Pub Date : 2024-08-23DOI: 10.1016/j.sleh.2024.07.007
Paula R. Pienaar PhD , Laura C. Roden PhD , Cécile R.L. Boot PhD , Willem van Mechelen PhD, MD , Jason A. Suter MD , Estelle V. Lambert PhD , Dale E. Rae PhD
Objectives
Corporate executive job demands may lead to poor sleep habits, increasing their risk for cardiometabolic disease. This study aimed to describe and explore associations between objectively measured habitual sleep characteristics and cardiometabolic disease risk of corporate executives, while accounting for occupational, psychological, and lifestyle factors.
Methods
Habitual sleep was measured using wrist-worn actigraphy and a sleep diary over seven consecutive days in 61 (68.3% men) corporate executives aged 46.4 ± 8.7 years. A composite cardiometabolic disease risk score was determined using body mass index, waist circumference, blood pressure and fasting glucose and lipid concentrations. Prediction models were built using a backward stepwise selection approach to explore associations between sleep characteristics and cardiometabolic disease risk factors adjusting for occupational, psychological, and lifestyle covariates.
Results
Average total sleep time was 6.60 ± 0.75 hours, with 51.7% of participants reporting poor sleep quality and 26.2% extending their weekend sleep. Adjusted models showed that lower sleep efficiency (β = − 0.25, 95%CI: − 0.43; − 0.08, P = .006), shorter weekday total sleep time (β = − 1.37, 95% CI: − 2.41, − 0.32; P = .011) and catch-up sleep (β = 0.84, 95%CI: 0.08, 1.60, P = .002) were associated with higher cardiometabolic disease risk scores. Adjusted models also found that shorter average time-in-bed (ß = − 2.00, 95%CI: − 3.76; − 0.18, P = .031), average total sleep time (ß = 1.98, 95%CI: − 3.70; − 0.25, P = .025) and weekday total sleep time (β = − 2.13, 95%CI: − 3.56; − 0.69, P = .025) as well as catch-up sleep (β = 1.67, 95% CI: 0.52; 2.83; P = .012) were all associated with a higher body mass index.
Conclusion
Corporate executives who compromise sleep duration during the working week may increase their risk for obesity and future cardiometabolic disease.
{"title":"Associations between habitual sleep characteristics and cardiometabolic disease risk in corporate executives","authors":"Paula R. Pienaar PhD , Laura C. Roden PhD , Cécile R.L. Boot PhD , Willem van Mechelen PhD, MD , Jason A. Suter MD , Estelle V. Lambert PhD , Dale E. Rae PhD","doi":"10.1016/j.sleh.2024.07.007","DOIUrl":"10.1016/j.sleh.2024.07.007","url":null,"abstract":"<div><h3>Objectives</h3><p>Corporate executive job demands may lead to poor sleep habits, increasing their risk for cardiometabolic disease. This study aimed to describe and explore associations between objectively measured habitual sleep characteristics and cardiometabolic disease risk of corporate executives, while accounting for occupational, psychological, and lifestyle factors.</p></div><div><h3>Methods</h3><p>Habitual sleep was measured using wrist-worn actigraphy and a sleep diary over seven consecutive days in 61 (68.3% men) corporate executives aged 46.4 ± 8.7<!--> <!-->years. A composite cardiometabolic disease risk score was determined using body mass index, waist circumference, blood pressure and fasting glucose and lipid concentrations. Prediction models were built using a backward stepwise selection approach to explore associations between sleep characteristics and cardiometabolic disease risk factors adjusting for occupational, psychological, and lifestyle covariates.