Sleep quality and risk of cancer: findings from the English longitudinal study of aging

Associations of objectively measured physical activity and sedentary behavior with sleep quality in college students

BACKGROUND

Sleep disorders are prevalent in college students and are often exacerbated by academic pressures. Accumulating evidence indicates that physical activity and sedentary behaviors exert divergent effects on sleep quality. This study aimed to investigate the associations of objectively measured physical activity and sedentary behavior with sleep quality in college students. The potential effects of substituting sedentary behavior with physical activity on sleep quality were also examined.

METHODS

This cross-sectional study included 349 college students (age range: 17-25 years; 57.6 % female) recruited from Shanghai, China. Light physical activity (LPA), moderate-to-vigorous physical activity (MVPA), and sedentary behavior were objectively measured using wrist-worn accelerometers for 7 days. Sleep quality was assessed using the Pittsburgh Sleep Quality Index. A single-factor model was used to examine independent associations, whereas an isotemporal substitution model (ISM) was used to estimate the effects of replacing sedentary behavior with physical activity on sleep quality.

RESULTS

Higher levels of LPA (B = -0.007, 95 % CI = -0.013 to -0.001, p < 0.05) and MVPA (B = -0.013, 95 % CI = -0.022 to -0.003, p < 0.05) were associated with better sleep quality. Conversely, sedentary time was negatively associated with sleep quality (B = 0.007, 95 % CI = 0.002 to 0.012, p < 0.05). In the ISM, replacing 30 min of sedentary behavior with an equivalent duration of MVPA was associated with improved sleep quality (B = -0.322, 95 % CI = -0.624 to -0.021, p < 0.05).

CONCLUSIONS

The findings indicated that physical activity was positively associated with sleep quality, whereas sedentary time was negatively associated with sleep quality in college students. Replacing sedentary behavior with an equivalent duration of MVPA positively affected sleep quality.

Sleep, Circadian Rhythms, and Lung Cancer

Lung cancer is the leading cause of cancer-related mortality worldwide, with the prevalence of the disease continually rising. Therefore, identifying disease-modifying risk factors is critical, with increasing recognition of the impact of sleep quality/sleep disorders. This narrative review summarizes the evidence on the role of five domains of sleep on lung cancer incidence and progression: (i) sleep quality/duration, (ii) sleep disordered breathing, (iii) circadian rhythm disturbances, (iv) sleep-related movement disorders, and (v) personal, environmental, and social factors that modulate each of these associations. Epidemiological evidence supports reduced sleep duration, increased sleep duration, poor sleep quality, insomnia, obstructive sleep apnea, evening chronotype, peripheral limb movements in sleep, and less robustly for night shift work and restless leg syndrome to be associated with increased risk of lung cancer development, with potential impacts on cancer survival outcomes. Proposed mechanisms underlying the biological plausibility of these epidemiological associations are also explored, with common theories relating to immune dysregulation, metabolic alterations, reductions in melatonin, sympathetic overactivation, increased reactive oxygen species, production of protumorigenic exosomes, and inflammation. We also summarized potential treatments addressing impaired sleep quality/sleep disorders and their ability to attenuate the risk of lung cancer and improve cancer survival. Although evidence on reversibility is inconsistent, there are trends toward positive outcomes. Future research should focus on clinical trials to confirm cause and effect relationships, large epidemiologic studies for incidence/prognosis, clarification on the relative efficacy of treatment modalities, and more in vivo animal models to establish the molecular mechanisms underlying these relationships.

Sleep health among sexual and gender minority people in the United States: A scoping review

Sleep has been found to be essential to physical and mental health. Sexual and gender minority (SGM; e.g., lesbian, gay, bisexual, transgender, nonbinary) individuals experience significant health disparities, and emerging research indicates that this includes disparities in sleep health. However, the current literature on sleep health in this population has not previously been rigorously reviewed. This scoping review provides a comprehensive overview and synthesis of the current literature on SGM sleep health in the United States. Following established scoping review methodology, we systematically searched PubMed, CINAHL, PsycINFO, LGBTQ + Source, and Scopus; 76 studies met inclusion criteria. Included studies indicated significant sleep disparities exist for SGM people, particularly sexual minority women and gender minority people. Social determinants of health, including bullying and discrimination, were associated with worse sleep health. Included studies were heterogeneous and had methodological weaknesses, leaving opportunities for future research. Overall, findings point to the need for more rigorous research to advance understanding of sleep health across SGM subgroups and inform interventions to improve sleep health among SGM people, given the known negative impact of poor sleep on overall health.

Association of sleep quality and its change with the risk of depression in middle-aged and elderly people: A 10-year cohort study from England

BACKGROUND

Persistently poor sleep quality in young adults is linked to a higher risk of depression. However, the impact of changes in sleep quality on depression risk in middle-aged and older adults remain unclear. This study investigates the association between sleep quality, its changes, and the risk of depression in middle-aged and elderly people.

METHODS

We included 4007 participants (mean age 63.0 ± 7.6 years, 53.0 % women) from the English Longitudinal Study of Ageing. Sleep quality was assessed using the Jenkins Sleep Problems Scale and a global sleep quality question. Depression was evaluated with the Center for Epidemiological Studies Depression Scale and self-reported doctor-diagnosed depression. Multivariable logistic regression, restricted cubic spline curve, and mediation analysis was employed.

RESULTS

After 10 years of follow-up, 777 individuals developed depression. Sleep quality scores positively correlated with depression risk. Among those with good sleep quality, worsening sleep quality increased depression risk (OR = 1.67, 95 % CI: 1.21-2.31). For those with intermediate sleep quality, improved sleep quality reduced depression risk (OR = 0.70, 95 % CI: 0.50-0.98). Conversely, worsening sleep quality increased depression risk (OR = 2.11, 95 % CI: 1.47-3.02). Pain and functional disability partially mediated the association between intermediate/poor sleep quality and depression (9.8 % and 4.2 %, respectively).

LIMITATIONS

Sleep quality is based on self-reported.

CONCLUSIONS

Intermediate, poor, and worsening sleep quality are linked to higher depression risk. Improving sleep quality mitigates depression risk in those with intermediate sleep quality. Sleep quality may influence depression indirectly through pain and functional disability.

