To investigate the acute effects of the coronavirus disease 2019 (COVID-19) on the lifestyle and metabolic parameters in patients with type 2 diabetes mellites. This cross-sectional and retrospective cohort study induced 203 patients who completed a questionnaire regarding stress levels and lifestyles. Data regarding stress levels, sleep time, exercise, and total diet, snack, and prepared food intake were obtained from the questionnaires. The changes in the body weight or HbA1c levels were determined by comparing the values at the time the questionnaire was administered to those noted 3 months ago. Increased levels of stress and decreased exercise levels were reported in approximately 40% and >50%. During the COVID-19 pandemic. There was a negative correlation between stress and exercise (r = -0.285, p < 0.001) and a positive correlation between stress and prepared food intake (r = 0.193, p = 0.009). Decreased exercise levels (r = -0.33, p < 0.001) and increased snack consumption (r = 0.24, p = 0.002) were associated with increased body weight. Furthermore, increased total diet intake (r = 0.16, p = 0.031) was associated with increased HbA1c levels. These relationships remained significant for patients aged <65 years and patients who did not engage in regular exercise. Many patients experienced stress and lifestyle changes due to the COVID-19 pandemic, and these changes were associated with increased body weight and HbA1c levels.

Background To investigate the acute effects of coronavirus disease (COVID-19) on lifestyle and metabolic parameters in patients with type 1 diabetes (T1D). Methods This retrospective cohort study included 34 patients who were admitted to our hospital from April 16 to May 1, 2020. Data on stress levels, sleep duration, exercise, total diet, snacks, and prepared food intake were obtained from the questionnaires. Changes in the values of hemoglobin A1c (HbA1c) and body weight from 3 months before the administration of the questionnaire to the time the study questionnaire was administered (pandemic year), and those from 15 months before to 12 months before the administration of the questionnaire (pre-pandemic year) were evaluated. Results Increased stress levels and decreased exercise volumes were observed in approximately 60% and 50% of participants during the COVID-19 pandemic, respectively. Decreased sleep duration was associated with changes in the body weight for 3 months during pandemic year ( r = − 0.40, p = 0.043). Furthermore, compared with changes in HbA1c for 3 months during pre-pandemic year, changes in HbA1c during the pandemic year were worse (0.12% [0.33] % during pandemic year vs. − 0.09 [0.39] % during pre-pandemic year, p = 0.027). Conclusions Many patients experienced stress and exercised less due to the COVID-19 pandemic. Glycemic control in patients with T1D was worse than that in the previous year. Since the pandemic is currently ongoing, more attention should be paid to stress and lifestyle factor management in patients with T1D. Supplementary Information The online version contains supplementary material available at 10.1007/s13340-021-00507-4.

BackgroundSarcopenia has reportedly been associated with increased risk of mortality in general populations. However, few studies have investigated the association between sarcopenia and mortality in older people with type 2 diabetes mellitus (T2D). This study aimed to investigate the effect of sarcopenia on incident all-cause mortality in older people with T2D.MethodsLow muscle strength were set at handgrip strength &lt;28 kg for men and &lt;18 kg for women, and low skeletal muscle mass index (SMI), evaluated using the impedance body composition analyzer, were set at SMI &lt;7.0 kg/m2 for men and &lt;5.7 kg/m2 for women. People who had both low muscle strength and low SMI were diagnosed with sarcopenia. Due to a low incidence of all-cause mortality, the propensity score was used. The propensity score was evaluated using multivariable logistic regression models with the following parameters: age, sex, duration of diabetes, history of heart disease, history of cancer, smoking, exercise, alcohol, sodium-glucose cotransporter-2 inhibitor, glucagon-like peptide-1 receptor agonist, insulin, corticosteroid, hypertension, body mass index, glycosylated hemoglobin A1c, triglycerides, and creatinine, and the C-statistic was 0.89.ResultsIn this prospective cohort study, 396 people with an average age and duration of diabetes of 71.3 (6.3) years and 16.3 (11.3) years, respectively, were included. Of those included, 14.6% had sarcopenia. During the average 40.5 (16.5) months of follow-up, 13 people (6 out of the 338 without sarcopenia and 7 out of the 58 with sarcopenia) died. Incident rate were 5.1/1000 person years of follow-up in people without sarcopenia and 41.3/1000 person years of follow-up in people with sarcopenia. According to Cox regression analysis, sarcopenia was associated with all-cause mortality (adjusted hazard ratio: 6.12, 95% confidence interval: 1.52–24.7, p = 0.011).ConclusionSarcopenia is associated with incident all-cause mortality in older outpatients with T2D.

