Subtypes of major depressive disorders and objectively measured physical activity and sedentary behaviors in the community

Factors related to sedentary behavior in older adult stroke patients in China: a study based on decision tree and logistic regression model

Objective

This study investigates the factors influencing sedentary behavior in older adult Chinese stroke patients using decision trees and logistic regression models.

Methods

Convenience sampling method was employed to enroll 346 respondents aged ≥60 years with stroke from the Department of Neurology of three tertiary-level A hospitals in Heilongjiang province, based on the inclusion criteria. The Sedentary Behavior Questionnaire for Older Adults, the International Physical Activity Questionnaire Short Form (IPAQ-S), the Pittsburgh Sleep Quality Index (PSQI), the Self-Rating Depression Scale (SDS), and the Social Support Scale (SSRS) were used to assess sedentary behavior, physical activity level, sleep quality, depressive symptoms, and social support, respectively. Decision tree and logistic regression models were employed to analyze the factors related to sedentary behavior in older adult stroke patients.

Results

Of the 346 respondents, 233 (67.3%) had sedentary behavior. The logistic regression model showed that education level (OR = 2.843, 95%CI: 1.219-6.626), BMI (OR = 3.686, 95%CI: 1.838-7.393), longest consecutive sitting time (OR = 3.853, 95%CI: 1.867-7.953), and sleep quality (OR = 3.832, 95%CI: 1.716-8.557) were identified as risk factors for sedentary behavior in older adult stroke patients, while drink alcohol (OR = 0.386, 95%CI: 0.184-0.809) and physical activity level (OR = 0.064, 95%CI: 0.030-0.140) were identified as protective factors for sedentary behavior. Besides, the decision tree model showed that physical activity level, longest consecutive sitting time, sleep quality, BMI, depressive symptoms, and age were associated with sedentary behavior. The sensitivity and specificity of the logistic regression model were 69.9 and 93.1%, respectively, and the area under the receiver operating characteristic (ROC) curve was 0.900 (95% CI: 0.863-0.938). The sensitivity and specificity of the decision tree model were 66.4, and 93.1% respectively, and the area under the ROC curve was 0.860 (95% CI: 0.816-0.904).

Conclusion

Our findings indicated that physical activity level, longest consecutive sitting time, sleep quality, and BMI were key factors associated with sedentary behavior. To achieve the purpose of improving rehabilitation effect and quality of life, this study combining decision trees with logistic regression models was of high value in studying factors influencing sedentary behavior in older adult stroke patients.

The Absence of Items Addressing Increased Appetite or Weight in Depressive-Symptom Questionnaires: Implications for Understanding the Link between Major Depressive Disorder, Antidepressants, and Obesity

Major depressive disorder (MDD) and obesity have a complex bidirectional relationship. However, most studies do not assess increased appetite or weight as a depressive symptom due to limitations in rating scales. Here we aimed to analyze frequently employed depressive-symptom scales and discuss the relevance of weight and appetite assessment items. To elaborate this perspective, we searched for validated questionnaires and scales evaluating depressive symptoms in English. We analyzed appetite and weight items from 20 depressive-symptoms rating scales. Only 8 of 20 rating scales assessed for increased weight or appetite. The scales reported in the literature as the most employed in antidepressants efficacy trials do not assess increased appetite or weight. The current use of rating scales limits our understanding of the relationship between MDD, antidepressants, and obesity. It is necessary to improve our weight and appetite measurements in MDD to clarify the respective impact of depressive symptoms and antidepressants on weight change.

Physical activity and lung function association in a healthy community-dwelling European population

BACKGROUND

The association of physical activity (PA) and lung function (LF) varies from no measurable effect to delayed LF decline. We assessed the association between accelerometery-assessed PA and LF in a sample of apparently healthy, community-dwelling subjects.

METHODS

We included two cross-sectional studies using data from the PneumoLaus study (2014-17 and 2018-21), conducted in Lausanne, Switzerland. PA was assessed by accelerometry and categorised as inactivity, light, moderate or vigorous. Forced expiratory volume in 1 second (FEV1), forced volume capacity (FVC) and maximal mid-expiratory flow (MMEF) were measured by spirometry and expressed in percentage of predicted value (PV).

RESULTS

Overall, 1'910 (54.7% women, 62.0 ± 9.7 years) and 1'174 (53.4% women, 65.8 ± 9.5 years) participants were included in the first and the second surveys, respectively. In both surveys, moderate and vigorous PA showed a weak but significant correlation with FEV1 in percentage (PV) (R = 0.106 and 0.132 for the first and 0.111 and 0.125 for the second surveys, p < 0.001). Similar correlations with FVC (p < 0.001) were found. Associations held irrespective of smoking status and remained after multivariable adjustment. Fewer associations were detected between LF and light PA or between MMEF and PA.

CONCLUSION

Moderate and vigorous intensity PA are associated with increased LF regardless of smoking status in apparently healthy community-dwelling European population. These associations are statistically but not clinically significant due to the small correlation coefficients (R < 0.30), corresponding to a weak association.