A Multimodal Sleep Foundation Model Developed with 500K Hours of Sleep Recordings for Disease Predictions

Sleep is a fundamental biological process with profound implications for physical and mental health, yet our understanding of its complex patterns and their relationships to a broad spectrum of diseases remains limited. While polysomnography (PSG), the gold standard for sleep analysis, captures rich multimodal physiological data, analyzing these measurements has been challenging due to limited flexibility across recording environments, poor generalizability across cohorts, and difficulty in leveraging information from multiple signals simultaneously. To address this gap, we curated over 585,000 hours of high-quality sleep recordings from approximately 65,000 participants across multiple cohorts and developed SleepFM, a multimodal sleep foundation model trained with a novel contrastive learning approach, designed to accommodate any PSG montage. SleepFM produces informative sleep embeddings that enable predictions of future diseases. We systematically demonstrate that SleepFM embeddings can predict 130 future diseases, as modeled by Phecodes, with C-Index and AUROC of at least 0.75 on held-out participants (Bonferroni-corrected p < 0.01). This includes accurate predictions for death (C-Index: 0.84 [95% CI: 0.81-0.87]), heart failure (C-Index: 0.80 [95% CI: 0.77-0.83]), chronic kidney disease (C-Index: 0.79 [95% CI: 0.77-0.81]), dementia (C-Index: 0.85 [95% CI: 0.82-0.87]), stroke (C-Index: 0.78 [95% CI: 0.76-0.81]), atrial fibrillation (C-Index: 0.78 [95% CI: 0.75-0.81]), and myocardial infarction (C-Index: 0.81 [95% CI: 0.78-0.84]). The model's generalizability was further validated through strong performance on the Sleep Heart Health Study (SHHS), a dataset unseen during pre-training. Additionally, SleepFM demonstrates strong performance on traditional sleep analysis tasks, achieving competitive results in both sleep staging (mean F1 scores: 0.70-0.78) and sleep apnea diagnosis (AUROC: 0.90-0.94). Beyond these standard applications, our analysis reveals that specific sleep stages and physiological signals carry distinct predictive power for different diseases. This work demonstrates how foundation models can leverage sleep polysomnography data to uncover the extensive relationship between sleep physiology and future disease risk.

Sleep Pattern, Lifestyle Pattern, and Risks of Overall and 20 Types of Cancers: Findings From the UK Biobank Cohort

Objectives

Sleep health and other lifestyle behaviours are gaining increasing attention in public health, particularly for cancer prevention, but a comprehensive assessment is lacking.

Methods

The study included 380,042 UK Biobank participants. A healthy sleep score was constructed based on five sleep factors: chronotype, sleep duration, insomnia, snoring, and daytime dozing. A healthy lifestyle score was constructed based on four lifestyle factors: smoking, alcohol consumption, diet and physical activity. The effect of healthy sleep and lifestyle on cancer risk was examined by Cox proportional hazard models.

Results

Both healthy sleep and lifestyle patterns were significantly associated with a reduced risk of overall cancer and specific cancer sites. Participants with healthy sleep and lifestyle patterns had a lower risk of overall cancer (HR = 0.72, 95% CI = 0.68-0.77), liver cancer (HR = 0.53, 95% CI = 0.31-0.90), bladder cancer (HR = 0.61, 95% CI = 0.47-0.79), lung cancer (HR = 0.22, 95% CI = 0.19-0.27), and colorectal cancer (HR = 0.80, 95% CI = 0.66-0.96) compared to those with unhealthy patterns.

Conclusion

Our findings highlight the importance of public health education and interventions to improve sleep and other lifestyle behaviours for cancer prevention.

A web-based tool for cancer risk prediction for middle-aged and elderly adults using machine learning algorithms and self-reported questions

BACKGROUND

From a global perspective, China is one of the countries with higher incidence and mortality rates for cancer.

OBJECTIVE

Our objective is to create an online cancer risk prediction tool for middle-aged and elderly Chinese adults by leveraging machine learning algorithms and self-reported data.

METHOD

Drawing from a cohort of 19,798 participants aged 45 and above from the China Health and Retirement Longitudinal Study (2011 - 2018), we employed nine machine learning algorithms (LR: Logistic Regression, Adaboost: Adaptive Boosting, SVM: Support Vector Machine, RF: Random Forest, GNB: Gaussian Naive Bayes, GBM: Gradient Boosting Machine, LGBM: Light Gradient Boosting Machine, XGBoost: eXtreme Gradient Boosting, KNN: K - Nearest Neighbors), which are mainly used for classification and regression tasks, to construct predictive models for various cancers. Utilizing non-invasive self-reported predictors encompassing demographic, educational, marital, lifestyle, health history, and other factors, we focused on predicting "Cancer or Malignant Tumour" outcomes. The types of cancers that can be predicted mainly include lung cancer, breast cancer, cervical cancer, colorectal cancer, gastric cancer, esophageal cancer, and other rare cancers.

RESULTS

The developed tool, MyCancerRisk, demonstrated significant performance, with the Random Forest algorithm achieving an AUC of 0.75 and ACC of 0.99 using self-reported variables. Key predictors identified include age, self-rated health, sleep patterns, household heating sources, childhood health status, living conditions, and smoking habits.

CONCLUSION

MyCancerRisk aims to serve as a preventative screening tool, encouraging individuals to undergo testing and adopt healthier behaviours to mitigate the public health impact of cancer. Our study also sheds light on unconventional predictors, such as housing conditions, offering valuable insights for refining cancer prediction models.

Sleep quality and incident hypertension

INTRODUCTION AND OBJECTIVES

Poor sleep quality poses significant public health challenges worldwide. This study aimed to investigate the association between sleep quality and the risk of hypertension.

METHODS

The study analyzed 284 250 adults from the UK Biobank (UKB) and 6104 participants from the English Longitudinal Study of Ageing (ELSA) without hypertension at baseline. The exposure of interest was sleep quality, which was evaluated based on questionnaires. Participants were divided into 3 groups based on the assessment of sleep quality. Sleep duration was assessed by self-reported sleep hours by each participant. The primary endpoint was new onset hypertension.

RESULTS

In the UKB cohort, participants with poor sleep quality showed a significantly higher risk of hypertension than those with healthy sleep quality (HR, 1.277; 95%CI, 1.21-1.346]. The results from the ELSA cohort effectively validated those from the UKB cohort; participants with poor sleep quality had a notably heightened risk of hypertension (HR, 1.264; 95%CI, 1.02-1.566). Prolonging sleep duration was associated with a decrease in the risk of hypertension in individuals with intermediate or healthy sleep quality. Although several factors were independently associated with a lower risk of hypertension (P<.001), the association between sleep quality and an increased risk of hypertension remained significant regardless of genetic susceptibility to hypertension (P for interaction=.067).

CONCLUSIONS

Considering the genetic predisposition to hypertension, poor sleep quality is associated with an elevated risk of hypertension. In intermediate or healthy levels of sleep quality, prolonging sleep duration is linked to a reduced risk of hypertension.

