Sleep Deprivation: Effects on Weight Loss and Weight Loss Maintenance

Sleep problems and their predictors in community-dwelling older adults with diabetes in India: Evidence from the Longitudinal Ageing Study in India

Objectives

To ascertain the prevalence and predictors of sleep disorders and poor sleep quality among older adults with Diabetes (DM) in India, and to assess the relationship between sleep quality and DM.

Methods

Data was utilized from the nationally representative Longitudinal Ageing Study in India (Wave-1, 2017-18), with a total sample of 66606 older adults (≥45 years) selected for the study. Sleep problems and sleep quality score were assessed using an adaptation based on the Jenkins Sleep Scale. Multivariate linear and logistic regressions were conducted to determine the effect of sociodemographic and clinical factors on sleep quality. Mediation analysis (Karlson-Holm-Breen) was done to assess the direct and indirect effects of independent variables on the sleep quality scores. Further, Propensity score matching (PSM) was done to assess the impact of diabetes on sleep problems.

Results

The prevalence of DM was 12.34% (n = 8564, 95% CI: 11.54, 13.20) among whom 24.38% (95% CI: 21.38, 27.65) reported sleep problems. On adjusted analysis, sleep problems were significantly associated with increasing education, higher wealth quintile, lack of physical activity, and multimorbidity. Mediation analysis showed adherence to anti-diabetes medication improved sleep quality (aB = -0.28 (95% CI: -0.54, -0.02)), while comorbidities worsened sleep quality (aB = 0.79 (95% CI: 0.67, 0.92)). Analysis from PSM indicated that DM was associated with a 6.2% higher chance of sleep problems.

Conclusions

Poor sleep quality is present in nearly one in four individuals diagnosed with DM in India and linked with certain adverse social determinants. Focused interventions to improve assessment and treatment of sleep problems in resource-limited primary care settings require prioritization.

Association of sleep quality with physical and psychological health indicators in overweight and obese rural Indians

Objective

To measure the association of sleep quality with physical (i.e., grip strength, functional mobility, balance) and psychological (depression, anxiety) health indicators in an overweight/obese population.

Methods

Baseline data of 2337 participants (1382 overweight/obese and 955 normal weight) from an aging cohort in rural southern India (CBR-SANSCOG) was analyzed retrospectively. Assessment tools included the Pittsburgh Sleep Quality Index (PSQI) for sleep quality, dynamometry for Hand Grip Strength (HGS), Timed Up-and-Go (TUG) for functional mobility, Chair Stand Test (CST) for lower limb strength, Geriatric Depression scale (GDS-30) for depressive symptoms and Generalized Anxiety Disorder scale (GAD-7) for anxiety symptoms. Linear regression models, adjusted for known confounders, were used to examine the association of sleep quality with the health parameters in overweight/obese and normal-weight groups.

Results

In the fully adjusted model, higher global PSQI score was associated with higher TUG time (β = 0.06, 95 % CI: 0.004,0.12), higher scores on GDS (β = 1.08, 95 % CI: 0.96,1.20) and GAD (β = 0.71, 95 % CI: 0.62,0.79), and lower scores on CST (β = -0.12, 95 % CI: -0.19,-0.06) in overweight/obese individuals. The sleep disturbance sub-component of PSQI was associated with most of the physical (TUG, CST) and psychological (GDS and GAD) health indicators. Sleep duration and use of sleep medication showed no significant association with any of the health indicators.

Conclusion

The concurrent presence of poor sleep quality and overweight/obesity could worsen physical and psychological health in middle-aged and older adults. We highlight the importance of early detection and timely management of sleep problems in this population to reduce physical and psychological morbidities.

Sleep quality and falls in middle-aged and older adults: ELSI-Brazil study

OBJECTIVE

To verify the association between low self-reported sleep quality (LSQ) and fall in middle-aged and older adults every half-decade of life.