</p></div><div><h3>Results</h3><p>Average total sleep time was 6.60 ± 0.75 hours, with 51.7% of participants reporting poor sleep quality and 26.2% extending their weekend sleep. Adjusted models showed that lower sleep efficiency (β = −<!--> <!-->0.25, 95%CI: −<!--> <!-->0.43; −<!--> <!-->0.08, <em>P</em> = .006), shorter weekday total sleep time (β = −<!--> <!-->1.37, 95% CI: −<!--> <!-->2.41, −<!--> <!-->0.32; <em>P</em> = .011) and catch-up sleep (β = 0.84, 95%CI: 0.08, 1.60, <em>P</em> = .002) were associated with higher cardiometabolic disease risk scores. Adjusted models also found that shorter average time-in-bed (ß<!--> <!-->=<!--> <!-->−<!--> <!-->2.00, 95%CI: −<!--> <!-->3.76; −<!--> <!-->0.18, <em>P</em> = .031), average total sleep time (ß<!--> <!-->=<!--> <!-->1.98, 95%CI: −<!--> <!-->3.70; −<!--> <!-->0.25, <em>P</em> = .025) and weekday total sleep time (β = −<!--> <!-->2.13, 95%CI: −<!--> <!-->3.56; −<!--> <!-->0.69, <em>P</em> = .025) as well as catch-up sleep (β = 1.67, 95% CI: 0.52; 2.83; <em>P</em> = .012) were all associated with a higher body mass index.</p></div><div><h3>Conclusion</h3><p>Corporate executives who compromise sleep duration during the working week may increase their risk for obesity and future cardiometabolic disease.</p></div>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":"10 5","pages":"Pages 550-557"},"PeriodicalIF":3.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352721824001669/pdfft?md5=fe19e6cb2127c89d30fcbdbcbb6e8715&pid=1-s2.0-S2352721824001669-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142047343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-21DOI: 10.1016/j.sleh.2024.06.002
Younghwa Baek, Kyoungsik Jeong, Siwoo Lee
Objective: Sleep is a potential risk factor for metabolic syndrome. We investigated the associations of various sleep characteristics with the status and incidence of metabolic syndrome in middle-aged Koreans.
Methods: Using data from a community-based Korean Medicine Daejeon Citizen Cohort study on participants aged 30-50years, cross-sectional (n = 1984) and longitudinal (n = 1216, median follow-up: 2.1years) analyses were performed. To study the association of metabolic syndrome and five components with various sleep characteristics, measured using the Pittsburgh Sleep Quality Index, we used Poisson and logistic regression and Cox proportional hazard regression analyses, adjusting for covariates.
Results: Of 1984 participants, 66%, 19%, and 15% belonged to the non-metabolic syndrome, pre-metabolic syndrome, and metabolic syndrome groups, respectively. After covariate adjustments, the pre-metabolic syndrome group was associated with late mid-sleep time (≥5:00; prevalence ratios 1.61, 95% confidence interval 1.01-2.54) and late bedtime (≥2:00; prevalence ratios 1.55, 95% confidence interval 1.03-2.34), and the metabolic syndrome group was associated with long sleep latency (prevalence ratios 1.33, 95% confidence interval 1.03-1.73), poor sleep quality (prevalence ratios 1.38, 95% confidence interval 1.07-1.78), and early wake time (<6:00; prevalence ratios 1.29, 95% confidence interval 1.01-1.63). Longitudinal analysis of participants without metabolic syndrome at baseline indicated a significant increase in metabolic syndrome risk associated with very short sleep duration (<6 hours; hazard ratio 1.72, 95% confidence interval 1.06-2.79), long sleep latency (>30 minutes; hazard ratio 1.86, 95% confidence interval 1.1-3.12), and early wake time (<6:00 o'clock; hazard ratio 1.73, 95% confidence interval 1.01-2.97).
Conclusion: Sleep characteristics, such as short duration, long latency, and early wake time, were associated with an increased risk of metabolic syndrome in middle-aged adults.