Development and validation of a nomogram for predicting the risk of developing gastric cancer based on a questionnaire: a cross-sectional study

Background

Detection of gastric cancer (GC) at early stages is an effective strategy for decreasing mortality. This study aimed to construct a prediction nomogram based on a questionnaire to assess the risk of developing GC.

Methods

Our study comprised a total of 4379 participants (2326 participants from outpatient at Fengqing People's Hospital were considered for model development and internal validation, and 2053 participants from outpatients at the endoscopy center at the Seventh Affiliated Hospital of Sun Yat-Sen University were considered for independent external validation) and gastric mucosa status was determined by endoscopy and biopsies. The eligible participants in development cohort from Fengqing people's Hospital were randomly separated into a training cohort (n=1629, 70.0%) and an internal validation cohort (n=697, 30.0%). The relevant features were selected by a least absolute shrinkage and selection operator (LASSO), and the ensuing features were evaluated through multivariable logistic regression analysis. Subsequently, the variables were selected to construct a prediction nomogram. The discriminative ability and predictive accuracy of the nomogram were evaluated by the C-index and calibration plot, respectively. Decision curve analysis (DCA) curves were used for the assessment of clinical benefit of the model. This model was developed to estimate the risk of developing neoplastic lesions according to the "transparent reporting of a multivariable prediction model for individual prognosis or diagnosis" (TRIPOD) statement.

Results

Six variables, including age, sex, alcohol consumption, cigarette smoking, education level, and Hp infection status, were independent risk factors for the development of neoplastic lesions. Thus, these variables were incorporated into the final nomogram. The AUC of the nomogram were 0.701, 0.657 and 0.699 in the training, internal validation, and external validation cohorts, respectively. The calibration curve showed that the nomogram was in good agreement with the observed outcomes. Compared to treatment of all patients or none, our nomogram showed a notably higher clinical benefit.

Conclusion

This nomogram proved to be a convenient, cost-effective tool to effectively predict an individual's risk of developing neoplastic lesions, and it can act as a prescreening tool before gastroscopy.

Feasibility and Acceptability Evaluation of a Digital Therapeutic Program for Improving Cancer Prevention: A Quasi-experimental Pre-post Interventional Pilot Study

Previous studies have proved that healthy behaviors hinder the onset and progression of tumors. Digital therapeutics (DTx), playing a pivotal role in facilitating behavioral adjustments through educational interventions, lifestyle support, and symptom monitoring, contribute to the goal of tumor prevention. We aim to optimize the evaluation of the feasibility and acceptability of DTx for cancer prevention. This involves assessing AITI's daily activity rates and user feedback, and comparing changes in behavioral habits and differences in SF-36 before and after the intervention. In a 4-week trial with 57 participants engaging actively, we found both the average daily activity rate and 4-week retention rate at 35 (61.4%). The USE Questionnaire scores (validity, ease of use, acquisition, and satisfaction) ranged from 68.06 to 83.10, indicating AITI's user-friendliness and acceptability. Furthermore, positive habit changes were noted among participants in exercise and diet (p < 0.0001), suggesting the effectiveness of the DTx approach in modifying behavioral habits related to physical activity and nutrition. This pilot study underscores the potential of DTx in advancing cancer prevention. However, larger and longer studies are needed to comprehensively assess its impact.

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis

BACKGROUND

Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers).

METHODS

Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs).

RESULTS

Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01).

CONCLUSIONS

Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Cancer Prevention Among Firefighters: Examining Lifestyle, Screening Behavior, and Beliefs

BACKGROUND

Firefighters are at increased risk of developing cancer due to occupational exposures, but they may also face increased risk due to their lifestyle, such as the quality of their diet and physical activity. Cancer beliefs and screening behavior could also influence their cancer risk. The current study aimed to identify individual differences associated with lifestyle behaviors, cancer screening, and cancer beliefs among firefighters; to describe the strategies firefighters use to adapt to their work schedule; and to describe topics firefighters believe are the most important to address in their workplace.

METHODS

Career firefighters (N = 171) in a medium-sized U.S. city completed an online survey.

FINDINGS

Logistic regression analyses identified age, education, racial identity, years of fire service, perceived stress, and rank as predictors of responses to items addressing cancer screening, lifestyle behaviors, and cancer beliefs. Although results varied, age, education, and racial identity were associated with most of the outcomes. Strategies related to sleep such as getting the right amount and napping, exercise, and getting family/roommate support were selected as the top adaptive strategies for work. Sleep, mental health/well-being, and work-life balance were selected most often as the most important topics to address in the fire service, with topics related to reducing occupational exposures receiving less attention.

CONCLUSIONS/APPLICATION TO PRACTICE

The findings suggest individual differences, such as age, education, and racial identity, should be considered when developing occupational health interventions for firefighters. Interventions related to mental health, work-life balance, and sleep may be desired most by those in the fire service.

Sleep and Oxidative Stress: Current Perspectives on the Role of NRF2

Sleep is a fundamental conserved physiological state across evolution, suggesting vital biological functions that are yet to be fully clarified. However, our understanding of the neural and molecular basis of sleep regulation has increased rapidly in recent years. Among various processes implicated in controlling sleep homeostasis, a bidirectional relationship between sleep and oxidative stress has recently emerged. One proposed function of sleep may be the mitigation of oxidative stress in both brain and peripheral tissues, contributing to the clearance of reactive species that accumulate during wakefulness. Conversely, reactive species, such as reactive oxygen species (ROS) and reactive nitrogen species (RNS), at physiological levels, may act as signaling agents to regulate redox-sensitive transcriptional factors, enzymes, and other effectors involved in the regulation of sleep. As a primary sensor of intracellular oxidation, the transcription factor NRF2 is emerging as an indispensable component to maintain cellular redox homeostasis during sleep. Indeed, a number of studies have revealed an association between NRF2 dysfunction and the most common sleep conditions, including sleep loss, obstructive sleep apnea, and circadian sleep disturbances. This review examines the evidence of the intricate link between oxidative stress and NRF2 function in the context of sleep, and highlights the potential of NRF2 modulators to alleviate sleep disturbances.

Sleep and liver function biomarkers in relation to risk of incident liver cancer: a nationwide prospective cohort study

BACKGROUND

To assess the largely undetermined separate and joint effects of sleep and liver function biomarkers on liver cancer.

METHODS

Data of 356,894 participants without cancer at baseline in the UK Biobank were analyzed. Sleep score was evaluated using five sleep traits (sleep duration, chronotype, insomnia, snoring, and excessive daytime sleepiness) and dichotomized into healthy or unhealthy sleep. Circulating liver function biomarkers were measured. Cox proportional hazard model was performed to investigate the independent and joint associations of sleep and liver function biomarkers with liver cancer incidence.

