Dose-response relationship between daily step count and prevalence of sarcopenia: A cross-sectional study.

OBJECTIVES: Daily step counts are an easy-to-understand indicator of physical activity; however, there is limited evidence regarding the optimal daily step count to prevent sarcopenia. This study examined the dose-response relationship between daily step count and the prevalence of sarcopenia and explored the optimal dose. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: The study included 7949 community-dwelling middle-aged and older adults (aged 45-74 years) from Japan. MEASUREMENTS: Skeletal muscle mass (SMM) was assessed using bioelectrical impedance spectroscopy, and muscle strength was quantified through handgrip strength (HGS) measurement. Participants who exhibited both low HGS (men: <28 kg, women: <18 kg) and low SMM (lowest quartile in each sex-specific category) were defined as having sarcopenia. Daily step counts were measured for 10 days using a waist-mounted accelerometer. To examine the association between daily step count and sarcopenia, a multivariate logistic regression analysis was performed, adjusting for potential confounding factors such as age, sex, body mass index, smoking status, alcohol consumption, protein intake, and medical history. The odds ratios (ORs) and confidence intervals (CIs) were calculated based on the daily step counts categorized into quartiles (Q1-Q4). Finally, a restricted cubic spline curve was fitted to further investigate the dose-response relationship between daily step count and sarcopenia. RESULTS: The prevalence of sarcopenia in the overall participants was 3.3 % (259/7949 participants), with a mean daily step count of 7292 ± 2966 steps. Expressed in quartiles, the mean daily step counts were 3873 ± 935 steps in Q1, 6025 ± 503 steps in Q2, 7942 ± 624 steps in Q3, and 11,328 ± 1912 steps in Q4. The prevalence of sarcopenia in each quartile of daily step count was 4.7 % (93/1987 participants) in Q1, 3.4 % (68/1987 participants) in Q2, 2.7 % (53/1988 participants) in Q3, and 2.3 % (45/1987 participants) in Q4. The ORs and 95 % CIs adjusted for covariates demonstrated a statistically significant inverse association between daily step count and sarcopenia prevalence (P for trend <0.01), as follows: Q1, reference; Q2, 0.79 (95 % CI: 0.55-1.11); Q3, 0.71 (95 % CI: 0.49-1.03); Q4, 0.61 (95 % CI: 0.41-0.90). The restricted cubic spline curve indicated that the ORs leveled off at approximately 8000 steps per day, and no statistically significant decrease in ORs was observed for daily step counts above this threshold. CONCLUSIONS: The study found a significant inverse association between daily step count and the prevalence of sarcopenia, with the association plateauing when the daily step count exceeded approximately 8000 steps. These findings suggest that 8000 steps per day may be the optimal dose to prevent sarcopenia. Further intervention and longitudinal studies are needed to validate the results.

Effect of the interaction between physical activity and estimated macronutrient intake on HbA1c: population-based cross-sectional and longitudinal studies.

INTRODUCTION: Healthy diet and physical activity (PA) are essential for preventing type 2 diabetes, particularly, a combination of diet and PA. However, reports on interaction between PA and diet, especially from large epidemiological studies, are limited. We investigated the effect of interaction between PA and macronutrient intake on hemoglobin A1c (HbA1c) levels in the general population. RESEARCH DESIGN AND METHODS: We conducted a cross-sectional study of 55 469 men and women without diabetes who participated in the baseline survey of the Japan Multi-Institutional Collaborative Cohort Study. A self-administered questionnaire ascertained PA and macronutrient intake (carbohydrate, fat, and protein). Multiple linear regression analyses were performed to adjust for confounding variables and examine the interactions. In addition, we conducted a longitudinal study during a 5-year period within a subcohort (n=6881) with accelerometer-assessed PA data. RESULTS: Overall, PA had a weak inverse association (ß=-0.00033, p=0.049) and carbohydrate intake had a strong positive association (ß=0.00393, p<0.001) with HbA1c. We observed a tendency of interactions between PA and carbohydrate or fat intake, but not protein intake, on HbA1c levels after adjusting for age, sex, study area, total energy intake, alcohol consumption, smoking, and medication for hypertension or hypercholesterolemia (Pinteraction=0.054, 0.006, and 0.156, respectively). The inverse associations between PA and HbA1c level were more evident in participants with high-carbohydrate (or low-fat) intake than in participants with low-carbohydrate (or high-fat) intake. Although further adjustment for body mass index slightly attenuated the above interactions (Pinteraction=0.098 for carbohydrate and 0.068 for fat), the associations between PA and HbA1c level in stratified analyses remained unchanged. Similar associations and interactions were reproduced in the longitudinal study. CONCLUSIONS: The present results suggest that the effect of PA on HbA1c levels is modified by intake of macronutrient composition.