Stair climbing,genetic predisposition,and the risk of incident type 2 diabetes:A large population-based prospective cohort study

Background:Cross-sectional evidence and small-scale trials suggest positive effects of stair climbing on cardiometabolic disease and glucose regulation.However,few studies have examined the long-term association between stair climbing and the incidence of type 2 diabetes(T2D).We aimed to prospectively evaluate the association of stair climbing with T2D and assess modifications by genetic predisposition to T2D.Methods:We included 451,699 adults(mean age=56.3±8.1 years,mean±SD;55.2%females)without T2D at baseline in the UK Biobank and followed up to March 31,2021.Stair climbing information was collected through the touchscreen questionnaire.Genetic risk score for T2D consisted of 424 single nucleotide polymorphisms.Results:During a median follow up of 12.1 years,14,896 T2D cases were documented.Compared with participants who reported no stair climbing,those who climbed stairs regularly had a lower risk of incident T2D(10-50 steps/day:hazard ratio(HR)=0.95,95%confidence interval(95%CI):0.89-1.00;60-100 steps/day:HR=0.92,95%CI:0.87-0.98;110-150 steps/day:HR=0.86,95%CI:0.80-0.91;>150 steps/day:HR=0.93,95%CI:0.87-0.99,p for trend=0.0007).We observed a significant interaction between stair climbing and genetic risk score on the subsequent T2D risk(p for interaction=0.0004),where the risk of T2D showed a downward trend in subjects with low genetic risk and those who reported stair climbing activity of 110-150 steps/day appeared to have the lowest overall T2D risk among those with intermediate to high genetic risk.Conclusion:A higher number of stairs climbed at home was associated with lower T2D incidence risk,especially among individuals with a low genetic predisposition to T2D.These findings highlight that stair climbing,as incidental physical activity,offers a simple and low-cost complement to public health interventions for T2D prevention.

Practical Use of Stairs to Assess Fitness, Prescribe and Perform Physical Activity Training

Aim: Evaluating climbing stairs for prescription and implementation of physical activity regimes. Methods: Healthy females (F, n = 14), and males (M, n = 15) participated. By climbing 100 steps of stairs with 0.173 m height, Heart rate (HR) and oxygen uptake were measured throughout the floors;Blood pressure (BP) was measured at ground and the 5th floors only. Results: Energy increased from 2 to 7.6 was metabolic equivalents (METs = 3.5 ml O2/min.kg) at 17.3 m elevation in 2 min. at the 5th floor, and percent Heart Rate Reserve (%HRR) was 66.17% in F and 48.7% in M, proportional to their aerobic efforts. Average climbing efficiency was 15.8 ± 2.3% (n = 29). Aerobic capacity estimated dividing the highest work rate (17.3 Kg.m/2min.Kg × 0.00239 = 0.0207 Kcal/min.Kg), by fractional effort (F = 0.6617, M = 0.487) and fractional efficiency (0.158), at 5 Kcal/L O2 was 0.040 in F and 0.054 L O2/Kg.min in M. Minimum training intensity reached at the 3rd floor by F. In M the highest %HRR reached was 48.7% at the 5th floor, insufficient for training. Conclusions: Stairs used for submaximal evaluation of aerobic capacity and for target intensity prescription. Training, levels climbed, repetitions per day (if 5, 100 Kcal per day, ascending) and number of days/week are adjusted. Full regime requires up to 7.6 METs, a total of 532 and 140 MET.min/week ascending and descending, respectively. Intensities >7.6 MET, climbing rate should be >8.65 m/min. Limiting ascent to 1 (3.5 METs) or 2 (5.5 METs) floors or only descents (2 - 3 METs) may be used for unfit subjects. This method is useful for those with no access to sophisticated facilities.

Obstacle detection and autonomous stair climbing of a miniature jumping robot

Miniature jumping robots(MJRs)have difficulty executing autonomous movements in unstructured environments with obstacles because of their limited perception and computing resources.This study investigates the obstacle detection and autonomous stair climbing methods for MJRs.We propose an obstacle detection method based on a combination of attitude and distance detections,as well as MJRs’motion.A MEMS inertial sensor collects the yaw angle of the robot,and a ranging sensor senses the distance between the robot and the obstacle to estimate the size of the obstacle.We also propose an autonomous stair climbing algorithm based on the obstacle detection method.The robot can detect the height and width of stairs and its position relative to the stairs and then repeatedly jump to climb them step by step.Moreover,the height,width,and position are sent to a control terminal through a wireless sensor network to update the information regarding the MJR and stairs in a control interface.Furthermore,we conduct stair detection,modeling,and stair climbing experiments on the MJR and obtain acceptable precisions for autonomous obstacle negotiation.Thus,the proposed obstacle detection and stair climbing methods can enhance the locomotion capability of the MJR in environmental monitoring,search and rescue,etc.