RESULTS

After a median follow-up time of 13.1 years, 394 cases of incident liver cancer were documented. The multivariable-adjusted hazard ratio (HR) for liver cancer was 1.46 (95% confidence interval: 1.15-1.85) associated with unhealthy sleep (vs. healthy sleep), and was 1.17 (1.15-1.20), 1.20 (1.18-1.22), 1.69 (1.47-1.93), 1.06 (1.06-1.07), 1.08 (1.07-1.09), 1.81 (1.37-2.39), or 0.29 (0.18-0.46) associated with each 10-unit increase in alanine transaminase (ALT), aspartate transaminase (AST), total bilirubin (TBIL), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), total protein (TP), or albumin (ALB), respectively. Individuals with unhealthy sleep and high (≥ median) ALT, AST, TBIL, GGT, ALP, or TP or low (< median) ALB level had the highest HR of 3.65 (2.43-5.48), 4.03 (2.69-6.03), 1.97 (1.40-2.77), 4.69 (2.98-7.37), 2.51 (1.75-3.59), 2.09 (1.51-2.89), or 2.22 (1.55-3.17) for liver cancer, respectively. Significant additive interaction of unhealthy sleep with high TP level on liver cancer was observed with relative excess risk due to an interaction of 0.80 (0.19-1.41).

CONCLUSIONS

Unhealthy sleep was associated with an increased risk of liver cancer, especially in participants with lower ALB levels or higher levels of ALT, AST, TBIL, GGT, ALP, or particularly TP.

Sleep fragmentation induces heart failure in a hypertrophic cardiomyopathy mouse model by altering redox metabolism

Sleep fragmentation (SF) disrupts normal biological rhythms and has major impacts on cardiovascular health; however, it has never been shown to be a risk factor involved in the transition from cardiac hypertrophy to heart failure (HF). We now demonstrate devastating effects of SF on hypertrophic cardiomyopathy (HCM). We generated a transgenic mouse model harboring a patient-specific myosin binding protein C3 (MYBPC3) variant displaying HCM, and measured the progression of pathophysiology in the presence and absence of SF. SF induces mitochondrial damage, sarcomere disarray, and apoptosis in HCM mice; these changes result in a transition of hypertrophy to an HF phenotype by chiefly targeting redox metabolic pathways. Our findings for the first time show that SF is a risk factor for HF transition and have important implications in clinical settings where HCM patients with sleep disorders have worse prognosis, and strategic intervention with regularized sleep patterns might help such patients.

Global prevalence of poor sleep quality in cancer patients: A systematic review and meta-analysis

OBJECTIVE

Poor sleep quality is common in patients with cancer, but the prevalence rates varied widely across studies. This systematic review and meta-analysis examined the pooled prevalence of poor sleep quality among patients with cancer.

METHODS

Systematic literature searches were independently conducted in the major databases (Web of Science, PubMed, EMBASE and PsycINFO). Studies that reported the prevalence of poor sleep quality in patients with cancer were analyzed using a random effects model. Funnel plots and Egger's tests were used to assess publication bias. Statistical analyses were performed using R software.

RESULTS

A total of 59 epidemiological studies involving 16,223 patients were included. The pooled prevalence of poor sleep quality in patients with cancer was 57.4% [95% confidence interval (CI): 53.3% - 61.6%]. Additionally, three comparative studies with 372 patients and 412 healthy controls were included. Compared to healthy controls, patients with cancer had a significantly higher risk for poor sleep quality [odd ratio (OR) = 3.0; 95%CI: 1.2-7.2; P < 0.05]. Subgroup analyses of the studies revealed that studies from Middle East & North Africa region and low income countries, and on gynecological cancer as well as those with a lower cut-off value of sleep quality (all P < 0.01) reported a higher prevalence of poor sleep quality. Meta-regression analyses showed that higher prevalence of poor sleep quality was associated with higher prevalence of comorbid depression (P < 0.05) and anxiety (P < 0.01), but was associated with a lower education level (P < 0.05) and alcohol use ratio (P < 0.05).

CONCLUSION

Poor sleep quality is common among patients with cancer. Considering the overall high prevalence rate and negative impact of poor sleep quality, appropriate measures to identify and improve poor sleep quality are needed to enhance the clinical outcomes in this group.

Poor Sleep Quality and Its Influencing Factors Among Iranian Patients with Esophageal and Gastric Cancer

Background

Sleep quality is a notable factor of well-being. It also may play a role in the development and progression of chronic diseases and cancers. Therefore, this study was performed to investigate poor sleep quality and its influencing factors among Iranian patients with esophageal and gastric cancer.

Methods

In this cross-sectional study, a total of 312 Iranian adult patients who suffered from esophageal and gastric cancers were employed from a gastrointestinal cancer-based cohort study conducted in a referral hospital in Tehran between 2015 and 2018. Persian version of the Pittsburg Sleep Quality Index (PSQI) was used to measure poor sleep quality. Univariate and multiple logistic regression models were applied to determine the related factors to poor sleep quality.

Results

Of the participants, 203 (65.06%) were men, and 75.96% had gastric cancer. The mean age was 63.13±12.10 years. The results demonstrated that more than 62% of the patients had poor sleep quality. 148 (62.44%) patients out of 237 patients with gastric cancer had poor-quality sleep. Also, 46 (64.38%) patients out of 237 patients with esophageal cancer had poor-quality sleep. Based on the results of multiple logistic regression models, marital status has a negative association with poor sleep quality (odds ratio [OR]=0.32, P=0.015). In addition, having chronic disease (OR=2.16; P=0.028) and wealth index (OR=3.11, P=0.013; OR=3.81, P=0.003; OR=3.29, P=0.009; OR=3.85, P=0.003 for rich, moderate, poor, and poorest subgroups, respectively) had a positive association with poor sleep quality.

Conclusion

The findings showed that about two-thirds of the patients studied were poor sleepers. Also, it was observed that marital status, chronic disease, and wealth index were important factors associated with poor sleep quality.

Poor sleep quality association with higher lung cancer risk: a nested case-control study

Background

Little is known about the relationship between sleep quality and lung cancer incidence. Thus, this study was conducted to investigate the potential connection between sleep quality and lung cancer incidence.

Methods

We performed and selected a nested case-control study that included 150 lung cancer cases and 150 matched controls based on the Lianyungang cohort. Univariate and multivariate logistic regression was utilized to investigate the connection between potential risk factors and lung cancer incidence risk.

