OBJECTIVE: To evaluate patterns of physical activity (PA), the prevalence of physical inactivity and the relationships between PA and sociodemographic, clinical and biochemical parameters among Sri Lankan adults. DESIGN: Descriptive cross-sectional study. SETTING: Nationally representative population-based survey conducted in Sri Lanka. SUBJECTS: Data on PA and associated details were obtained from 5000 adults. PA was assessed using the International Physical Activity Questionnaire (short-form). A binary logistic regression analysis was performed using the dichotomous variable ‘health-enhancing PA’ (05‘active’, 15‘inactive’). RESULTS: Sample size was 4485. Mean age was 46.1 (SD 15.1) years, 39.5% were males. The mean weekly total MET (metabolic equivalents of task) minutes of PA among the study population was 4703 (SD 4369). Males (5464 (SD 5452)) had a significantly higher weekly total MET minutes than females (4205 (SD 3394); P,0.001). Rural adults (5175 (SD 4583)) were significantly more active than urban adults (2956 (SD 2847); P<0.001). Tamils had the highest mean weekly total MET minutes among ethnicities. Those with tertiary education had lowest mean weekly total MET minutes. In all adults 60.0% were in the ‘highly active’ category, while only 11.0% were ‘inactive’ (males 14.6%, females 8.7%; P<0.001). Of the ‘highly active’ adults, 85.8% were residing in rural areas. Results of the binary logistic regression analysis indicated that female gender (OR52?1), age .70 years (OR53.8), urban living (OR52.5), Muslim ethnicity (OR52.7), tertiary education (OR53.6), obesity (OR51.8), diabetes (OR51.6), hypertension (OR51.2) and metabolic syndrome (OR51.3) were all associated with significantly increased odds of being physically ‘inactive’. CONCLUSIONS: The majority of Sri Lankan adults were ‘highly active’ physically. Female gender, older age, urban living, Muslim ethnicity and tertiary education were all significant predictors of physical inactivity. Physical inactivity was associated with obesity, diabetes, hypertension and metabolic syndrome.
OBJECTIVE: To evaluate patterns of physical activity (PA), the prevalence of physical inactivity and the relationships between PA and sociodemographic, clinical and biochemical parameters among Sri Lankan adults. DESIGN: Descriptive cross-sectional study. SETTING: Nationally representative population-based survey conducted in Sri Lanka. SUBJECTS: Data on PA and associated details were obtained from 5000 adults. PA was assessed using the International Physical Activity Questionnaire (short-form). A binary logistic regression analysis was performed using the dichotomous variable ‘health-enhancing PA’ (05‘active’, 15‘inactive’). RESULTS: Sample size was 4485. Mean age was 46.1 (SD 15.1) years, 39.5% were males. The mean weekly total MET (metabolic equivalents of task) minutes of PA among the study population was 4703 (SD 4369). Males (5464 (SD 5452)) had a significantly higher weekly total MET minutes than females (4205 (SD 3394); P,0.001). Rural adults (5175 (SD 4583)) were significantly more active than urban adults (2956 (SD 2847); P<0.001). Tamils had the highest mean weekly total MET minutes among ethnicities. Those with tertiary education had lowest mean weekly total MET minutes. In all adults 60.0% were in the ‘highly active’ category, while only 11.0% were ‘inactive’ (males 14.6%, females 8.7%; P<0.001). Of the ‘highly active’ adults, 85.8% were residing in rural areas. Results of the binary logistic regression analysis indicated that female gender (OR52?1), age .70 years (OR53.8), urban living (OR52.5), Muslim ethnicity (OR52.7), tertiary education (OR53.6), obesity (OR51.8), diabetes (OR51.6), hypertension (OR51.2) and metabolic syndrome (OR51.3) were all associated with significantly increased odds of being physically ‘inactive’. CONCLUSIONS: The majority of Sri Lankan adults were ‘highly active’ physically. Female gender, older age, urban living, Muslim ethnicity and tertiary education were all significant predictors of physical inactivity. Physical inactivity was associated with obesity, diabetes, hypertension and metabolic syndrome.
Authors: N W I A Jayawardana; W A T A Jayalath; W M T Madhujith; U Ralapanawa; R S Jayasekera; S A S B Alagiyawanna; A M K R Bandara; N S Kalupahana Journal: BMC Public Health Date: 2017-01-05 Impact factor: 3.295
Authors: P Ranasinghe; A S A D Pigera; M H Ishara; L M D T Jayasekara; R Jayawardena; P Katulanda Journal: BMC Public Health Date: 2015-11-23 Impact factor: 3.295