scholarly journals Associations Between Diagnosis with Type 2 Diabetes and Changes in Physical Activity among Middle-Aged and Older Adults in the United States

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Emily J Nicklett ◽  
Jieling Chen ◽  
Xiaoling Xiang ◽  
Leah R Abrams ◽  
Amanda J Sonnega ◽  
...  

Abstract Background and Objectives Physical activity (PA) is an effective strategy for diabetes self-management and is central to the diabetes regimen. Diagnostic events present an opportunity for health behavior change; however, many older adults with type 2 diabetes (T2D) do not engage in regular PA. The relationships between diagnosis events and subsequent changes in PA are not well understood. Drawing upon life-course theory, this is the first study to examine whether the diagnosis of T2D is followed by a change in PA, whether these changes are sustained, and the sociodemographic characteristics associated with these changes. Research Design and Methods We examined associations between T2D diagnosis and PA changes among 2,394 adults ages 51+ from the Health and Retirement Study (2004–2014). PA changes were measured using metabolic equivalents of task (METs) estimated values accounting for the vigor and frequency of self-reported PA. Using piecewise mixed models, we examined initial and sustained changes in METs over time and tested whether these changes were modified by race/ethnicity, educational level, gender, and age at diagnosis. Results Across participants, a significant postdiagnosis increase was observed in self-reported PA following the diagnostic event (β: 0.54, 95% CI: 0.10, 0.97). The steepness of decline in PA participation over time did not change significantly following T2D diagnosis. Age at diagnosis and race/ethnicity significantly moderated these relationships: participants diagnosed at older ages were less likely to improve PA following diagnosis and non-Hispanic whites experienced relatively steeper rates of decline following diagnosis with T2D. Discussion and Implications Modest diagnosis-related increases in PA were observed among participants overall. The usual rate of decline in PA appears unaffected by diagnosis overall. Age at diagnosis and race/ethnicity moderated these relationships. Key implications for future research and clinical practice are discussed.

Geriatrics ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 15
Author(s):  
Marjan Mosalman Haghighi ◽  
Yorgi Mavros ◽  
Shelley Kay ◽  
Kylie A. Simpson ◽  
Michael K. Baker ◽  
...  

Background: We examined the effect of power training on habitual, intervention and total physical activity (PA) levels in older adults with type 2 diabetes and their relationship to metabolic control. Materials and Methods: 103 adults with type 2 diabetes were randomized to receive supervised power training or sham exercise three times/week for 12 months. Habitual, intervention, and total PA, as well as insulin resistance (HOMA2-IR) and glycosylated hemoglobin (HbA1c), were measured. Results: Participants were aged 67.9 ± 5.5 yrs, with well-controlled diabetes (HbA1c = 7.1%) and higher than average habitual PA levels compared to healthy peers. Habitual PA did not change significantly over 12 months (p = 0.74), and there was no effect of group assignment on change over time in habitual PA over 0–6 (p = 0.16) or 0–6–12 months (p = 0.51). By contrast, intervention PA, leg press tonnage and total PA increased over both 6- and 12-month timepoints (p = 0.0001), and these changes were significantly greater in the power training compared to the sham exercise group across timepoints (p = 0.0001). However, there were no associations between changes in any PA measures over time and changes in metabolic profile. Conclusion: Structured high-intensity power training may be an effective strategy to enhance overall PA in this high-risk cohort.


Author(s):  
Kelly Akemi Kikuti‐Koyama ◽  
Henrique Luiz Monteiro ◽  
Ítalo Ribeiro Lemes ◽  
Luana Carolina Morais ◽  
Rômulo Fernandes ◽  
...  

2021 ◽  
Vol 29 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Ramit Ravona-Springer ◽  
Anthony Heymann ◽  
Hung-Mo Lin ◽  
Xiaoyu Liu ◽  
Yuval Berman ◽  
...  

2017 ◽  
Vol 10 (2) ◽  
pp. 166-178 ◽  
Author(s):  
William R. Boyer ◽  
James R. Churilla ◽  
Samantha F. Ehrlich ◽  
Scott E. Crouter ◽  
Lyndsey M. Hornbuckle ◽  
...  