Results

In this study, the average age of participants was 66.5 ± 9.1 years, with 58.7% being male, and 52.7% reportedly experiencing sleep quality problems. The results of multivariate logistic regression showed that poor sleep quality was connected to an increased lung cancer incidence risk (P = 0.033, odds ratio = 1.83, 95% confidence interval = [1.05-3.19]) compared with those with good sleep quality. The stratified analyses showed a significantly positive connection between poor sleep quality (vs. good sleep quality) and cancer risk in smokers (vs. non-smoker, P for interaction = 0.085). The combined effect analysis indicated that smokers with poor sleep quality suffered from a 2.79-fold increase in cancer incidence rates when compared with non-smokers with good sleep quality.

Conclusions

Poor sleep quality was positively connected to an increased lung cancer incidence risk. In addition, among those individuals with poor sleep quality, smoking increased the lung cancer incidence risk.

The chain mediation model of social support and life satisfaction among migrant older adults with children: The role of mental health and sleep quality

INTRODUCTION

Few studies have examined the life satisfaction of migrant older adults with children (MOAC), who emerged due to rapid urbanization and population aging in China. This study aimed to explore the chain mediating effect of mental health and sleep quality on the association between social support and life satisfaction among MOAC in Weifang, China.

METHODS

A cross-sectional study was conducted using multi-stage cluster random sampling, and 613 participants were included. The Social Support Rating Scale, Depression Anxiety Stress Scale, Pittsburgh Sleep Quality Index, and Scale with Life Satisfaction were used to measure the social support, mental health, sleep quality, and life satisfaction of MOAC, respectively. Descriptive statistics, t-tests, and ANOVA were used to explore the relationship between sociodemographic variables and life satisfaction. Pearson's correlation analysis and structural equation modeling (SEM) were conducted to investigate the association between social support, mental health, sleep quality, and life satisfaction.

RESULTS

The mean total SWLS score was 27.87±5.58. SEM analysis demonstrated that social support had a positive effect on life satisfaction (β= 0.197). Mental health and sleep quality partially mediated the association between social support and life satisfaction (95% CI: 0.083-0.193), and the mediating effect accounted for 39.198% of the total effect.

CONCLUSION

Life satisfaction was relatively high, and mental health and sleep quality partially mediated the association between social support and life satisfaction. Policy suggestions were provided based on these results.

Fatigue and fallibility: the perils of prolonged shifts for neonatologists

Sleep deprivation is a major challenge for neonatologists, who face increasing demands in the complex healthcare system. Current neonatal intensive care unit (NICU) schedule models often include extended shifts and overnight call, which can lead to sleep deprivation. This lack of sufficient sleep poses adverse health risks to neonatologists and can impair cognitive function, which increases the risk of medical errors and compromises patient safety. This paper proposes reducing shift durations and implementing policies and interventions to reduce fatigue among neonatologists and improve patient safety. The paper also offers policymakers, healthcare leaders, and NICU physicians valuable insights on potential ways to promote the health of the neonatologist workforce and safety in the NICU.

Bidirectional Associations Between Sleep Quality and Grip Strength and the Mediating Role of Depression: Evidence From Two Nationally Representative Cohorts

BACKGROUND

Although studies have demonstrated associations between sleep quality (SQ) and grip strength (GS) in older adults, the direction and underlying mechanisms of this relationship are yet to be better delineated. We aimed to longitudinally investigate the bidirectional association between SQ and GS and the mediating role of depression in this association.

METHODS

Based on 2 nationally representative samples with people aged ≥50 years from the China Health and Retirement Longitudinal Study (CHARLS; 4 200 participants) and English Longitudinal Study of Ageing (ELSA; 5 922 participants), cross-lagged panel models were employed to examine the potential bidirectional relationships between objectively measured GS and self-reported SQ.

RESULTS

We observed a GS-SQ bidirectional association dominated by GS. After adjusting for potential confounders, a higher GS at T1 predicted better SQ at T2 (ELSA: β = 0.075; CHARLS: β = 0.104, p < .001) and vice versa (ELSA: β = 0.034; CHARLS: β = 0.030, p < .01). Moreover, depression partially mediated the impact of GS on subsequent SQ (ELSA, indirect effect: 0.0057, 95% confidence interval [CI]: 0.0035-0.0084; CHARLS, indirect effect: 0.0086, 95% CI: 0.0051, 0.0131), but not vice versa.

CONCLUSIONS

The results regarding data from both cohorts consistently supported a bidirectional association between GS and SQ and the mediating role of depression in the dominant pathway of this bidirectional relationship. Older adults with a low GS should be made aware of a potentially vicious cycle related to depression that can affect their sleep. Regular screening for depression may help to break this cycle.

Serial multiple mediation of loneliness and depressive symptoms in the relationship between pain and cognitive function among older people

OBJECTIVES

Although the negative effect of pain on cognitive function has been widely reported, it is unclear how the effect is mediated. The aim of this study is to analyze the mediating role of loneliness and depressive symptoms in the association between pain and cognitive function.

METHODS

A total of 6,309 participants aged ≥50 years from 2012/13 (T1), 2014/15 (T2), 2016/17 (T3) and 2018/19 (T4) of the English Longitudinal Study of Aging (ELSA) were included. Of them, 55.8% were females, and the median age (rang) was 65 (50-99) years at T1. Serial mediation analysis was performed using Mplus 8.3.

RESULTS

The mediation model explained 10.1% of the variance in loneliness, 22.1% of the variance of depressive symptoms, and 22.7% of the variance of cognitive function. Higher level pain was associated with poorer cognitive function (c: β = -0.057; p < 0.001). The negative effect of pain on cognition was mediated separately and sequentially through loneliness and depressive symptoms, with loneliness and depressive symptoms explaining 8.8% of the total effect, respectively, and the pathway of loneliness and subsequent depression explaining 1.8%.

CONCLUSIONS

Diversified interventions aimed at treating pain in older adults would be beneficial for their mental health and cognitive function.

Association of plant-based diet index with sleep quality in middle-aged and older adults: The Healthy Dance Study

OBJECTIVES

To investigate the association between plant-based diet indices and sleep quality in Chinese middle-aged and older adults.

METHODS

The study included 2424 participants aged 45 years and older. Dietary data were collected using a semi-quantitative food frequency questionnaire, and sleep quality was assessed by the Pittsburgh Sleep Quality Index scale. Plant-based diet was categorized based on 3 indices (score range, 17-85) covering 17 food groups: the overall plant-based diet index, healthful plant-based diet index, and unhealthful plant-based diet index. The associations between these plant-based diet indices and sleep quality were examined using logistic and linear regression analyses.

