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Associations among Sleep, Diet, Quality of Life, and Subjective Health
Abstract
Objective: We set out to improve understanding of the health behaviors of older adults by ex-amining the interrelationships of a low-fat diet and subjective measures of sleep. Methods: Old-er adults (N = 126) completed a paper-and-pencil questionnaire about sleep, health behaviors, quality of life, and subjective health. Results: Path analysis revealed sleep quality was related to daytime functioning, which was positively interrelated with quality of life and subjective health. The positive relationship between low-fat diet and quality of life may be connected to increased daytime functioning. Conclusion: Together with a healthy diet, sleep seems to play a role for older adults in maintaining a functional and healthy lifestyle, improved quality of life, and a positive perception of health.
... Sleep patterns tend to change with aging, with a shorter total time spent asleep, for instance, (Mander et al., 2017), sometimes with clear detrimental effects on older adults' physical and mental health (Reid et al., 2006), as well as on their daytime functioning and QoL (Schubert et al., 2002). Studies addressing the association between older adults' QoL and sleep quality have found that a worse self-reported sleep quality is associated with a worse global QoL (Dragioti et al., 2017;Faubel et al., 2009;Kuok et al., 2017;Lee et al., 2009;Reid et al., 2006;Schubert et al., 2002;Tan et al., 2018). The above-mentioned studies mainly examined the associations between QoL and sleep quality in older people with sleeping disorders (e.g., insomnia) or other clinical conditions (e.g., depression), rather than in healthy older adults. ...
... These are among the sleeping difficulties that can make individuals worry about their sleep quality, exacerbating any dissatisfaction with their health and daytime functioning (Soehner & Harvey, 2012;Ustinov et al., 2010). This same effect is seen for the QoL of older adults with clinical conditions or relevant sleeping disorders (e.g., insomnia) (Dragioti et al., 2017;Faubel et al., 2009;Kuok et al., 2017;Lee et al., 2009;Reid et al., 2006;Schubert et al., 2002;Tan et al., 2018). In short, self-reported sleep efficiency, as an aspect of sleep quality, also seems to relate to perceived QoL in healthy elderly people with no sleeping disorders. ...
Objective/Background: Quality of life (QoL) is a broad multidimensional construct, which can be influenced by several factors across the lifespan, including sleep quality. The aim of this study was to examine the association between QoL (and its specific domains), objective and self-reported sleep quality, and subjective sleep-related factors (i.e., dysfunctional beliefs and attitudes about sleep, and metacognitive beliefs about sleeping difficulties) in healthy elderly people. Participants: Fifty healthy older adults (mean age = 70.40 years, SD = 7.43) participated in the study. Methods: QoL was assessed using the World Health Organization’s Quality of Life Assessment, BREF version (WHOQOL-BREF). Self-reported sleep quality and efficiency were measured with the Pittsburgh Sleep Quality Index (PSQI) and sleep diary. Dysfunctional beliefs and attitudes about sleep (DBAS), and
metacognitive beliefs about sleeping difficulties (MCQ-I) (subjective sleep-related factors) were assessed with self-report questionnaires. Objective sleep quality and efficiency were measured using actigraphy over 7 days. Results: Regression analyses showed that self-reported sleep efficiency and dysfunctional beliefs and attitudes about sleep explained 24% of the variance in global QoL. Dysfunctional beliefs and attitudes about sleep were the only significant predictor of QoL in the environmental domain. Conclusions: Taken together, these findings underscore the influence of sleep-related factors, and particularly dysfunctional beliefs and attitudes about sleep, along with sleep efficiency, on the perception of QoL in healthy older adults. These factors need to be considered in efforts to sustain QoL, in late adulthood at least.
