Relationship of sleep pattern and snoring with chronic disease: findings from a nationwide population-based survey

Highlighting the importance of healthy sleep patterns in the risk of adult asthma under the combined effects of genetic susceptibility: a large-scale prospective cohort study of 455 405 participants

BACKGROUND

Individuals with asthma usually have comorbid sleep disturbances; however, whether sleep quality affects asthma risk is still unclear. We aimed to determine whether poor sleep patterns could increase the risk of asthma and whether healthy sleep patterns could mitigate the adverse effect of genetic susceptibility.

METHODS

A large-scale prospective study was performed in the UK Biobank cohort involving 455 405 participants aged 38-73 years. Polygenic risk scores (PRSs) and comprehensive sleep scores, including five sleep traits, were constructed. A multivariable Cox proportional hazards regression model was used to investigate the independent and combined effects of sleep pattern and genetic susceptibility (PRS) on asthma incidence. Subgroup analysis across sex and sensitivity analysis, including a 5-year lag, different covariate adjustments and repeat measurements were performed.

RESULTS

A total of 17 836 individuals were diagnosed with asthma during over 10 years of follow-up. Compared with the low-risk group, the HRs and 95% CIs for the highest PRS group and the poor sleep pattern group were 1.47 (95% CI: 1.41 to 1.52) and 1.55 (95% CI: 1.45 to 1.65), respectively. A combination of poor sleep and high genetic susceptibility led to a twofold higher risk compared with the low-risk combination (HR (95% CI): 2.22 (1.97 to 2.49), p<0.001). Further analysis showed that a healthy sleep pattern was associated with a lower risk of asthma in the low, intermediate and high genetic susceptibility groups (HR (95% CI): 0.56 (0.50 to 0.64), 0.59 (0.53 to 0.67) and 0.63 (0.57 to 0.70), respectively). Population-attributable risk analysis indicated that 19% of asthma cases could be prevented when these sleep traits were improved.

CONCLUSIONS

Individuals with poor sleep patterns and higher genetic susceptibility have an additive higher asthma risk. A healthy sleep pattern reflected a lower risk of asthma in adult populations and could be beneficial to asthma prevention regardless of genetic conditions. Early detection and management of sleep disorders could be beneficial to reduce asthma incidence.

Influence of Snoring on the Incidence of Metabolic Syndrome: A Community-Based Prospective Cohort Study in Rural Northeast China

In recent years, there has been an increase in the incidence of metabolic syndrome (MetS) in rural China. Thus, for better intervention, it is necessary to identify the possible risk factors of MetS. This community-based prospective cohort study was performed to evaluate the relationship between the snoring status and incidence of MetS. In this Northeast China rural cardiovascular health study, 4980 residents aged ≥35 years (2586 men and 2394 women; follow-up proportion: 87.5%) at baseline were recruited between 2012 and 2013 and were followed up between 2015 and 2017. The primary outcome was the incidence of MetS, as defined by the unified criteria for MetS defined in 2009. The residents were classified based on their snoring status, and the outcomes were compared between the two groups. The odds ratio (OR) for MetS incidence was estimated using a logistic regression model and adjusted for confounding factors. With a median follow-up duration of 4.6 years, the MetS incidence was higher among the snorers (men, 26.2%; women, 33.5%) than in the non-snorers (men, 19.7%; women, 23.2%). The participants' diastolic blood pressure was increased at follow-up as compared with the baseline values among the male snorers; however, a decrease was noted among the male non-snorers. Similarly, the female snorers had higher blood glucose levels during the follow-up, whereas the non-snorers had lower blood sugar levels. A significant association was noted between snoring and the incidence of MetS (adjusted OR = 1.51; 95% confidence interval = 1.32-1.74). Moreover, the incidence of severe snoring increased with increased levels of snoring, with severe snorers having an OR twice as high as that of the non-snorers (adjusted OR = 2.10; 95% confidence interval = 1.38-3.20). Overall, snoring was independently associated with a higher incidence of newly diagnosed MetS in rural Northeast China. Thus, more attention should be paid to residents with snoring problems.

Association between self-reported snoring and metabolic-associated fatty liver disease: A cross-sectional analysis of the NHANES 2017-2018

BACKGROUND

Snoring may play an important role in a variety of diseases, especially metabolic diseases. However, there are no reports on the relationship between snoring and the risk of metabolic-associated fatty liver disease (MAFLD). This study aimed to investigate the association between snoring and MAFLD.

