The causal relationship between sleep and risk of psychiatric disorders: A two-sample mendelian randomization study.

Introduction: Sleep is associated with psychiatric disorders. However, their causality remains unknown. Methods: The study explored the causal relationship between seven sleep parameters (sleep duration, insomnia, sleep apnea, chronotype, daytime dozing, napping during the day, and snoring) and three psychiatric disorders including major depressive disorder (MDD), schizophrenia, and attention-deficit/hyperactivity disorder (ADHD) using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for sleep parameters were obtained from the United Kingdom biobank, FinnGen biobank, and EBI databases. MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW(fixed effects) were used to perform the MR analysis. The heterogeneity was detected by Cochran's Q statistic. The horizontal pleiotropy was detected by MR Egger. The sensitivity was investigated by the leave-one-out analysis. Results: Insomnia (OR = 2.02, 95%CI = 1.34-3.03, p = 0.001, False-discovery rate (FDR) corrected p-value = 0.011) and napping during the day (OR = 1.81, 95%CI = 1.34-2.44, FDR corrected p-value<0.001) were associated with an increased risk of MDD. Longer sleep duration (OR = 2.20, 95%CI = 1.24-3.90, FDR corrected p-value = 0.049) had an association with the increased risk of schizophrenia, while daytime dozing (OR = 4.44, 95%CI = 1.20-16.41, corrected p-value = 0.088)and napping during the day (OR = 2.11, 95%CI = 1.11-4.02, FDR corrected p-value = 0.088) had a suggestive association with an increased risk of schizophrenia. Longer sleep duration had a suggestive association with a decreased risk of ADHD (OR = 0.66, 95%CI = 0.42-0.93, FDR corrected p-value = 0.088). Conclusion: This study provides further evidence for a complex relationship between sleep and psychiatric disorders. Our findings highlight the potential benefits of addressing sleep problems in the prevention of psychiatric disorders.

The relationship between daytime napping and glycemic control in people with type 2 diabetes.

Aim: To examine the association between napping characteristics and glycemic control in people with type 2 diabetes. Design: This study used a cross-sectional design. Methods: A convenience sample of people with type 2 diabetes (N=226) were included. Glycemic control was indicated by HbA1c which was measured by A1C Now®+. Napping characteristics including napping frequency, duration, timing, and type were measured by validated questionnaires. Other variables, such as insomnia, cognitive impairment, and depression were measured by the Insomnia Severity Index, Montreal Cognitive Assessment, and Patient Health Questionnaire-9, respectively. Multivariate linear regression analyses were performed. Results: The sample consisted of 122 women (54.0%), with a median age of 67 years. Their median HbA1c was 6.8%. No significant relationship was found between napping frequency and HbA1c. Among nappers, after controlling for covariates, long napping duration (≥60 min) and morning napping were both associated with poorer glycemic control. Compared with appetitive napping, restorative napping was associated with better glycemic control. Conclusion: Daytime napping (e.g., duration and type) is an important modifiable factor for glycemic control in people with type 2 diabetes. This study provides new insights into the relationship between napping and glucose management among people with diabetes.

Sleep health predicted glucose metabolism among pregnant women: A prospective cohort study.

AIMS: To examine whether sleep health in the first trimester could predict glucose metabolism in the second trimester. METHODS: Pregnant women (N = 127) during the first trimester were recruited (August 2022 to March 2023). Overall sleep health was assessed by the Sleep Health Index. Various dimensions of sleep health were measured using a 7-day sleep diary and questionnaires. The outcomes, including diagnosis of gestational diabetes mellitus (GDM) and HbA1c, were obtained from the medical records in the second trimester. Poisson regression analysis and multiple linear regression were used for data analysis. RESULTS: The average age of the participants was 32.6 years. The incidence of GDM was 28.3 % and the mean HbA1c was 5.2 % (33 mmol/mol). Sleep duration regularity (RR = 1.808; 95 %CI 1.023, 3.196) was associated with GDM after controlling for confounders. SHI total score (ß = -0.278; 95 %CI -0.022, -0.005) and sleep duration regularity (ß = 0.243; 95 %CI 0.057, 0.372) were associated with HbA1c. CONCLUSIONS: Worse sleep health, particularly lower sleep regularity, predicted worse glucose metabolism among pregnant women. Healthcare professional may consider adding sleep-related assessment to prenatal care. Maintaining regular sleep should be encouraged. Studies examining the impact of sleep intervention on glucose metabolism among pregnant women are warranted.

Validity and reliability of the sleep health index among patients with spinal degenerative diseases.

OBJECTIVE: To test the validity and reliability of the Sleep Health Index (SHI) in a Chinese clinical sample, and thereby provide more evidence for the assessment of sleep health in future research and clinical practice. METHODS: This study used a cross-sectional design. A convenient sample of 265 participants with spinal degenerative diseases was recruited from outpatient clinics. The SHI, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Patient Health Questionnaire-9 (PHQ-9), Visual Analogue Scale (VAS), and EuroQoL 5-Dimension 5-Level (EQ-5D-5L) were administered via REDCap. Structural, concurrent, convergent, known-group validity, internal consistency, and test-retest reliability were evaluated. RESULTS: Confirmatory factor analysis confirmed a 3-factor structure (sleep duration, sleep quality, and disordered sleep). The overall SHI score had a high correlation with PSQI and ISI (r = -0.62 and -0.70, respectively) as well as a moderate correlation with PHQ-9 (r = -0.50, p<0.001). The overall SHI was significantly associated with VAS, ESS, and EQ-5D-5L (r = -0.15 to -0.23, p<0.05). Participants with pain had a lower score on the sleep quality sub-index than those without (p<0.001). Those with chronic diseases had a significantly lower score on the sleep duration sub-index than those without (p<0.05). Those with depression, poor sleep quality, and insomnia had lower scores on the overall scale and the three sub-indices than those without (p<0.05). The overall SHI showed acceptable internal consistency (Cronbach's α = 0.74) and test-retest reliability (intraclass correlation coefficient = 0.73). CONCLUSIONS: The Chinese version of SHI showed good validity and acceptable reliability and could be used to assess sleep health among clinical populations.