... Insbesondere zu den Annahmen 1-3 gibt es zahlreiche wissenschaftliche Befunde (z. B.Cihlar und Lippke 2017; Lippke und Cihlar 2020;Tan et al. 2018). Diese Befundlage kann eine entsprechende Nutzung als Grundlage für ein betriebliches Gesundheitsförderungsprogramm rechtfertigen und helfen, verschiedene Ziele und Verhaltensweisen besser in Einklang zu bringen.Mehrere Studien zeigen auch, dass parallel vorliegende multiple Ziele in Konflikt geraten können, aber nicht müssen (z. ...
... Insbesondere zu den Annahmen 1-3 gibt es zahlreiche wissenschaftliche Befunde (z. B. Abrantes et al. 2017;Cihlar und Lippke 2017;Paech und Lippke 2017;Tan et al. 2018). Diese Befundlage kann eine entsprechende Nutzung als Grundlage für ein Gesundheitsförderungsprogramm rechtfertigen und helfen, verschiedene Ziele besser in Einklang zu bringen. ...
Betriebliche Gesundheitsförderung, die auf gesunde Ernährung und Bewegung abzielt, ist effektiv, um Verhalten zu ändern und die Gesundheit der Mitarbeiterinnen und Mitarbeiter sowie den wirtschaftlichen Erfolg des Betriebes zu sichern. In diesem Kapitel wird eine Übersicht gegeben, welche Ansätze es bereits gibt, damit Mitarbeiterinnen und Mitarbeiter sich gesünder verhalten, d. h. sich gesund ernähren und mehr bewegen und wie sie gesetzlich fundiert sind. Neuere Ansätze können bereits bestehende Angebote innovativer und wirksamer gestalten. Insbesondere das theoretische Verständnis und die Kenntnis von Techniken kann helfen zu verstehen, warum einige Angebote von Mitarbeiterinnen und Mitarbeitern angenommen werden und wirken, und andere nicht bzw. wie sie verbessert werden sollten. Daraus ergeben sich auch Empfehlungen, wie Maßnahmen sinnvoll implementiert werden sollten, damit sie von den Mitarbeiterinnen und Mitarbeitern akzeptiert werden und nachhaltig wirksam sind.
Es gibt verschiedene Theorien und Modelle, die Gesundheitsverhalten beschreiben und erklären. Diese Theorien und Modelle sind vor allem deswegen wichtig, weil sie die Grundlage für die Entwicklung und Evaluation von Maßnahmen zur Verbesserung gesundheitsbezogenen Handelns und generell für die Optimierung von Verhaltensänderung sein können. Die Evidenz aus Studien zu diesen Theorien und Modellen kann außerdem eine Entscheidungshilfe für die Gestaltung von Interventionen sein. In diesem Kapitel unterscheiden wir zwischen Theorien, die Erwartungen als zentrale Einflussgröße von Verhaltensmotivation (auch Absicht, Intention oder Schutzmotivation genannt) annehmen, und Theorien, die die Verhaltensänderung als eine Abfolge von unterschiedlichen Denkweisen (mindsets) verstehen. Außerdem stellen wir neuere Ansätze vor, die sich mit der Einbindung von Umwelt- und sozialen Faktoren in die Erklärung von Gesundheitsverhalten sowie mit der Beschreibung und Vorhersage von zusammenhängenden parallel ausgeführten Verhaltensweisen beschäftigen.
Purpose
Patients with chronic obstructive pulmonary disease (COPD) suffer from many health problems including poor sleep. This paper aims to evaluate the relationship between diet quality indices (DQIs) and sleep quality in COPD.
Design/methodology/approach
The current cross-sectional study was carried on 121 COPD patients. Subjective quality of sleep was determined by Pittsburgh Sleep Quality Index (PSQI) and categorized into “poor” and “good” sleep quality. Dietary history was assessed by the DQIs. Disease status was categorized according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) Guidelines.
Findings
In total, 103 men and 18 women with a mean age of 66.1 ±10.9 were studied. The subjects were categorized into four groups based on GOLD; 3.3% of subjects were at Stage 1, 38% in Stage 2, 38% in Stage 3 and 20.7% in Stage 4. In total, 38% of subjects were good, and 62% were bad sleepers according to PSQI score. There was no significant relationship between the severity of COPD and PSQI score. We observed a significant inverse relation between PSQI total score and Mediterranean diet (MED) scale, Healthy Eating Index (HEI)-2010 and HEI-2005 ( p = 0.024, 0.037 and 0.024, respectively) in males.