METHOD

A cross-sectional study was conducted using data from the first wave (2015-2016) of the Brazilian Longitudinal Study of Aging (ELSI-Brazil), which is nationally representative. The sample consisted of 8,950 participants who were allocated into eight age groups: 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, 80-84, and ≥ 85 years. The questionnaires used included self-reported sleep quality and the International Physical Activity Questionnaire short version. Fisher's exact test followed by binary logistic regression analysis was performed to identify the odds ratio of sleep quality for fall occurrence, controlled for confounding variables.

RESULTS

Individuals aged 50-105 years (63.6 ± 10.2 years), 57.0% females and 43.0% males, participated in this study. Overall, 21.5% of participants experienced at least one fall. The relative frequency of participants classified as having high or LSQ remained constant across each half-decade of life. The LSQ exhibited a statistically significant OR (p < 0.05) for falls across age groups up to 84, even after accounting for confounding variables.

CONCLUSION

LSQ is significantly associated with an increased occurrence of fall in adults aged >50 years, but not for ≥ 85 years regardless of sex and physical activity level.

Key messages on obesity care from the 2023 ASPEN Physician Preconference Course: A narrative review

Obesity is a challenging chronic disease process that continues to affect a large percentage of the population at large. With the advent of new therapeutic options and interventions and a deeper scientific understanding of obesity as a complex illness, there is hope in curtailing this evolving pandemic. In this article, we present key medical information to engage and empower nutrition-focused providers to manage obesity and its nutrition complications. The topics summarized here were presented during the 2023 American Society for Parenteral and Enteral Nutrition Preconference Physician Course and include pathophysiology and hormonal regulation of obesity, multidisciplinary care planning and nutrition risk stratification of patients, and common approaches to treatment, including lifestyle modifications, antiobesity medications, and procedures from the perspective of the nutrition specialist.

The Integration of Sleep Research Into Eating Disorders Research: Recommendations and Best Practices

OBJECTIVE

Sleep disturbance is common among individuals with eating disorders (EDs), with approximately 50% of patients with EDs reporting sleep disturbance. Sleep problems may promote, exacerbate, or maintain ED symptoms through a variety of hypothesized mechanisms, such as impaired executive function, increased negative affect, and disruptions to appetitive rhythms. Although research investigating the role of sleep in EDs is growing, the current literature suffers from methodological limitations and inconsistencies, which reduce our ability to translate findings to improve clinical practice. The purpose of this forum is to propose a coordinated approach to more seamlessly integrate sleep research into ED research with particular emphasis on best practices in the definition and assessment of sleep characteristics.

METHODS

In this article, we will describe the current status of sleep-related research and relevant gaps within ED research practices, define key sleep characteristics, and review common assessment strategies for these sleep characteristics. Throughout the forum, we also discuss study design considerations and recommendations for future research aiming to integrate sleep research into ED research.

RESULTS/DISCUSSION

Given the potential role of sleep in ED maintenance and treatment, it is important to build upon preliminary findings using a rigorous and systematic approach. Moving forward as a field necessitates a common lens through which future research on sleep and EDs may be conducted, communicated, and evaluated.

Weight Loss Programs: Why Do They Fail? A Multidimensional Approach for Obesity Management

PURPOSE OF REVIEW

Despite the prevalence of weight loss programs, their success rates remain discouraging, with around half of individuals regaining lost weight within two years. The primary objective of this review is to explore the factors contributing to the failure of weight loss programs and to provide insights into effective weight management strategies.

RECENT FINDINGS

Factors contributing to the failure of weight loss programs include the impracticality of restrictive diets, potential metabolic impacts, limited focus on lifestyle changes, genetic predispositions, psychological influences, socioeconomic status, and medical conditions. A holistic approach considering these factors is crucial for safe and sustainable weight loss. Key findings indicate the importance of holistic approaches to weight management, including lifestyle modifications, medical interventions, and behavioral and psychological strategies. Effective weight loss strategies emphasize low-calorie, nutrient-rich diets, regular physical activity, and interventions tailored to individual needs. Combining multiple approaches offers the best chance of successful weight management and improved health outcomes. This review provides insights into the complexities of obesity management and the factors contributing to the failure of weight loss programs. It highlights the necessity of adopting a holistic approach that addresses dietary habits, physical activity, genetic factors, psychological well-being, and socioeconomic influences. Recommendations include implementing lifestyle modifications, medical interventions when necessary, and integrating behavioral and psychological support to achieve sustainable weight loss and mitigate the global health challenge posed by obesity.

