Patterns and predictors of sleep quality before, during, and after hospitalization in older adults.

Background: Depression is one of the most common mental disorders and one of the leading causes of disability and suicide. Approximately 50 – 90% of patients with depression experience sleep disturbance as an additional symptom. Sleep disorders not only represent as a primary factor for patients with depression to seek for professional help but also represent as a risk factor for suicide and self-harm. A good sleep quality can improve mood and support the recovery process in patients with depression. Methods: The type of research used in this study is a cross-sectional study employing a demographic and PSQI (Pittsburgh Sleep Quality Index) questionnaire to assess sleep quality among patients with depression at Outpatient Psychiatric Department of Dr. Soetomo General Hospital. This study utilized primary data obtained through guided-interviews and secondary data collected from the patient's medical records. Results: Based on 81 respondents at Outpatient Psychiatric Department of Dr. Soetomo General Hospital, most respondents were female patients around 18 – 25 years old. According to the PSQI (Pittsburgh Sleep Quality Index) score, 74 respondents (91.35%) had poor subjective sleep quality. The PSQI components include fairly good subjective sleep quality (41.98%), poor sleep latency (64.2%), very good sleep duration (34.57%), very good sleep efficiency (49.38%), fairly frequent sleep disturbance (50.62%), frequently use of sleep medication (65.43%), and fairly poor daytime disfunction (40.74%). Conclusion: Based on a cross-sectional study of 81 patients with depression at the Outpatient Psychiatric Department of Dr. Soetomo General Hospital, it can be concluded that the majority of respondents were female patients aged 18 – 25 years. According to the PSQI (Pittsburgh Sleep Quality Index) score, 74 respondents (91.35%) had poor sleep quality. The PSQI components include subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction. The main factors contributing to poor sleep quality among respondents were physical comorbidities and drugs interactions from medications being taken.

The relationship between Pittsburgh Sleep Quality Index (PSQI) score and survival of dialysis patients has not been well studied. The aim of this study was to explore the association between PSQI score and all-cause mortality in dialysis patients. Fifty-one hemodialysis and 58 peritoneal dialysis patients were enrolled in this study. PSQI score > 5 and ≤ 5 indicated "poor sleepers" and "good sleepers", respectively. The primary outcome was all-cause mortality. Kaplan-Meier survival curve and Cox proportional hazards regression analysis were performed. The median PSQI score was 7.0 (4.0-10.0). Sixty-seven (61.5%) patients had poor sleep quality (SQ). Compared with good sleepers, poor sleepers had significantly lower levels of hemoglobin [74.0 (61.0, 85.0) vs. 78.0 (68.0, 97.0), P = 0.03] and serum bicarbonate (18.0 ± 4.5 vs. 20.0 ± 3.7, P = 0.022). The follow-up time was 69.1 ± 29.9months. By multivariate Cox proportional hazards analysis, PSQI total score was the independent risk factor of all-cause mortality [hazard ratio (HR) 1.20, 95% confidence interval (CI) 1.05-1.36, P = 0.007]. Restricted cubic spline (RCS) analysis showed that 7 was the cutoff value at which the effect of PSQI score on mortality changed. Patients with a PSQI score > 7 had a 2.96-fold increased risk of all-cause mortality (HR 2.96, 95% CI 1.15-7.61, P = 0.025). PSQI score can be used as a predictor of all-cause mortality in dialysis patients, and those with PSQI > 7 were associated with increased odds of mortality.

