Preplanned Studies: Impact of Daily Step Count on Diabetes Management and Complications Among Elderly Individuals — Jiangsu Province, China, 2020–2022

The prevalence of type 2 diabetes mellitus (T2DM) is notably increasing within the population of older adults. Research has noted a compelling link between elevated levels of physical activity (PA) and enriched functional health, diminished risk of falls, and enhanced cognitive health in older adults (1). More specifically, PA quantified in daily step counts emerges as a vital modifiable behavior for diabetes management among the geriatric population. Substantial evidence from various studies substantiates that regular PA can lead to a better prognosis on diabetes. Historically, PA was primarily evaluated through questionnaires, which often yielded higher outputs when compared to device-measured activities (2). The advent of movement sensors, such as pedometers, has facilitated more accurate, tangible measurement of PA, in terms of daily step counts. This metric communicated as steps/day is highly translatable, memorable, and readily accessible via modern wearables and smartphones that are now ubiquitous (3). The detection and quantification of appropriate PA levels in older adults has become an area of intensified focus as it plays a significant role in estimating and promoting their overall health status (4).

In the course of this study, we assembled a geriatric diabetic cohort and undertook an analysis of baseline data collected between 2020 and 2022. Our primary focus was the correlation between daily steps and diabetic complications. To accurately assess step counts, we distributed electronic smart wristbands in three distinct streets in Xiangcheng District, Suzhou City, Jiangsu Province. These were primarily given to the elderly diabetic population during freely provided annual health check-ups, sponsored by the local government (5). A total of 1,415 individuals, all 65 years or older and diagnosed with diabetes according to the standards set by the American Diabetes Association (6), participated in the study from 2020 to 2022 (305, 964, and 146 cases per year, respectively).

High-sensitivity cardiac troponin T (hs-cTnT), albuminuria, serum creatine, and other laboratory parameters were measured using Roche Cobas 6000. Microalbuminuria (MA) was defined as a urine albumin-creatinine ratio ≥30 mg/g, subclinical myocardial injury (SMI) as hs-cTnT ≥14 ng/L (7), and chronic kidney disease (CKD) as an estimated glomerular filtration rate (eGFR) <60 mL/(min∙1.73 m²) using the CKD-EPI equation (8). Additional pre-existing conditions such as cancer, chronic obstructive pulmonary disease (COPD), etc. were self-reported by participants through questionnaires, with reference to previous studies (9). This research received approval from the Ethics Committee of Zhongshan Hospital, Fudan University [Approval No. B2020-201(3)], and all participants willingly gave consent to partake in this study.

The study employed t-tests and chi-squared tests for the evaluation of means and category distributions, respectively, based on variables calculated according to steps per day categories. A linear regression model was utilized to estimate correlations, with adjustments made for key potential confounding variables, which included age, gender, body mass index (BMI), HbA1c, amongst other factors. Covariates adjusted for in the logistic regression consisted of age (categorized, <75 and ≥75), gender, BMI (categorized, <18.5, 18.5–23.9, 24.0–27.9, and ≥28.0), HbA1c (categorized, <7% and ≥7%), and triglycerides (TG) (categorized, <1.7 and ≥1.7). Statistical analysis of all data was performed using STATA for Windows (Version 17.0; Stata-Corp, College Station, TX, USA), and two-tailed P values less than 0.05 were deemed statistically significant.

The participant pool of 1,415 individuals comprised 664 males and 751 females, each averaging 6,370 steps/day (±4,431). A trend emerged wherein those who walked more steps daily were generally younger and demonstrated lower BMIs, diastolic blood pressure, and triglyceride levels. Correspondingly, there was a general decrease in HbA1c levels as daily step counts increased. Interestingly, no significant variances were observed in education level, the proportions of current drinkers or smokers, or residential status in relation to step count. With respect to comorbid conditions, the incidences of cancer, COPD, and MA appeared to decline with increased daily steps, albeit falling short of statistical significance. Importantly, higher daily steps were associated with lower levels of the myocardial injury biomarker hs-cTnT, as well as reduced UACR, an indicator of kidney damage or elevated kidney disease risk. Simultaneously, higher estimated glomerular filtration rates (eGFR) correlated with increased steps/day (Table 1).

The linear correlation analysis results indicated negative correlations between the steps per day, and both hs-cTnT (β=−0.207, r=0.14, P<0.001) and the log-transformed UACR (β=−0.0268, r=0.087, P<0.001). A positive correlation surfaced with eGFR (β=0.709, r=0.16, P<0.001). The correlations involving hs-cTnT and eGFR remained significant even after adjusting for variables such as age, gender, BMI, HbA1c, TG, LDL-c, UA, smoking status, residential status, educational level, and insulin administration. (Table 2).

The results from multivariable-adjusted logistic regressions suggest that, when compared to the first quartile, the odds ratios [95% confidence interval (CI)] for self-reported cardiovascular diseases (CVD) (comprising stroke, coronary heart disease, and heart failure) were 0.398 (0.230–0.689), and 0.620 (0.386–0.994) for elevated hs-cTnT — indicating SMI; both showing a statistically significant trend (P<0.05, Table 3). In terms of renal complications, such as MA and decreased eGFR (indicative of CKD), the odds ratios (95% CI) stood at 0.886 (0.617–1.272) and 0.777 (0.374–1.616) respectively. However, these results did not achieve statistical significance (Table 3).