METHODS

A cross-sectional analysis was performed based on the National Health and Nutrition Examination Survey (NHANES) 2017-2018. Self-reported snoring frequency was grouped into four categories (never, rarely, occasionally, and frequently). MAFLD was diagnosed based on the evidence of hepatic steatosis and any of the following three conditions: overweight/obesity, diabetes mellitus or metabolic dysfunction. Logistic regression with sampling weights was used to examine the association between snoring and MAFLD.

RESULTS

A total of 5016 patients were included, and 50.14% of individuals had MAFLD. Compared with nonsnorers, those who snored frequently were associated with increased odds for MAFLD (odds ratio (OR): 1.376, 95% confidence interval (CI): 1.122-1.688, p trend <0.001). The subgroup analyses suggested that no significant interactions were found between snoring and other potential effect modifiers, including age, sex, body mass index (BMI), smoking status, chronic obstructive pulmonary disease (COPD) and hypertension.

CONCLUSION

Snoring was independently and positively associated with a higher prevalence of MAFLD, suggesting that attention to snoring may contribute to the early detection of MAFLD.

Dependable algorithm for visualizing snoring duration through acoustic analysis: A pilot study

Snoring is a nuisance for the bed partners of people who snore and is also associated with chronic diseases. Estimating the snoring duration from a whole-night sleep period is challenging. The authors present a dependable algorithm for visualizing snoring durations through acoustic analysis. Both instruments (Sony digital recorder and smartphone's SnoreClock app) were placed within 30 cm from the examinee's head during the sleep period. Subsequently, spectrograms were plotted based on audio files recorded from Sony recorders. The authors thereby developed an algorithm to validate snoring durations through visualization of typical snoring segments. In total, 37 snoring recordings obtained from 6 individuals were analyzed. The mean age of the participants was 44.6 ± 9.9 years. Every recorded file was tailored to a regular 600-second segment and plotted. Visualization revealed that the typical features of the clustered snores in the amplitude domains were near-isometric spikes (most had an ascending-descending trend). The recorded snores exhibited 1 or more visibly fixed frequency bands. Intervals were noted between the snoring clusters and were incorporated into the whole-night snoring calculation. The correlative coefficients of snoring rates from digitally recorded files examined between Examiners A and B were higher (0.865, P < .001) than those with SnoreClock app and Examiners (0.757, P < .001; 0.787, P < .001, respectively). A dependable algorithm with high reproducibility was developed for visualizing snoring durations.

Cardiovascular diseases and sleep disorders in South Asians: A scoping review

BACKGROUND

South Asians comprise 20% of the world population. There is a high prevalence of cardiovascular diseases among South Asians, and sleep disorders may be a key risk factor.

OBJECTIVE

The review examined literature about cardiovascular and sleep disorders in South Asian countries and in the United States, United Kingdom, Canada, and the Netherlands.

METHODS

Methods from Arksey and O'Malley's framework and Peter et al. were used to synthesize findings from 23 research studies.

RESULTS

The studies addressed sleep disorders with hypertension, heart failure, diabetes, and obesity. Obstructive sleep apnea and short sleep duration were common and associated with cardiovascular morbidity and mortality at early ages in South Asians. Researchers analyzed polysomnography-derived sleep measures, vascular functions, polymorphisms, C-reactive protein levels, public knowledge about cardiovascular health, and sleep-related questionnaire scores. Most studies were conducted in major metropolitan areas; no data were available about people living in locations with limited health care resources. Among migrant South Asians, researchers did not explore the role of acculturation on sleep patterns and cardiovascular outcomes.

CONCLUSIONS

The review highlights important considerations for researchers who plan to investigate cardiovascular conditions in South Asian communities. There is a need for more knowledge about sleep-related risk factors, and researchers should also examine cultural, political, and socioeconomic factors that affect health care access. This knowledge will be imperative for designing effective and tailored disease prevention strategies for South Asian populations.

Development and Validation of a Coronary Heart Disease Risk Prediction Model in Snorers with Hypertension: A Retrospective Observed Study

Purpose

To develop and validate a risk prediction model for coronary heart disease (CHD) in snorers with hypertension, including traditional and new risk factors.

Patients and Methods

Twenty factors were evaluated in the records of 2810 snorers with hypertension. Training (70%) and validation (30%) sets were created by random allocation of data, and a new nomogram model was developed. The model's discrimination and calibration were measured by calculating the area under the receiver operating curve (AUC) and creating calibration charts. The performance of the nomogram model was compared with that of the Prediction for ASCVD Risk in China (China-PAR) and Framingham models by decision curve analysis. An optimal cutoff point for the risk score in the training set was computed to stratify patients.

