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  • Author: Pradeep Y. Ramulu x
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Paul D. Loprinzi, Gina Pariser and Pradeep Y. Ramulu

Background:

To examine the association between accelerometer-assessed physical activity and visual acuity among a nationally representative sample of adults with evidence of diabetes.

Methods:

Six hundred seventy adult participants with diabetes (age 20 to 85) from the 2003–2006 NHANES cycles constituted the analyzed sample. Participants wore an accelerometer for 7 days to quantify time spent in sedentary behavior, light-intensity physical activity and moderate-to-vigorous physical activity. Visual acuity was objectively assessed for each eye.

Results:

In multivariable models, every 1-hour increment in daily sedentary behavior was associated with 23% greater likelihood (OR = 1.23; 95% CI: 1.01–1.52) of having uncorrected refractive error as opposed to normal sight. Performing more than 5 minutes of daily moderate-to-vigorous physical activity was associated with a 82% lower likelihood of having vision impairment as opposed to normal sight (OR = 0.18; 95% CI: 0.06–0.50) while every 1-hour increment in daily light-intensity physical activity was, after adjustments, independently associated with a 38% lower likelihood of vision impairment (OR = 0.62; 95% CI: 0.42–0.92).

Conclusion:

People with diabetes spending more time in sedentary behavior and less time performing light or moderate-to-vigorous physical activity are more likely to have poorer vision.

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Pradeep Y. Ramulu, Emilie S. Chan, Tara L. Loyd, Luigi Ferrucci and David S. Friedman

Background:

Measuring physical at home and away from home is essential for assessing health and well-being, and could help design interventions to increase physical activity. Here, we describe how physical activity at home and away from home can be quantified by combining information from cellular network–based tracking devices and accelerometers.

Methods:

Thirty-five working adults wore a cellular network–based tracking device and an accelerometer for 6 consecutive days and logged their travel away from home. Performance of the tracking device was determined using the travel log for reference. Tracking device and accelerometer data were merged to compare physical activity at home and away from home.

Results:

The tracking device detected 98.6% of all away-from-home excursions, accurately measured time away from home and demonstrated few prolonged signal drop-out periods. Most physical activity took place away from home on weekdays, but not on weekends. Subjects were more physically active per unit of time while away from home, particularly on weekends.

Conclusions:

Cellular network–based tracking devices represent an alternative to global positioning systems for tracking location, and provide information easily integrated with accelerometers to determine where physical activity takes place. Promoting greater time spent away from home may increase physical activity.