RESULTS

After controlling for sociodemographic, lifestyle, and multiple disease-related factors, participants in the highest quartile of the healthful plant-based diet index had 0.55 higher odds of better sleep quality (95% CI: 0.42, 0.72; Ptrend< .001). In contrast, participants in the highest quartile of the unhealthful plant-based diet index had 2.03 higher odds of poor sleep quality (95% CI: 1.51, 2.72; Ptrend< .001). In addition, plant-based diet index and healthful plant-based diet index were inversely associated with Pittsburgh Sleep Quality Index scores, while unhealthful plant-based diet index and Pittsburgh Sleep Quality Index scores were positively associated.

CONCLUSIONS

We found unhealthy plant-based diets are significantly associated with poor sleep quality. Adherence to overall plant-based diets, especially healthy plant-based diets, was positively associated with optimal sleep quality.

Association of sleep quality, its change and sleep duration with the risk of type 2 diabetes mellitus: Findings from the English longitudinal study of ageing

AIMS

This study aimed to evaluate the association of sleep quality and its long-term change with the risk of type 2 diabetes mellitus (T2DM) and to assess the relationship between sleep duration and the risk of T2DM according to categories of sleep quality.

MATERIALS AND METHODS

5728 participants free of T2DM at wave 4 from the English Longitudinal Study of Ageing were included and received a follow-up with a median time of 8 years. We created a sleep quality score to evaluate sleep quality, which was based on three Jenkins Sleep Problems Scale questions (the frequency of feeling hard to fall asleep, waking up at night, and feeling tired in the morning) and one question for rating overall sleep quality. Participants were allocated into three groups according to their baseline sleep quality scores (groups of good [4-8], intermediate [8-12], and poor quality [12-16]). Sleep duration was assessed by a self-reporting sleep hours from each participant.

RESULTS

411 (7.2%) T2DM cases were documented during the follow-up. Compared with the good quality group, subjects with poor sleep quality showed a significantly higher risk of T2DM (hazard ratio (HR) 1.45, confidence interval (CI) 1.09, 1.92). In participants with good baseline sleep quality, those who experienced worsened sleep quality showed a significantly increased T2DM risk (HR 1.77, 95% CI 1.26, 2.49). Type 2 diabetes mellitus risk was not changed regardless of sleep duration in subjects with good quality. Short sleep duration (≤4h) was associated with an elevated T2DM risk in participants with intermediate sleep quality, and both short (≤4h) and prolonged sleep time (≥9h) were associated with an increased T2DM risk in the poor sleep quality group.

CONCLUSIONS

Poor sleep quality is correlated with an increase in T2DM risk, and regulating sleep quality to a good range could potentially be an effective approach for preventing T2DM.

Dietary insulinemic potential, sleep quality and quantity in Iranian adults: Yazd health study and TAMYZ study

BACKGROUND & AIMS

To examine the link between dietary insulin index (DII) and load (DIL) and sleep duration/quality for the first time.

METHODS

This cross-sectional study conducted on data from the recruitment phase of Yazd Health Study (YaHS)-Yazd Nutrition Study (TAMYZ), prospective study in Yazd, central Iran. Data on demographic characteristics, dietary intakes, sleep quantity and quality, and potential confounders were gathered by interview. Sleep quality and its components (insufficient sleep, delay in falling asleep, medication use for sleep, and sleep disorder) were assessed by a modified version of Pittsburgh questionnaire. The link between DII/DIL and low sleep quality and short/long sleep duration was studied using multivariable logistic regression.

RESULTS

In total, 5925 individuals aged 20 to 70 were eligible to take part in the current study. After adjustment for all potential confounders, participants in the highest DIL score tertile had a lower chance for sleep disorder (OR = 0.38; 95%CI: 0.17-0.85, Ptrend = 0.02) and delay in falling asleep (OR = 0.66; 95%CI: 0.42-1.03, Ptrend = 0.05) compared to those in the lowest tertile. The DII was also linked to a lower chance for sleep disorder (OR = 0.61; 95% CI: 0.39-0.93, P trend = 0.02). The DIL was inversely associated with sleep medication use and delay in falling sleep in men and women, respectively (P < 0.05). Moreover, DII was linked to a decreased odds of sleep disorder in women (P < 0.05). The associations were observed in those with overweight or obesity but not in those without overweight (P < 0.05).

CONCLUSION

Higher DIL and DII might be associated with sleep quality and its components. Prospective investigations are needed in the future to confirm these findings.

Tackling Insomnia Symptoms through Vestibular Stimulation in Patients with Breast Cancer: A Perspective Paper

Insomnia symptoms are common among patients with breast cancer (BC; 20-70%) and are predictors of cancer progression and quality of life. Studies have highlighted sleep structure modifications, including increased awakenings and reduced sleep efficiency and total sleep time. Such modifications may result from circadian rhythm alterations consistently reported in this pathology and known as carcinogenic factors, including lower melatonin levels, a flattened diurnal cortisol pattern, and lower rest-activity rhythm amplitude and robustness. Cognitive behavioral therapy and physical activity are the most commonly used non-pharmacological interventions to counter insomnia difficulties in patients with BC. However, their effects on sleep structure remain unclear. Moreover, such approaches may be difficult to implement shortly after chemotherapy. Innovatively, vestibular stimulation would be particularly suited to tackling insomnia symptoms. Indeed, recent reports have shown that vestibular stimulation could resynchronize circadian rhythms and improve deep sleep in healthy volunteers. Moreover, vestibular dysfunction has been reported following chemotherapy. This perspective paper aims to support the evidence of using galvanic vestibular stimulation to resynchronize circadian rhythms and reduce insomnia symptoms in patients with BC, with beneficial effects on quality of life and, potentially, survival.

The impact of sleep quality and its change on the long-term risk of stroke in middle-aged and elderly people: Findings from the English Longitudinal Study of Ageing

OBJECTIVE

This study focused on middle-aged and elderly adults (mean age ≥60 years) in England and aimed to evaluate the impact of sleep quality and change in sleep quality on the long-term risk of stroke.

PATIENTS/METHODS

The current prospective study enrolled 6214 participants without stroke from wave 4 (2008-2009) of the English Longitudinal Study Aging (ELSA) dataset. From the ELSA questionnaires, sleep quality scores were calculated and used to evaluate the sleep quality of each participant. Cox proportional hazards regression models were used to assess the association between sleep status and stroke risk. Restricted cubic spline (RCS) was employed for the relationship between sleep quality score and the risk of stroke.