The aim of this cross-sectional study was to examine the association between the geriatric nutritional risk index (GNRI) and the prevalence of sarcopenia in people with type 2 diabetes (T2DM). Having both low handgrip strength (<28 kg for men and <18 kg for women) and low skeletal muscle mass index (<7.0 kg/m2 for men and <5.7 kg/m2 for women) was diagnosed as sarcopenia. GNRI was estimated by the formula as below: GNRI = (1.489 × serum albumin level [g/L]) + (41.7 × [current body weight (kg)/ideal body weight (kg)]). Participants were dichotomized on the basis of their GNRI scores (GNRI < 98, low; or GNRI ≥ 98, high). Among 526 people (301 men and 225 women) with T2DM, the proportions of participants with sarcopenia and low GNRI were 12.7% (n = 67/526) and 5.1% (n = 27/526), respectively. The proportion of sarcopenia in participants with low-GNRI was higher than that with high GNRI (44.4% [n = 12/27] vs. 11.0% [n = 55/499], p < 0.001). The GNRI showed positive correlations with handgrip strength (r = 0.232, p < 0.001) and skeletal muscle mass index (r = 0.514, p < 0.001). Moreover, low GNRI was related to the prevalence of sarcopenia (adjusted odds ratio, 4.88 [95% confidence interval: 1.88–12.7], p = 0.001). The GNRI, as a continuous variable, was also related to the prevalence of sarcopenia (adjusted odds ratio, 0.89 [95% confidence interval: 0.86–0.93], p < 0.001). The present study revealed that low GNRI was related to the prevalence of sarcopenia.

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Exercise has been reported to be effective in maintaining and recovering muscle; however, the effect of exercise combined with adequate or inadequate protein intake on muscle mass is not clear. Therefore, this study investigates the effect of exercise habit on changes in muscle mass, with adequate or inadequate protein intake. This retrospective cohort study included 214 elderly patients with type 2 diabetes. The rate of skeletal muscle mass index (SMI) change (%) was defined as ((SMI at follow-up minus SMI at baseline)/(follow-up years [kg/m2/year] × SMI at baseline [kg/m2])) × 100. Adequate protein intake was defined as protein intake ≥ 1.2 g/kg ideal body weight/day. During a mean follow-up duration of 18.0 (7.1) months, the rate of SMI change was −1.14 (4.10)% in the whole sample. The rate of SMI change of non-habitual exercisers with inadequate protein intake, habitual exercisers with inadequate protein intake, non-habitual exercisers with adequate protein intake, and habitual exercisers with adequate protein intake was −1.22 (3.71), −2.31 (3.30), −1.88 (4.62), and 0.36 (4.29)%, respectively. Compared with patients with exercise habit and adequate protein intake, the odds ratio for decreasing SMI was 2.50 (0.90–6.90, p = 0.078) in patients with no exercise habit and inadequate protein intake, 3.58 (1.24–10.4, p = 0.019) in those with exercise habit and inadequate protein intake, and 3.03 (1.27–7.22, p = 0.012) in those with no exercise habit and adequate protein intake, after adjusting for covariates. Therefore, exercise habit without adequate protein intake was associated with an increased risk of decreasing SMI compared with exercise habit with adequate protein intake.

Non-alcoholic fatty liver disease (NAFLD), often complicated by type 2 diabetes mellitus (T2DM), is reported to be associated with diet habits, including eating speed, in the general population. However, the association between eating speed and NAFLD in patients with T2DM, especially sex difference, has not been reported so far. This cross-sectional study included 149 men and 159 women with T2DM. Eating speed was evaluated by a self-reported questionnaire and divided into three groups: fast, moderate, and slow eating. Nutrition status was evaluated by a brief-type self-administered diet history questionnaire. NAFLD was defined as the hepatic steatosis index ≥36 points. Body mass index and carbohydrate/fiber intake in the fast-eating group were higher than those in the slow-eating group in men, whereas this difference was absent in women. In men, compared with eating slowly, eating fast had an elevated risk of the presence of NAFLD after adjusting for covariates (odds ratio (OR) 4.48, 95% confidence interval (CI) 1.09–18.5, p = 0.038). In women, this risk was not found, but fiber intake was found to be negatively associated with the presence of NAFLD (OR 0.85, 95% Cl 0.76–0.96, p = 0.010). This study indicates that eating speed is associated with the presence of NAFLD in men but not in women.

Background: The aim of this study was to investigate the effect of the coronavirus disease (COVID-19) pandemic restrictions on the change in muscle mass in older patients with type 2 diabetes (T2D), who were not infected with COVID-19. Methods: In this retrospective cohort study, data were obtained from outpatients who underwent bioelectrical impedance analysis at least twice before April 2020 and at least once thereafter. Skeletal muscle mass index (SMI, kg/m2) was calculated as appendicular muscle mass (kg) divided by height squared (m2). Change in SMI (kg/m2/year) was calculated as (follow-up SMI—baseline SMI/follow-up period). The differences between the changes in SMI before and after the start of the COVID-19 pandemic were evaluated using paired t test. Results: This study recruited 56 patients, with a mean (SD) age of 75.2 (7.1) years. SMI changed from 6.7 (0.9) to 6.8 (0.9) kg/m2 before the COVID-19 pandemic, whereas SMI changed from 6.8 (0.9) to 6.6 (0.9) kg/m2 after the start of the COVID-19 pandemic. SMI decreased after the start of the COVID-19 pandemic compared with before the pandemic (−0.117 (0.240) vs. 0.005 (0.289) kg/m2/year, p = 0.049). This decrease was observed in men (−0.159 (0.257) vs. 0.031 (0.325) kg/m2/year, p = 0.038), patients with poor glycemic control (−0.170 (0.264) vs. 0.031 (0.285) kg/m2/year, p = 0.042), and those with a long diabetes duration (−0.153 (0.229) vs. 0.082 (0.291) kg/m2, p = 0.049). Conclusions: The COVID-19 pandemic restrictions caused muscle mass loss in older patents with T2D. Actions, including recommendation of exercise and adequate diet intake, are needed to prevent loss of muscle mass.