Results

In the nomogram model, the AUCs for predicting CHD at 5, 7 and 9 years in the training set were 0.706 (95% confidence interval [CI] 0.649-0.763), 0.703 (95% CI 0.655-0.751) and 0.669 (95% CI 0.593-0.744), respectively. The respective AUCs were 0.682 (95% CI 0.607-0.758), 0.689 (95% CI 0.618-0.760) and 0.664 (95% CI 0.539-0.789) in the validation set. The calibration chart showed that the predicted events from the nomogram score were close to the observed events. Decision curve analysis indicated that the nomogram score was slightly better than the Prediction for ASCVD Risk in China (China-PAR) and Framingham models for predicting the risk of CHD in snorers with hypertension. A cutoff point was identified for being CHD-free (a nomogram score of ≤121), which could be helpful for the early identification of individuals at high-risk of CHD.

Conclusion

The nomogram score predicts the risk probability of CHD in snorers with hypertension at 5, 7 and 9 years, and shows good capability in terms of discrimination and calibration. It may be a useful tool for identifying individuals at high risk of CHD.

Correlation between snoring sounds and obstructive sleep apnea in adults: a meta-regression analysis

OBJECTIVE

Snoring is a dominant clinical symptom in patients with obstructive sleep apnea (OSA), and analyzing snoring sounds might be a potential alternative to polysomnography (PSG) for the assessment of OSA. This study aimed to systematically examine the correlation between the snoring sounds and the apnea-hypopnea index (AHI) as the measures of OSA severity.

MATERIAL AND METHODS

A comprehensive literature review using the MEDLINE, Embase, Cochrane Library, Scopus, and PubMed databases identified the published studies reporting the correlations between and severity of snoring and the AHI values by meta-regression analysis.

RESULTS

In total, 13 studies involving 3,153 adult patients were included in this study. The pooled correlation coefficient for snoring sounds and AHI values was 0.71 (95%CI: 0.49, 0.85) from the random-effects meta-analysis with the Knapp and Hartung adjustment. The I 2 and chi-square Q test demonstrated significant heterogeneity (97.6% and p<0.001). After adjusting for the effects of the other covariates, the mean value of the Fisher's r-to-z transformed correlation coefficient would have 0.80 less by the snoring rate (95%CI = -1.02, -0.57), 1.46 less by the snoring index (95%CI = -1.85, -1.07), and 0.21 less in the mean body mass index (95%CI = -0.31, -0.11), but 0.15 more in the mean age (95%CI = 0.10, 0.20). It fitted the data very well (R 2=0.9641).

CONCLUSION

A high correlation between the severity of snoring and the AHI was found in the studies with PSG. As compared to the snoring rate and the snoring index, the snoring intensity, the snoring frequency, and the snoring time interval index were more sensitive measures for the severity of snoring.

Associations of chronic diarrheal symptoms and inflammatory bowel disease with sleep quality: A secondary analysis of NHANES 2005-2010

Objective

Poor sleep quality is highly prevalent in patients with chronic diarrheal symptoms or inflammatory bowel disease (IBD). This study aimed to evaluate the associations of chronic diarrheal symptoms and IBD with sleep quality in the general US population.

Methods

14,696 adults (≥20 years) from the National Health and Nutrition Examination Survey (2005-2010) were included in the study. Chronic diarrheal symptoms and IBD were defined by self-reports. Sleep quality was assessed by sleep disorder, sleep trouble, and sleep duration. Multivariable logistic regression models were used to examine the associations.

Results

After adjustment of a series of covariates, we found that participants with chronic diarrheal symptoms or IBD had higher odds of sleep disorder [chronic diarrheal symptoms: odds ratio (OR) = 1.20, 95% confidence interval (CI) = 1.04-1.38; IBD: OR = 3.86, 95% CI = 1.92-7.77] and sleep trouble (chronic diarrheal symptoms: OR = 1.19, 95% CI = 1.09-1.30; IBD: OR = 2.32, 95% CI = 1.30-4.14), respectively. Sleep duration for participants with IBD was significantly shorter than that for those without IBD (β = -0.39, 95% CI = -0.78 to 0.01, P = 0.045). Subgroup analyses revealed that the associations of chronic diarrheal symptoms and IBD with sleep disorder and sleep trouble were more pronounced among women.

Conclusions

In this large sample of US adults, we found that chronic diarrheal symptoms and IBD were significantly associated with sleep quality, particularly in women. The findings highlight the importance of managing bowel health to promote high quality of sleep; and thus, improve quality of life in this subpopulation.

