Long-term changes in sleep duration, energy balance and risk of type 2 diabetes

Long-term trajectories of sleep duration are associated with incident diabetes in middle-to-older-aged Black and White Americans

AIMS/HYPOTHESIS

Both short and long sleep durations have been linked to higher diabetes risk. However, sleep duration may vary over time, and there has been limited research focusing on individual sleep trajectories and diabetes risk. There are substantial racial disparities in both sleep health and diabetes risk in the USA. Thus, it is important to understand the role of suboptimal sleep patterns in diabetes risk in different racial groups.

METHODS

We assessed long-term trajectories of sleep duration and incident diabetes in 22,285 Black adults (mean age ± SD, 51.1 ± 8.2 years; 64.8% women) and 13,737 White adults (mean age ± SD, 54.4 ± 9.0 years; 63.8% women) enrolled in the Southern Community Cohort Study. Nine sleep trajectories were derived based on self-reported sleep duration at baseline and after a mean of 5 years of follow-up: normal-normal (reference), short-normal, normal-short, short-short, long-normal, normal-long, long-long, long-short and short-long. Diabetes was reported using a validated questionnaire. Multivariable-adjusted logistic regression was used to determine relationships between sleep trajectories and incident diabetes.

RESULTS

When compared with the normal-normal trajectory, suboptimal sleep trajectories were associated with higher likelihoods of developing diabetes (OR; 95% CI: short-normal 1.19; 1.09, 1.31; normal-short 1.14; 1.02, 1.27; short-short 1.17; 1.07, 1.28; long-normal 1.13; 0.98, 1.30; normal-long 1.16; 1.00, 1.34; long-long 1.23; 1.02, 1.48; long-short 1.45; 1.19, 1.77; short-long 1.51; 1.28, 1.77). Stratified analyses by race and socioeconomic status (i.e. education and household income) showed that most suboptimal sleep trajectories were consistently associated with incident diabetes in all sociodemographic subgroups. We also noted potential interaction with race and education for several sleep trajectories (i.e. short-long and normal-short with race; long-long and short-short with education).

CONCLUSIONS/INTERPRETATION

Adults with suboptimal sleep duration trajectories are more likely to develop incident diabetes. Future research is needed to study how sociodemographic factors modulate this relationship.

Negative health outcomes in long sleepers: The societal sleep restriction hypothesis

Society imposes work and school schedules, as well as social expectations, that militate against consistently obtaining more than 7-9 h of sleep every 24 h. For most but not all adults this sleep duration is adequate. But among those who consistently obtain more than 9 h of sleep per day ("long sleepers"), there likely exists a subpopulation of individuals who are nevertheless failing to obtain enough sleep to satisfy their physiological sleep needs - a consequence of "restricting" their daily sleep durations to whatever extent they can tolerate so as to conform as closely as possible to society's norms and expectations. It is hypothesized that the 'long sleep arm' of the seemingly paradoxical U-shaped relationship between sleep duration and negative health outcomes can be explained, at least in part, by the existence of a subpopulation of such 'sleep-restricted long sleepers.'

Effects of sleep duration and changes in body mass index on diabetic kidney disease: a prospective cohort study

Aims

To examine the associations of sleep duration and changes in BMI with the onset of diabetic kidney disease (DKD).

Materials and methods

2,959 participants with type 2 diabetes were divided into three groups based on sleep duration: short (<7 h/day), intermediate (7-9 h/day), or long (>9 h/day). Changes in BMI during follow-up were trisected into loss, stable, or gain groups. DKD was defined as either the urinary albumin/creatinine ratio (UACR) ≥ 3.39 mg/mmol or the estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73m², or both. Cox regression models were used to assess hazard ratios (HRs) and 95% confidence intervals (CIs).

Results

During a mean follow-up of 2.3 years, DKD occurred in 613 participants (20.7%). A J-shaped curve was observed between sleep duration and DKD. Compared to intermediate sleep duration, long sleep duration was associated with higher risks of DKD (HR 1.47; 95% CI: 1.19-1.81). In the joint analyses, compared to participants with intermediate sleep duration and stable BMI, long sleep duration with BMI gain had the highest risks of DKD (HR 2.04; 95% CI: 1.48-2.83). In contrast, short or intermediate sleep duration accompanied by decrease in BMI was associated with a reduced risk of DKD, with HRs of 0.50 (95% CI: 0.31-0.82) and 0.61 (95% CI:0.47-0.80), respectively.

Conclusions

Long sleep duration is significantly associated with an increased risk of DKD, which is further amplified by obesity or BMI gain. These findings suggest that both proper sleep duration and weight control are essential to preventing DKD.