Background:Impaired quality of life (QOL) is an issue considered in patients with multiple sclerosis (MS). There are limited studies evaluated poor sleep and impaired QOL in these cases. The aim of this study was to evaluate quality of sleep and poor sleep in Iranian patients with MS and the relationship between Pittsburgh Sleep Quality Index (PSQI) score and QOL subscales.Methods:One-hundred and fourteen cases with definite MS due to MC Donald criteria enrolled who referred to MS clinic of Sina and Imam Hospitals were enrolled. Patients asked to fill valid and reliable Persian versions of PSQI and MSQOL-54 questionnaires. Demographic data (sex, age), duration of the disease, education level and marital status were extracted from patients medical files. After neurological examination, Kurtzke Expanded Disability Status Scale (EDSS) was assessed.Results:Ninety-one (79.8%) patients were female and 23 (20.2%) were male. Mean age and EDSS was 34.7 ± 9.6 years and 2.3 (median: 1.5). Mean PSQI score and overall QOL score were 4.5 and 57. Sixty-seven cases were good sleepers (PSQI ≤ 5) and 47 were poor sleepers (PSQI > 5). Except five subscales, all others were significantly different between good and poor sleepers. There was significant positive correlation between PSQI score and EDSS (r = 0.24, P < 0.001) and negative correlation between EDSS and physical and mental health (r = −0.48, P < 0.001, r = −0.43, P < 0.001). EDSS and total PSQI score were independent predictors of physical and mental health composites.Conclusions:Sleep quality as a factor which affecting QOL should be considered and evaluated properly in MS patients.

BackgroundSleep-related complaints are common among older adults, and recent research indicates that changes in sleep patterns may be associated with alterations in the composition of the gut microbiome (GM). However, investigations into the relationship between sleep measures and GM abundance among older adults have been limited thus far. This study represents the first large-scale effort to comprehensively explore the connection between GM composition and both subjective and objective sleep measures in older adults.MethodsThe study included 279 cognitively-normal older adults from the community who had not used sleep medication, antibiotics, or probiotics for at least one month before providing stool samples. Participants were categorized as good sleepers (GS) or poor sleepers (PS) based on the Pittsburgh Sleep Quality Index (PSQI) scores. GM diversity and relative abundance were compared between both groups, and their associations with PSQI scores and objective sleep measures were also examined.ResultsAlpha and beta diversity did not show significant differences between the GS and PS groups. However, significant differences in GM relative abundance across various taxonomic levels were found between the GS and PS groups. In the overall sample, higher PSQI scores were linked to lower abundance of the species Hungatella_hathewayi (p = 0.005, false discovery rate = 0.035). However, there were no significant associations between GM abundance and objective sleep measures after corrections for multiple comparisons.ConclusionThese findings suggest that specific gut microbial taxa are associated with subjective sleep disturbances in older adults.

Article AbstractBecause this piece does not have an abstract, we have provided for your benefit the first 3 sentences of the full text.To the Editor: Sleep disturbances commonly co-occur with mental disorders and often are sufficiently severe to warrant targeted treatment. Left untreated, sleep disturbances may exacerbate comorbid conditions and complicate recovery. Moreover, sleep disturbances are considered modifiable risk factors for onset and relapse of mental disorders.