{"title":"Association of sleep timing, sleep duration, and sleep latency with metabolic syndrome in middle-aged adults in Korea: A cross-sectional and longitudinal study.","authors":"Younghwa Baek, Kyoungsik Jeong, Siwoo Lee","doi":"10.1016/j.sleh.2024.06.002","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.06.002","url":null,"abstract":"<p><strong>Objective: </strong>Sleep is a potential risk factor for metabolic syndrome. We investigated the associations of various sleep characteristics with the status and incidence of metabolic syndrome in middle-aged Koreans.</p><p><strong>Methods: </strong>Using data from a community-based Korean Medicine Daejeon Citizen Cohort study on participants aged 30-50years, cross-sectional (n = 1984) and longitudinal (n = 1216, median follow-up: 2.1years) analyses were performed. To study the association of metabolic syndrome and five components with various sleep characteristics, measured using the Pittsburgh Sleep Quality Index, we used Poisson and logistic regression and Cox proportional hazard regression analyses, adjusting for covariates.</p><p><strong>Results: </strong>Of 1984 participants, 66%, 19%, and 15% belonged to the non-metabolic syndrome, pre-metabolic syndrome, and metabolic syndrome groups, respectively. After covariate adjustments, the pre-metabolic syndrome group was associated with late mid-sleep time (≥5:00; prevalence ratios 1.61, 95% confidence interval 1.01-2.54) and late bedtime (≥2:00; prevalence ratios 1.55, 95% confidence interval 1.03-2.34), and the metabolic syndrome group was associated with long sleep latency (prevalence ratios 1.33, 95% confidence interval 1.03-1.73), poor sleep quality (prevalence ratios 1.38, 95% confidence interval 1.07-1.78), and early wake time (<6:00; prevalence ratios 1.29, 95% confidence interval 1.01-1.63). Longitudinal analysis of participants without metabolic syndrome at baseline indicated a significant increase in metabolic syndrome risk associated with very short sleep duration (<6 hours; hazard ratio 1.72, 95% confidence interval 1.06-2.79), long sleep latency (>30 minutes; hazard ratio 1.86, 95% confidence interval 1.1-3.12), and early wake time (<6:00 o'clock; hazard ratio 1.73, 95% confidence interval 1.01-2.97).</p><p><strong>Conclusion: </strong>Sleep characteristics, such as short duration, long latency, and early wake time, were associated with an increased risk of metabolic syndrome in middle-aged adults.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-10DOI: 10.1016/j.sleh.2024.07.004
Louise J. Fangupo PhD , Jillian J. Haszard PhD , Takiwai Russell-Camp BMVA , Rachael W. Taylor PhD , Rosalina Richards PhD , Barbara C. Galland PhD , Justine Camp PhD
Objectives
To modify an existing questionnaire Brief Infant Sleep Questionnaire – Revised (BISQ-R) to ensure that it is suitable to measure nocturnal sleep health in a diverse sample of young children from Aotearoa New Zealand whānau (families), and to develop a “Perception of Infant and Toddler Sleep Scale” (PoITSS) to use as a primary outcome measurement in an upcoming trial.
Methods
Items from the BISQ-R were adapted for use among ethnically diverse whānau, and tested online with caregivers of 0-2 year old children. A PoITSS score was generated by scaling the responses from three of the questionnaire items to create a value between 0 (very poor) and 10 (very good). Caregivers provided qualitative feedback about the ease of interpreting and answering questionnaire items.
Results
Caregivers of 957 children (35% Māori, 12% Pacific) completed the questionnaire. Few differences in children’s nocturnal sleep were observed by demographic characteristics. The mean PoITSS score was 6.9 (SD 2.3) and was slightly higher among Māori children (mean difference 0.4, 95% CI 0.1, 0.7). Test-retest indicated good reliability (ICC = 0.81). While the majority (86%) of caregivers did not find it difficult to answer any of the items which formed the PoITSS, qualitative feedback indicated that simple modifications to some items would help ensure that they would be well understood by most caregivers.
Conclusions
Items from the BISQ-R were successfully adapted, and the PoITSS scale was shown to be appropriate, for use in ethnically diverse Aotearoa New Zealand whānau with young children.