Sleep duration, plasma metabolites, and obesity and diabetes: a metabolome-wide association study in US women

Short and long sleep duration are associated with adverse metabolic outcomes, such as obesity and diabetes. We evaluated cross-sectional differences in metabolite levels between women with self-reported habitual short (<7 h), medium (7-8 h), and long (≥9 h) sleep duration to delineate potential underlying biological mechanisms. In total, 210 metabolites were measured via liquid chromatography-mass spectrometry in 9207 women from the Nurses' Health Study (NHS; N = 5027), the NHSII (N = 2368), and the Women's Health Initiative (WHI; N = 2287). Twenty metabolites were consistently (i.e. praw < .05 in ≥2 cohorts) and/or strongly (pFDR < .05 in at least one cohort) associated with short sleep duration after multi-variable adjustment. Specifically, levels of two lysophosphatidylethanolamines, four lysophosphatidylcholines, hydroxyproline and phenylacetylglutamine were higher compared to medium sleep duration, while levels of one diacylglycerol and eleven triacylglycerols (TAGs; all with ≥3 double bonds) were lower. Moreover, enrichment analysis assessing associations of metabolites with short sleep based on biological categories demonstrated significantly increased acylcarnitine levels for short sleep. A metabolite score for short sleep duration based on 12 LASSO-regression selected metabolites was not significantly associated with prevalent and incident obesity and diabetes. Associations of single metabolites with long sleep duration were less robust. However, enrichment analysis demonstrated significant enrichment scores for four lipid classes, all of which (most markedly TAGs) were of opposite sign than the scores for short sleep. Habitual short sleep exhibits a signature on the human plasma metabolome which is different from medium and long sleep. However, we could not detect a direct link of this signature with obesity and diabetes risk.

Association of sleep duration and insomnia with metabolic syndrome and its components in the Women's Health Initiative

BACKGROUND

Epidemiological evidence suggests that inadequate sleep duration and insomnia may be associated with increased risk of metabolic syndrome (MetS). However, longitudinal data with repeated measures of sleep duration and insomnia and of MetS are limited. We examined the association of sleep duration and insomnia with MetS and its components using longitudinal data from the Women's Health Initiative (WHI).

METHODS

The study included postmenopausal women (ages 50-79 years) diabetes-free at enrollment in the WHI, with baseline data on sleep duration (n = 5,159), insomnia (n = 5,063), MetS, and its components. Repeated measures of self-reported sleep duration and insomnia were available from years 1 or 3 of follow-up and of the MetS components from years 3, 6 and 9. Associations were assessed using logistic regression and generalized estimating equations models, and odds ratios and 95% confidence intervals (CI) adjusted for major risk factors were calculated.

RESULTS

In cross-sectional analysis, baseline sleep duration ≥ 9 h was positively associated with MetS (OR = 1.51; 95%CI 1.12-2.04), while sleep duration of 8- < 9 h was associated with waist circumference > 88 cm and triglycerides ≥ 150 mg/dL (OR = 1.18; 95%CI 1.01-1.40 and OR = 1.23; 95%CI 1.05-1.46, respectively). Insomnia had a borderline positive association with MetS (OR = 1.14; 95%CI 0.99-1.31), and significant positive associations with waist circumference > 88 cm and glucose ≥ 100 mg/dL (OR = 1.18; 95%CI 1.03-1.34 and OR = 1.17; 95%CI 1.02-1.35, respectively). In the longitudinal analysis, change from restful sleep to insomnia over time was associated with increased odds of developing MetS (OR = 1.40; 95%CI 1.01-1.94), and of a triglyceride level ≥ 150 mg/dL (OR = 1.48; 95%CI 1.08-2.03).

CONCLUSIONS

Among postmenopausal women in the WHI, sleep duration and insomnia were associated with current and future risk of MetS and some of its components.

Healthy lifestyle over the life course: Population trends and individual changes over 30 years of the Doetinchem Cohort Study

For five health-related lifestyle factors (physical activity, weight, smoking, sleep, and alcohol consumption) we describe both population trends and individual changes over a period of 30 years in the same adult population. Dichotomous indicators (healthy/unhealthy) of lifestyle were analyzed for 3,139 participants measured every 5 years in the Doetinchem Cohort Study (1987-2017). Population trends over 30 years in physical inactivity and "unhealthy" alcohol consumption were flat (i.e., stable); overweight and unhealthy sleep prevalence increased; smoking prevalence decreased. The proportion of the population being healthy on all five lifestyle factors declined from 17% in the round 1 to 10.8% in round 6. Underlying these trends a dynamic pattern of changes at the individual level was seen: sleep duration and physical activity level changed in almost half of the individuals; Body Mass Index (BMI) and alcohol consumption in one-third; smoking in one-fourth. Population trends don't give insight into change at the individual level. In order to be able to gauge the potential for change of health-related lifestyle, it is important to take changes at the individual level into account.

Healthy Lifestyle Score Including Sleep Duration and Cardiovascular Disease Risk

INTRODUCTION

Although insufficient or prolonged sleep duration is associated with cardiovascular disease, sleep duration is not included in most lifestyle scores. This study evaluates the relationship between a lifestyle score, including sleep duration and cardiovascular disease risk.

