Association between Sleep Habits and Metabolically Healthy Obesity in Adults: A Cross-Sectional Study

The association between trouble sleeping and obesity among the U.S. elderly from NHANES 2011-2014: A moderated mediation model of depressive symptoms and cognitive function

BACKGROUND

Studies have shown a close association between trouble sleeping and obesity in older adults. However, no studies have explored the underlying mechanism of this relationship. The present study was designed to evaluate the roles of depressive symptoms and cognitive function in the association between trouble sleeping and obesity in older American adults.

METHODS

A cross-sectional study with 2575 participants (≥60 years old) in the National Health and Nutrition Examination Survey (NHANES) 2011-2014 was used for analysis. Obesity, depressive symptoms, and cognitive function (including Established Consortium for Word Learning in Alzheimer's Disease (CERAD-WL) (immediate learning and recall and delayed recall), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST)) were objectively measured, and trouble sleeping was assessed using a self-reported questionnaire. The moderated mediation analysis was conducted by Hayes' PROCESS macro.

RESULTS

Trouble sleeping was positively associated with obesity among older adults. Depressive symptoms partially and indirectly mediated this association, and DSST moderated the association between trouble sleeping and depressive symptoms. Trouble sleeping had a lower impact on depressive symptoms in older adults with higher cognitive function.

LIMITATIONS

The cross-sectional design prevents making causal inferences, and part of self-reported information was not objective enough.

CONCLUSION

Cognitive function moderated the mediation of depressive symptoms on the indirect, positive association between trouble sleeping and obesity; hence, incorporating methods to strengthen cognitive function and alleviate depressive symptoms may help weak the link between trouble sleeping and obesity among older adults.

Obesity, cardiovascular risk, and lifestyle: cross-sectional and prospective analyses in a nationwide Spanish cohort

AIMS

To assess whether overweight and obesity are independently associated with cardiometabolic health [as categorized based on the presence/absence of cardiovascular disease (CVD) risk factors (diabetes, hypercholesterolaemia, or hypertension)], and the role of lifestyle on this association.

METHODS AND RESULTS

A nationwide cohort of Spanish adults (18-64 years) was studied using a cross-sectional design and prospective observational design. Lifestyle-related factors (physical activity, sleeping characteristics, alcohol drinking, and smoking) were registered, and participants were classified as having an 'unhealthy' or 'healthy' cardiometabolic status attending to the presence or absence, respectively, of ≥1 CVD risk factor. A number of 596 111 participants (44 ± 9 years, 67% male) were studied at baseline, with prospective analyses in a subcohort [n = 302 061; median follow-up, 2 years (range, 2 to 5)]. Compared to normal weight, overweight and obesity were associated with a higher prevalence [odds ratio, 1.67 (95% confidence interval, 1.61-1.67) and 2.70 (2.69-2.78), respectively] and incidence [1.62 (1.59-1.67) and 2.70 (2.63-2.78)] of an unhealthy cardiometabolic status. Meeting physical activity guidelines reduced the odds of an unhealthy cardiometabolic status at baseline [0.87 (0.85-0.88)] among individuals with overweight/obesity, as well as of transitioning from a healthy status to an unhealthy status during the follow-up [0.87 (0.84-0.94)]. No significant associations were found for the remainder of lifestyle factors.

CONCLUSION

Overweight and obesity are independently associated with an unhealthy cardiometabolic status. Regular physical activity attenuates not only the prevalence but also the incidence of CVD risk factors.

Obesity and the risk of cardiometabolic diseases

The prevalence of obesity has reached pandemic proportions, and now approximately 25% of adults in Westernized countries have obesity. Recognized as a major health concern, obesity is associated with multiple comorbidities, particularly cardiometabolic disorders. In this Review, we present obesity as an evolutionarily novel condition, summarize the epidemiological evidence on its detrimental cardiometabolic consequences and discuss the major mechanisms involved in the association between obesity and the risk of cardiometabolic diseases. We also examine the role of potential moderators of this association, with evidence for and against the so-called 'metabolically healthy obesity phenotype', the 'fatness but fitness' paradox or the 'obesity paradox'. Although maintenance of optimal cardiometabolic status should be a primary goal in individuals with obesity, losing body weight and, particularly, excess visceral adiposity seems to be necessary to minimize the risk of cardiometabolic diseases.

Do lifestyle factors and quality of life differ in people with metabolically healthy and unhealthy obesity?

BACKGROUND AND OBJECTIVES

Although obesity is typically associated with metabolic co-morbidities, some people with obesity do not develop metabolic abnormalities. We evaluated whether modifiable lifestyle factors (i.e., physical activity, dietary composition, and sleep characteristics) can help explain why some people with obesity are metabolically healthy (MHO) and whether metabolically unhealthy obesity (MUO) affects quality of life (QOL).