RESULTS

During the 8-year follow-up, 130 (2.1%) cases of stroke were recorded. Participants with poor baseline sleep quality had a significantly higher long-term risk of stroke compared with those with good sleep quality (hazard ratio [HR] 2.37, 95% confidence intervals [CI] 1.44, 3.91). For the influence of change in sleep quality on stroke risk, worsened sleep quality was associated with a significant increase in the risk of stroke in the good (HR 2.08, 95% CI, 1.02, 4.26) and intermediate sleep quality groups (HR 2.15, 95% CI, 1.16, 3.98). Moreover, improved sleep quality decreased stroke risk among subjects with poor sleep quality (HR 0.31, 95% CI, 0.15, 0.61).

CONCLUSIONS

Poor and worsened sleep quality is associated with an increased risk of stroke. Emphasis should be placed on improving sleep quality in middle-aged and elderly individuals.

Cancer and Potential Prevention with Lifestyle among Career Firefighters: A Narrative Review

Career firefighters are at considerable risk for chronic diseases, including an increased risk of various cancers, compared to the general population. Over the last two decades, several systematic reviews and large cohort studies have demonstrated that firefighters have statistically significant increases in overall and site-specific cancer incidence and site-specific cancer mortality compared to the general population. Exposure assessment and other studies have documented exposures to a variety of carcinogens in fire smoke and within the fire station. Other occupational factors such as shift work, sedentary behavior, and the fire service food culture may also contribute to this working population's increased cancer risk. Furthermore, obesity and other lifestyle behaviors such as tobacco use, excessive alcohol consumption, poor diet, inadequate physical activity, and short sleep duration have also been associated with an increased risk of certain firefighting-associated cancers. Putative prevention strategies are proposed based on suspected occupational and lifestyle risk factors.

Global research on cancer and sleep: A bibliometric and visual analysis of the last two decades

Objective

The study aimed to analyze the research status, hotspots, and frontiers of global research on cancer and sleep through bibliometrics and provide references and guidance for future research.

Methods

The literature regarding cancer and sleep from 2002 to 2022 was searched from the Web of Science Core Collection (WoSCC) database. CiteSpace 5.6.R3 was performed for visualization analysis.

Results

A total of 1,172 publications were identified. The number of publications in the field has gradually increased over the past two decades. The United States had the most prominent contributions. Taipei Medical University and the University of California, San Francisco, and David Gozal were the most prolific institutions and author, respectively. The most published academic journal was Supportive Care in Cancer. The research hotspots can be summarized into the symptom cluster intervention for cancer survivors and the association between cancer and melatonin and/or obstructive sleep apnea (OSA). The complex interaction between cancer and sleep disruption and the influencing factors of sleep quality may be the emerging trends of research.

Conclusion

This study systematically analyzed the hotspots and frontiers in the field of cancer and sleep and called for strengthening cooperation among countries, institutions, and authors. In addition, intervention measures for the cancer symptom cluster, the bioavailability of exogenous melatonin, the causal relationship between OSA and cancer, the mechanism of tumor-induced sleep disruption, the dose–response relationship between sleep duration and cancer risk, and the path relationship between sleep quality influencing factors may be the focus of future research.

Risk-Reducing Measures for Cancer Prevention

Cancer, or malignancy, continues to be one of the most serious health problems in the world, leading to death and disability. Unlike in previous years, where new cases of cancer were predominant in developed nations, the number of cases of cancer and the resultant deaths are increasing in low- and middle-income countries. This is partially attributable to the current trend of adopting a Western lifestyle, substantial urbanization, and the rise in infections, such as the human papillomavirus (HPV) and hepatitis B virus (HBV), which together account for over 30% of cancer cases in underdeveloped and developing nations. The deleterious impact of cancer, as cases multiply worldwide, is multi-dimensional. Cancer exerts serious physical, psychological, and monetary burdens, not only on cancer patients but also on their family members, close friends, health care systems, and society at large. Importantly, over half of all cancer types can be prevented globally by mitigating the risk and causative factors as well as prompt adherence to scientifically recommended prevention measures. This review provides various scientifically based and people-centered strategies that every individual could adopt to reduce their risk of developing cancer in the future. It is recommended that, for these cancer prevention strategies to be effective, there should be a strong political will from the governments of individual countries to enact specific laws and implement policies that will significantly reduce sedentary lifestyles and unhealthy eating among the general public. Likewise, HPV and HBV vaccines, as well as cancer screenings, should be made available, affordable, and accessible on a timely basis for those who are eligible to take them. Finally, intensified campaigns and numerous informative and educational programs that promote cancer prevention should be initiated globally.

How Are You Sleeping? Why Nutrition Professionals Should Ask Their Patients About Sleep Habits

Current literature has identified relationships among sleep, nutrition, and diet-related chronic diseases; however, knowledge about how sleep influences diet-related diseases is lacking in dietetics practice. This narrative review briefly explains sleep physiology and outlines the relationships between sleep duration and quality and common nutrition-related diseases, including obesity, diabetes, cardiovascular disease, obstructive sleep apnea, and cancer. Additionally, the review discusses how sleep influences wound healing and pregnancy outcomes and why hospitalized patients are likely to experience sleep problems. Plausible mechanisms explaining the relationships between sleep and disease are presented. Finally, commonly used sleep assessment tools and interventions are reviewed. Given the importance of sleep to health, dietitians should not only be aware of the role sleep plays in disease development and prevention but also assess sleep when feasible and refer patients and clients who are at high risk for sleep problems to a sleep clinic or community program that can address sleep issues.Teaching points:Sleep duration and quality influence risk and outcomes of common nutrition-related diseases.Sleep health evaluation is a missing piece in dietetic practice.There are easy-to-use, validated tools that dietitians can use to screen for sleep problems in order to refer patients and clients to sleep experts.

Sleep Fragmentation Accelerates Carcinogenesis in a Chemical-Induced Colon Cancer Model

Aims of this study were to test whether sleep fragmentation (SF) increased carcinogenesis and to investigate the possible mechanisms of carcinogenesis in a chemical-induced colon cancer model. In this study, eight-week-old C57BL/6 mice were divided into Home cage (HC) and SF groups. After the azoxymethane (AOM) injection, the mice in the SF group were subjected to SF for 77 days. SF was accomplished in a sleep fragmentation chamber. In the second protocol, mice were divided into 2% dextran sodium sulfate (DSS)-treated, HC, and SF groups and were exposed to the HC or SF procedures. Immunohistochemical and immunofluorescent stainings were conducted to determine the level of 8-OHdG and reactive oxygen species (ROS), respectively. Quantitative real-time polymerase chain reaction was used to assess the relative expression of inflammatory and ROS-generating genes. The number of tumors and average tumor size were significantly higher in the SF group than in the HC group. The intensity (%) of the 8-OHdG stained area was significantly higher in the SF group than in the HC group. The fluorescence intensity of ROS was significantly higher in the SF group than the HC group. SF accelerated cancer development in a murine AOM/DSS-induced model of colon cancer, and the increased carcinogenesis was associated with ROS- and oxidative stress-induced DNA damage.

