Association of sociodemographic, anthropometric, and sleep quality factors with accelerometer-measured sitting and physical activity times among Emirati working women during the COVID-19 pandemic: A cross-sectional study.

BACKGROUND: Although a significant lack of physical activity has been linked to an increase in obesity among Emirati women, the factors associated with accelerometer-measured sitting and physical activity times in Emirati women remain unclear. OBJECTIVES: To explore the association of accelerometer-measured sitting and physical activity times with sociodemographic, anthropometric, and sleep quality factors among Emirati working women. DESIGN: A cross-sectional study. METHODS: A convenience sample of 163 healthy working Emirati women aged 18-45 years was used. Sedentary and physical activity times were measured using the Fibion accelerometers worn on the thighs for 4-7 days. General demographic information, anthropometric measurements, and self-reported sleep quality (Pittsburgh sleep quality index score) were collected. Only participants who had valid data (i.e. wear time of ⩾600 min (10 h) per day for a minimum of 4-7 days) were evaluated. All values were normalized to a 16-h day to mitigate differences in wear time among the participants. RESULTS: Overall, 110 Emirati women were included. The mean sitting time per 16-h day was 11.6 ± 1.1 h; mean moderate activity time per day, 40.88 ± 17.99 min; and mean vigorous activity time per day, 2.41 ± 1.21 min. Longer sitting time was associated with high body fat, secondary education, and divorce. Sitting time was reduced in those with good sleep quality. Moderate-to-vigorous physical activity time was increased in women with postgraduate education and was decreased in women with a longer work experience and with comorbidities. The total activity time increased with increasing age and good sleep quality, whereas it decreased with increasing body fat, presence of at least one comorbidity, secondary education, and divorce. CONCLUSION: Certain demographic, anthropometric, and sleep quality factors were associated with accelerometer-measured sitting and physical activity times among Emirati working women. Future longitudinal studies should consider these factors when investigating predictors of physical activity levels in this population.

Effect of night-time data on sedentary and upright time and energy expenditure measured with the Fibion accelerometer in Emirati women.

BACKGROUND AND AIMS: Wearing an accelerometer during night-time could conflate sedentary behavior time and sleep hours. It is important to assess the impact of including night-time data on sedentary and upright behavior in a sedentary population. Therefore, we investigated differences in sitting and upright time and associated energy expenditure (EE), recorded by a Fibion accelerometer, with and without night-time data in Emirati women working in desk-based jobs. METHODS: Thirty-one healthy Emirati women working in the government offices used the Fibion accelerometer for a week. Fibion data were included if the participants wore the device for ≥600 min per day for a minimum of three weekdays and one weekend day. Sedentary (sitting) and upright time and associated energy expenditure (EE) were recorded using the Fibion. Variables were compared with and without night-time data using the paired t tests or Wilcoxon signed-rank tests. Effect sizes were determined using Cohen's d. RESULTS: Statistically significant differences for 15 out of 18 variables were observed when the night-time data were included. Except for cycling time, cycling EE, and vigorous activity time, nearly all other outcome measures showed a significant increase (moderate to large effect sizes) with night-time data compared to those without night-time data. CONCLUSIONS: Cycling time/EE and vigorous activity time did not change with standard night-time data. Therefore, studies examining only cycling and/or vigorous activity time with the Fibion accelerometer do not require night-time data removal. An analysis of other variables relating to sedentary and upright time will require night-time data exclusion.