{"title":"The measurement of young children’s nocturnal sleep health and the development of the Perception of Infant and Toddler Sleep Scale (PoITSS) in Aotearoa New Zealand whānau (families)","authors":"Louise J. Fangupo PhD , Jillian J. Haszard PhD , Takiwai Russell-Camp BMVA , Rachael W. Taylor PhD , Rosalina Richards PhD , Barbara C. Galland PhD , Justine Camp PhD","doi":"10.1016/j.sleh.2024.07.004","DOIUrl":"10.1016/j.sleh.2024.07.004","url":null,"abstract":"<div><h3>Objectives</h3><p>To modify an existing questionnaire Brief Infant Sleep Questionnaire – Revised (BISQ-R) to ensure that it is suitable to measure nocturnal sleep health in a diverse sample of young children from Aotearoa New Zealand whānau (families), and to develop a “Perception of Infant and Toddler Sleep Scale” (PoITSS) to use as a primary outcome measurement in an upcoming trial.</p></div><div><h3>Methods</h3><p>Items from the BISQ-R were adapted for use among ethnically diverse whānau, and tested online with caregivers of 0-2 year old children. A PoITSS score was generated by scaling the responses from three of the questionnaire items to create a value between 0 (very poor) and 10 (very good). Caregivers provided qualitative feedback about the ease of interpreting and answering questionnaire items.</p></div><div><h3>Results</h3><p>Caregivers of 957 children (35% Māori, 12% Pacific) completed the questionnaire. Few differences in children’s nocturnal sleep were observed by demographic characteristics. The mean PoITSS score was 6.9 (SD 2.3) and was slightly higher among Māori children (mean difference 0.4, 95% CI 0.1, 0.7). Test-retest indicated good reliability (ICC<!--> <!-->=<!--> <!-->0.81). While the majority (86%) of caregivers did not find it difficult to answer any of the items which formed the PoITSS, qualitative feedback indicated that simple modifications to some items would help ensure that they would be well understood by most caregivers.</p></div><div><h3>Conclusions</h3><p>Items from the BISQ-R were successfully adapted, and the PoITSS scale was shown to be appropriate, for use in ethnically diverse Aotearoa New Zealand whānau with young children.</p></div>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":"10 5","pages":"Pages 567-575"},"PeriodicalIF":3.4,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S235272182400161X/pdfft?md5=50712382b53e7af418b381f62445c455&pid=1-s2.0-S235272182400161X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141917888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-10DOI: 10.1016/j.sleh.2024.07.005
Connor M. Sheehan PhD , Nathan D. Martin PhD
Objectives
In this study, we explore the relationship between political party affiliation and sleep quality since the COVID-19 pandemic.
Methods
We analyze online survey data collected for a sample of adult residents of Arizona in February and March 2023 (N = 922). We fit ordered-logistic regression models to examine how party affiliation and changes to one’s personal life due to the COVID-19 pandemic are associated with the self-reported frequency of sleep difficulty.
Results
Compared to Republicans, Democrats and Independents report significantly worse sleep quality, net of the influence of sociodemographic controls. Additionally, having experienced major changes to one’s personal life due to the COVID-19 pandemic is significantly associated with more frequent trouble sleeping for Democrats and Independents, but not for Republicans.
Conclusions
We document a partisan divide in sleeping patterns among adults in a swing state and highlight an underappreciated factor contributing to sleep health amidst heightened political polarization.