Background:Psoriatic arthritis (PsA) is a chronic immune-mediated inflammatory disease. It has a heterogeneous clinical presentation with main features being joint swelling and pain, skin and nail psoriasis, enthesitis, and dactylitis. Self-reported outcomes such as quality of sleep and fatigue are often neglected topics although having great impact on patients’ everyday lives.Objectives:The primary objective was to analyze the prevalence of PsA patients suffering from poor quality of sleep, defined by Pittsburgh Sleep Quality Index (PSQI) score ≥ 5, and to study the association between being a good or poor sleeper and clinical- and patient-reported outcomes.Secondary, the effects on outcomes after initiation of treatment.Methods:Patient characteristics, disease activity and self-reported outcomes were obtained from the PIPA cohort. To evaluate the primary objective, a cross-sectional analysis was conducted including PSQI score at baseline and corresponding data. Patients were divided into two groups, defined as good or poor sleepers (Table 1).Data from initiation of treatment (baseline) and 4 months follow-up were included when assessing the effect of treatment. Transition of good and poor sleepers from baseline to 4 months follow-up was depicted by a chi-squared test.A crosstab analysis was performed with baseline PSQI and whether they had widespread pain to investigate a possible link, additionally a Mann-Whitney U test.Results:From January 2018-November 2020 a total of 109 patients were included. The prevalence of PsA patients suffering from poor quality of sleep at baseline were 66.1% whereas the remaining 33.9% were deemed good sleepers.There was no statistically significant difference in patient demographics when comparing good and poor sleepers at baseline. There was a statistically significant difference in patient-reported outcomes such as Visual Analogue Scale (VAS) pain, VAS global, Health Assessment Questionnaire (HAQ) score and Disease Activity Score (DAS28-CRP), with poor sleepers scoring higher.57 patients had complete data at 4 months follow-up. At baseline 71.9% of them were classified as poor sleepers (Figure 1). A chi-squared test presented the transition at 4 months follow-up. 47.4% of the patients were now classified as poor sleepers.While 27 poor sleepers became good sleepers, 13 good sleepers became poor sleepers, with data being statistically significant (p 0.001).The crosstab analysis exposed 75 patients without widespread pain (mean 7.13±3.79) and 31 patients with widespread pain (mean 9.52±4.93).Baseline PSQI and whether the patients had widespread pain was statistically significant (p 0.018).Conclusion:Overall, PsA patients with poor quality of sleep have higher levels in terms of self-reported pain and disease activity.The amount of good sleepers after 4 months increased, but there was a negative transition of patients going from good to poor sleepers. This could indicate that more factors are important for quality of sleep, e.g. sociopsychological aspects like anxiety, depression, ability to work.Table 1.Patient characteristicsTotaln = 109Good sleepersPSQI ≤ 5n = 37Poor sleepersPSQI &gt; 5n = 72nnpFemale, n (%)65 (59.4%)19 (51.4%)3746 (63.9%)720.206Age, yrs53.9 (45.4-62.25)60.4 (45.5-65.2)3751.5 (44.7-59.95)720.144Disease duration, yrs3.86 (1.0-11.0)4.5 (1.04-11.06)342.91 (1.0-10.75)680.352csDMARD, n (%)71 (65.1%)26 (70.2%)3745 (62.5%)720.420bDMARD, n (%)70 (64.2%)24 (64.8%)3746 (63.9%)720.920Patient pain assessment0-100 mm VAS50.0 (21.0-74.5)27.0 (9.0-60.5)3763.5 (32.25-78.0)72&lt;0.001Patient global assessment0-100 mm VAS61.0 (27.5-78.5)35.0 (17.5-59.0)3769.5 (50.0-85.75)72&lt;0.001PsAID fatigue6.0 (3.0-8.0)4.0 (2.5-7.0)376.5 (4.0-8.0)720.488HAQ score, 0-30.75 (0.38-1.25)0.38 (0.25-0.81)370.88 (0.63-1.38)72&lt;0.001PASI1.7 (0.0-9.75)2.0 (0.0-7.3)351.2 (0.0-11.5)650.940DAS28-CRP3.77 (3.02-4.58)3.44 (2.65-3.94)374.07 (3.28-4.93)720.001Disclosure of Interests:Peter Benzin: None declared., Zara Rebecca Stisen: None declared., Marie Skougaard: None declared., Tanja Schjødt Jørgensen Speakers bureau: Received consulting fees and/or speaking fees from AbbVie, Pfizer, Roche, Novartis, UCB, Biogen and Eli Lilly, Consultant of: Received consulting fees and/or speaking fees from AbbVie, Pfizer, Roche, Novartis, UCB, Biogen and Eli Lilly, Rebekka L. Hansen: None declared., Lourdes M. Perez-Chada: None declared., Mette Mogensen: None declared., Joseph F. Merola Consultant of: Consultant and/or investigator for Merck, Bristol-Myers Squibb, AbbVie, Dermavant, Eli Lilly, Novartis, Janssen, UCB, Sanofi, Regeneron, Arena, Sun Pharma, Biogen, Pfizer, EMD Sorono, Avotres and Leo Pharma., Lars Erik Kristensen Speakers bureau: Received fees for speaking and consultancy from Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly, and Janssen pharmaceuticals., Consultant of: Received fees for speaking and consultancy from Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly, and Janssen pharmaceuticals.

