Background An understanding of the nature and magnitude of within- and between-day variability in physical behaviour is necessary to translate epidemiological findings into tangible public health recommendations. The aim of this paper is to compare daily cumulative patterns of minute-by-minute accelerometer measured physical behaviour activity intensities across healthy and unhealthy cardiometabolic profiles.

Methods Data are from a subsample of the Mitchelstown cohort; 475 (59.7 ± 5.5 years) middle-aged adults. Participants wore the wrist GENEActiv accelerometer for 7-consecutive days. Data was summarised into 60s epochs and each time interval categorised based on thresholds. Cumulative distribution plots were created for each day of the week across several cardiometabolic health profiles (diabetes, hypertension, metabolic syndrome and obesity). Adjusted-logistic regression examined the relationship between cumulative activity and cardiometabolic health.

Results Our data highlight significant differences in early evening MVPA and late evening sedentary activity among high risk subgroups including obese and metabolic syndrome subjects compared to their healthy counterparts. Furthermore the obese individuals had significantly higher light activity and MVPA during the morning. Diabetic participants had significantly higher sedentary activity and lower light activity in late evening compared to non-diabetic subjects, while hypertensives had significantly lower levels of physical activity in the morning. In addition, results highlight that activity that occurred after 9:00 pm mainly consisted of sedentary and light activity while regression analysis highlighted the significant change in odds of adverse cardiometabolic health outcomes associated with a 1 h increase in each physical behaviour intensity.

Discussion This study demonstrates that there is considerable within- and between-day variation in physical activity and sedentary behaviour across healthy cardiometabolic health profiles and their unhealthy counterparts. A better understanding of such patterns will aid development of future targeted interventions tailored to an individual’s cardiometabolic health status.