SUBJECTS/METHODS

Physical activity and sleep characteristics were assessed by using tri-axial accelerometers and dietary intake, sleep quality, and QOL were evaluated by using validated questionnaires in people stratified into three groups: (1) lean with normal glucose tolerance, plasma triglyceride (TG) concentration and intrahepatic TG (IHTG) content (metabolically healthy lean [MHL]; n = 20); (2) obesity and normal glucose tolerance, plasma TG concentration and IHTG content (MHO; n = 36); and (3) obesity with abnormal glucose metabolism and hepatic steatosis (MUO; n = 43).

RESULTS

People with MHO performed ~45-min more light-intensity physical activity/day than the MHL and MUO groups (P < 0.05). QOL, particularly the physical function domain, was higher in the MHO than the MUO group (P < 0.05). Although self-reported intake of starch, dairy, and cured meats were higher in the MUO than the MHO group (P < 0.02), the absolute differences were small and unlikely to have metabolic effects. No differences were found in sleep duration or quality between groups.

CONCLUSIONS

These data suggest physical activity, but not sleep or dietary intake, contribute to better metabolic health in people with MHO than those with MUO, and that QOL is lower in people with MUO than those with MHO.

Selected Organ and Endocrine Complications According to BMI and the Metabolic Category of Obesity: A Single Endocrine Center Study

Obesity is a chronic and complex disease associated with metabolic, organ and endocrine complications. In the study, we analyzed a group of 105 patients suffering from obesity without any other previously recognized serious disorders who had been referred to a single endocrine center. The study aimed to assess the prevalence of selected organ and endocrine complications by subdividing the group, firstly according to body mass index (BMI) and secondly with regard to metabolic syndrome (MetS), pre-MetS and the metabolically healthy obesity (MHO) category. We have observed that in our groups, the prevalence of hyperlipidemia, hypertension, asthma, obstructive sleep apnea (OSA) depended on BMI category, whereas the incidence of hyperlipidemia, hypertension, OSA, hypothyroidism, non-alcoholic fatty liver disease, prediabetes, and type 2 diabetes was related to the metabolic category. We concluded that the distribution of particular organ and endocrine complications change significantly with increased BMI and with the shift from MHO to pre-MetS and MetS. Thus, to determine the risk of organ and endocrine complications more effectively, BMI and metabolic status should be assessed during the examination of patients with obesity.

Association of sleep quality with insulin resistance in obese or overweight subjects

Introduction

Obesity or overweight are two factors associated with insulin resistance (IR). There are limited studies with regard to the role of some non-traditional factors such as sleep quality in level of IR in obese individuals. The current study aimed at investigating the association of sleep quality with IR in overweight or obese people.

Material and Methods

In this cross-sectional study, 612 obese or overweight participants of the Qazvin metabolic disease study (QMDS) were evaluated. Sleep quality was measured using the Pittsburgh sleep quality index (PSQI) and compared between two groups of participants with and without IR.

Results

Our findings showed that the total score of sleep quality in the IR group was significantly lower than that in the non-insulin resistant group (8.78±2.78 vs. 8.13±2.70, p=0.008). After adjustment, each unit increase of the sleep latency and subjective sleep quality scores was associated with a 1.23 and 1.33 times increased risk of IR, respectively (p<0.05).

Conclusion

In the obese or overweight people, sleep quality is associated with IR.

Healthy Obese Subjects Differ in Chronotype, Sleep Habits, and Adipose Tissue Fatty Acid Composition from Their Non-Healthy Counterparts

Obesity is not the same in all individuals and two different phenotypes have been described: metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). The aim of this study was to identify factors that explain metabolic health status in a rigorously matched Spanish population. Subcutaneous and visceral fat, adipocyte size and fatty acid composition, cardiometabolic markers in serum, and lifestyle habits were assessed. Higher physical activity in the mornings (Odds Ratio (95% Confidence Interval) (OR (95% CI) = 1.54 (1.09–2.18), p = 0.01)), earlier bedtimes (8:30–10:30 pm) (OR = 2.11 (1.02–4.36), p = 0.04), a complete breakfast (OR = 1.59 (1.07–2.36), p = 0.02), and a greater number of meals per day (4.10 ± 0.05 vs. 3.93 ± 0.05, p < 0.01), were associated with the MHO phenotype. Concentrations of 20:5 n-3 eicosapentaenoic acid (0.26 ± 0.46 vs. 0.10% ± 0.11%, p = 0.04) and 18:3 n-6 gamma-linolenic acid (0.37 ± 0.24 vs. 0.23% ± 0.22%, p = 0.04) in subcutaneous adipocytes were higher and omental adipocyte size (187 094 ± 224 059 µm³ vs. 490 953 ± 229 049 µm³, p = 0.02) was lower in MHO subjects than in those with MUO. Visceral fat area differed between MHO and MUO subjects (135 ± 60 cm² vs. 178 ± 85 cm², p = 0.04, respectively). The study highlights specific lifestyle habits that could form part of obesity therapies, not only involving healthier eating habits but also earlier sleeping and exercise patterns.