Pairing Evidence-Based Strategies With Motivational Interviewing to Support Optimal Nutrition and Weight Gain in Pregnancy

OBJECTIVE

Because eating, nutrition, and weight management patterns adopted during pregnancy may persist beyond the postpartum period, pregnancy provides an opportunity for health education that affects the future health of the pregnant person, the fetus, and the family. This systematic review aimed to find nutrition and weight management behaviors that could be used safely during pregnancy to optimize gestational weight gain.

METHODS

PubMed, MEDLINE, and Web of Science were searched for research or systematic reviews published in English from 2018 to 2023 using terms including gestational weight gain maintenance, weight, management, pregnancy, behavior, strategy, and strategies. Excluded research used pediatric or adolescent populations, restrictive diets such as no carbohydrate or no fat diets, fasting, bariatric surgery, weight loss medications, private industry, or profit-earning programs using food brands or specific diet programs.

RESULTS

The abstracts reviewed in these areas: excessive gestational weight gain (1019), low-glycemic index diet (640), Mediterranean diet (220), MyPlate diet (2), the Dietary Approaches to Stop Hypertension (DASH) diet (50), portion control (6), home meal preparation (6), mindful eating (13), intuitive eating (10), self-weighing (10), and motivational interviewing during pregnancy (107), were reduced to 102 studies. Studies in those 10 areas were reviewed for nutrition and eating behaviors that are safe to use during pregnancy and could be used along with motivational interviewing.

CONCLUSION

Clinicians can discuss these behaviors using motivational interviewing techniques to assist clients in optimizing gestational weight gain. Dialogue examples pairing these strategies with motivational interviewing principles are included.

Mechanisms of improved body composition among perimenopausal women practicing Meditative Movement: a proposed biobehavioral model

OBJECTIVES

Weight gain and unfavorable body composition are prevalent among midlife/older women throughout menopause. These shifts may negatively impact health, well-being, and longevity. Efforts to attenuate weight and body composition changes are traditionally driven by manipulation of diet and/or exercise; however, sustained results are limited, possibly because the full spectrum of biobehavioral systems is not addressed by diet and exercise alone. We propose a biobehavioral model detailing mechanisms of body composition decline among perimenopausal women and the associated components of Meditative Movement (ie, tai chi, qigong, yoga) that address each of these factors.

METHODS

Based on our previous work and extensive review of the literature, we developed a multifactorial and multidimensional biobehavioral model including factors that most directly relate to body composition among perimenopausal women: 1) psychological (ie, stress and mood, mindfulness and self-compassion, body awareness), 2) behavioral (ie, sleep, physical activity, eating behaviors), and 3) physiological (ie, cortisol, estrogen). Relationships between each factor, Meditative Movement practice components, and predicted effects on body composition were explored in detail.

RESULTS

Our model describes select psychological, behavioral, and physiological factors, and potential mechanistic pathways of Meditative Movement practice driving improved changes in body composition and weight outcomes for perimenopausal women.

CONCLUSIONS

The proposed model details a novel, evidence-supported means to reduce the risk of deleterious shifts in body composition throughout perimenopause and menopause thereafter. We suggest that these changes may occur directly and/or indirectly through psychological, behavioral, and physiological mechanisms that facilitate the desired changes in body composition.