Originality/value
This study showed a high prevalence of poor quality of sleep and sleep disturbances among COPD patients. There was an inverse association between PSQI and sleep disorders and DQIs scores in COPD patients. Regardless of the severity of airflow obstruction, poor diet quality may constitute a risk factor for sleep quality.
Background:
Ample evidence demonstrates that university students are at high risk for sedentary behaviors and inadequate fruit and vegetable intake (FVI). Internet-based interventions for multiple health behavior appear to be promising in changing such unhealthy habits. Limited randomized controlled trials have tested this assumption among Chinese university students.
Objective:
Our objective was to test the efficacy of an 8-week Web-based intervention compared with a control group condition to improve physical activity (PA) and FVI in Chinese university students. The intervention content was based on the health action process approach, and developed on the basis of previous evidence from the Western hemisphere. We evaluated self-reported data including PA and FVI, stages of change for PA and FVI, and motivational (risk perception, outcome expectancies, self-efficacy), volitional (action planning, coping planning, social support), and distal (intention, habit) indicators for PA and FVI, as well as perceived mental health outcomes (quality of life, depression).
Methods:
In a randomized controlled trial, we recruited 566 university students from one university in the central region of China during their general physical education class. After random allocation and exclusion of unsuitable participants, we assigned 493 students to 1 of 2 groups: (1) intervention group: first 4 weeks on PA and subsequent 4 weeks on FVI, (2) control group. We conducted 3 Web-based assessments: at the beginning of the intervention (T1, n=493), at the end of the 8-week intervention (T2, n=337), and at a 1-month follow-up after the intervention (T3, n=142). The entire study was conducted throughout the fall semester of 2015.
Results:
Significant time ⨯ group interactions revealed superior intervention effects on FVI; motivational, volitional, and distal indicators of FVI; and PA behavior changes, with an effect size (η(2)) ranging from .08 to .20. In addition, the overall intervention effects were significant for stage progression to the action group from T1 to T2 in PA (χ(2)1=11.75, P=.001) and FVI (χ(2)1=15.64, P=.03). Furthermore, the intervention effect was seen in the improvement of quality of life (F3,492=1.23, η(2)=.03, P=.02).
Conclusions:
This study provides evidence for the efficacy of a Web-based multiple health behavior intervention among Chinese university students tested with different outcome variables. Future research should address the high dropout rate and optimize the most effective components of this intervention.
Trial registration:
Clinicaltrials.gov NCT01909349; https://clinicaltrials.gov/ct2/show/NCT01909349 (Archived by WebCite at http://www.webcitation.org/6pHV1A0G1).
Combined exposure to several healthy behaviors (HB) is associated with reduced mortality in older adults but its impact on health-related quality of life (HRQL) is uncertain. This is a cohort study of 2,388 individuals aged ≥60 recruited in 2000–2001, whose data were updated in 2003 and 2009. At baseline, participants reported both traditional HB (non-smoking, being very or moderately active, healthy diet) and non-traditional HB (sleeping 7–8 h/d, being seated <8 h/d, and seeing friends every day). HRQL was measured with the SF-36 questionnaire at baseline, in 2003 (short-term) and in 2009 (long-term); a higher score on the SF-36 represents better HRQL. Linear regression models were used to assess the association between HB at baseline and HRQL in 2003 and 2009, with adjustment for the main confounders including baseline HRQL. In the short-term, being physically active, sleeping 7–8 h/d, and being seated <8 h/d was associated with better HRQL. Compared to having ≤1 of these HB, the β (95% confidence interval) for the score on the physical component summary of the SF-36 in 2003 was 1.42 (0.52–2.33) for 2 HB, and 2.06 (1.09–3.03) for 3 HB, p-trend <0.001. Corresponding figures for the mental component summary score were 1.89 (0.58–3.21) for 2 HB and 3.35 (1.95–4.76) for 3 HB, p-trend <0.001. Non-smoking, a healthy diet or seeing friends did not show an association with HRQL. In the long-term, being physically active was the only HB associated with better physical HRQL. As a conclusion, a greater number of HB, particularly more physical activity, adequate sleep duration, and sitting less, were associated with better short-term HRQL in older adults. However, in the long-term, being physically active was the only HB associated with better physical HRQL.