Metabolically healthy obesity: facts and fantasies

Although obesity is typically associated with metabolic dysfunction and cardiometabolic diseases, some people with obesity are protected from many of the adverse metabolic effects of excess body fat and are considered "metabolically healthy." However, there is no universally accepted definition of metabolically healthy obesity (MHO). Most studies define MHO as having either 0, 1, or 2 metabolic syndrome components, whereas many others define MHO using the homeostasis model assessment of insulin resistance (HOMA-IR). Therefore, numerous people reported as having MHO are not metabolically healthy, but simply have fewer metabolic abnormalities than those with metabolically unhealthy obesity (MUO). Nonetheless, a small subset of people with obesity have a normal HOMA-IR and no metabolic syndrome components. The mechanism(s) responsible for the divergent effects of obesity on metabolic health is not clear, but studies conducted in rodent models suggest that differences in adipose tissue biology in response to weight gain can cause or prevent systemic metabolic dysfunction. In this article, we review the definition, stability over time, and clinical outcomes of MHO, and discuss the potential factors that could explain differences in metabolic health in people with MHO and MUO - specifically, modifiable lifestyle factors and adipose tissue biology. Better understanding of the factors that distinguish people with MHO and MUO can produce new insights into mechanism(s) responsible for obesity-related metabolic dysfunction and disease.

Metabolically healthy versus metabolically unhealthy obesity

Obesity-related disease complications reduce life quality and expectancy and increase health-care costs. Some studies have suggested that obesity not always entails metabolic abnormalities and increased risk of cardiometabolic complications. Because of the lack of universally accepted criteria to identify metabolically healthy obesity (MHO), its prevalence varies widely among studies. Moreover, the prognostic value of MHO is hotly debated, mainly because it likely shifts gradually towards metabolically unhealthy obesity (MUO). In this review, we outline the differential factors contributing to the metabolic heterogeneity of obesity by discussing the behavioral, genetic, phenotypical, and biological aspects associated with each of the two metabolic phenotypes (MHO and MUO) of obesity and their clinical implications. Particular emphasis will be laid on the role of adipose tissue biology and function, including genetic determinants of body fat distribution, depot-specific fat metabolism, adipose tissue plasticity and, particularly, adipogenesis. Finally, the emerging role of gut microbiota in obesity and adipose tissue dysfunction as well as the search for novel biomarkers for the obesity-related metabolic traits and associated diseases will be briefly presented. A better understanding of the main determinants of a healthy metabolic status in obesity would allow promotion of this favorable condition by targeting the relevant pathways.

Sleep duration and apolipoprotein B in metabolically healthy and unhealthy overweight/obese phenotypes: a cross-sectional study in Chinese adults

OBJECTIVES

Short sleep duration is independently associated with an increased risk of developing cardiovascular disease; however, the association has not yet been examined in obese populations. We assessed the associations between sleep duration, metabolic phenotype and apolipoprotein variables in a nationally representative Chinese population with overweight/obesity.

STUDY DESIGN

Cross-sectional study.

SETTINGS

The study conducted in nine provinces of China that vary substantially in geography and economic development.

PATIENTS

Data were obtained from 4149 adults with overweight/obesity aged 18 to 94 years from the 2009 China Health and Nutrition Survey. Sleep duration was categorised as ≤6, 7-8 or ≥9 hour. Phenotypes were determined based on body mass index and metabolic health status and categorised as metabolically healthy overweight/obesity (MHOO) and metabolically unhealthy overweight/obesity (MUOO).

MAIN OUTCOME MEASURE

The outcome variables were elevated apolipoproteins.

RESULTS

Compared with MHOO phenotype, MUOO phenotypes were more likely to report shorter sleep duration (12.2%vs9%). In the MUOO group, the multivariate-adjusted OR (95% CI) for elevated apolipoprotein B (apoB) was 1.66 (1.23 to 2.23) for those with ≤6 hours of sleep and 1.12 (0.86 to 1.45) for those with ≥9 hours of sleep, using 7-8 hours of sleep as a reference. Similar results were obtained in the subgroup of subjects who were ≥45 or<45 years old, but shorter sleep duration was more strongly associated with elevated apoB in those <45 years (p interaction=0.023). However, no association was observed in the MHOO phenotype.

CONCLUSIONS

The high prevalence of short sleep duration and its strong association with elevated apoB in adults who are metabolically unhealthy overweight/obese suggest an increased risk of cardiovascular disease in this population. The differences in sleep sufficiency among obese phenotypes may account for the disparities in their cardiovascular outcomes.