Metabolic diseases and healthy aging: identifying environmental and behavioral risk factors and promoting public health

Aging is a progressive and irreversible pathophysiological process that manifests as the decline in tissue and cellular functions, along with a significant increase in the risk of various aging-related diseases, including metabolic diseases. While advances in modern medicine have significantly promoted human health and extended human lifespan, metabolic diseases such as obesity and type 2 diabetes among the older adults pose a major challenge to global public health as societies age. Therefore, understanding the complex interaction between risk factors and metabolic diseases is crucial for promoting well-being and healthy aging. This review article explores the environmental and behavioral risk factors associated with metabolic diseases and their impact on healthy aging. The environment, including an obesogenic environment and exposure to environmental toxins, is strongly correlated with the rising prevalence of obesity and its comorbidities. Behavioral factors, such as diet, physical activity, smoking, alcohol consumption, and sleep patterns, significantly influence the risk of metabolic diseases throughout aging. Public health interventions targeting modifiable risk factors can effectively promote healthier lifestyles and prevent metabolic diseases. Collaboration between government agencies, healthcare providers and community organizations is essential for implementing these interventions and creating supportive environments that foster healthy aging.

The Menstrual Cycle's Influence on Sleep Duration and Cardiovascular Health: A Comprehensive Review

The menstrual cycle, a fundamental biological process in women, extends its influence beyond reproduction, impacting sleep duration and cardiovascular health. This comprehensive review delves into the intricate connections that bind these three vital aspects of women's health. Beginning with thoroughly exploring the menstrual cycle, we uncover its phases and the dynamic hormonal fluctuations that underlie each stage. We pay special attention to estrogen and progesterone, the primary sex hormones orchestrating the menstrual cycle. With their rhythmic rise and fall, these hormones orchestrate events, affecting sleep duration, sleep patterns, and various indicators of cardiovascular well-being. The review examines how the menstrual cycle influences sleep patterns, exploring the nuanced changes in sleep duration observed throughout menstrual phases. We elucidate the contributing factors, encompassing hormonal fluctuations, the impact of pain and discomfort, and the significance of emotional and psychological factors. All of these elements collectively contribute to variations in sleep quality. Shifting our focus to the cardiovascular system, we investigate the bidirectional relationships between sleep disturbances and cardiovascular conditions, emphasizing the need to address sleep-related issues in the context of cardiovascular risk. The menstrual cycle is analyzed as a pivotal mediator in these intricate connections, exploring how hormonal fluctuations across menstrual phases can influence sleep patterns and cardiovascular health. This analysis provides valuable insights into the complex causality web. As clinical implications emerge, we emphasize the importance of tailoring healthcare strategies for individuals with irregular menstrual cycles. We explore potential interventions, from personalized care and hormone management to lifestyle adjustments, to improve sleep and cardiovascular well-being. In conclusion, this comprehensive review sheds light on the interplay between the menstrual cycle, sleep duration, and cardiovascular health. It underscores the urgent necessity for personalized healthcare approaches and preventive strategies, empowering women to navigate these intricate relationships. Ultimately, through a nuanced understanding of these interactions, we can work towards enhancing women's overall well-being and reducing cardiovascular risk within the context of menstrual cycle-related influences.

Exploring factors related to heart attack complicated with hypertension using a Bayesian network model: a study based on the China Health and Retirement Longitudinal Study

Objectives

While Bayesian networks (BNs) represents a good approach to discussing factors related to many diseases, little attention has been poured into heart attack combined with hypertension (HAH) using BNs. This study aimed to explore the complex network relationships between HAH and its related factors, and to achieve the Bayesian reasoning for HAH, thereby, offering a scientific reference for the prevention and treatment of HAH.

Methods

The data was downloaded from the Online Open Database of CHARLS 2018, a population-based longitudinal survey. In this study, we included 16 variables from data on demographic background, health status and functioning, and lifestyle. First, Elastic Net was first used to make a feature selection for highly-related variables for HAH, which were then included into BN model construction. The structural learning of BNs was achieved using Tabu algorithm and the parameter learning was conducted using maximum likelihood estimation.

