ObjectiveThe aim of this study was to examine the associations between sedentary behavior and different intensities of physical activity with cardiometabolic risk, and to analyze the simultaneous effect of excess sedentary behavior and recommended levels of physical activity on cardiometabolic risk markers in older adults.MethodsWe conducted a population-based cross-sectional study on a sample of older adults (60+) living in Florianopolis, Brazil. The objectively measured predictors were sedentary time, light physical activity and moderate to vigorous physical activity, and the outcomes were markers of cardiometabolic risk. Data were considered valid when the participant had used the accelerometer for at least four days per week.ResultsThe sample included 425 older adults (59.8% women), with a mean age of 73.9 years (95%CI: 73.5–74.4). Sedentary behavior was associated with lower systolic blood pressure levels (β = -0.03; 95%CI: -0.05; -0.01) and lower HDL cholesterol (β = -0.02; 95%CI: -0.02; -0.01). Light physical activity was not associated with any cardiovascular risk markers after adjustment. Each minute spent in moderate to vigorous physical activity was associated with lower waist circumference (β = -0.15; 95%CI: -0.24; -0.05), systolic blood pressure (β = -0.18; 95%CI: -0.32; -0.04) and plasma glucose (β = -0.18; 95%CI: -0.33;-0.02), and with higher HDL cholesterol (β = 0.10; 95%CI: 0.01; 0.18). Moreover, physically inactive and sedentary individuals had a greater mean waist circumference and lower HDL cholesterol than physically active and non-sedentary subjects.ConclusionThe results suggest that moderate to vigorous physical activity have a positive impact on cardiometabolic risk markers in older adults. Light physical activity does not appear to have a beneficial effect on the cardiometabolic markers, and despite the benefits provided by the different intensities of physical activity, the simultaneous presence of sedentary behavior and low physical activity level was associated with poor cardiometabolic risk markers.
This study aims to examine the association between neighborhood environment attributes and changes in walking for transportation among older adults. Longitudinal analysis was performed considering a population-based study (EpiFloripa Idoso), carried out in 2009–2010 with follow-up in 2013–2014. Changes in walking, obtained with the International Physical Activity Questionnaire during both waves were associated with data from the environment perception, evaluated using individual items from the Neighborhood Environment Walkability Scale (baseline only) performing multinomial logistic regression. A total of 1,162 older adults (65.2% women, mean age = 73.7 years) participated. Those who reported the presence of parks and squares (OR = 2.44, 95% confidence interval [CI; 1.70, 3.51]), sidewalks (OR = 1.66, 95% CI [1.03, 2.70]), crosswalks (OR = 1.69, 95% CI [1.05, 2.72]), illuminated streets (OR = 2.80, 95% CI [1.24, 6.33]), and safety for day walks (OR = 1.93, 95% CI [1.14, 3.24]) were more likely to remain active or become active when commuting (≥150 min/week). Older adults are more active in neighborhoods that present more favorable attributes regarding walking for transportation.
Little is known about the relationship between perceived environmental characteristics and sedentary behavior (SB) using accelerometry in older adults. e aim of this study was to investigate the association between perceived neighborhood environmental characteristics and SB using accelerometry in 423 older adults from Florianopolis, Brazil. e time spent in SB was measured by an accelerometer (Actigraph-GT3X and GT3X+) for seven days and it was defined as < 100 counts per minute. Neighborhood characteristics were assessed using the 17-item of the A-NEWS scale. Linear regression was used to examine the association between perceived neighborhood environmental characteristics and SB. The results showed that older adults spent about 631.9 minutes/day in SB which corresponds to 66% of their waking time/day. Men who reported “access to shops” (β = -66.87; 95%CI: -113.80; -19.66), “access to services” (β = -65.65; 95%CI: -118.63; -12.61), “access to food shops” (β = -78.38; 95%CI: -123.79; -32.93) and “access to bus stop” (β = -66.69; 95%CI: -110.32; -22.95) spent over one hour less in SB. In women, lower SB was associated to easier “access to clubs and gyms” (β = -24.57; 95%CI: -48.13; -0.89) and “access to open spaces gyms” (β = -31.67 95%CI: -58.80; -4.21). These findings indicate that better access and greater diversity of places in the neighborhood environment could be an important factor to reduce SB in older Brazilian adults.
The aim was to identify the main geospatial indicators used in bikeability index through constructive methodological studies. The study protocol was registered in PROSPERO under the registration number CRD42020166795, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guide. Original studies indexed in the electronic databases Lilacs, PubMed, Science Direct, Scopus, SPORTDiscus, Trid, and Web of Science were selected. The review also included grey literature through Google Scholar, OpenGrey, ProQuest, and a list of references and documents pointed out by experts. After removing duplicates and analyzing titles and abstracts, the review considered only 11 out of the 703 initial papers, which provided 100 environment indicators with varied definitions and metrics for estimating the Bikeability index. The census tract was the most used unit of the analysis found in the papers, which used GIS (Geographic Information System) data besides self-reported information on environmental characteristics. The results indicate that the most usual indicators relate to infrastructure – existence and width of bike lanes – destination, slope, speed limit, and connectivity and intersections. The creation and maintenance of bicycle-friendly environments could consider the implementation of more infrastructure on flat and connected streets with changes in speed limits in neighborhoods, especially in regions with low density of intersections, to decrease accidents and increase cyclists’ perception of safety.
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