METHODS

A prospective analysis among 67,250 women in the Nurses' Health Study and 29,114 men in Health Professionals Follow-up Study (1986-2016) was conducted in 2021. Lifestyle factors were updated every 2-4 years using self-reported questionnaires. The traditional lifestyle score was defined as not smoking, having a normal BMI, being physically active (≥30 minutes/day of moderate physical activity), eating a healthy diet, and drinking alcohol in moderation. Low-risk sleep duration, defined as sleeping ≥6 to <8 hours/day, was included as an additional component in the updated lifestyle score. Cox proportional hazard regression models were used to estimate cardiovascular disease risk. The likelihood-ratio test and C-statistics were used to compare both scores.

RESULTS

A total of 11,710 incident cardiovascular disease cases during follow-up were documented. The multivariable-adjusted hazard ratios comparing 6 with 0 low-risk factors in the healthy lifestyle score including sleep duration were 0.17 (95% CI=0.12, 0.23) for cardiovascular disease, 0.14 (95% CI=0.10, 0.21) for coronary heart disease, and 0.20 (95% CI=0.12, 0.33) for stroke. Approximately 66% (95% CI=56%, 75%) of cardiovascular disease, 67% (95% CI=54%, 77%) of coronary heart disease, and 62% (95% CI=42%, 76%) of stroke cases were attributable to poor adherence to a healthy lifestyle including sleep. Adding sleep duration to the score slightly increased the C-statistics from 0.64 (95% CI=0.63, 0.64) to 0.65 (95% CI=0.64, 0.65) (p<0.001).

CONCLUSIONS

Adopting a healthy lifestyle including sleep recommendations could substantially reduce the risk of cardiovascular disease in U.S. adults.

The links between sleep duration, obesity and type 2 diabetes mellitus

Global rates of obesity and type 2 diabetes mellitus (T2DM) are increasing globally concomitant with a rising prevalence of sleep deprivation and sleep disorders. Understanding the links between sleep, obesity and T2DM might offer an opportunity to develop better prevention and treatment strategies for these epidemics. Experimental studies have shown that sleep restriction is associated with changes in energy homeostasis, insulin resistance and β-cell function. Epidemiological cohort studies established short sleep duration as a risk factor for developing obesity and T2DM. In addition, small studies suggested that short sleep duration was associated with less weight loss following lifestyle interventions or bariatric surgery. In this article, we review the epidemiological evidence linking sleep duration to obesity and T2DM and plausible mechanisms. In addition, we review the impact of changes in sleep duration on obesity and T2DM.

Poor Sleep Quality Linked to Decreased Brain Gray Matter Density in Adults with Type 2 Diabetes

BACKGROUND

Poor sleep is common in adults with Type 2 Diabetes Mellitus (T2DM), which may contribute to brain tissue changes. However, the impact of sleep quality on brain tissue in T2DM individuals is unclear. We aimed to evaluate differential sleep quality with brain changes, and brain tissue integrity in T2DM patients.

METHODS

Data were collected from 34 patients with T2DM and included sleep quality (assessed by the Pittsburgh Sleep Quality Index [PSQI], and high-resolution T1-weighted brain images using a 3.0-Tesla MRI scanner. Gray matter density (GMD) maps were compared between subjects with good vs poor sleep quality as assessed by PSQI (covariates: age, sex, BMI).

RESULTS

Of 34 T2DM patients, 17 showed poor sleep quality. Multiple brain sites, including the hippocampus, cerebellum, prefrontal, amygdala, thalamus, hypothalamus, insula, cingulate, and temporal areas, showed reduced gray matter in T2DM patients with poor sleep quality over patients with good sleep quality. Negative associations emerged between PSQI scores and gray matter density in multiple areas.

CONCLUSIONS

T2DM patients with poor sleep quality show brain tissue changes in sites involved in sleep regulation. Findings indicate that improving sleep may help mitigate brain tissue damage, and thus, improve brain function in T2DM patients.

Weekend night vs. school night sleep patterns, weight status, and weight-related behaviors among adolescents

OBJECTIVE

In this study, we examine associations between objectively measured weekend night vs. school night sleep patterns, weight status, and weight-related behaviors among adolescents.

DESIGN

Cross-sectional study.

SETTING

Five Minnesota high schools that started early (7:30 or 7:45 AM) in Spring 2016.

PARTICIPANTS

Ninth grade students, ages 14.5-16 years (n = 284).

MEASUREMENTS

Students completed surveys, had body measurements taken, and wore sleep (wrist) actigraphs for 1 week (n = 284). We examined weekend night-school night differences in sleep duration and sleep timing. We then assessed whether these factors were related to weight status and weight-related behaviors (eating behaviors, food consumption, physical activity, beverage consumption) using generalized linear mixed models.

RESULTS

On average, students slept 1.5 hours (95% confidence interval 1.3-1.7) more and had a sleep midpoint 1.9 hours (1.8-2.1) later on weekend nights compared to school nights. Female students had larger increases in sleep duration on weekend nights than males but similar timing differences. Sleep duration differences were uncorrelated with sleep timing differences (r = 0.01). Neither duration nor timing differences were associated with overweight, obesity, or any of the eating behaviors we examined. However, sleeping longer on weekend nights than on school nights was associated with lower probability of being active 6-7 days per week (p = .02).