Systematic Review of Physical Activity, Sedentary Behaviour and Sleep Among Adults Living with Chronic Respiratory Disease in Low- and Middle-Income Countries

Abstract

Physical activity (PA), sedentary behaviour (SB) and sleep are important lifestyle behaviours associated with chronic respiratory disease (CRD) morbidity and mortality. These behaviours need to be understood in low- and middle-income countries (LMIC) to develop appropriate interventions.

Purpose

Where and how have free-living PA, SB and sleep data been collected for adults living with CRD in LMIC? What are the free-living PA, SB and sleep levels of adults living with CRD?

Patients and Methods

The literature on free-living PA, SB and sleep of people living with CRD in LMIC was systematically reviewed in five relevant scientific databases. The review included empirical studies conducted in LMIC, reported in any language. Reviewers screened the articles and extracted data on prevalence, levels and measurement approach of PA, SB and sleep using a standardised form. Quality of reporting was assessed using bespoke criteria.

Results

Of 89 articles, most were conducted in Brazil (n=43). PA was the commonest behaviour measured (n=66). Questionnaires (n=52) were more commonly used to measure physical behaviours than device-based (n=37) methods. International Physical Activity Questionnaire was the commonest for measuring PA/SB (n=11). For sleep, most studies used Pittsburgh Sleep Quality Index (n=18). The most common ways of reporting were steps per day (n=21), energy expenditure (n=21), sedentary time (n=16), standing time (n=13), sitting time (n=11), lying time (n=10) and overall sleep quality (n=32). Studies revealed low PA levels [steps per day (range 2669-7490steps/day)], sedentary lifestyles [sitting time (range 283-418min/day); standing time (range 139-270min/day); lying time (range 76-119min/day)] and poor sleep quality (range 33-100%) among adults with CRD in LMIC.

Conclusion

Data support low PA levels, sedentary lifestyles and poor sleep among people in LMIC living with CRDs. More studies are needed in more diverse populations and would benefit from a harmonised approach to data collection for international comparisons.

Justificatory explanations in machine learning: for increased transparency through documenting how key concepts drive and underpin design and engineering decisions

Given the pervasiveness of AI systems and their potential negative effects on people's lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more "explainable" by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of "health", which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing "justificatory explanations" about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of "health", we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that "justificatory explanations" are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project's main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project.

Association Between Snoring and Diabetes Among Pre- and Postmenopausal Women

Purpose

To examine the relationship between diabetes and snoring frequency and determine the effect of menopause and postmenopausal years on this relationship.

Methods

We included 12,218 premenopausal and postmenopausal women from part of the baseline of the China Multi-Ethnic Cohort study (CMEC) in Chongqing province. Face-to-face questionnaires, physical examination, and biological samples were used to collect data. Logistic regression and subgroup analysis were used to explore the relationship between snoring and diabetes in women with various menopausal statuses.

Results

The risk of diabetes increased with the snoring frequency, with adjusted odds ratios of 1.23 (95% CI:1.05–1.43) and 1.47 (95% CI:1.25–1.73) for sometimes snoring and frequent snoring, compared to non-snoring. In premenopausal and postmenopausal women, frequent snoring increased the odds of diabetes by 58% (95% CI: 7–132%) and 43% (95% CI: 20–72%), respectively, compared to non-snoring. Only in women who were ≥10 years postmenopausal had a statistical association between frequent snoring and diabetes, with a 54% (95% CI: 23–92%) increased odds of diabetes, compared to women who did not snore.

Conclusion

Snoring frequency is positively associated with diabetes. Women who snore frequently before and for at least ten years after menopause are at higher risk of developing diabetes. Frequent snorers and long-term postmenopausal women should monitor blood glucose levels to aid in the early detection and treatment of diabetes.

Prevalence and correlates of total sleep time among the older adults during COVID-19 pandemic in Bangladesh

Purpose

The present study was aimed to identify inappropriate sleep duration and its correlates among the Bangladeshi older adults during the COVID-19 pandemic.

Material and methods

This cross-sectional study was carried out among 1030 older adults aged 60 years and above in Bangladesh. Information was collected through telephone interviews using a pretested semi-structures questionnaire installed in SurveyCTO mobile app. Sleep duration was defined as total sleep time (TST) in last 24 h including day and nighttime sleep. TST was further categorized into shorter (<7 h), recommended (7-8 h), and longer sleep (>8 h) according to 2015 National Sleep Foundation guideline. The multinomial logistic regression model identified the factors associated with sleep duration.

