Association of the "Weekend Warrior" and Other Physical Activity Patterns with Metabolic Syndrome in the South Korean Population

Whether weekend warriors (WWs) achieve equivalent benefits in lipid accumulation products (LAP) reduction as other leisure-time physical activity patterns? -Results from a population-based analysis of NHANES 2007-2018

BACKGROUND

Obesity is characterized by excessive fat accumulation in the body. Physical activity (PA) is an effective intervention to combat obesity, but the effectiveness of different PA patterns on controlling obesity is unclear. Lipid accumulation product (LAP), derived from waist circumference and triglycerides, is a novel indicator for obesity evaluation. However, the association between PA patterns (i.e., weekend warriors and regularly active) and LAP remains unexplored. This study aims to elucidate the relationship between PA patterns and LAP in US adult population.

METHODS

Adult individuals with complete data on LAP, PA patterns, and other covariates from the National Health and Nutrition Examination Survey (NHANES) database (2007-2018) were included in this study. Multivariate linear regression models were utilized to explore the association between PA patterns and LAP. Subgroup analyses, interaction tests, restricted cubic spline (RCS) regression analyses, and threshold and saturation effect analyses were also performed to investigate the stability and nonlinearity of PA-LAP association, respectively.

RESULTS

A total of 11,212 participants were included in this study. After adjusting for all potential covariates, being regularly active (RA) (β=-8.85, P < 0.05) obtained significantly higher LAP reduction as opposed to being weekend warriors (WWs) (β=-4.70, P = 0.3841). Furthermore, subgroup analyses and interaction tests indicated that the PA-LAP association was more pronounced in individuals with higher education levels (P interaction = 0.0084) and diabetes (P interaction = 0.0062). Additionally, a significant, non-linear, and negative correlation between weekly total PA and LAP in non-inactive individuals was identified by RCS analysis (P for overall < 0.001, P for nonlinearity = 0.009). A threshold of 440 min in weekly total PA was found to arouse favorable LAP reduction.

CONCLUSIONS

Being regularly active obtained better LAP reduction as opposed to being WWs. For non-inactive adults, engaging in more than 440 min of PA per week helps to reduce LAP effectively.

The association between different physical activity (PA) patterns and cardiometabolic index (CMI) in US adult population from NHANES (2007-2016)

Background

Physical activity (PA) is widely recommended for preventing and combating obesity, but the most effective PA pattern for treating obesity remains unclear. Cardiometabolic index (CMI), derived from waist height ratio and triglycerides to high-density lipoprotein-cholesterol ratio, is a novel indicator for evaluating obesity. However, the relationship between different PA patterns and CMI remains unelucidated.

Objective

This study aimed to explore the association between different PA patterns and CMI in U.S. adults.

Methods

Participants with complete information in CMI, PA patterns, and other covariates in the National Health and Nutrition Examination Survey database (2007-2016) were included in this study. Multivariate linear regression models were utilized to explore the relationship between PA patterns and CMI. Moreover, stratified analyses, interaction tests and restricted cubic spline (RCS) regression analysis were used to investigate the stability and nonlinearity of the association, respectively.

Results

A total of 16,442 adults were included in this study. After adjusting for all potential covariates, only the regularly active group was significantly associated with CMI reduction (β = -0.13, 95% CI: 0.19 to -0.07, P < 0.0001), while the weekend warriors group did not achieve equivalent CMI reduction (β = -0.09, 95% CI: 0.32 to 0.14, P = 0.4204). Subgroup analyses and interaction tests revealed that the CMI-PA association was more pronounced in the subgroup with age≤45 or >60, with higher education level, and who are current drinkers. Furthermore, RCS analysis indicated that total PA in a week was significantly, nonlinearly associated with CMI in non-inactive adults, and that a total of PA more than 330 min can reap favorable CMI reduction.

Conclusion

Being regularly active is associated with significant CMI reduction, while being weekend warriors and insufficiently active do not achieve equivalent benefits. For non-inactive individuals, engaging in PA for more than 330 min weekly helps to reduce CMI effectively.

Association of domain-specific physical activity with albuminuria among prediabetes and diabetes: a large cross-sectional study

BACKGROUND

Albuminuria, the presence of excess of protein in urine, is a well-known risk factor for early kidney damage among diabetic/prediabetic patients. There is a complex interaction between physical activity (PA) and albuminuria. However, the relationship of specific-domain PA and albuminuria remained obscure.

METHODS

Albuminuria was defined as urinary albumin/creatinine ratio (ACR) > 30 mg/g. PA was self-reported by participants and classified into transportation-related PA (TPA), occupation-related PA (OPA), and leisure-time PA (LTPA). Weighted logistic regression was conducted to compute the odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic spline (RCS) was used to evaluate the dose-response of PA domains with the risk of albuminuria.

RESULTS

A total of 6739 diabetic/prediabetic patients (mean age: 56.52 ± 0.29 years) were enrolled in our study, including 3181 (47.20%) females and 3558 (52.80%) males. Of them, 1578 (23.42%) were identified with albuminuria, and 5161(76.58%) were without albuminuria. Diabetic/prediabetic patients who adhered the PA guidelines for total PA had a 22% decreased risk of albuminuria (OR = 0.78, 95%CI 0.64-0.95), and those met the PA guidelines for LTPA had a 28% decreased of albuminuria (OR = 0.72, 95%CI 0.57-0.92). However, OPA and TPA were both not associated with decreased risk of albuminuria. RCS showed linear relationship between the risk of albuminuria with LTPA.

CONCLUSIONS

Meeting the PA guideline for LTPA, but not OPA and TPA, was inversely related to the risk of albuminuria among diabetic/prediabetic patients. Additionally, achieving more than 300 min/week of LTPA conferred the positive effects in reducing albuminuria among diabetic/prediabetic patients.