A cross-sectional population-based survey, the National FINRISK 2012 Study, designed to monitor chronic diseases and their risk factors in Finland. A random sample of 10,000 adults aged 25–74 years, and of them, 64% (n=6424) participated the study. Participants subjectively reported the total durations for sleep and naps (n=6238), sleep quality (n=5878), bedtimes and wake-up times separately for working days and weekends yielding the amount of sleep debt (n=5878), and the seasonal variation in sleep duration (n=4852). The participants were asked whether they were diagnosed or treated for common chronic diseases in the past 12 months. Logistic regression models were adopted to analysis and adjusted for a range of covariates as potential confounding factors. Total sleep duration and nap duration prolonged in depression and other mental disorder (p<.001 for all). Seasonal variation in sleep duration was associated with depression (p=.014), hypertension (p=.018) and angina pectoris (p=.024). Participants with gallstones, cardiac insufficiency, depression, or degenerative arthritis had poor sleep quality (odds ratios of 1.6–6.3, p=.001 or less for each). Those with degenerative arthritis had sleep debt less (p<.05) and those with angina pectoris more (p<.05) than individuals without these medical conditions. Depression is significantly associated with sleep problems, albeit no sleep debt. Cardiovascular diseases, degenerative arthritis, and gallstones had significant associations with one or more sleep problems. There is therefore a need for more successful management of sleep problems in chronic diseases to improve the quality of life, to reduce treatment relapses, and to increase health and longevity in a population.
Non-communicable diseases (i.e., chronic diseases including cardiovascular disease, cancer, chronic respiratory disease, diabetes and obesity) result in 36 million deaths each year. Individuals' habitual participation in a single health-risk behaviors substantially contribute to morbidity and mortality (e.g., tobacco use, daily fast food intake, etc.); however, more concerning is the impact of typically co-occurring or clustering of multiple health-risk behaviors. This burden can be minimized through successful cessation of health-risk behaviors and adoption of healthy behaviors; namely healthy lifestyle adoption or multiple health behavior change (MHBC). MHBC is a developing field and future research recommendations are provided to advance MHBC research. A valid measure of MHBC (i.e., lifestyle) is warranted to provide the needed basis for MHBC investigations and evaluations. MHBC is thought to occur through shared co-variation of underlying motivating mechanisms, but how these relationships influence behavior remains unclear. A better understanding of the relationship between behaviors and the related motivating mechanisms (and potential cross-relationship of influences) is needed. Future research should also aim to improve lifestyles through understanding how to change multiple health behaviors. Finally, MHBC research should target the development of sustainable interventions which result in lasting effects (e.g., capacity, systems, policy and environmental changes), with dissemination considered during development. Focusing MHBC research in these areas will increase our understanding and maximize the impact on the health of populations.
Objective: We sought to determine the accuracy with which individuals with obesity would complete an inventory of high-calorie foods in the home. Methods: Lean adults (BMI<25) and adults with clinically-defined obesity (BMI≥30) self-administered a home food inventory of high-calorie foods. This was followed by a visit to the home by research staff who administered their own inventory. Results: Twelve of 20 participants with obesity underreported the number of high-calorie foods in their homes by 4 or more items, compared to only 3 of 22 lean participants (p < .001). Conclusions: Many adults with obesity not only underreport the amount of energy they consume, but also the kinds of foods kept in their homes.