PurposeStudy the impact of impaired sleep quality on symptom change and future exacerbation of chronic obstructive pulmonary disease (COPD) patients.MethodsThis was a prospective study. Patients with COPD were recruited into the study and followed up for one year. Pittsburgh sleep quality index (PSQI) was collected at baseline. Symptom change was assessed with Minimum clinically important difference (MCID) in COPD Assessment Test (CAT) at 6-month visit, which is an indicator to assess symptom improvement. Exacerbation was recorded during the one-year visit. PSQI score > 5 was defined as poor sleep quality, whereas PSQI score ≤ 5 was defined as good sleep quality. MCID was defined as attaining a CAT decrease ≥ 2.ResultsA total of 461 patients were enrolled for final analysis. Two hundred twenty-eight (49.4%) patients had poor sleep quality. Overall, 224 (48.6%) patients attained MCID at 6-month visit and the incidence of exacerbation during the one-year visit was 39.3%. Fewer patients with impaired sleep quality achieved MCID than patients with good sleep quality. Good sleepers were significantly more likely to attain MCID (OR: 3.112, p < 0.001) than poor sleepers. Fewer poor sleepers in GOLD A and D groups attained MCID with ICS/LABA, and fewer poor sleepers in the GOLD D group attained MCID with ICS/LABA/LAMA than good sleepers. Poor sleep quality was a greater risk factor of future exacerbation in Cox regression analysis. The ROC curves showed that PSQI score had a predictive capacity for future exacerbation. More patients with poor sleep quality experienced future exacerbation in GOLD B and D group with treatment of ICS/LABA/LAMA compared to good sleepers.ConclusionsCOPD patients with impaired sleep quality were less likely to achieve symptom improvement and were at increased risk of future exacerbation compared to patients with good sleep quality. Besides, sleep disturbance may affect the symptom improvement and future exacerbation of patients with different inhaled medication or in different GOLD groups.

This study aims to determine the predictors of poor sleep quality in rheumatoid arthritis (RA). This was a monocentric, cross sectional, case-control study which was conducted at the Putrajaya Hospital, Malaysia. We recruited 46 patients with RA (3 males; 43 females; mean age 48.15±14.96) and 46 age and sex-matched healthy controls (3 males; 43 females; mean age 47.11±12.22). RA patients were assessed for their disease activity based on disease activity score in 28 joints, disease damage based on radiographic erosions, and functional status based on Health Assessment Questionnaire Disability Index. The Pittsburgh Sleep Quality Index (PSQI) scores were determined by interviewing all the subjects. Subjects with RA were further subdivided based on their PSQI scores as "good sleepers" with PSQI scores of <5 and "poor sleepers" with PSQI scores of ≥5. The percentage of poor sleepers was significantly higher among RA patients (47.83% versus 9.57%). Median scores of 5 out of 7 components of the PSQI were higher among RA patients compared to controls. Among poor sleepers with RA, a significantly higher proportion tested positive for anti-citrullinated cyclic peptide autoantibodies (p=0.037). Besides, poor sleepers had significantly higher median Health Assessment Questionnaire Disability Index (p=0.017) than good sleepers. However, both Health Assessment Questionnaire Disability Index (p=0.968) and anti-citrullinated cyclic peptide (p=0.431) were insignificant when entered in the equation of a logistic regression model. The findings of this study demonstrate a link between functional disability, anti-citrullinated cyclic peptide antibodies, and sleep quality in RA.

