Physical Activity in Patients With Type 2 Diabetes: The Case for Objective Measurement in Routine Clinical Care

Oosterom, Nicole; Gant, Christina M.; Ruiterkamp, Niels; Beijnum, Bert-Jan van; Hermens, Hermie; Bakker, Stephan J. L.; Navis, Gerjan; Vollenbroek-Hutten, Miriam Marie Rosé; Laverman, Gozewijn D.

doi:10.2337/dc17-2041

Cited by 11 publications

(11 citation statements)

References 4 publications

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“…However, performance of at least any physical exercise on top of normal daily activities was not an independent determinant of muscle mass. Of note, it has been previously demonstrated that the self-reported physical activity as applied here provides an overestimation [40]. Unfortunately, we were not able to draw conclusions about physical activity since no functional data on muscle performance are available.…”

Section: Discussionmentioning

confidence: 83%

Clinical and Dietary Determinants of Muscle Mass in Patients with Type 2 Diabetes: Data from the Diabetes and Lifestyle Cohort Twente

Jalving

Oosterwijk

Hagedoorn

et al. 2021

JCM

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Low muscle mass in patients with type 2 diabetes is associated with a progressively higher risk of morbidity and mortality. The aim of this study was to identify modifiable targets for intervention of muscle mass in type 2 diabetes. Cross-sectional analyses were performed in 375 patients of the Diabetes and Lifestyle Cohort Twente-1 study. Muscle mass was estimated by 24 h urinary creatinine excretion rate (CER, mmol/24 h). Patients were divided in sex-stratified tertiles of CER. To study determinants of CER, multivariable linear regression analyses were performed. Protein intake was determined by Maroni formula and by a semi-quantitative Food Frequency Questionnaire. The mean CER was 16.1 ± 4.8 mmol/24 h and 10.9 ± 2.9 mmol/24 h in men and women, respectively. Lower CER was significantly associated with older age (p < 0.001) as a non-modifiable risk factor, whereas higher BMI (p = 0.015) and lower dietary protein intake (both methods p < 0.001) were identified as modifiable risk factors for lower CER. Overall body mass index (BMI) was high, even in the lowest CER tertile the mean BMI was 30.9 kg/m2, mainly driven by someone’s body weight (p = 0.004) instead of someone’s height (p = 0.58). In the total population, 28% did not achieve adequate protein intake of >0.8 g/kg/day, with the highest percentage in the lowest CER tertile (52%, p < 0.001). Among patients with type 2 diabetes treated in secondary care, higher BMI and low dietary protein intake are modifiable risk factors for lower muscle mass. Considering the risk associated with low muscle mass, intervention may be useful. To that purpose, dietary protein intake and BMI are potential targets for intervention.

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Section: Discussionmentioning

confidence: 83%

Clinical and Dietary Determinants of Muscle Mass in Patients with Type 2 Diabetes: Data from the Diabetes and Lifestyle Cohort Twente

Jalving

Oosterwijk

Hagedoorn

et al. 2021

JCM

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“…However, the vast majority of patients with type 2 diabetes do not adhere to the American Diabetes Association (ADA) guidelines of >150 min per week of moderate to vigorous PA, which is comparable with 7000 steps per day [ 3 , 4 , 5 ]. Traditionally, a goal of 10,000 steps per day has been advocated by popular media, although this goal is under debate in scientific literature [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Low Physical Activity in Patients with Complicated Type 2 Diabetes Mellitus Is Associated with Low Muscle Mass and Low Protein Intake

Hagedoorn

Braber

Oosterwijk

et al. 2020

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Objective: In order to promote physical activity (PA) in patients with complicated type 2 diabetes, a better understanding of daily movement is required. We (1) objectively assessed PA in patients with type 2 diabetes, and (2) studied the association between muscle mass, dietary protein intake, and PA. Methods: We performed cross-sectional analyses in all patients included in the Diabetes and Lifestyle Cohort Twente (DIALECT) between November 2016 and November 2018. Patients were divided into four groups: <5000, 5000–6999, 7000–9999, ≥ 10,000 steps/day. We studied the association between muscle mass (24 h urinary creatinine excretion rate, CER) and protein intake (by Maroni formula), and the main outcome variable PA (steps/day, Fitbit Flex device) using multivariate linear regression analyses. Results: In the 217 included patients, the median steps/day were 6118 (4115–8638). Of these patients, 48 patients (22%) took 7000–9999 steps/day, 37 patients (17%) took ≥ 10,000 steps/day, and 78 patients (36%) took <5000 steps/day. Patients with <5000 steps/day had, in comparison to patients who took ≥10,000 steps/day, a higher body mass index (BMI) (33 ± 6 vs. 30 ± 5 kg/m2, p = 0.009), lower CER (11.7 ± 4.8 vs. 14.8 ± 3.8 mmol/24 h, p = 0.001), and lower protein intake (0.84 ± 0.29 vs. 1.08 ± 0.22 g/kg/day, p < 0.001). Both creatinine excretion (β = 0.26, p < 0.001) and dietary protein intake (β = 0.31, p < 0.001) were strongly associated with PA, which remained unchanged after adjustment for potential confounders. Conclusions: Prevalent insufficient protein intake and low muscle mass co-exist in obese patients with low physical activity. Dedicated intervention studies are needed to study the role of sufficient protein intake and physical activity in increasing or maintaining muscle mass in patients with type 2 diabetes.

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“…Of note, lifestyle behaviour is not measured routinely and objectively in clinical practice. However, objective measurements are of great importance in adequately mapping lifestyle, because patients grossly overestimate their healthy lifestyle behaviours [14].…”

Section: Introductionmentioning

confidence: 99%

Requirements of an Application to Monitor Diet, Physical Activity and Glucose Values in Patients with Type 2 Diabetes: The Diameter

et al. 2019

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Adherence to a healthy diet and regular physical activity are two important factors in sufficient type 2 diabetes mellitus management. It is recognized that the traditional treatment of outpatients does not meet the requirements for sufficient lifestyle management. It is hypothesised that a personalized diabetes management mHealth application can help. Such an application ideally measures food intake, physical activity, glucose values, and medication use, and then integrates this to provide patients and healthcare professionals insight in these factors, as well as the effect of lifestyle on glucose values in daily life. The lifestyle data can be used to give tailored coaching to improve adherence to lifestyle recommendations and medication use. This study describes the requirements for such an application: the Diameter. An iterative mixed method design approach is used that consists of a cohort study, pilot studies, literature search, and expert meetings. The requirements are defined according to the Function and events, Interactions and usability, Content and structure and Style and aesthetics (FICS) framework. This resulted in 81 requirements for the dietary (n = 37), activity and sedentary (n = 15), glycaemic (n = 12), and general (n = 17) parts. Although many applications are currently available, many of these requirements are not implemented. This stresses the need for the Diameter as a new personalized diabetes application.

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Physical Activity in Patients With Type 2 Diabetes: The Case for Objective Measurement in Routine Clinical Care

Cited by 11 publications

References 4 publications

Clinical and Dietary Determinants of Muscle Mass in Patients with Type 2 Diabetes: Data from the Diabetes and Lifestyle Cohort Twente

Clinical and Dietary Determinants of Muscle Mass in Patients with Type 2 Diabetes: Data from the Diabetes and Lifestyle Cohort Twente

Low Physical Activity in Patients with Complicated Type 2 Diabetes Mellitus Is Associated with Low Muscle Mass and Low Protein Intake

Requirements of an Application to Monitor Diet, Physical Activity and Glucose Values in Patients with Type 2 Diabetes: The Diameter

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