Background Smartphones and wearable devices can be used to obtain diverse daily log data related to circadian rhythms. For patients with mood disorders, giving feedback via a smartphone app with appropriate behavioral correction guides could play an important therapeutic role in the real world. Objective We aimed to evaluate the effectiveness of a smartphone app named Circadian Rhythm for Mood (CRM), which was developed to prevent mood episodes based on a machine learning algorithm that uses passive digital phenotype data of circadian rhythm behaviors obtained with a wearable activity tracker. The feedback intervention for the CRM app consisted of a trend report of mood prediction, H-score feedback with behavioral guidance, and an alert system triggered when trending toward a high-risk state. Methods In total, 73 patients with a major mood disorder were recruited and allocated in a nonrandomized fashion into 2 groups: the CRM group (14 patients) and the non-CRM group (59 patients). After the data qualification process, 10 subjects in the CRM group and 33 subjects in the non-CRM group were evaluated over 12 months. Both groups were treated in a similar manner. Patients took their usual medications, wore a wrist-worn activity tracker, and checked their eMoodChart daily. Patients in the CRM group were provided with daily feedback on their mood prediction and health scores based on the algorithm. For the CRM group, warning alerts were given when irregular life patterns were observed. However, these alerts were not given to patients in the non-CRM group. Every 3 months, mood episodes that had occurred in the previous 3 months were assessed based on the completed daily eMoodChart for both groups. The clinical course and prognosis, including mood episodes, were evaluated via face-to-face interviews based on the completed daily eMoodChart. For a 1-year prospective period, the number and duration of mood episodes were compared between the CRM and non-CRM groups using a generalized linear model. Results The CRM group had 96.7% fewer total depressive episodes (n/year; exp β=0.033, P=.03), 99.5% shorter depressive episodes (total; exp β=0.005, P<.001), 96.1% shorter manic or hypomanic episodes (exp β=0.039, P<.001), 97.4% fewer total mood episodes (exp β=0.026, P=.008), and 98.9% shorter mood episodes (total; exp β=0.011, P<.001) than the non-CRM group. Positive changes in health behaviors due to the alerts and in wearable device adherence rates were observed in the CRM group. Conclusions The CRM app with a wearable activity tracker was found to be effective in preventing and reducing the recurrence of mood disorders, improving prognosis, and promoting better health behaviors. Patients appeared to develop a regular habit of using the CRM app. Trial Registration ClinicalTrials.gov NCT03088657; https://clinicaltrials.gov/ct2/show/NCT03088657
An association between fiber intake and allergic diseases in children has been reported; however, many studies have not been conducted to assess this association in adults. We aimed to evaluate the association between dietary fiber intake and allergic diseases (asthma, allergic rhinitis, and atopic dermatitis) among 10,479 adults using data from the Korean National Health and Nutrition Examination Survey (2010–2011). As dietary fiber intake increased, the prevalence of asthma (Q4 adjusted odds ratio (OR): 0.656; 95% confidence interval (CI): 0.48–0.91, p for trend < 0.0001) and atopic dermatitis (Q3 crude OR: 0.746; 95% CI: 0.57–0.98; Q4 adjusted OR: 0.712; 95% CI: 0.50–1.01, p for trend < 0.0001) decreased. The prevalence of allergic rhinitis (Q2 adjusted OR: 0.840; 95% CI: 0.70–1.00, p for trend < 0.0001) tended to decrease, especially in males. Subgroup analysis revealed that fiber intake reduced allergic rhinitis symptoms, including watery rhinorrhea (Q3 adjusted OR: 0.734; 95% CI: 0.55–0.97; Q4 adjusted OR: 0.722; 95% CI: 0.54–0.97) and dog allergen sensitization (Q3 adjusted OR: 0.319; 95% CI: 0.13–0.82; Q4 adjusted OR: 0.338; 95% CI: 0.13–0.86), exclusively in males. Thus, dietary fiber intake influences allergic diseases in adults, especially males.