CONCLUSIONS

Adolescents have substantial sleep duration and sleep timing differences on weekend nights vs. school nights. While these differences may not be associated with weight status or weight-related behaviors, they reflect the reality that most adolescents have schedules that restrict their sleep.

Distinct Relevance of Nightly Sleep Duration to Metabolic, Anthropometric, and Lifestyle Factors in Patients with Type 2 Diabetes

Objective Although a number of studies have shown that both short and long sleep durations were associated with the risk of metabolic disorders related to obesity, the underlying mechanism is still not fully understood. In this study, we analyzed the association of sleep duration with metabolic, anthropometric, and lifestyle factors in patients with type 2 diabetes. Methods The subjects were 279 patients with type 2 diabetes 63 (52-70) years old (median and interquartile range) with a body mass index of 25.0 (22.2-28.3) kg/m² and HbA1c levels of 8.7% (7.6-10.3%). Patients with advanced complications were excluded from the study. Diets were evaluated by registered dietitians using a software program. Body composition was assessed by the multifrequency bioelectrical impedance method. Results The mean self-reported nightly sleep duration was 6.4 hours with no marked gender difference. Sleep duration was inversely correlated with the HbA1c levels, total energy intake, and intakes of carbohydrate, protein, and fat. The body fat ratio and skeletal muscle mass were correlated positively and negatively, respectively, with sleep duration. When the subjects were divided into three groups based on sleep duration, the intakes of total energy, carbohydrates, and fat tended to be high in those with <5.5 hours of sleep, and the percentage of patients who had habitual physical activities was lower in those with >7 hours of sleep. Conclusion The observation that sleep duration is distinctly associated with excessive eating and a sedentary lifestyle may provide a basis for effective lifestyle management of patients with type 2 diabetes.

Association between objectively measured body composition, sleep parameters and physical activity in preschool children: a cross-sectional study

OBJECTIVE

Associations between self-reported sleep duration and obesity indices in children are well recognised; however, there are no studies on associations between objectively measured other sleep parameters and physical activity with body composition in preschoolers. Therefore, the aim of this study was to determine the associations between sleep parameters and moderate-to-vigorous physical activity (MVPA) with body composition indices in preschoolers using objective measures.

DESIGN

A cross-sectional study.

PARTICIPANTS

The study group consisted of 676 children aged 5-6 years, who were enrolled in kindergartens in the 2017/2018 school year.

OUTCOME MEASURES

Sleep parameters and MVPA were measured using accelerometers for 7 days. Bioelectrical impedance analysis was used to estimate body composition.

RESULTS

Sleep duration and sleep efficiency were inversely associated with body fat percentage (BFP) (β=-0.013 and β from -0.311 to -0.359, respectively) and body mass index (BMI) (β from -0.005 to -0.006 and from -0.105 to -0.121, respectively), and directly associated with fat-free mass (FFM) (β from 0.010 to 0.011 and from 0.245 to 0.271, respectively) and muscle mass (β from 0.012 to 0.012 and from 0.277 to 0.307, respectively) in unadjusted and adjusted models. BFP was inversely associated with MVPA and positively associated with number of awakenings and sleep periods. Number of sleep periods was inversely associated with FFM, and positively with BMI and muscle mass. Correlation matrix indicated significant correlation between BFP, FFM and muscle mass with sleep duration, sleep efficiency, number of sleep periods and MVPA.

CONCLUSIONS

Periodic assessment of sleep parameters and MVPA in relation to body composition in preschool children may be considered, especially in those who are at risk for obesity.

The Associations of Trajectory of Sleep Duration and Inflammation with Hypertension: A Longitudinal Study in China

BACKGROUND

Existing evidence suggested that sleep duration may be involved in hypertension; however, the conclusions were still controversial. This study aimed to examine the association of longitudinal trajectory of sleep duration with hypertension and to explore the role of the inflammation in such associations.

METHODS

A total of 3178 subjects over 30 years of age without hypertension were enrolled in 2004, and they were followed until 2009. Self-reported sleep duration was recorded, and inflammation was measured by highly sensitive C reactive protein (hs-CRP). Log-binomial regression models were applied to examine the association of sleep duration trajectory and inflammation with the risk of hypertension. The mediating effect of elevated hs-CRP was examined by the bootstrap and the process software.

RESULTS

The prevalence of persistent short (≤7 hours/day), normal (8-9 hours/day), and long (>9 hours/day) sleep duration over 5 years were 9.1%, 37.7%, and 2.3%, respectively. The incidence of hypertension was 26.6% during the follow-up period. Compared with those who persistently slept 8-9 hours/day from baseline to follow-up, those who persistently slept ≤7 hours/day, persistently slept ≥10 hours/day, and those whose sleep duration changed have higher risks of hypertension by 1.375-fold (95% CI: 1.121, 1.686), 1.557-fold (95% CI: 1.171, 2.069) and 1.299-fold (95% CI: 1.135, 1.487), respectively. In addition, persistently slept ≤7 hours/day was found to be associated with higher risk of inflammation (RR: 1.285, 95% CI: 1.008, 1.638). The mediation analysis did not find significant mediating effect of elevated CRP on the association between sleep duration trajectory and hypertension.

