Participants
This is a cross-sectional study using the baseline survey data in WASEDA’S Health Study (Waseda Alumni's Sports, Exercise, Daily Activity, Sedentariness and Health Study). WASEDA’S Health Study is a cohort study conducted with Waseda University’s alumni and their spouses aged 40 or older to examine the relationship between their health outcomes and their habits of sports, exercises, physical activities and sedentary behavior.
We published the overview and objectives of the study through its alumni association, which includes approximately 660 000 people, to invite participants. WASEDA’S Health Study consists of four cohorts (Cohort A to D). For participants in Cohort A, a survey about their physical activities and health outcomes was conducted through the online self-administered questionnaire. For participants in Cohort B, measurements of the amount of their physical activities and the hours of their sitting behavior were conducted using an accelerometer, in addition to the online self-administered questionnaire. For participants in Cohort C, several medical tests were conducted, in addition to Cohort B’s survey items. For participants in Cohort D, physical fitness tests and more detailed medical tests were conducted, in addition to Cohort C’s survey items. Alumni who wanted to join WASEDA'S Health Study could choose any course from Cohort A to D. The participants in Cohort D were chosen as the participants of this study.
The participants in this study were 1387 individuals who joined the Cohort D survey of WASEDA’S Health Study from March 2015 to March 2020 and performed the maximal exercise test and LEP measurement as baseline measurements. The participants include those taking medication due to hypertension, diabetes, and dyslipidemia. Several exclusion criteria were established for accurate analysis. First, those who could not perform the LEP measurement or whose data were clearly abnormal (n = 7), those who had consumed any food in the morning of the measurement (n = 12), and those who had missing blood test data (n = 7) were excluded from the analysis. Then, we also excluded those with missing data of self-administered questionnaire (n = 3), CRF (n = 10), leg circumference (n = 52), grip strength (n = 6), and body fat percentage (n = 1). Those with a history of heart disease (n = 66) were also excluded. Women (n = 427) were excluded because the number of female diabetes patients was small (n = 6), thus only men were included in the analysis of this study (n = 796).
Before the baseline survey, all participants received an explanation of the study and provided their written informed consent. This study has been approved by the research ethics committee of Waseda University (approval number: 2014-G002 and 2018-G001). The report was prepared in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines for cohort studies.
Measures
Medical tests
We conducted a survey on the participants’ sex, age, exercise habits, family history of diabetes, drinking habits, and smoking habits by using a self-administered questionnaire. Exercise habits were categorized into two groups: “with exercise habit” and “without exercise habit”; smoking habits were categorized into three groups: “never smoker”, “former smoker”, and “current smoker”; and drinking habits were classified into four groups: “non-drinker”, “ ≤ 1 day/week”, “2 − 3 days/week”, and “ ≥ 4 days/week”.
A stadiometer and body composition analyzer (MC-980A; Tanita Corp., Tokyo, Japan) were used to measure their height, weight, and body fat percentage. Body weight was measured with participants removing their shoes and wearing light clothing. Based on the results, body mass index was determined. The waist circumference and calf circumference were measured with a measuring tape. The grip strength was also measured using a digital grip strength tester (T.K.K.5401; Takei Scientific Instruments Co., Ltd., Niigata, Japan).
The participants were instructed to fast from the night before the blood test. Blood collection was performed prior to the physical fitness tests. We collected the participants’ venous blood from their forearm vein after making sure that they did not have breakfast. The survey items used for this study include the items related to fat metabolism (total cholesterol, HDL cholesterol, LDL cholesterol, triglycerides) and glucose metabolism (fasting blood glucose, HbA1c). The blood pressure at rest was measured based on the Japanese Society of Hypertension Guidelines for the Management of Hypertension [22] using automated sphygmomanometer (HEM-7250-IT; Omron Healthcare Co., Ltd., Kyoto, Japan).