BackgroundStatin therapy reduces the risk of cardiovascular events across a broad spectrum of patients; however, it increases the risk of new-onset diabetes (NOD). Although the highest dose pitavastatin is considered to not be associated with NOD, there are limited data regarding the impact of long-term highest dose pitavastatin use on the development of NOD in patients at high risk of developing diabetes. Therefore, we prospectively compared the differences in the development of NOD between the lowest and the highest dose of pitavastatin in patients at high risk of developing diabetes during a 3-year follow-up.MethodsThis post hoc analysis of a prospective, single-blinded, randomized study compared the risk of NOD between the highest dose of pitavastatin (4 mg) and the lowest dose of pitavastatin (1 mg) over a 3-year follow-up in patients with acute coronary syndrome. Among 1044 patients of the original study, 667 patients at high risk of developing type 2 diabetes mellitus were in the subgroup analysis. The primary endpoint was a comparison of the differences in the cumulative incidence of NOD in the pitavastatin 1 mg and 4 mg groups during a 3-year follow-up.ResultsWith propensity score matching, there were no significant differences in baseline demographic characteristics between the 2 groups. Incidence of NOD was similar between the pitavastatin 1 mg and 4 mg groups [12 of 289 patients (4.2%) and 8 of 289 patients (2.8%), respectively; p = 0.36]. In a prespecified analysis, there were no significant differences in NOD events according to sex, age, diagnosis, body mass index, glucose intolerance, or dyslipidemia.ConclusionsAdministration of highest-dose pitavastatin did not increase the risk of NOD in patients at high risk of developing diabetes during the 3-year follow-up. Moreover, various risk factors for NOD such as metabolic syndrome components, glucose intolerance, dyslipidemia, obesity, or hypertension did not affect the development of NOD during pitavastatin administration. Thus, the highest dose pitavastatin can be safely used in patients with metabolic syndrome who are at high risk of developing diabetes.Trial registration Clinical Trial registration information. URL: https://clinicaltrials.gov/ct2/show/NCT02545231. Unique identifier: NCT02545231
BackgroundUnhealthy body composition, including high fat mass, low muscle mass and low bone mass, is a critical health issue in adults. The weight‐adjusted waist index (WWI) estimates fat and muscle mass and may have implications for bone health. We examined its association with body composition outcomes in a large Korean adult cohort.MethodsThis study used data from the Korean National Health and Nutrition Examination Survey (2008–2011). WWI was calculated as waist circumference (cm) divided by the square root of body weight (kg). Dual‐energy X‐ray absorptiometry was used to measure bone mineral density (BMD), appendicular lean mass (ALM) and total body fat percentage. Unhealthy body composition was defined as combined presence of high fat mass, low bone mass and low muscle mass.ResultsA total of 5983 individuals (3034 men [50.7%] and 2949 women [49.3%]; mean age: 63.5 ± 8.7 years) were included. WWI was positively correlated with total body fat percentage (r = 0.478, P < 0.001) and inversely with ALM/weight (r = −0.485, P < 0.001) and BMD at the lumbar spine (r = −0.187, P < 0.001), femoral neck (r = −0.269, P < 0.001) and total hip (r = −0.255, P < 0.001). Higher WWI quartiles correlated with lower BMD, T‐scores and ALM/weight, along with increased total body fat, evident in both genders and more pronounced in women, even after adjusting for confounders. This trend remained statistically significant across WWI quartiles for all analyses (P < 0.001). Higher WWI quartiles were also significantly associated with higher odds of unhealthy body composition, with adjusted odds ratio in the highest WWI group of 18.08 (95% CI, 4.32–75.61) in men and 6.36 (95% CI, 3.65–11.07) in women. The optimal cutoff values of WWI for unhealthy body composition were 10.4 cm/√kg in men and 10.5 cm/√kg in women.ConclusionsIn community‐dwelling adults, high WWI values are associated with unfavourable body composition outcomes, indicating high fat mass, low muscle mass and low bone mass. WWI can potentially serve as an integrated index of body composition, underscoring the need for further research to validate its use in clinical settings.
Background: Many mood disorder patients experience seasonal changes in varying degrees. Studies on seasonality have shown that bipolar disorder has a higher prevalence rate in such patients; however, there is limited research on seasonality in early-onset mood disorder patients. This study estimated the prevalence of seasonality in early-onset mood disorder patients, and examined the association between seasonality and mood disorders. Methods: Early-onset mood disorder patients (n = 378; 138 major depressive disorder; 101 bipolar I disorder; 139 bipolar II disorder) of the Mood Disorder Cohort Research Consortium and healthy control subjects (n = 235) were assessed for seasonality with Seasonality Pattern Assessment Questionnaire (SPAQ).Results: A higher global seasonality score, an overall seasonal impairment score, and the prevalence of seasonal affective disorder (SAD) and subsyndromal SAD showed that mood disorder subjects had higher seasonality than the healthy subjects. The former subject group had a significantly higher mean overall seasonal impairment score than the healthy subjects (p < .001); in particular, bipolar II disorder subjects had the highest prevalence of SAD, and the diagnosis of bipolar II disorder had significantly higher odds ratios for SAD when compared to major depression and bipolar I disorder (p < .05).Conclusions: Early-onset mood disorders, especially bipolar II disorder, were associated with high seasonality. A thorough assessment of seasonality in early-onset mood disorders may be warranted for more personalized treatment and proactive prevention of mood episodes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.