CONCLUSION

Experiencing both a short or long sleep duration, especially for a long time, could lead to higher risk of hypertension. Persistent exposure to short sleep duration was also associated with inflammation. However, the higher risk of hypertension caused by persistent short sleep duration does not seem to be directly mediated through inflammation.

Gender and age differences in the association between sleep characteristics and fasting glucose levels in Chinese adults

AIM

The present study examined the associations between night-time sleep duration, midday napping duration and bedtime, and fasting glucose levels, and whether or not such associations are dependent on gender and age.

METHODS

This study was a cross-sectional analysis of 172,901 adults aged≥40 years living in mainland China. Sleep duration was obtained by self-reports of bedtime at night, waking-up time the next morning and average napping duration at midday. Fasting plasma glucose (FPG)≥7.0mmol/L was defined as hyperglycaemia. Independent associations between night-time sleep duration, midday naptime duration and bedtime with hyperglycaemia were evaluated using regression models.

RESULTS

Compared with night-time sleep durations of 6-7.9h, both short (<6h) and long (≥8h) night-time sleep durations were significantly associated with an increased risk of hyperglycaemia in women [odds ratio (OR): 1.12, 95% confidence interval (CI): 1.01-1.29 and OR: 1.14, 95% CI: 1.08-1.21, respectively], and revealed a U-shaped distribution of risk in women and no significant association in men. Long midday nap durations (≥1h) were significantly but weakly associated with hyperglycaemia (OR: 1.04, 95% CI: 1.01-1.09) compared with no napping without interactions from gender or age, whereas the association between bedtime and fasting glucose levels did vary according to gender and age.

CONCLUSION

Night-time sleep duration, midday napping duration and bedtime were all independently associated with the risk of hyperglycaemia, and some of the associations between these sleep characteristics and hyperglycaemia were gender- and age-dependent.

Sleep Duration Patterns in Early to Middle Adulthood and Subsequent Risk of Type 2 Diabetes in Women

OBJECTIVE

To identify sleep duration trajectories from early to middle adulthood and their associations with incident type 2 diabetes.

RESEARCH DESIGN AND METHODS

Using a group-based modeling approach, we identified sleep duration trajectories based on sleep duration in ages 20-25, 26-35, 36-45, and 46+ years, which were retrospectively assessed in 2009 among 60,068 women from the Nurses' Health Study II (median age 54.9 years) who were free of diabetes, cardiovascular disease, and cancer. We investigated the prospective associations between sleep duration trajectories and diabetes risk (2009-2017) using multivariable Cox proportional hazards models.

RESULTS

We documented 1,797 incident diabetes cases over a median follow-up of 7.8 years (442,437 person-years). Six sleep duration trajectories were identified: persistent 5-, 6-, 7-, or 8-h sleep duration and increased or decreased sleep duration. After multivariable adjustment for diabetes risk factors, compared with the persistent 7-h sleep duration group, the hazard ratio was 1.43 (95% CI 1.10, 1.84) for the 5-h group, 1.17 (1.04, 1.33) for the 6-h group, 0.96 (0.84, 1.10) for the 8-h group, 1.33 (1.09, 1.61) for the increased sleep duration group, and 1.32 (1.10, 1.59) for the decreased sleep duration group. Additional adjustment for time-updated comorbidities and BMI attenuated these associations, although a significantly higher risk remained in the decreased sleep duration group (1.24 [1.03, 1.50]).

CONCLUSIONS

Persistent short sleep duration or changes in sleep duration from early to middle adulthood were associated with higher risk of type 2 diabetes in later life. These associations were weaker after obesity and metabolic comorbidities were accounted for.

Building Risk Prediction Models for Type 2 Diabetes Using Machine Learning Techniques

Introduction

As one of the most prevalent chronic diseases in the United States, diabetes, especially type 2 diabetes, affects the health of millions of people and puts an enormous financial burden on the US economy. We aimed to develop predictive models to identify risk factors for type 2 diabetes, which could help facilitate early diagnosis and intervention and also reduce medical costs.

Methods

We analyzed cross-sectional data on 138,146 participants, including 20,467 with type 2 diabetes, from the 2014 Behavioral Risk Factor Surveillance System. We built several machine learning models for predicting type 2 diabetes, including support vector machine, decision tree, logistic regression, random forest, neural network, and Gaussian Naive Bayes classifiers. We used univariable and multivariable weighted logistic regression models to investigate the associations of potential risk factors with type 2 diabetes.

Results

All predictive models for type 2 diabetes achieved a high area under the curve (AUC), ranging from 0.7182 to 0.7949. Although the neural network model had the highest accuracy (82.4%), specificity (90.2%), and AUC (0.7949), the decision tree model had the highest sensitivity (51.6%) for type 2 diabetes. We found that people who slept 9 or more hours per day (adjusted odds ratio [aOR] = 1.13, 95% confidence interval [CI], 1.03–1.25) or had checkup frequency of less than 1 year (aOR = 2.31, 95% CI, 1.86–2.85) had higher risk for type 2 diabetes.