Cardiorespiratory fitness
All participants performed a maximal exercise test on a cycle ergometer (828E; Monarch Exercise AB, Kingdom of Sweden) to determine the peak oxygen uptake as an index of CRF. After recording an electrocardiogram (ML-9000 and MLX-1000; Fukuda Denshi Co., Ltd., Tokyo, Japan) for three minutes at rest, the participants started the exercise test (men starting from 30 W, women starting from 15 W), increasing 15 W every minute until they were exhausted. They were wearing a mask for respiratory gas analysis during the exercise test and expired gases, pulmonary VO2, and VCO2, by a breath-by-breath method using an automated gas analysis system were analyzed (AE310S and AE100i; Minato Medical Science Co., Ltd., Osaka, Japan). A blood pressure cuff was also attached to the left upper arms to evaluate blood pressure using an automatic blood pressure monitor for the exercise test (Tango M2; Sun Tech Medical Inc., Morrisville, North Carolina, USA). Heart rate and blood pressure were used for safety control before and during the exercise. The endpoint of the exercise test was when their heart rate reached approximately 90% of the predicted maximum heart rate by age, achieving a respiratory exchange ratio > 1.1, and rating of perceived exertion of ≥ 18 or plateauing oxygen intake [23]. We determined that the test was valid if participants had achieved three of the four criteria. The exercise test was stopped when the participants expressed an inability to continue exercise; or when the systolic blood pressure reached 250 mmHg. After the exercise, the participants had a one-minute recovery time and a two-minute rest in the sitting position to conclude the test. Then the highest value of the average oxygen intake at intervals of 30 s during exercise was defined as peak oxygen uptake.
Leg extension power
LEP was measured using a LEP measurement machine that applied a brake load (AnaeroPress 3500; Combi Corp., Tokyo, Japan) during the measurement, the patients were sitting deeply in the chair so that the gap between the waist and back was as narrow as possible, with both feet placed on the foot plate. The chair position was adjusted so that the knee angle was 90 degrees. Their waist and both legs were secured with belts respectively. Five leg extension movements were performed at full force with a load value equal to the body weight of the participants. The participants were instructed to grip the levers on both sides and kick as hard and fast as they could. Calibration (bending and stretching of the legs twice) was performed between each trial, at which time we checked whether the legs were fully extended and whether the waist position shifted. The maximum value of five trials was used for data analysis. Since LEP is affected by body weight, relative LEP (rLEP) which is LEP per body weight (W/kg), was used as an index of muscular fitness.
Determination of diabetes
We defined the participants who answered that they had diabetes in the self-administered questionnaire conducted during the baseline survey as diabetics. In addition, in accordance with the Japan Diabetes Society guidelines, the participants with fasting blood glucose level of 126 mg/dL (7.0 mmol/L) or above in the baseline survey, or with HbA1c of 6.5% or above were also defined as diabetics [24].
Statistics analysis
In order to ascertain the physical characteristics of the study participants, we classified the participants into two groups of diabetics and non-diabetics, and the physical characteristics of both groups were compared. The study participants were divided into two groups by the median of CRF and rLEP, and the physical characteristics of the low CRF group (low CRF), high CRF group (high CRF), the low rLEP group (low rLEP), and the high rLEP group (high rLEP) were compared. The group with low CRF and low rLEP was designated as "low CRF & low rLEP", the group with low CRF and high rLEP was designated as "low CRF & high rLEP", the group with high CRF and low rLEP was designated as "high CRF & low rLEP", and the group with high CRF and high rLEP was designated as "high CRF & high rLEP " for comparison of physical characteristics.
A logistic regression model was used to evaluate how CRF and rLEP each related to the prevalence of diabetes after adjusting for potential confounding factors. First, the relationship between CRF and the prevalence of diabetes was analyzed by inputting the presence of diabetes as the dependent variable and CRF as the independent variable. Factors adjusted using a logistic regression model were age (continuous), body mass index (continuous), exercise habits (yes, no), family history of diabetes (yes, no), smoking habits (current smoker, former smoker, never smoker), and drinking habits (non-drinker, ≤ 1 day/week, 2 − 3 days/week, ≥ 4 days/week). Next, the relationship between rLEP and the prevalence of diabetes was analyzed using a logistic regression model with the presence of diabetes as the dependent variable and rLEP as the independent variable. In addition, we conducted an analysis to determine the relationship between the combination of CRF and rLEP and the prevalence of diabetes. IBM SPSS Statistics 26 (IBM Corp., Armonk, NY, USA) was used for analysis.
