The Influence of Different Physical Activity Behaviours on the Gut Microbiota of Older Irish Adults

OBJECTIVE

A 24-hour day is made up of time spent in a range of physical activity (PA) behaviours, including sleep, sedentary time, standing, light-intensity PA (LIPA) and moderate-to-vigorous PA (MVPA), all of which may have the potential to alter an individual's health through various different pathways and mechanisms. This study aimed to explore the relationship between PA behaviours and the gut microbiome in older adults.

DESIGN

Cross-sectional study.

SETTINGS AND PARTICIPANTS

Participants (n=100; age 69.0 [3.0] years; 44% female) from the Mitchelstown Cohort Rescreen (MCR) Study (2015-2017).

METHODS

Participants provided measures of gut microbiome composition (profiled by sequencing 16S rRNA gene amplicons), and objective measures of PA behaviours (by a 7-day wear protocol using an activPAL3 Micro).

RESULTS

Standing time was positively correlated with the abundance of butyrate-producing and anti-inflammatory bacteria, including Ruminococcaceae, Lachnospiraceae and Bifidobacterium, MVPA was positively associated with the abundance of Lachnospiraceae bacteria, while sedentary time was associated with lower abundance of Ruminococcaceae and higher abundance of Streptococcus spp.

CONCLUSION

Physical activity behaviours appear to influence gut microbiota composition in older adults, with different PA behaviours having diverging effects on gut microbiota composition.

The cross-sectional associations between objectively measured sedentary time and cardiometabolic health markers in adults - a systematic review with meta-analysis component

Sedentary time is viewed as an independent risk factor for adverse cardiometabolic health (CMH). No systematic review and meta-analysis on the cross-sectional associations between objectively measured sedentary time and CMH markers has been conducted. PubMed, Scopus and Web of Science Core Collection were searched for papers that examined the cross-sectional association between objectively measured sedentary time and CMH markers in adults. Forty-six papers met the inclusion criteria. The included papers had a combined sample size of 70,576 and an age range of 18-87 years. To examine the effect of increased levels of sedentary time on CMH markers, data on effect sizes and moderators were extracted, where possible. By pooling the unadjusted data from the included papers, increased sedentary time was shown to have a significant detrimental association with fasting glucose (Δ = 0.12, 95% confidence interval [CI]: 0.02, 0.23), fasting insulin (Δ = 0.19, 95% CI: 0.06, 0.32), triglycerides (Δ = 0.25, 95% CI: 0.14, 0.37), high-density lipoprotein cholesterol (Δ = -0.20, 95% CI: -0.28, -0.13) and waist circumference (Δ = 0.25, 95% CI: 0.15, 0.35). How sedentary time was quantified and the device used to measure sedentary time significantly influence the size of the effect reported. Future interventions focused on both decreasing sedentary time and increasing physical activity may be the most effective strategy to improve CMH.