Conclusion

Of the 8 predictive models, the neural network model gave the best model performance with the highest AUC value; however, the decision tree model is preferred for initial screening for type 2 diabetes because it had the highest sensitivity and, therefore, detection rate. We confirmed previously reported risk factors and also identified sleeping time and frequency of checkup as 2 new potential risk factors related to type 2 diabetes.

Duration and Quality of Sleep and Risk of Physical Function Impairment and Disability in Older Adults: Results from the ENRICA and ELSA Cohorts

Sleep duration and quality have been associated with poor physical function, but both the temporality of the association and the independence of sleep duration and quality are unclear. We examined the prospective association of sleep duration and quality with physical function impairment and disability in older adults. Data were taken from participants in the Seniors-ENRICA (2012-2015, n= 1,773) and in the ELSA cohort (waves 4 and 6, n=4,885) aged ≥60 years. Sleep duration and quality were self-reported. Physical function impairment and disability was obtained either from self-reports (ENRICA and ELSA) or from performance assessment (ENRICA). Logistic regression models were adjusted for potential confounders. After a follow-up of 2.0-2.8 years, no association was found between changes in sleep duration and physical function impairment or disability. However, in both studies, poor general sleep quality was linked to higher risk of impaired agility [OR: 1.93 (95% CI: 1.30-2.86) in Seniors-ENRICA and 1.65 (1.24-2.18) in ELSA study] and mobility [1.46 (0.98-2.17) in Seniors-ENRICA and 1.59 (1.18-2.15) in ELSA study]. Poor general sleep quality was also associated with decreased physical component summary (PCS) [1.39 (1.05-1.83)], disability in instrumental activities of daily living [1.59 (0.97-2.59)] and in basic activities of daily living [1.73 (1.14-2.64)] in Seniors-ENRICA. In addition, compared to those with no sleep complaints, participants with 2 or more sleep complaints had greater risk of impaired agility, impaired mobility, decreased PCS and impaired lower extremity function in both cohorts. Poor sleep quality was associated with higher risk of physical impairment and disability in older adults from Spain and from England.

Short sleep duration is associated with specific food intake increase among school-aged children in China: a national cross-sectional study

Background

The relationship between sleep duration and food intake is unclear. This study aims to examine the relationship among children aged 6–17 years in China.

Methods

The sample consisted of 70,519 children aged 6–17 years, which were randomly selected from 7 representative areas from China, from September to November, 2013. In the structured questionnaire, children reported daily sleep hours (less than 7 h, 7–9 h and more than 9 h), weekly food intake amount (including vegetables, fruit, sugar beverages and meat), physical activity and sedentary time. The relationship of sleep duration with vegetable, sugar beverage, fruit and meat intake was evaluated by multi-nominal logistic regression and multi-variable adjusted.

Results

A total of 62,517 children (51.6% boys) completed the study. Short sleep duration (SSD, < 7 h) was independently associated with increased sugar beverage intake (SBI, Odd Ratio, OR: 1.29, 95% CI: 1.19–1.40) but decreased vegetable (VI, OR: 0.94, 95% CI: 0.90–0.98) & fruit intake (FI, OR: 0.94, 95% CI: 0.88–0.99). Stratified by age and gender, SSD increased SBI for boys of both young (6–12 years) & older (13–17 years) groups and older girls (ORs: 1.25, 1.25, 1.49, 95% CI: 1.08–1.44, 1.04–1.50, 1.22–1.81, respectively), but decreased VI and FI for older girls (ORs: 0.84& 0.81, 95% CI: 0.74–0.96& 0.68–0.96, respectively).

Conclusions

Among school-aged children in China, short sleep duration was associated with increased risks of more sugar beverage intake among those younger and boys but less vegetable & fruit intake among those older and girls. Longitudinal research is needed to clarify the causation in between.

Healthy eating index versus alternate healthy index in relation to diabetes status and health markers in U.S. adults: NHANES 2007-2010

BACKGROUND

It remains to be determined whether the Alternate Healthy Eating Index 2010 (AHEI-2010) or the Healthy Eating Index 2010 (HEI-2010) is preferably recommended as means to assess dietary quality in people with type 2 diabetes (T2DM).

METHODS

The purpose of this study was to determine whether the AHEI-2010 provides a more accurate assessment of dietary quality than the HEI-2010 in relation to diabetes status, while controlling for health markers, sociodemographic and lifestyle factors. The 2007-2010 National Health and Nutrition Examination Survey (NHANES) was used as a representative sample of U.S. adults age 20+ years (n = 4097). HEI-2010 and the AHEI-2010 scores were used as measures of dietary quality and were calculated using data from the first 24-h dietary recall. Health markers evaluated include anthropometrics, blood pressure, lipid and inflammatory markers, and presence of co-morbid diseases. Least Squares Means were computed to determine differences across diabetes status (nondiabetes, prediabetes, T2DM) for total and sub-component HEI-2010 and AHEI-2010 scores, and to determine differences across total HEI-2010 and AHEI-2010 quartiles for health markers. Covariate-adjusted logistic regression was used to examine the association between total HEI-2010 and AHEI-2010 scores and diabetes status.