Poor sleep quality has been associated with increased risk of metabolic syndrome and type 2 diabetes as well as acceleration of neurodegenerative diseases. In rodents, sleep restriction decreases glucose transport into the brain via downregulation of GLUT1, the primary glucose transporter at the blood-brain barrier. However, little is known about the association between sleep quality and glucose transport and metabolism in the human brain. In this exploratory analysis, we quantified cerebral glucose levels amongst individuals with good and poor sleep quality as defined by the widely used and well-validated Pittsburgh Sleep Quality Index (PSQI), which assesses 7 different components of sleep quality over a 1 month time period (PSQI≥5 = Poor sleep; PSQI&amp;lt;5 = Good sleep). Twelve healthy subjects completed the PSQI questionnaire. Eight (6F, age 27.6 ± 5.7, BMI 26.6 ± 8.2 kg/m2, HgbA1c 5.4 ± 0.2%) had good and 4 (2F, age 29.5± 2.4, BMI 27.8 ± 6.5 kg/m2, HgbA1c 5.2 ± 0.2%) had poor sleep. All subjects underwent 13C magnetic resonance spectroscopy brain scanning at 4 Tesla during a 2-hour hyperglycemic clamp (plasma glucose target ∼180 mg/dl) to measure absolute cerebral glucose levels as part of a larger study to investigate obesity and cerebral glucose metabolism. There were no differences in age, BMI, or HbA1c levels between groups with good and poor sleep. Individuals with good sleep had 63% higher absolute cerebral glucose levels at steady state compared to those with poor sleep (3.4 ± 0.7 mmol/L vs. 2.1 ± 0.9 mmol/L, p=.017). Higher PSQI scores correlated with lower absolute cerebral glucose levels (r= -0.725, p=0.008, PSQI for all subjects (mean±SD) = 4 ± 2). In this pilot and exploratory study, individuals with poor sleep quality have significantly lower absolute cerebral glucose levels, which suggests an association between poor sleep and altered cerebral glucose transport and/or metabolism. These findings may have wide-ranging implications for understanding the effects of sleep on brain function. Disclosure T.K. Stanley: None. F. Gunawan: None. N.S. Redeker: None. L. Jiang: None. A. Coppoli: None. D.L. Rothman: None. G.F. Mason: None. J. Hwang: Research Support; Self; General Electric. Funding American Diabetes Association (1-17-ICTS-013 to J.H.); National Institutes of Health (1R03DK121048)

This field study (a) assessed sleep quality of sailors on the U.S. Navy (USN) ships while underway, (b) investigated whether the Pittsburgh Sleep Quality Index (PSQI) scores were affected by occupational factors and sleep attributes, and (c) assessed whether the PSQI could predict impaired psychomotor vigilance performance. Longitudinal field assessment of fit-for-duty USN sailors performing their underway duties (N = 944, 79.0% males, median age 26 years). Participants completed questionnaires, wore actigraphs, completed logs, and performed the wrist-worn 3-min Psychomotor Vigilance Task (PVT). Sailors slept on average 6.60 ± 1.01 h/day with 86.9% splitting their sleep into more than one episode/day. The median PSQI Global score was 8 (interquartile range [IQR] = 5); 80.4% of the population were classified as "poor sleepers" with PSQI scores >5. PSQI scores were affected by sailor occupational group, rank, daily sleep duration, and number of sleep episodes/day. Sleep quality showed a U-shape association with daily sleep duration due to the confounding effect of split sleep. Sailors with PSQI scores >9 had 21.1% slower reaction times (p < 0.001) and 32.8%-61.5% more lapses combined with false starts (all p < 0.001) than sailors with PSQI scores ≤9. Compared to males and officers, females and enlisted personnel had 86% and 23% higher risk, respectively, of having PSQI scores >9. Sailors in the PSQI > 9 group had more pronounced split sleep. Working on Navy ships is associated with elevated PSQI scores, a high incidence of poor sleep, and degraded psychomotor vigilance performance. The widely used PSQI score>5 criterion should be further validated in active-duty service member populations.