Background: Obesity, particularly morbid obesity, has various physical and mental complications. Excessive daytime somnolence
(EDS) is a sleep disorder that reduces individuals’ performance capability and the accuracy of their short-term memory and causes
learning problems. This retrospective study aimed to document the presence of EDS in a sample of obese patients in comparison to
patients with a normal weight.
Objectives: This article compares the excessive daytime sleepiness of obese and non-obese patients in the minimally invasive
surgery research center in Tehran, Iran.
Patients and Methods: In this case-control study, we compared excessive daytime sleepiness in 55 obese patients who were candidates
for laparoscopic surgery, with a body mass index (BMI) of equal to or greater than 30 kg/m2, with 55 controls with a normal
BMI (19.5 - 24.9 kg/m2). The process of selecting the control group in our case-control study is matching in group levels, so that the
controls are similar to the case group with regard to certain key characteristics, such as age, sex, and race. The sleep assessment
was based on the Epworth sleepiness scale (ESS) questionnaire. Analysis of variance (ANOVA) was used to compare the means of
quantitative data, such as the ESS score of groups.
Results: Sleepiness was not affected by gender in cases or controls. The sleepiness prevalence was 29 (52.7%) in the cases group and
17 (30.9%) in the control group (OR = 2.493 (95% CI 1.144 -5.435)). The mean ESS scores in cases and controls were 7.82 � 3.86 and
10.54�6.15, respectively (P = 0.007). Moreover, the prevalence of sleepiness and the mean ESS scores in class III of obesity differed
significantly from the controls (16 (57.1%) vs. 17 (30.9%)) (OR = 2.980 (95% CI 1.162 - 7.645)) and (11.04�5.93 vs. 7.82�3.86) (P = 0.013),
respectively.
Conclusions: Our findings suggest a strong relationship between EDS and obesity, particularly morbid obesity. Therefore, physicians
must be familiar with EDS as a mixed clinical entity indicating careful assessment and specific treatment planning.
Keywords: Excessive Somnolence Disorders, Obesity, Morbid Obesity
Short sleep duration has been associated with obesity in numerous epidemiological studies. However, such association studies cannot establish evidence of causality. Clinical intervention studies, on the other hand, can provide information on a causal effect of sleep duration on markers of weight gain: energy intake and energy expenditure. Herein is an overview of the science related to the impact of sleep restriction, in the context of clinical intervention studies, on energy intake, energy expenditure and body weight. Additionally, studies that evaluate the impact of sleep restriction on weight loss and the impact of sleep extension on appetite are discussed. Information to date suggests that weight management is hindered when attempted in the context of sleep restriction, and the public should be made aware of the negative consequences of sleep restriction for weight regulation.
Sleep is increasingly recognized as an important lifestyle contributor to health. However, this has not always been the case, and an increasing number of Americans choose to curtail sleep in favor of other social, leisure, or work-related activities. This has resulted in a decline in average sleep duration over time. Sleep duration, mostly short sleep, and sleep disorders have emerged as being related to adverse cardiometabolic risk, including obesity, hypertension, type 2 diabetes mellitus, and cardiovascular disease. Here, we review the evidence relating sleep duration and sleep disorders to cardiometabolic risk and call for health organizations to include evidence-based sleep recommendations in their guidelines for optimal health.
Dispositional optimism has been related to beneficial influences on physical health outcomes. However, its links to global sleep quality and the psychological mediators responsible for such associations are less studied. This study thus examined if trait optimism predicted global sleep quality, and if measures of subjective well-being were statistical mediators of such links. A community sample of 175 participants (93 men, 82 women) completed measures of trait optimism, depression, and life satisfaction. Global sleep quality was assessed using the Pittsburgh Sleep Quality Index. Results indicated that trait optimism was a strong predictor of better PSQI global sleep quality. Moreover, this association was mediated by depression and life satisfaction in both single and multiple mediator models. These results highlight the importance of optimism for the restorative process of sleep, as well as the utility of multiple mediator models in testing distinct psychological pathways.