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Accelerometer Profile of Physical Activity and Sedentary Behavior in a Multi-Ethnic Urban Asian Population

Chu AHY, Bernard JY, Koh D, Müller-Riemenschneider F

Res Q Exerc Sport, 2021 Sep;92(3):361-368.
PMID: 32154777 DOI: 10.1080/02701367.2020.1734520

Purpose: Variability in accelerometry-data processing decisions limited data comparability across studies. We aimed to examine different accelerometry-data processing rules: varying bout lengths and allowance of 0- and 2-min interruptions on the total and bout-accumulated time spent in moderate-to-vigorous physical activity (MVPA) and sedentary behavior estimates, and describe the distribution of activity time based on counts per min (CPM) in granular categories. Method: Using the Singapore Health 2 survey, this study included 746 adults (41.8% women, median age 45.0 years) who provided valid ActiGraph GT3X+ accelerometer-data (≥4 valid days with ≥10-h/day). Quantile regression analysis adjusting for accelerometry daily wear time, age, and gender was performed to calculate the median and interquartile range of accelerometry estimates. Results: Median MVPA time accumulated in bouts of 1-min versus bouts of 10-min was 39.2 min/day and 6.0 min/day, respectively. MVPA time was higher when considering a 2-min interruption (range: 1.8-39.2 min/day) compared to 0-min interruption (range: 0-35.5 min/day) across bout lengths of 1- to 15-min. Participants were sedentary (≤100 CPM) for a daily median of 7.6 h/day. Median activities min/day on the lower-intensity activity spectrum (100-2499 CPM) decreased from 63.4 to 4.6 min/day, while on the higher-intensity activity spectrum (≥2500 CPM) was ≤2.9 min/day. Men generally spent more time in MVPA than women. Conclusions: This study highlights the differences in accelerometry estimates based on data processing decisions, and the importance of quantifying accelerometry-based activity time across the granular intensity spectrum. More studies are warranted to understand the determinants and health impact of these behaviors.

Matched MeSH terms: Sedentary Lifestyle/ethnology*
Gender-related Differences in Sedentary Behavior of Japanese Living Overseas in Malaysia

Izawa KP, Oka K

Rev Recent Clin Trials, 2020 5 26;15(3):214-218.
PMID: 32448105 DOI: 10.2174/1574887115666200524235754

BACKGROUND: The purpose of the present study was to clarify the differences in social demographic factors and sedentary behavior by gender in Japanese living overseas in Malaysia.
METHODS: First, 130 subjects were surveyed by self-entry questionnaire for statistical factors related to social demographics and sedentary behavior. These factors were age (years), gender (man/woman), body mass index (BMI, kg/m2), educational history (>13 years, %), employment (full-time or part-time, yes, %), alcohol intake (a certain amount, yes, %), smoking behavior (yes, %), and marital status (yes, %). BMI, as obtained from the participants' weight and height, was collected from the self-reported questionnaire and assessed. Sitting behavior time as an index of sedentary behavior on workdays, non-workdays, and total time was identified by questionnaire. Data were analyzed using the chi square-test and t-test, respectively. The criterion for a statistically significant difference was p < 0.05.
RESULTS: Finally, 107 subjects (68 men, 39 women) were analyzed. The ratios of social demographic factors of the men versus women group were age (58.5 ± 14.7 vs. 61.0 ± 12.1 years, p = 0.36), BMI (23.1 ± 2.6 vs. 21.8 ± 2.6 kg/m2, p = 0.01), educational history (86.7% vs. 56.4%, p < 0.001), employment (51.5% vs. 10.3%, p <0.001), alcohol intake (86.7% vs. 35.9%, p < 0.001), smoking behavior (30.9% vs. 10.3%, p = 0.01), and marital status (88.2% vs. 100%, p = 0.02). Sitting behavior time was 501.8 ± 254.6 vs. 346.0 ± 153.4 minutes (p < 0.001) on workdays, 415.1 ± 225.3 vs. 320.6 ± 178.7 minutes (p = 0.019) on non-workdays, and 458.5 ± 203.9 vs. 333.3 ± 132.1 minutes (p < 0.001) in total.
CONCLUSION: These findings indicated that social demographic factors and sitting behavior time differed by gender. However, there are some limitations. This was a cross-sectional study conducted in only one city with a small number of participants who completed a self-entry questionnaire. In conclusion, assessment of the differences in social demographic factors and postponement of sedentary behavior for both genders may reduce sitting behavior time in overseas Japanese residents and may help in developing public health strategies.