Background: Emerging evidence suggests a bidirectional relationship between systemic inflammation and both epilepsy and sleep dysfunction. High-sensitivity C-reactive protein (Hs-CRP), a sensitive marker of low-grade systemic inflammation, is elevated in response to pro-inflammatory cytokines. However, the specific link between Hs-CRP levels and subjective sleep quality within the epilepsy population required further investigation. This study aimed to investigate the relationship between serum Hs-CRP levels and sleep quality in patients diagnosed with epilepsy. Methods: A cross-sectional study was conducted involving 40 patients diagnosed with epilepsy attending the neurology clinic at Dr. M. Djamil General Hospital, Padang, Indonesia, between January and February 2025. Patients aged over 17 years diagnosed by a neurologist were included. Serum Hs-CRP levels were quantified using an enzyme-linked immunosorbent assay (ELISA). Sleep quality over the preceding month was assessed using the validated Indonesian version of the Pittsburgh Sleep Quality Index (PSQI). Mann-Whitney U test was employed to analyze the difference in median Hs-CRP levels between patients with good and poor sleep quality. Relationships between baseline characteristics and sleep quality were assessed using Chi-square/Fisher's exact tests for categorical variables and the Mann-Whitney U test for continuous variables. Results: Forty epilepsy patients (median age 25.5 years, range 17-50; 52.5% female) were enrolled. The median duration of epilepsy was 10 years (range 1-35). A majority of patients exhibited uncontrolled seizures (75%) and were receiving AED polytherapy (60%). Based on PSQI scores, 24 patients (60%) were classified as poor sleepers, while 16 (40%) were good sleepers. A significant difference was observed in median serum Hs-CRP levels between the two groups: patients with good sleep quality had significantly lower median Hs-CRP levels compared to those with poor sleep quality (1,271.50 ng/ml [range 58–5,837] vs. 2,771.50 ng/ml [range 509–27,187], p=0.027). Poor sleep quality was significantly associated with younger age (median 23 vs. 36 years, p=0.039) and AED polytherapy (75% vs. 25%, p=0.018). Conclusion: This study demonstrated a significant association between elevated serum Hs-CRP levels and poor subjective sleep quality in patients with epilepsy. Epilepsy patients experiencing poor sleep exhibited significantly higher levels of this inflammatory biomarker. These findings underscore the potential role of systemic inflammation in the complex interplay between epilepsy and sleep disturbances, suggesting Hs-CRP could serve as a potential biomarker linking these conditions.

Policing is an intense and stressful profession since police officers (PO) deal with different types of crimes and job-related situations that often are life-threatening. Studies have shown that policing routine may negatively impact the PO's sleep and quality of life, making those two aspects important indicators to be better understood among PO. PURPOSE: To investigate sleep quality (SQ) and quality of life (QoL) among Brazilian Civil Police Officers, and its associations. METHODS: We evaluated 55 PO (50.9% men) with a mean age of 28.1 ± 5.7 yrs, BMI of 25.8 ± 3.8 kg/m2, VO2max of 34.1 ± 7.3 ml•(kg•min)-1. We assessed SQ and QoL by validated self-report questionnaires. Participants completed the Pittsburgh Sleep Quality Index (PSQI), and the World Health Organization Quality of Life (WHOQOL) questionnaires. SQ was categorized as poor (PSQI score ≥ 5) or good (PSQI score < 5). The 26-item WHOQOL questionnaire assesses QoL in four domains: physical, psychological, social, and environmental. We compared QoL between poor and good sleepers using the Mann-Whitney test (p ≤ 0.05). Data are presented as median and extremes (min-max). RESULTS: 16 (29,1%) PO were classified as good sleepers. The QoL was 71.4 (25.0-96.4) in the physical domain, 70.8 (29.2-100.0) in the psychological, 75.0 (41.7-100.0) in the social and 65.6 (15.6-93.8) in the environmental one. Those with good SQ showed higher physical domain of QoL [76.8 (64.3-96.4)] as compared to the poor sleepers [67.9 (25.0-96.4)] (p = 0.001 - Figure 1). CONCLUSION: This sample of civil PO showed a high proportion of poor sleepers and median QoL that could be considered relatively impaired (≤75% of the maximum). Also, better scores of SQ were associated with higher scores in the QoL physical domain. Our findings highlight the importance to assess and promote SQ and QoL among those public safety professionals.