2021 ◽  
Author(s):  
Stefano Balducci ◽  
Jonida Haxhi ◽  
Massimo Sacchetti ◽  
Giorgio Orlando ◽  
Patrizia Cardelli ◽  
...  

<a><strong>Objective.</strong></a> In the Italian Diabetes and Exercise Study_2, a behavioral counseling <a>promoted</a> a sustained increase in physical activity (PA) volume (+3.3 metabolic equivalents-hour·week<sup>-1</sup>), moderate-to-vigorous-intensity PA (MVPA, +6.4 min·day<sup>-1</sup>), and light-intensity PA (LPA, +0.8 hours·day<sup>-1</sup>) and decrease in sedentary time (SED-time, -0.8 hours·day<sup>-1</sup>). Here, we investigated <a>the relationships of changes in PA/SED-time with changes in physical fitness and cardio-metabolic risk profile in individuals with type 2 diabetes</a>. <p><b>Research Design and Methods. </b><a>In this 3-year randomized clinical trial, 300 physically inactive and sedentary patients were randomized 1:1 to receive one-month theoretical and practical counseling once-a-year or standard care. </a>Changes in physical fitness and cardiovascular risk factors/scores according to quartiles of accelerometer-measured changes in PA/SED-time were assessed, together with univariate and multivariable associations between these parameters<a>, in the whole cohort and by study arm</a>.</p> <p><b>Results. </b>Physical fitness increased and HbA<sub>1c</sub> and coronary heart disease 10-year risk scores decreased with quartiles of MVPA and SED-time change. In quartile IV of MVPA increase and SED-time decrease, cardiorespiratory fitness increased by 5.23 and 4.49 ml·min<sup>-1</sup>·kg<sup>-1</sup> and HbA<sub>1c</sub> decreased by 0.73 and 0.85%, respectively. Univariate correlations confirmed these relationships and mean changes in both MPVA and SED-time predicted changes in physical fitness and cardiovascular risk factors/scores independently of one another and of other confounders. Similar findings were observed with LPA and PA volume and in each group separately.</p> <p><b>Conclusions. </b>Even modest increments in MVPA may have a clinically meaningful impact and reallocating SED-time to LPA may also contribute to improve outcomes, possibly by increasing total energy expenditure.</p>


2021 ◽  
Author(s):  
Ioana A. Moldovan ◽  
Alexa Bragg ◽  
Anna Nidhiry ◽  
Barbara A. De La Cruz ◽  
Suzanne E. Mitchell

BACKGROUND Incorporating physical activity in lifestyle routines is recommended for individuals living with type 2 diabetes. Accelerometer devices offer a promising alternative to self-report methods for measuring physical activity performance. However, the extant literature for accelerometer-measured physical activity among middle-aged/older adults with chronic conditions is lacking. OBJECTIVE We conducted a comprehensive scoping review of the literature to capture accelerometry methodologies in older adults with type 2 diabetes, specifically in relation to cutpoints that classify physical activity into intensity categories (sedentary, light, moderate, vigorous, very vigorous). METHODS Applying the Joanna Briggs Institute’s methodology, we searched PubMed, Web of Science, EMBASE, and Engineering Village to identify studies that used research-grade accelerometers to objectively measure physical activity intensity levels of adults with type 2 diabetes using cutpoints in participant samples of mean age 50 years and older. RESULTS We identified 46 studies that met our inclusion criteria. The ActiGraph was the most popular accelerometer among researchers, and the Freedson (1998) and Troiano (2008) cutpoints were favored the most. The Lopes (2009) cutpoints were developed by calibrating the ActiGraph accelerometer in middle-aged and older adults with overweight/ obesity and type 2 diabetes. Several studies noted limitations of accelerometry use that could lead to an underestimation or inaccurate representation of physical activity for our population of interest. Limitations included decreased accuracy due to variation in device placement and underestimation of activity intensity attributed to using cutpoints in older adults with lower fitness levels that were originally validated with younger adults. CONCLUSIONS Considering the high variability among accelerometry methodologies, more work needs to be done to understand activity intensity cut-offs for populations with a high burden of chronic disease, older age, and suboptimal physical functioning.


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