Matched MeSH terms: Sedentary Lifestyle/ethnology*
Correlates of sedentary behaviour in Asian adults: A systematic review

Müller AM, Chen B, Wang NX, Whitton C, Direito A, Petrunoff N, et al.

Obes Rev, 2020 04;21(4):e12976.
PMID: 31919972 DOI: 10.1111/obr.12976

The objective of this study is to systematically review the evidence on correlates of sedentary behaviour (SB) among Asian adults. We searched for studies that examined individual, environmental, and political/cultural correlates of total and domain-specific SB (transport, occupation, leisure, and screen time) in Asian adults published from 2000 onwards in nine scientific databases. Two reviewers independently screened identified references. Following quality assessment of included studies, we performed narrative synthesis that considered differences based on SB measurements, regions, and population characteristics (PROSPERO: CRD42018095268). We identified 13 249 papers of which we included 49, from four regions and 12 countries. Researchers conducted cross-sectional analyses and most relied on SB self-report for SB measurement. Of the 118 correlates studied, the following associations were consistent: higher age, living in an urban area (East Asia), and lower mental health with higher total SB; higher education with higher total and occupational SB; higher income with higher leisure-time SB; higher transit density with higher total SB in older East Asians; and being an unmarried women with higher SB in the Middle East. We encourage more research in non-high-income countries across regions, further exploration of important but neglected correlates using longitudinal designs and qualitative research, and the use of objective instruments to collect SB data.

Matched MeSH terms: Sedentary Lifestyle/ethnology*
Fulltext Television screen time, but not computer use and reading time, is associated with cardio-metabolic biomarkers in a multiethnic Asian population: a cross-sectional study

Nang EE, Salim A, Wu Y, Tai ES, Lee J, Van Dam RM

Int J Behav Nutr Phys Act, 2013;10:70.
PMID: 23718927 DOI: 10.1186/1479-5868-10-70

BACKGROUND: Recent evidence shows that sedentary behaviour may be an independent risk factor for cardiovascular diseases, diabetes, cancers and all-cause mortality. However, results are not consistent and different types of sedentary behaviour might have different effects on health. Thus the aim of this study was to evaluate the association between television screen time, computer/reading time and cardio-metabolic biomarkers in a multiethnic urban Asian population. We also sought to understand the potential mediators of this association.
METHODS: The Singapore Prospective Study Program (2004-2007), was a cross-sectional population-based study in a multiethnic population in Singapore. We studied 3305 Singaporean adults of Chinese, Malay and Indian ethnicity who did not have pre-existing diseases and conditions that could affect their physical activity. Multiple linear regression analysis was used to assess the association of television screen time and computer/reading time with cardio-metabolic biomarkers [blood pressure, lipids, glucose, adiponectin, C reactive protein and homeostasis model assessment of insulin resistance (HOMA-IR)]. Path analysis was used to examine the role of mediators of the observed association.
RESULTS: Longer television screen time was significantly associated with higher systolic blood pressure, total cholesterol, triglycerides, C reactive protein, HOMA-IR, and lower adiponectin after adjustment for potential socio-demographic and lifestyle confounders. Dietary factors and body mass index, but not physical activity, were potential mediators that explained most of these associations between television screen time and cardio-metabolic biomarkers. The associations of television screen time with triglycerides and HOMA-IR were only partly explained by dietary factors and body mass index. No association was observed between computer/ reading time and worse levels of cardio-metabolic biomarkers.
CONCLUSIONS: In this urban Asian population, television screen time was associated with worse levels of various cardio-metabolic risk factors. This may reflect detrimental effects of television screen time on dietary habits rather than replacement of physical activity.
MESH: screen time

Matched MeSH terms: Sedentary Lifestyle/ethnology*