Dynamic changes in clinical biomarkers of cardiometabolic diseases by changes in exercise behavior, and network comparisons: a community-based prospective cohort study in Korea

Abstract

OBJECTIVES: Lifestyles, including exercise behaviors, change continually over time. This study examined whether the clinical biomarkers (CBs) related to cardiometabolic diseases (CMDs) and their relationships differed with changes in exercise behavior. METHODS: The Ansan-Ansung cohort study (third to fifth phases; n=2,668) was used in the current study. Regular exercise behavior was investigated using a yes/no questionnaire. Changes in exercise behavior were classified into 4 groups: Y-N, N-Y, Y-Y, and N-N, with “Y” indicating that a participant regularly engaged in exercise at a given time point and “N” indicating that he or she did not. Fourteen CBs related to CMDs were used, and the associations between changes in exercise behavior and relative changes in CBs were examined. CB networks were constructed and topological comparisons were conducted.RESULTS: Y-N was associated with increases in fasting blood sugar and insulin levels in men, and increased total cholesterol and low-density lipoprotein cholesterol levels in women. Meanwhile, N-Y was inversely associated with body fat percentage, visceral fat percentage, fasting insulin, and triglyceride level. Waist circumference played a central role in most networks. In men, more edges were found in the N-Y and Y-Y groups than in the N-N and Y-N groups, whereas women in the N-Y and Y-Y groups had more edges than those in the N-N and Y-N groups. CONCLUSIONS: Consistent exercise or starting to engage in regular exercise had favorable effects on CBs related to CMDs, although their network patterns differed between the sexes.

A 6-month exercise intervention clinical trial in women: effects of physical activity on multi-omics biomarkers and health during the first wave of COVID-19 in Korea

“…A number of epidemiological studies have shown the associations between PA and decreased risk of death and chronic diseases [ 10 , 11 ]; however, biological processes and the underlying mechanisms for the benefit of PA are still unclear [ 14 ]. Recently, studies have been conducted to understand the benefits of PA more thoroughly way by using not only various anthropometric and blood biomarkers [ 15 , 16 ] but also metabolites [ 17 , 18 ] and microbiomes [ 19 , 20 ]. PA induces changes in various objective measurements and clinical biomarkers in a health-promoting direction such as reducing levels of triglyceride, total cholesterol, blood glucose, and insulin, waist circumference, and body fat, while increasing HDL and muscle mass [ 15 , 16 ].…”

“…Recently, studies have been conducted to understand the benefits of PA more thoroughly way by using not only various anthropometric and blood biomarkers [ 15 , 16 ] but also metabolites [ 17 , 18 ] and microbiomes [ 19 , 20 ]. PA induces changes in various objective measurements and clinical biomarkers in a health-promoting direction such as reducing levels of triglyceride, total cholesterol, blood glucose, and insulin, waist circumference, and body fat, while increasing HDL and muscle mass [ 15 , 16 ]. The influence of PA on the metabolome shows a positive association with TCA cycle metabolites, including lactate, pyruvate, and ketones.…”