Analysis of preoperative sleep quality and related influencing factors in cancer patients

PURPOSE

The sleep disturbance in cancer patients is more prevalent, and it significantly affects these patients' recovery after the operation. However, the clinical characteristics regarding sleep quality are scarce. This study aimed to evaluate the quality of preoperative sleep quality and its risk factors in different cancer patients requiring elective surgery.

PATIENTS AND METHODS

Cancer patients who were scheduled for elective surgery were selected. The demographic data, basic preoperative diseases, and factors related to the preoperative hospital environment were also recorded. Self-made questionnaires (such as gender, age, and personal history), and the Anxiety Self-Assessment Scale were used to assess the patient's underlying condition. The modified Pittsburgh Sleep Quality Index (PSQI) was used to evaluate the preoperative sleep status.

RESULTS

A total of 297 patients completed the investigation. The incidence of preoperative sleep disturbance in cancer patients was 47.8%. Multiple logistic regression showed that patients with PSQI ≥ 7 were associated with females (odds ratios [95% confidence intervals]): 1.815 [1.031-3.193], p = 0.039), and the ward space was confined (3.127 [1.016-9.625], p = 0.047), which increased the possibility of sleep disturbance in cancer patients. Meanwhile, increased anxiety levels (1.323 [1.261-1.439], p < 0.001) significantly increased the likelihood of sleep disorders in cancer patients.

CONCLUSION

47.8% of sleep disturbance in cancer patients before surgery. Female patients, preoperative anxiety, and confined ward environment were independent risk factors of subjective sleep disturbance.

Psychosocial stress and cancer risk: a narrative review

BACKGROUND

It is unclear which psychological factors (stressors, emotional correlates, and psychophysiological markers) induce cancer risk. This currently limits the potential for prevention strategies.

PURPOSE

The aim of this review is to bring forth evidence of stress as a determinant of cancer risk from a public health perspective, written for a broad public of practitioners and scientists.

METHODS

Based on a semisystematic literature search, the impact of different aspects/types of stress and the potential physiological and behavioral pathways are summarized, while highlighting further research, public health and clinical implications.

RESULTS

Between 2007 and 2020, 65 case-control or cohort studies have been identified. Apart from overall cancer ( N = 24), 12 cancer types have been associated with psychological stress with most for breast ( N = 21), colorectal ( N = 11) and lung/prostate/pancreas cancer ( N = 8 each). Although the evidence regarding the mechanisms is still scarce, cancer development in relation to stress might be due to interacting and combined effects of different stress(or) types, but such interaction has not really been tested yet. The path from stress towards cancer incidence consists of a biological pathway with endocrinology and immunology as well as stress-induced behavioral pathways, including smoking, alcoholism, sleep disruption, an unhealthy diet, and low physical activity together with the related phenomenon of obesity.

CONCLUSION

Not only the stress but also the stress-induced lifestyle should be targeted for cancer prevention and treatment. Future research should include a more diverse spectrum of cancer types (not only hormonal related like breast cancer) and of stress measures while also considering behavioral covariates.

Effect of healthy lifestyle index and lifestyle patterns on the risk of mortality: A community-based cohort study

Background

Limited evidence was available on the association of the integrated effect of multidimensional lifestyle factors with mortality among Chinese populations. This cohort study was to examine the effect of combined lifestyle factors on the risk of mortality by highlighting the number of healthy lifestyles and their overall effects.

Methods

A total of 11,395 participants from the Guangzhou Heart Study (GZHS) were followed up until 1 January 2020. Individual causes of death were obtained from the platform of the National Death Registry of China. The healthy lifestyle index (HLI) was established from seven dimensions of lifestyle, and lifestyle patterns were extracted from eight dimensions of lifestyle using principal component analysis (PCA). Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated using the Cox proportional hazard regression model.

Results

During 35,837 person-years of follow-up, 184 deaths (1.61%) were observed, including 64 from cardiovascular disease. After adjustment for confounders, HLI was associated with a 50% (HR: 0.50, 95% CI: 0.25–0.99) reduced risk of all-cause mortality when comparing the high (6–7 lifestyle factors) with low (0–2 lifestyle factors) categories. Three lifestyle patterns were defined and labeled as pattern I, II, and III. Lifestyle pattern II with higher factor loadings of non-smoking and low-level alcohol drinking was associated with a decreased risk of all-cause mortality (HR: 0.63, 95% CI: 0.43–0.92, P_–trend = 0.023) when comparing the high with low tertiles of pattern score, after adjustment for confounders. Every 1-unit increment of pattern II score was associated with a decreased risk (HR: 0.97, 95% CI: 0.95–0.99) of all-cause mortality. The other two patterns were not associated with all-cause mortality, and the association of cardiovascular mortality risk was observed with neither HLI nor any lifestyle pattern.

Conclusion

The results suggest that the more dimensions of the healthy lifestyle the lower the risk of death, and adherence to the lifestyle pattern characterized with heavier loading of non-smoking and low-level alcohol drinking reduces the risk of all-cause mortality. The findings highlight the need to consider multi-dimensional lifestyles rather than one when developing health promotion strategies.

Healthy Sleep Every Day Keeps the Doctor Away

When one considers the big picture of their health, sufficient sleep may often go overlooked as a keystone element in this picture. Insufficient sleep in either quality or duration is a growing problem for our modern society. It is essential to look at what this means for our health because insufficient sleep increases our risks of innumerable lifechanging diseases. Beyond increasing the risk of developing these diseases, it also makes the symptoms and pathogenesis of many diseases worse. Additionally, consistent quality sleep can not only improve our physical health but has also been shown to improve mental health and overall quality of life. Substandard sleep health could be a root cause for numerous issues individuals may be facing in their lives. It is essential that physicians take the time to learn about how to educate their patients on sleep health and try to work with them on an individual level to help motivate lifestyle changes. Facilitating access to sleep education for their patients is one way in which physicians can help provide patients with the tools to improve their sleep health. Throughout this paper, we will review the mechanisms behind the relationship between insufficient sleep health and chronic disease and what the science says about how inadequate sleep health negatively impacts the overall health and the quality of our lives. We will also explain the lifechanging effects of sufficient sleep and how we can help patients get there.