Information Needs and Its Association With Depressive Symptoms in People With Type 2 Diabetes.

PURPOSE: The purpose of this study was to describe the information needs and examine its association with depressive symptoms in people with type 2 diabetes (T2D). METHODS: A descriptive, correlational design was used. People with T2D (N = 358) were recruited from 12 communities in Shanghai, China. Self-reported information needs and depressive symptoms were measured using the Information Needs in Diabetes Questionnaire and Patient Health Questionnaire-9 (PHQ-9), respectively. Multivariate linear regression analysis was performed. RESULTS: The participants were 64.8 years on average, and 46.6% were men. One hundred fifty-one (42.2%) had depressive symptoms (PHQ-9 ≥ 5). Participants had the least knowledge about "diabetes research," "acute complications," and "lifestyle adjustment." The sample had the highest levels of information needs about topics including "mental strain," "treatment/therapy," and "diabetes in everyday life." Compared to those without depressive symptoms, those experiencing depressive symptoms were less informed and had higher levels of need for further information. Controlling for covariates, higher levels of need for further information were significantly associated with greater depressive symptoms (B = 0.368, 95% CI, 0.155-0.582, P = .001). CONCLUSIONS: This study demonstrated areas that should be prioritized when meeting patients' information needs. It also showed the potential negative effect of unmet information needs on depression. These findings may help develop a more tailored intervention for people with T2D.

Multidimensional sleep health and diabetic retinopathy: Systematic review and meta-analysis.

Diabetic retinopathy (DR) is one of the most prevalent microvascular diabetic complications. Poor sleep health and obstructive sleep apnea (OSA) are risk factors for diabetes and poor glycemic control. Recent studies have suggested associations between poor sleep health/OSA and DR. Furthermore, there have been suggestions of melatonin dysregulation in the context of DR. We conducted a systematic review and meta-analysis exploring the associations between multidimensional sleep health (duration, satisfaction, efficiency, timing/regularity and alertness), OSA and melatonin with DR. Forty-two studies were included. Long, but not short sleep, was significantly associated with DR, OR 1.41 (95%CI 1.21, 1.64). Poor sleep satisfaction was also significantly associated with DR, OR 2.04 (1.41, 2.94). Sleep efficiency and alertness were not associated with DR, while the evidence on timing/regularity was scant. Having OSA was significantly associated with having DR, OR 1.34 (1.07, 1.69). Further, those with DR had significantly lower melatonin/melatonin metabolite levels than those without DR, standardized mean difference -0.94 (-1.44, -0.44). We explored whether treating OSA with continuous positive airway pressure (CPAP) led to improvement in DR (five studies). The results were mixed among studies, but potential benefits were observed in some. This review highlights the association between poor multidimensional sleep health and DR.

Bidirectional Associations between Parental Feeding Practices and Child Eating Behaviors in a Chinese Sample.

BACKGROUND: Child eating behaviors (CEBs) and parental feeding practices (PFPs) play critical roles in childhood obesity. However, the bidirectional relationships between CEBs and PFPs remain equivocal. This longitudinal study aimed to explore their bidirectional relationships. METHODS: A convenience sample of 870 parents with preschoolers was recruited in this longitudinal study (Shanghai, China). Three non-responsive feeding practices (NFPs), three responsive feeding practices (RFPs), five CEBs, and covariates were collected using validated questionnaires at baseline and the 6-month follow-up. Cross-lagged analyses using structural equation modeling (SEM) were performed to examine their bidirectional relationships. RESULTS: Eight hundred and fifty-three parents completed questionnaires, with a response rate of 98%. The mean age of their children at baseline was 4.39 years (standard deviation = 0.72 years). Eighteen out of sixty longitudinal cross-lagged paths were statistically significant. Parental encouragement of healthy eating and content-restricted feeding were found to be bidirectionally associated with child food fussiness. Four parent-driven associations and one child-driven association were identified between RFPs and CEBs. For example, monitoring was negatively associated with children's unhealthy eating habits (ß = -0.066, standard error (SE) = 0.025, p < 0.01). Eight child-driven associations and one parent-driven association were observed between NFPs and CEBs. For example, higher child satiety responsiveness predicted a higher pressure to eat (ß = 0.057, SE = 0.029, p < 0.01) and the use of food as a reward (ß = 0.083, SE = 0.031, p < 0.01). CONCLUSIONS: There were bidirectional, parent-driven, and child-driven associations. Parents should be encouraged to adopt RFPs to shape CEBs. Increasing parents' understanding of CEBs and providing them with reasonable coping strategies would help optimize PFPs.