Results

Among 19,752 individuals (9,313 men and 10,439 women) aged 64.73 ± 10.32 years, Among 19,752 individuals (9,313 men and 10,439 women), there are 8,370 ones without HAH (42.4%) and 11,382 ones with HAH (57.6%). What's more, after feature selection using Elastic Net, Physical activity, Residence, Internet access, Asset, Marital status, Sleep duration, Social activity, Educational levels, Alcohol consumption, Nap, BADL, IADL, Self report on health, and age were included into BN model establishment. BNs were constructed with 15 nodes and 25 directed edges. The results showed that age, sleep duration, physical activity and self-report on health are directly associated with HAH. Besides, educational levels and IADL could indirectly connect to HAH through physical activity; IADL and BADL could indirectly connect to HAH through Self report on health.

Conclusion

BNs could graphically reveal the complex network relationship between HAH and its related factors. Besides, BNs allows for risk reasoning for HAH through Bayesian reasoning, which is more consistent with clinical practice and thus holds some application prospects.

Behavioral and Psychological Factors Affecting Weight Loss Success

PURPOSE OF REVIEW

There is a large variability between individuals in the weight loss response to any given diet treatment, which fuels interest into personalized or precision nutrition. Although most efforts are directed toward identifying biological or metabolic factors, several behavioral and psychological factors can also be responsible for some of this interindividual variability.

RECENT FINDINGS

There are many factors that can influence the response to dietary weight loss interventions, including factors related to eating behavior (emotional eating, disinhibition, restraint, perceived stress), behaviors and societal norms related to age and sex, psychological and personal factors (motivation, self-efficacy, locus of control, self-concept), and major life events. The success of a weight loss intervention can be influenced by many psychological and behavioral constructs and not merely by physiological factors such as biology and genetics. These factors are difficult to capture accurately and are often overlooked. Future weight loss studies should consider assessing such factors to better understand the underlying reasons for the large interindividual variability to weight loss therapy.

Gestational weight gain among pregnant women in Ibadan, Nigeria: Pattern, predictors and pregnancy outcomes

BACKGROUND

Gestational weight gain (GWG) is a risk factor for adverse pregnancy outcomes, future obesity and chronic diseases among women. However, has not received much attention in many low and middle-income countries such as Nigeria. We investigated the pattern, associated factors and pregnancy outcomes of GWG in Ibadan, Nigeria, using the Ibadan Pregnancy Cohort Study (IbPCS).

METHODOLOGY

The IbPCS is a multicentre prospective cohort study conducted among 1745 pregnant women recruited from four health facilities in Ibadan, Nigeria. GWG, the primary outcome, was categorised according to the Institute of Medicine's classification into insufficient, adequate and excessive weight gain. Pregnancy outcomes were the secondary outcome variables. Logistic regression analysis (Adjusted odds ratios and 95% confidence interval CI) was used to examine associations, and Poisson regression analyses were used to investigate associations with outcomes.

RESULTS

Only 16.9% of women had optimal GWG, 56.8% had excessive GWG, and 26.9% had insufficient GWG. Excessive GWG was associated with high income '> #20,000-' (AOR: 1.64, 95% CI: 1.25-2.17), being overweight (AOR: 2.12, 95% CI: 1.52-2.95) and obese (AOR: 1.47, 95% CI: 1.02-2.13) after adjusting for confounders. In contrast, increased odds of insufficient GWG have associated women with depression (AOR: 1.70, 95% CI 1.17-2.47). There was no significant association between inappropriate GWG and pregnancy outcomes However, there was an increased odds for postpartum haemorrhage (AOR: 2.44, 95% CI 1.14-5.22) among women with obesity and excessive GWG.

CONCLUSIONS

Excessive GWG was the most typical form of GWG among our study participants and was associated with high maternal income, and being overweight or obese. GWG needs to be monitored during antenatal care, and interventions that promote appropriate GWG should be implemented among pregnant women in Nigeria.