Results

Mean TST was 7.9 h (SD=1.62). Of the total participants, 28.2% had longer and 17.8% shorter sleep duration. In the regression model, participants' age of ≥80 years (OR: 3.36, 1.46-7.73), monthly family income of <5,000 Bangladeshi Taka (OR: 3.50, 1.79-6.82), difficulty in getting medicine during COVID-19 (OR: 1.72, 1.05-2.82), lack of communication during the pandemic (OR: 2.20, 1.43-3.40) and receiving COVID-19 related information from friends/family/neighbours (OR: 1.83, 1.11-3.01) were significantly associated with shorter TST. On the other hand, monthly family income of < 5,000 Bangladeshi Taka (OR: 2.00, 1.13-3.53), difficulty in getting medicine during COVID-19 pandemic (OR: 2.01, 1.33-3.03) and receiving COVID-19 related information from radio/TV (OR: 2.09, 1.22-3.59) were associated with longer TST.

Conclusions

The study findings suggest implementing sleep management program for older adults in Bangladesh, particularly during emergencies like COVID-19.

A Deep Learning Model for Snoring Detection and Vibration Notification Using a Smart Wearable Gadget

Snoring, a form of sleep-disordered breathing, interferes with sleep quality and quantity, both for the person who snores and often for the person who sleeps with the snorer. Poor sleep caused by snoring can create significant physical, mental, and economic problems. A simple and natural solution for snoring is to sleep on the side, instead of sleeping on the back. In this project, a deep learning model for snoring detection is developed and the model is transferred to an embedded system—referred to as the listener module—to automatically detect snoring. A novel wearable gadget is developed to apply a vibration notification on the upper arm until the snorer sleeps on the side. The gadget is rechargeable, and it is wirelessly connected to the listener module using low energy Bluetooth. A smartphone app—connected to the listener module using home Wi-Fi—is developed to log the snoring events with timestamps, and the data can be transferred to a physician for treating and monitoring diseases such as sleep apnea. The snoring detection deep learning model has an accuracy of 96%. A prototype system consisting of the listener module, the wearable gadget, and a smartphone app has been developed and tested successfully.

Association between nighttime-daytime sleep patterns and chronic diseases in Chinese elderly population: a community-based cross-sectional study

Background

This study aimed to assess the relationship between specific nighttime-daytime sleep patterns and prevalence of different chronic diseases in an elderly population.

Methods

We conducted a community-based cross-sectional study in 4150 elderly Chinese, with an average age of 74 years. Sleep-related variables (nighttime sleep duration, daytime napping and duration) and chronic disease status, including diabetes, cardiovascular diseases (CVD), dyslipidemia cancer and arthritis were collected for the study. Multivariable logistic regression models were used to analyze the relationship between nighttime-daytime sleep patterns and prevalence of chronic diseases.

Results

Overall prevalence of any of chronic diseases was 83.8%. Nighttime-daytime sleep patterns were defined according to nighttime sleep duration and habitual nappers/non-nappers. Taking the nighttime-daytime sleep pattern “short nighttime sleep with daytime napping” as reference, those with “long nighttime sleep without daytime napping” had higher prevalence of diabetes [OR and 95% CI, 1.35 (1.01–1.80)] and lower prevalence of arthritis [OR and 95% CI, 0.46 (0.33–0.63)]. And those with “long nighttime sleep with daytime napping” had higher prevalence of diabetes [OR and 95% CI, 1.36 (1.05–1.78)] while lower prevalence of cancer [OR and 95% CI, 0.48 (0.26–0.85)] and arthritis [OR and 95% CI, 0.67 (0.51–0.86)]. Further, in habitual nappers, subjects were classified according to duration of nighttime sleep and daytime naps. Compared to “short nighttime sleep with long daytime napping”, individuals with “long nighttime sleep with short daytime napping” had significantly positive association with diabetes prevalence [OR and 95% CI, 1.73 (1.15–2.68)] while border-significantly and significantly negative association with cancer [OR and 95% CI, 0.49 (0.23–1.07)] and arthritis [OR and 95% CI, 0.64 (0.44–0.94)], respectively.

Conclusions

Elderly individuals with chronic diseases had different nighttime-daytime sleep patterns, and understanding these relationships may help to guide the management of chronic diseases.

Electronic supplementary material

The online version of this article (10.1186/s12877-019-1136-9) contains supplementary material, which is available to authorized users.