{"title":"Does sleep quality differ across political parties? Results from a survey of Arizona adults","authors":"Connor M. Sheehan PhD , Nathan D. Martin PhD","doi":"10.1016/j.sleh.2024.07.005","DOIUrl":"10.1016/j.sleh.2024.07.005","url":null,"abstract":"<div><h3>Objectives</h3><p>In this study, we explore the relationship between political party affiliation and sleep quality since the COVID-19 pandemic.</p></div><div><h3>Methods</h3><p>We analyze online survey data collected for a sample of adult residents of Arizona in February and March 2023 (N = 922). We fit ordered-logistic regression models to examine how party affiliation and changes to one’s personal life due to the COVID-19 pandemic are associated with the self-reported frequency of sleep difficulty.</p></div><div><h3>Results</h3><p>Compared to Republicans, Democrats and Independents report significantly worse sleep quality, net of the influence of sociodemographic controls. Additionally, having experienced major changes to one’s personal life due to the COVID-19 pandemic is significantly associated with more frequent trouble sleeping for Democrats and Independents, but not for Republicans.</p></div><div><h3>Conclusions</h3><p>We document a partisan divide in sleeping patterns among adults in a swing state and highlight an underappreciated factor contributing to sleep health amidst heightened political polarization.</p></div>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":"10 5","pages":"Pages 590-593"},"PeriodicalIF":3.4,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141914320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-06DOI: 10.1016/j.sleh.2024.07.002
Jess Grebby BSc , Emma L. Slack PhD , Natalja Wells-Dean BSc , Helen St. Clair-Thompson PhD , Mark S. Pearce PhD
Objectives
Poor sleep quality has been linked to adverse health outcomes. It is important to understand factors contributing to sleep quality. Previous research has suggested increased cognition and education duration have a protective effect on sleep quality in old age. This study aimed to assess the hypothesis that age-11 intelligence quotient and highest achieved education level are associated with subjective sleep quality at age 60.
Methods
Participants are members of the Newcastle Thousand Families Study birth cohort, all born in 1947. Data included a calculated intelligence quotient score based on participant’s 11-plus exam results, highest achieved education level, social class at ages 25 and 50 and global Pittsburgh Sleep Quality Index (PSQI) at age 60. Multivariable regression analysis was used to investigate effect sizes of variables on global PSQI, which formed the basis of a path analysis model.
Results
After excluding participants with incomplete data, and those who had been diagnosed with sleep apnea, 251 participants were included in the path analysis model. Education level was associated with global PSQI (R = − 0.653; 95% CI − 1.161, − 0.145; P = .012) but age-11 intelligence quotient was not. While a similar association was seen for women in the stratified analysis, no such associations were seen for men.
Conclusions
The results of this study show an inverse relationship between education level, but not childhood intelligence quotient, and sleep quality in later life, in women only. Future research is needed to examine the mechanism underlying this relationship.
{"title":"Exploring the relationship between early cognitive ability and age-60 sleep quality: The Newcastle Thousand Families Study birth cohort","authors":"Jess Grebby BSc , Emma L. Slack PhD , Natalja Wells-Dean BSc , Helen St. Clair-Thompson PhD , Mark S. Pearce PhD","doi":"10.1016/j.sleh.2024.07.002","DOIUrl":"10.1016/j.sleh.2024.07.002","url":null,"abstract":"<div><h3>Objectives</h3><p>Poor sleep quality has been linked to adverse health outcomes. It is important to understand factors contributing to sleep quality. Previous research has suggested increased cognition and education duration have a protective effect on sleep quality in old age. This study aimed to assess the hypothesis that age-11 intelligence quotient and highest achieved education level are associated with subjective sleep quality at age 60.</p></div><div><h3>Methods</h3><p>Participants are members of the Newcastle Thousand Families Study birth cohort, all born in 1947. Data included a calculated intelligence quotient score based on participant’s 11-plus exam results, highest achieved education level, social class at ages 25 and 50 and global Pittsburgh Sleep Quality Index (PSQI) at age 60. Multivariable regression analysis was used to investigate effect sizes of variables on global PSQI, which formed the basis of a path analysis model.</p></div><div><h3>Results</h3><p>After excluding participants with incomplete data, and those who had been diagnosed with sleep apnea, 251 participants were included in the path analysis model. Education level was associated with global PSQI (R<!--> <!-->=<!--> <!-->−<!--> <!-->0.653; 95% CI −<!--> <!-->1.161, −<!--> <!-->0.145; <em>P</em> = .012) but age-11 intelligence quotient was not. While a similar association was seen for women in the stratified analysis, no such associations were seen for men.</p></div><div><h3>Conclusions</h3><p>The results of this study show an inverse relationship between education level, but not childhood intelligence quotient, and sleep quality in later life, in women only. Future research is needed to examine the mechanism underlying this relationship.</p></div>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":"10 5","pages":"Pages 594-601"},"PeriodicalIF":3.4,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352721824001591/pdfft?md5=55d7f872f347f2b51fd1028f20789aa1&pid=1-s2.0-S2352721824001591-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141903279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.sleh.2024.03.008
Objectives
An estimated 30% of Canadian adolescents do not get the recommended 8-10 hours of sleep. No prior study has examined the role of income inequality, the gap between rich and poor within a society, in adolescent sleep. The aim of this study is to examine the association between income inequality and sleep duration among Canadian adolescents, how this association differs by gender, and whether depressive symptoms, anxiety, and social cohesion mediate this relationship.