RESULTS

Adults with T2DM showed higher HEI-2010 and AHEI-2010 scores compared to adults with prediabetes and nondiabetes but did not have better health markers. For HEI-2010 component scores, adults with T2DM had highest consumption (highest score) of total protein foods and lowest consumption (highest score) for empty calories (p < 0.01). For AHEI-2010 component scores, adults with T2DM had the lowest consumption (highest score) for sugar-sweetened beverages and fruit juice, sodium, and alcohol (lowest score). In addition, adults with T2DM had the highest consumption (lowest score) for red and/or processed meats (p < 0.01). However, neither total HEI-2010 nor AHEI-2010 scores were significantly associated with diabetes status (p > 0.05). Results suggest that neither index was clearly superior to the other in terms of its predictive ability in relation to T2DM.

CONCLUSION

Neither total HEI-2010 nor AHEI-2010 scores performed better in terms of their relationship with diabetes status. However, the significant relationships between 1) diabetes status and health markers and 2) between HEI-2010 and AHEI-2010 scores and health markers suggest that diet has some influence on T2DM.

Sleep, Health, and Metabolism in Midlife Women and Menopause: Food for Thought

Sleep and metabolism are essential components of health. Metabolic health depends largely on individual's lifestyle. Disturbances in sleep health, such as changes in sleep patterns that are associated with menopause/reproductive aging and chronologic aging, may have metabolic health consequences. Sleep restriction and age-related changes in sleep and circadian rhythms may influence changes in appetite and reproductive hormones, energy expenditure, and body adiposity. In this article, the authors describe how menopause-related sleep disturbance may affect eating behavior patterns, immunometabolism, immunometabolic dysfunction, and associations between sleep and metabolic outcomes.

Association between long sleep duration and increased risk of obesity and type 2 diabetes: A review of possible mechanisms

For the last two decades research has revealed an alarming association between short sleep duration and metabolic disorders. In tandem, the hormonal, behavioral, and genetic mechanisms underlying this relationship have been extensively investigated and reviewed. However, emerging evidence is revealing that excessive sleep duration has remarkably similar deleterious effects. Unfortunately, to date there has been little attention to what drives this connection. This narrative review therefore aims to summarize existing epidemiological findings, experimental work, and most importantly putative molecular and behavioral mechanisms connecting excessive sleep duration with both obesity and type 2 diabetes mellitus. It will also address recent findings suggesting a worrisome bidirectional effect such that metabolic disorders create a positive feedback loop which further perpetuates excessive sleep.

Characterizing Adult Sleep Behavior Over 20 Years-The Population-Based Doetinchem Cohort Study

Study Objectives:

To describe sleep duration patterns of adults over a 20-year period; to compare sociodemographic, lifestyle, and health characteristics across these patterns; and to relate the patterns to sleep quality.

Methods:

The study population consisted of 3695 adults aged 20 to 59 years at baseline. Five measurements of self-reported sleep duration were used to compose seven patterns from 1987 to 2012: persistent short (≤6 hours), moderate (7–8 hours), or long (≥9 hours) sleep duration and several changing patterns (varying and became short, moderate, or long sleepers). Multinomial logistic regression analyses were used to compare characteristics across sleep duration patterns.

Results:

About 56% of the adults had persistent moderate sleep duration over 20 years. This group had a better sleep quality than the other groups. Of the adults who changed in their sleep duration (40%), 43% became a short sleeper. Sleep duration patterns that deviate from persistent moderate sleep duration were associated with physical inactivity during leisure time (odds ratios [ORs] and 95% confidence intervals [95% CIs] varied between 1.26 [1.04–1.53] and 1.58 [1.06–2.37]) and with poor self-rated health (ORs [95% CIs] varied between 1.50 [1.20–1.87] and 2.15 [1.48–3.12]).

Conclusions:

Nearly half of the adults did not have persistent moderate sleep duration over a 20-year period and more than one-sixth became short sleeper. This is reason for concern considering the adverse health status associated with short and long sleep duration. Leisure-time physical activity is a potential important target to prevent unfavorable changes in sleep duration over the life course.

Sleep, circadian dysrhythmia, obesity and diabetes

Synchrony of biological processes with environmental cues developed over millennia to match growth, reproduction and senescence. This entails a complex interplay of genetic, metabolic, chemical, light, hormonal and hedonistic factors across life forms. Sleep is one of the most prominent rhythms where such a match is established. Over the past 100 years or so, it has been possible to disturb the synchrony between sleep-wake cycle and environmental cues. Development of electric lights, shift work and continual accessibility of the internet has disrupted this match. As a result, many non-communicable diseases such as obesity, insulin resistance, type 2 diabetes, coronary artery disease and malignancies have been attributed in part to such disruption. In this presentation a review is made of the origin and evolution of sleep studies, the pathogenic mediators for such asynchrony, clinical evidence and relevance and suggested management options to deal with the disturbances.