Prevalence and Risk Factors for Poor Sleep Quality in People Living with HIV: Preliminary Observations from an HIV Outpatient Clinic

INTRODUCTION

Sleep disorders have been reported in individuals living with HIV (PLWH), with a prevalence rate of over 50%. The main risk factors contributing to the development of sleep disturbances are not yet fully understood. We investigate the prevalence and risk factors associated with poor sleep quality in a population of PLWH who are receiving antiretroviral therapy (ART).

METHODS

The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality in PLWH attending our HIV Outpatient Clinic between October 2022 and April 2023. All subjects with a PSQI score > 5 were considered bad sleepers. A logistic regression analysis was carried out to assess risk factors associated with a PSQI score > 5.

RESULTS

A total of 132 PLWH (78% males) who received ART for at least one month were included in this observational study. The median age was 56 (IQR 47-61). Among all, 41 (31%) had a history of AIDS, and 95 (72%) were receiving an INSTI-based ART. The study population was divided into two groups: PSQI ≤ 5 (90; 68.2%) and PSQI > 5 (42; 31.8%). A lower BMI and the use of bictegravir in the current ART were associated with a PSQI score ≤ 5. In the multivariate analysis, the use of a bictegravir-based ART remained the only factor associated with better sleep quality (OR 0.17; p = 0.0222). No further associations between sleep disturbances and other epidemiological and clinical features were found.

CONCLUSION

In this real-life scenario, poor sleep quality was observed in 31% of the cases, primarily among individuals with higher BMI. In addition, bictegravir users might seem to have a lower likelihood of experiencing poor sleep quality.

Examining bedtime procrastination, study engagement, and studyholism in undergraduate students, and their association with insomnia

Introduction

Compulsive overstudying, known as studyholism, is an emerging behavioral addiction. In this study, we examine the prevalence of, and the relationships between, insomnia, study engagement, studyholism, bedtime procrastination among undergraduate students.

Methods

The Studyholism (SI-10), Athens Insomnia (AIS), and bedtime procrastination scales were administered to a convenience sample of 495 university students.

Results

Our findings indicate that the prevalence of insomnia was 75.31%, high studyholism was found in 15.31% of the sample, and increased study engagement was detected in 16.94%. Gender differences analysis revealed that females reported higher studyholism and bedtime procrastination than males. Fifth-year students had higher levels of studyholism than internship (p < 0.001), first-year (p < 0.01), and sixth-year students (p < 0.05). Insomnia was positively related to studyholism and bedtime procrastination. Furthermore, insomnia can be positively predicted by studyholism and bedtime procrastination. Participants with a medium level of studyholism were twice as likely to experience insomnia as those with a low level. Studyholics were six times more susceptible to insomnia than students with low studyholism levels. Compared to individuals with low bedtime procrastination levels, those with medium and high bedtime procrastination were twice as likely to report insomnia.

Conclusion

Our study highlights the interplay between insomnia, studyholism, and bedtime procrastination. Further, the findings indicate the need to increase awareness of insomnia.

The relationship between sleep and appetitive conditioning: A systematic review and meta-analysis

This systematic review and meta-analysis (PROSPERO registration animal/human studies: CRD42021234793/CRD42021234790) examined the relationship between sleep and appetitive conditioning. Inclusion criteria included: a) appetitive conditioning paradigm; b) measure of conditioning; c) sleep measurement and/or sleep loss; d) human and/etor non-human animal samples; and e) written in English. Searches of seven databases returned 3777 publications. The final sample consisted of 42 studies using primarily animal samples and involving food- and drug-related conditioning tasks. We found sleep loss disrupted appetitive conditioning of food rewards (p < 0.001) but potentiated appetitive conditioning of drug rewards (p < 0.001). Furthermore, sleep loss negatively impacted extinction learning irrespective of the reward type. Post-learning sleep was associated with increases in REM sleep (p = 0.02). Findings suggest sleep loss potentiates the impact of psychoactive substances in a manner likely to produce an increased risk of problematic substance use. In obese/overweight populations, sleep loss may be associated with deficits in the conditioning and extinction of reward-related behaviours. Further research should assess the relationship between sleep and appetitive conditioning in humans.