Methods
Multilevel path models were conducted using cross-sectional survey data from 74,501 adolescents who participated in the Cannabis, Obesity, Mental health, Physical activity, Alcohol use, Smoking, and Sedentary behavior (COMPASS) study in 2018-2019. Income inequality was measured at the census division level and sleep duration, gender, depressive symptoms, anxiety, and social cohesion were measured at the individual level.
Results
A 1% increase in income inequality was associated with a 3.67-minute decrease in sleep duration (95% CI = − 5.64 to − 1.70). The cross-level interactions between income inequality and gender were significant, suggesting that income inequality has more adverse associations with sleep among females than males. Both depressive symptoms and anxiety were significant mediators, wherein greater income inequality was associated with higher levels of depressive symptoms and anxiety, which were in turn, associated with a shorter sleep duration.
Conclusion
Interventions that reduce income inequality may prevent depressive symptoms and anxiety and improve sleep in adolescents. Reducing societal income gaps may improve adolescent sleep especially in those attending school in high income inequality areas, females, and those experiencing depressive symptoms and anxiety.
{"title":"Exploring the association between income inequality and sleep in Canadian adolescents: A path analysis approach","authors":"","doi":"10.1016/j.sleh.2024.03.008","DOIUrl":"10.1016/j.sleh.2024.03.008","url":null,"abstract":"<div><h3>Objectives</h3><p>An estimated 30% of Canadian adolescents do not get the recommended 8-10<!--> <span><span>hours of sleep. No prior study has examined the role of income inequality<span>, the gap between rich and poor within a society, in adolescent sleep. The aim of this study is to examine the association between income inequality and sleep duration among Canadian adolescents, how this association differs by gender, and whether depressive symptoms, anxiety, and </span></span>social cohesion mediate this relationship.</span></p></div><div><h3>Methods</h3><p><span>Multilevel path models were conducted using cross-sectional survey data from 74,501 adolescents who participated in the Cannabis, Obesity, Mental health, </span>Physical activity<span><span>, Alcohol use<span>, Smoking, and Sedentary behavior (COMPASS) study in 2018-2019. Income inequality was measured at the census division level and </span></span>sleep duration, gender, depressive symptoms, anxiety, and social cohesion were measured at the individual level.</span></p></div><div><h3>Results</h3><p><span>A 1% increase in income inequality was associated with a 3.67-minute decrease in sleep duration (95% CI</span> <!-->=<!--> <!-->−<!--> <!-->5.64 to −<!--> <!-->1.70). The cross-level interactions between income inequality and gender were significant, suggesting that income inequality has more adverse associations with sleep among females than males. Both depressive symptoms and anxiety were significant mediators, wherein greater income inequality was associated with higher levels of depressive symptoms and anxiety, which were in turn, associated with a shorter sleep duration.</p></div><div><h3>Conclusion</h3><p>Interventions that reduce income inequality may prevent depressive symptoms and anxiety and improve sleep in adolescents. Reducing societal income gaps may improve adolescent sleep especially in those attending school in high income inequality areas, females, and those experiencing depressive symptoms and anxiety.</p></div>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":"10 4","pages":"Pages 410-417"},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140877675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.sleh.2024.04.002
Objectives
Many studies have examined links between sleep and blood pressure, with mixed findings, mostly using self-reported sleep data and cross-sectional designs. We examined whether actigraph-estimated sleep characteristics are associated with concurrent blood pressure or 5-year blood pressure change in a national cohort of older adults (National Social Life, Health and Aging Project), and whether these associations differ by hypertension medication use.