Short-term changes in sleep duration and risk of type 2 diabetes: Kailuan prospective study

Evidence suggests short or long sleep duration is associated with a higher risk of diabetes. Using a large longitudinal data set spanning 2 years, we examined whether a change in sleep duration is associated with diabetes.Current analysis included 56,588 participants who were free of diabetes during both 2006-2007 (exam1) and 2008-2009 (exam2). Sleep duration was categorized into 7 groups: ≤5.5 hours, 6.0 to 6.5 hours, 7.0 hours, 7.5 to 8.0 hours, ≥8.5 hours, decrease ≥2 hours, and increase ≥2 hours. Cox proportional hazards models were used to calculate hazard ratios (HRs) and their confidence intervals (CI) for diabetes, according to sleep duration.Compared to the reference group of persistent 7-h sleepers, participants who slept 7.5 to 8 hours per night (HR, 1.20; 95% CI, 1.02-1.40), ≥8.5 hours per night (HR, 1.37; 95% CI, 1.03-1.81) and an increase of ≥2 hours sleep per night (HR, 1.24; 95% CI, 1.05-1.48) were all associated with an increased risk of developing diabetes in analyses adjusted for age, sex, education level, income level, smoking status, drinking status, physical activity, BMI, snoring status, hypertension, hyperlipidemia, and family history of diabetes. The abovementioned associations of sleep duration and incident diabetes were only prominent among individuals aged <64 years.This study suggests that individuals whose sleep duration increases ≥2 hours per night are at an increased risk of diabetes.

Sleep Duration and Obesity in Adults: What Are the Connections?

Collectively, cross-sectional and longitudinal studies on self-reported sleep duration and obesity do not show a clear pattern of association with some showing a negative linear relationship, some showing a U-shaped relationship, and some showing no relationship. Associations between sleep duration and obesity seem stronger in younger adults. Cross-sectional studies using objectively measured sleep duration (actigraphy or polysomnography (PSG)) also show this mixed pattern whereas all longitudinal studies to date using actigraphy or PSG have failed to show a relationship with obesity/weight gain. It is still too early and a too easy solution to suggest that changing the sleep duration will cure the obesity epidemic. Given novel results on emotional stress and poor sleep as mediating factors in the relationship between sleep duration and obesity, detection and management of these should become the target of future clinical efforts as well as future research.

Metabolic disturbances: role of the circadian timing system and sleep

The incidence of metabolic disorders such as obesity and diabetes is on the rise, and food quality is not alone to blame. Sleep disturbances, altered feeding time and circadian disruption are linked to metabolic disturbances in many clinical research studies and cross-sectional analyses. This review tried to summarize the role of the circadian timing system and sleep on energy and metabolic homeostasis. We also tried to explain the molecular and endocrine mechanisms behind circadian misalignment and sleep disorders that lead to metabolic disorders.

The role of sleep duration in diabetes and glucose control

Sleep curtailment is common in the Westernised world and coincides with an increase in the prevalence of type 2 diabetes mellitus (T2DM). This review considers the recently published evidence for whether sleep duration is involved in the development of T2DM in human subjects and whether sleep has a role to play in glucose control in people who have diabetes. Data from large, prospective studies indicate a U-shaped relationship between sleep duration and the development of T2DM. Smaller, cross-sectional studies also support a relationship between short sleep duration and the development of both insulin resistance and T2DM. Intervention studies show that sleep restriction leads to insulin resistance, with recent sleep extension studies offering tantalising data showing a potential benefit of sleep extension on glucose control and insulin sensitivity. In people with established diabetes the published literature shows an association between poor glucose control and both short and long sleep durations. However, there are currently no studies that determine the causal direction of this relationship, nor whether sleep interventions are likely to offer benefit for people with diabetes to help them achieve tighter glucose control.

Epidemiology of Obesity and Diabetes and Their Cardiovascular Complications

Obesity and diabetes mellitus have reached epidemic proportions in the past few years. During 2011 to 2012, more than one-third of the US population was obese. Although recent trend data indicate that the epidemic has leveled off, prevalence of abdominal obesity continues to rise, especially among adults. As seen for obesity, the past few decades have seen a doubling of the diabetes mellitus incidence with an increasing number of type 2 diabetes mellitus cases being diagnosed in children. Significant racial and ethnic disparities exist in the prevalence and trends of obesity and diabetes mellitus. In general, in both adults and children, non-Hispanic blacks and Mexican Americans seem to be at a high risk than their non-Hispanic white counterparts. Secular changes in agricultural policies, diet, food environment, physical activity, and sleep have all contributed to the upward trends in the diabesity epidemic. Despite marginal improvements in physical activity and the US diet, the food environment has changed drastically to an obesogenic one with increased portion sizes and limited access to healthy food choices especially for disadvantaged populations. Interventions that improve the food environment are critical as both obesity and diabetes mellitus raise the risk of cardiovascular disease by ≈2-fold. Among those with type 2 diabetes mellitus, significant sex differences occur in the risk of cardiovascular disease such that diabetes mellitus completely eliminates or attenuates the advantages of being female. Given the substantial burden of obesity and diabetes mellitus, future research efforts should adopt a translational approach to find sustainable and holistic solutions in preventing these costly diseases.