To compare pain characteristics, functional limitation, psychosocial factors, and sociodemographic characteristics between patients with chronic LBP reporting good or poor sleep quality. A secondary analysis of 444 patients with a current episode of chronic low back pain (CLBP). Sleep quality was measured by an item of the Pittsburgh Sleep Quality Index (PSQI). Pain intensity (two items from The Brief Pain Inventory, BPI), functional limitation (The Patient-Specific Functional Scale, PSFS, and BPI), and psychosocial factors (The Brief Screening Questions, BSQ) were also assessed. Features of participants with good and poor sleep quality were compared. Participants were classified as "good sleep quality" (n = 228) or "poor sleep quality" (n = 216). Those with poor sleep quality showed greater functional limitations (Good sleepers = 5.38 ± 2.54; Poor sleepers = 6.48 ± 2.35; p < 0.01), higher pain interference with functionality (Good sleepers = 35.90 ± 23.87; Poor sleepers = 50.84 ± 26.89; p < 0.01), and more significant psychosocial issues, such as anxiety [Good sleepers = 165 (37%); Poor sleepers = 186 (42%); p < 0.01], and depressive symptoms [Good sleepers = 37 (8%); Poor sleepers = 73 (16%); p < 0.01]. Chronic LBP patients with poor sleep quality significantly faced more functional limitation, increased pain interference, and a higher prevalence of psychological problems, including anxiety and depression, than those with good sleep quality. Our results emphasize the impact of poor sleep quality in clinical measures of LBP patients.

Objective:To examine the associations between eating behavior traits and weight loss according to sleep quality and duration in adults enrolled in common weight-loss interventions.Methods:Participants included overweight and obese men and women (n=150) (mean±s.d. age, 38.8±8.6 years; mean±s.d. body mass index (BMI), 33.3±3.5 kg m−2) who were subjected to a dietary intervention over a period of 12–16 weeks. Anthropometric measurements, eating behavior traits (Three-Factor Eating Questionnaire), sleep quality (total Pittsburgh Sleep Quality Index (PSQI) score) and sleep duration (hours per night, self-reported from the PSQI) were assessed at both baseline and post intervention. Linear regression analysis was used to quantify the relationships between eating behavior traits and changes in anthropometric markers for all subjects and by sleep categories (short sleep: <7 h per night vs recommended sleep: ⩾7 h per night; poor sleep quality: ⩾5 PSQI score vs good sleep quality: <5 PSQI score). We adjusted for age, sex and baseline BMI in analyses.Results:Baseline eating behavior traits were modest predictors of weight-loss success, but they were all significantly associated with their changes over the weight-loss intervention (P<0.01). The diet intervention induced significant changes in eating behavior traits and even more for those having a non-favorable eating behavior profile at baseline. We observed that changes in flexible control and strategic dieting behavior were constantly negatively associated with changes in body weight and fat mass (P<0.05) for recommended duration sleepers. The change in situational susceptibility to disinhibition was positively associated with the change in fat mass and body weight for those having healthy sleeping habits (P<0.05). For poor quality sleepers, the change in avoidance of fattening foods was negatively associated with changes in adiposity (P<0.05).Conclusion:Eating behavior traits and sleep may act together to influence the outcome of weight-loss programs.

Impact of resistance training on sleep quality, mental health, and functional capacity in older women with varying baseline sleep quality: A randomized controlled trial.