Methods
Subjects were 669 older adults (62-90 years), 471 with 5-year follow-up data. Sleep characteristics were duration (linear plus quadratic terms); sleep percentage; and categorical onset, midpoint, and waking times. Multivariable linear models adjusted for age, race, gender, obesity, smoking, daytime napping, and hypertension medication use. Interactions between sleep characteristics and hypertension medication were tested among the 401 subjects with consistent hypertension medication status over time.
Results
We found U-shaped cross-sectional and longitudinal relationships between duration and blood pressure, with shorter and longer sleep times associated with higher blood pressure. Later onset times were cross-sectionally associated with higher systolic blood pressure, while earlier onset times were longitudinally associated with systolic blood pressure increase. Midpoint, wake time, and sleep percentage were not significantly associated with blood pressure. Significant interaction terms suggested hypertension medications attenuated associations of sleep onset and wake time with diastolic blood pressure.
Conclusions
These results with actigraph-estimated parameters confirm some, but not all, associations reported from research based on self-reported sleep data. Our findings are consistent with recommended intermediate sleep durations for cardiovascular health and suggest hypertension medication use may attenuate some associations between sleep timing and blood pressure.
{"title":"Associations of actigraph sleep characteristics with blood pressure among older adults","authors":"","doi":"10.1016/j.sleh.2024.04.002","DOIUrl":"10.1016/j.sleh.2024.04.002","url":null,"abstract":"<div><h3>Objectives</h3><p>Many studies have examined links between sleep and blood pressure, with mixed findings, mostly using self-reported sleep data and cross-sectional designs. We examined whether actigraph-estimated sleep characteristics are associated with concurrent blood pressure or 5-year blood pressure change in a national cohort of older adults (National Social Life, Health and Aging Project), and whether these associations differ by hypertension medication use.</p></div><div><h3>Methods</h3><p>Subjects were 669 older adults (62-90<!--> <!-->years), 471 with 5-year follow-up data. Sleep characteristics were duration (linear plus quadratic terms); sleep percentage; and categorical onset, midpoint, and waking times. Multivariable linear models adjusted for age, race, gender, obesity, smoking, daytime napping, and hypertension medication use. Interactions between sleep characteristics and hypertension medication were tested among the 401 subjects with consistent hypertension medication status over time.</p></div><div><h3>Results</h3><p><span><span>We found U-shaped cross-sectional and longitudinal relationships between duration and blood pressure, with shorter and longer sleep times associated with higher blood pressure. Later onset times were cross-sectionally associated with higher </span>systolic blood pressure<span>, while earlier onset times were longitudinally associated with systolic blood pressure increase. Midpoint, wake time, and sleep percentage were not significantly associated with blood pressure. Significant interaction terms suggested hypertension medications attenuated associations of sleep onset and wake time with </span></span>diastolic blood pressure.</p></div><div><h3>Conclusions</h3><p>These results with actigraph-estimated parameters confirm some, but not all, associations reported from research based on self-reported sleep data. Our findings are consistent with recommended intermediate sleep durations for cardiovascular health and suggest hypertension medication use may attenuate some associations between sleep timing and blood pressure.</p></div>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":"10 4","pages":"Pages 455-461"},"PeriodicalIF":3.4,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141437683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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