Physical Activity Pattern of Adults With Metabolic Syndrome Risk Factors: Time-Series Cluster Analysis

Background

Physical activity plays a crucial role in maintaining a healthy lifestyle, and wrist-worn wearables, such as smartwatches and smart bands, have become popular tools for measuring activity levels in daily life. However, studies on physical activity using wearable devices have limitations; for example, these studies often rely on a single device model or use improper clustering methods to analyze the wearable data that are extracted from wearable devices.

Objective

This study aimed to identify methods suitable for analyzing wearable data and determining daily physical activity patterns. This study also explored the association between these physical activity patterns and health risk factors.

Methods

People aged >30 years who had metabolic syndrome risk factors and were using their own wrist-worn devices were included in this study. We collected personal health data through a web-based survey and measured physical activity levels using wrist-worn wearables over the course of 1 week. The Time-Series Anytime Density Peak (TADPole) clustering method, which is a novel time-series method proposed recently, was used to identify the physical activity patterns of study participants. Additionally, we defined physical activity pattern groups based on the similarity of physical activity patterns between weekdays and weekends. We used the χ2 or Fisher exact test for categorical variables and the 2-tailed t test for numerical variables to find significant differences between physical activity pattern groups. Logistic regression models were used to analyze the relationship between activity patterns and health risk factors.

Results

A total of 47 participants were included in the analysis, generating a total of 329 person-days of data. We identified 2 different types of physical activity patterns (early bird pattern and night owl pattern) for weekdays and weekends. The physical activity levels of early birds were less than that of night owls on both weekdays and weekends. Additionally, participants were categorized into stable and shifting groups based on the similarity of physical activity patterns between weekdays and weekends. The physical activity pattern groups showed significant differences depending on age (P=.004) and daily energy expenditure (P<.001 for weekdays; P=.003 for weekends). Logistic regression analysis revealed a significant association between older age (≥40 y) and shifting physical activity patterns (odds ratio 8.68, 95% CI 1.95-48.85; P=.007).

Conclusions

This study overcomes the limitations of previous studies by using various models of wrist-worn wearables and a novel time-series clustering method. Our findings suggested that age significantly influenced physical activity patterns. It also suggests a potential role of the TADPole clustering method in the analysis of large and multidimensional data, such as wearable data.

Weekend warrior physical activity pattern is associated with lower depression risk: Findings from NHANES 2007-2018

OBJECTIVE

This study aimed to explore the association between weekend warrior physical activity (PA) pattern and depression risk in American adults.

METHODS

Data of adults (n = 21,125) from NHANES 2007-2018 were used. Adults were categorized into 4 PA patterns (inactive, insufficiently active, weekend warrior, and regularly active) by self-reported PA levels. Participant characteristics in different groups were tested using the Rao & Scott adjusted χ2 test. Multivariate logistic regression models with adjustment for demographics data, behavioral factors and health condition were used to explore the association between PA patterns and depression risk. Finally, interaction analyses were conducted to test if the associations differ by gender, age, race, education level, income level and marital status.

RESULTS

Multivariate logistic regression models showed that insufficiently active, weekend warrior and regularly active adults had 31% (OR: 0.69, 95%CI:0.54-0.88), 57% (OR: 0.43, 95%CI:0.25-0.74) and 54% (OR: 0.46, 95%CI:0.39-0.54) reduced depression risk when compared with inactive adults, respectively. When compared with regularly active adults, inactive (OR: 2.188, 95%CI:1.842-2.600) and insufficiently active (OR: 1.505, 95%CI:1.159-1.955) adults had elevated depression risk, but no significant difference was found between weekend warrior (OR: 0.949, 95%CI:0.538-1.675) and regularly active adults. Moreover, the associations did not differ by demographic variables.

CONCLUSIONS

This study showed that adults who engaged in either regularly active pattern or weekend warrior pattern, experienced lower risk of depression compared to inactive adults. Weekend warrior and regularly active patterns showed similar benefits for lowering depression risk in adults, encouraging adults to take up PA in limited sessions.

Association of main meal frequency and skipping with metabolic syndrome in Korean adults: a cross-sectional study

BACKGROUND

Reduced meal frequency can increase the risk of metabolic syndrome (MetS). However, limited studies have examined the association between meal frequency and skipping meals with MetS. This study aims to analyze the association between main meal frequency and meal skipping with MetS in Korean adults aged ≥ 19 years.

METHODS

In this study, we included data from 22,699 Korean adult participants from the 2016-2020 Korea National Health and Nutrition Examination Survey (KNHANES). The 24-h dietary recall method was used to classify the participants into three groups based on main meal frequency (one, two, or three meals per day) and seven groups based on the type of main meal they skipped. Multivariable logistic regression analysis was conducted to determine the association between main meal frequency and the types of main meals skipped with the odds of MetS and its associated components. Appropriate estimates were accounted for using sampling weights, stratification, and clustering.

RESULTS

The prevalence of MetS in the study population was 33.8%. The average age of the participants was 47.2 years with 42.6% being men, and 57.4% being women. Men who consumed two meals per day had higher odds of MetS than those who consumed three meals per day (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.01-1.33). Women who consumed two meals per day, and skipped breakfast had increased odds of having elevated fasting blood glucose levels (OR 1.18, 95% CI 1.02-1.35), and elevated triglycerides (OR 1.19, 95% CI 1.02-1.39). However, women who skipped dinner had reduced odds of having elevated fasting blood glucose levels (OR 0.74, 95% CI 0.58-0.94).

CONCLUSIONS

Our findings suggest that meal frequency and the type of main meal skipped may be associated with MetS and emphasize the importance of consuming breakfast to prevent MetS.