure of sleep. For, included studies, qualitative and quantitative data were extracted, and study quality was assessed with The National Institute of Health's Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Bivariate correlations were extracted and entered into a meta-analysis, along with a qualitative review of articles. These analyses revealed that SES was associated with sleep parameters in the predicted direction, with lower SES associated with worse sleep parameters. Specifically, lower SES was associated with lower total sleep time, longer sleep latency, greater sleep fragmentation, and higher variability in sleep onset and sleep latency. Higher education, higher perceived economic well-being, and higher income were significantly associated with improved sleep efficiency and longer sleep duration. For the 19 articles included, 10 were rated as fair or poor in study quality. Thus, higher quality studies in this area are needed. This meta-analysis and systematic review demonstrated that social inequities of sleep can be measured objectively, opening the path to the development and integration of methodologies combining actigraphy with current subjective measures for utilization in clinical practice.

Why Are Individuals With Diabetes Less Active? The Mediating Role of Physical, Emotional, and Cognitive Factors

BACKGROUND

Despite the key role of physical activity in the management of diabetes, many individuals with diabetes do not engage in the recommended levels of physical activity. However, our knowledge of the mechanisms underlying the relationship between diabetes and physical inactivity is limited.

PURPOSE

To investigate the associations between diabetes and the levels and evolution of physical activity across aging, and to determine whether physical, emotional, and cognitive factors mediate these associations.

METHODS

Data from 105,622 adults aged 50-96 years from the Survey of Health, Ageing and Retirement in Europe (SHARE) were used in adjusted linear mixed models to examine whether diabetes was associated with physical activity levels and variations across aging. The potential mediators were subjective energy, muscle strength, physical and cognitive disability, sleep problems, depressive symptoms, and cognitive functions. The variables were measured up to seven times over a 13-year period.

RESULTS

Individuals with diabetes demonstrated a lower level and a steeper decrease in physical activity across aging than individual without diabetes. Mediators explained ~53% and 94% of the association of diabetes with the level of physical activity and with the linear evolution of physical activity across aging, respectively. All mediators were significantly associated with physical activity. Physical and cognitive disability as well as depressive symptoms were the strongest mediators, while sleep was the lowest one.

CONCLUSIONS

These findings suggest that the etiology of physical inactivity in individuals with diabetes can result from several physical, emotional, and cognitive changes associated with the emergence of this disease.

24-hour movement behaviour and executive function in preschoolers: A compositional and isotemporal reallocation analysis

Adherence to healthy behaviours promotes several health benefits in preschool children, including executive function (EF). Recently, the predictive power of the 24-hour movement behaviour (24 h MB) composition on health outcomes has been evidenced; however, its relationship with EF in preschoolers is unknown. Thus, the present study had two objectives: (1) to analyse the associations between the 24 h MB composition and EF of preschoolers; and (2) to investigate the theoretical changes in EF when time in different movement behaviours is reallocated. This cross-sectional study was carried out with 123 preschoolers (3-5 years old) of low socioeconomic status. Physical activity (PA) and sedentary behaviour were assessed using an accelerometer for 7 days, sleep time was obtained through interviews with parents, and EF was measured using the Early Tool Box battery. To verify the association between 24 h MB and EF, compositional data analysis was used, and for time reallocation, compositional isotemporal substitution analysis was utilized. It was observed that the 24 h MB composition was positively associated with EF (p < .0001; R² = 0.34), and that reallocating 5, 10, 15 or 20 min of the time spent on sleep and light PA to moderate-to-vigorous PA, respectively, was associated with significant improvements in EF (p < .05). These findings provide hitherto unseen insight into the relationship between 24 h MB and EF in preschool children, and warrants consideration for researchers and practitioners seeking to improve EF and PA in preschool children.

Association Between Childhood Behavioral Problems and Insomnia Symptoms in Adulthood

Importance

Life-course determinants of insomnia, particularly the long-term association of childhood behavioral problems with insomnia later in life, are unknown. As childhood behaviors are measurable and potentially modifiable, understanding their associations with insomnia symptoms may provide novel insights into early intervention strategies to reduce the burden.

Objective

To investigate the association between behavioral problems at 5, 10, and 16 years of age and self-reported insomnia symptoms at 42 years of age.

Design, Setting, and Participants

This cohort study used data from the United Kingdom 1970 Birth Cohort Study, an ongoing large-scale follow-up study. Participants were followed up from birth (1970) to age 42 years (2012). Missing data were imputed via multiple imputation. Statistical analysis was performed from February 1 to July 15, 2019.

Exposures

Behavior measured at 5, 10, and 16 years of age using the Rutter Behavioral Scale (RBS). Children's behavior was classified as normal (≤80th percentile), moderate behavioral problems (>80th to ≤95th percentile), and severe behavioral problems (>95th percentile) based on their RBS score.

Main Outcomes and Measures

Self-reported difficulties initiating or maintaining sleep (DIMS) were collected using a self-administered questionnaire at 42 years of age. Log-binomial logistic regression, adjusted for several potential confounders, was used to estimate the association of childhood behavioral problems with insomnia symptoms in adulthood. Sensitivity analyses were conducted to check robustness of the findings.

Results

Participants were followed up from a baseline age of 5 years (n = 8050; 3854 boys and 4196 girls), 10 years (n = 9090; 4365 boys and 4725 girls), or 16 years (n = 7653; 3575 boys and 4078 girls) until age 42 years. There was a 39% higher risk of DIMS (odds ratio [OR], 1.39; 95% CI, 1.04-1.84; P = .06 for trend) for participants with severe behavioral problems at 5 years of age compared with those with a normal RBS score. The odds of DIMS plus not feeling rested on waking (DIMS plus) in participants with severe behavioral problems at 5 years of age were 29% higher (odds ratio, 1.29; 95% CI, 0.97-1.70; P = .14 for trend) than participants with a normal RBS score, although this result was not statistically significant. Moderate and severe behavioral problems at 16 years of age were positively associated with DIMS and DIMS plus (moderate: OR, 1.28; 95% CI, 1.07-1.52; severe: OR, 1.67; 95% CI, 1.22-2.30; P < .001 for trend) and DIMS plus (moderate: OR, 1.32; 95% CI, 1.11-1.56; severe: OR, 1.47; 95% CI, 1.09-1.98; P < .001 for trend). Externalizing behavioral problems at 5 and 10 years of age were positively associated with insomnia symptoms at 42 years of age.

Conclusions and Relevance

This study is the first to show associations of early-life behavioral problems, particularly early- and middle-childhood externalizing problems, with insomnia symptoms in adulthood. These findings underline the importance of addressing insomnia from a life-course perspective and considering the benefits of early behavioral intervention to sleep health.