Next Article in Journal
A Psychometric Pilot Study Examining the Functions of Suicidal Communications Using IRT and Factor Analysis
Next Article in Special Issue
Development and Validation of Waist Girth-Based Equations to Evaluate Body Composition in Colombian Adults: Rationale and STROBE–Nut-Based Protocol of the F20 Project
Previous Article in Journal
Burden of Food Insecurity and Mental Health Symptoms among Adults with Cardiometabolic Conditions during the COVID-19 Pandemic
Previous Article in Special Issue
Elite Adolescent Ice Hockey Players: Analyzing Associations between Anthropometry, Fitness, and On-Ice Performance
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Comparative Analysis of Male Cyclist Population in Four Asia Countries for Anthropometric Measurements

1
School of Industrial Design, Karnavati University, Gandhinagar 342422, Gujarat, India
2
College of Management and Design, Ming Chi University of Technology, New Taipei City 243303, Taiwan
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(16), 10078; https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191610078
Submission received: 15 July 2022 / Revised: 9 August 2022 / Accepted: 13 August 2022 / Published: 15 August 2022
(This article belongs to the Special Issue The Role of Anthropometry in Sport Performance, Health and Nutrition)

Abstract

:
This study aimed to compare the anthropometric variables of male cyclist samples from India, China, Singapore, and Taiwan. The cyclist’s body dimensions were measured among 413 randomly chosen males (aged between 18 to 60), which included 104 Indians, 106 Taiwanese, 100 Singaporeans, and 103 Chinese. Based on the previous research articles, the considered 17 anthropometric variables were weight, stature, BMI, buttock extension, shoulder height (sitting), shoulder-elbow length, elbow height (sitting), lower leg length, knee height, acromion-grip length, hand length, elbow-hand length, buttock-popliteal length, buttock-knee length, elbow-to-elbow breadth, hip breadth (sitting), and foot breadth. Using statistical techniques (descriptive statistics, the Mann–Whitney U test, and Kruskal–Wallis H test), the data were analysed in SPSS, version 25.0. The results of the statistical analyses showed significant differences among the cyclists across selected anthropometric characteristics, except for the weight and sitting-related anthropometric measurements. The outcome of the descriptive statistics (percentile values), such as the percentile range (5th to 95th percentile), could be applied to the seat-height adjustment system to cover 95% of the bicyclist population. These types of implantation could enhance the ergonomic benefits for the bicyclist.

1. Introduction

The World Health Organization (WHO) declared that people engaged in physical activity have a significant affirmative effect on health development, such as walking and cycling [1]. The number of recreational cyclists is increasing in North America [2,3], Canada [4], various European countries [5], and also Asian countries [6]. In recent years, with the improvement of road construction and the promotion of healthy lifestyles in Asian countries, more and more people have begun to participate in cycling activities [7]. For example, the number of cyclists in Taiwan has tripled in just three years, and 80% of them are for recreational exercise purposes, as reported by the Council for Economic Planning and Development of Taiwan. Among other Asian countries (e.g., China, India, and Singapore), the overall cycling rates are continuously increasing [8]. This means an incredible demand for bicycle use is occurring. Moreover, an improper bicycle design and body fitting might cause discomfort, neck pain, muscle fatigue, and poor riding performance due to the awkward postures used [9,10,11]. Hence improving a cyclist’s riding comfort through designs with ergonomic concepts became vital. One of the critical features influencing the riding posture and performance was reported as anthropometric data [12], such as body-surface dimensions and frontal-body dimensions [13]. Many studies have recommended that anthropometric data can achieve better human–machine interactions, comfort, and performance, especially in cycling, bike design, and bike fitting [14,15,16,17].
Anthropometry has been indicated as an indispensable reference for product design to enhance the user’s performance and comfort. Thus, many whole-body anthropometric databases have been reported in various Asian countries, for example, Taiwan [18], the Philippines [19], Thailand [20], Turkey [21], Bangladesh [22], Iran [23], Malaysia [24], Western India [25], Indonesia [26], Singapore [27], and India [28]. The anthropometric differences among countries may be attributed to racial, social, and economic environments [29]. Regrettably, some previous studies are outdated and need to be updated.
With the changes in living habits and economic development, the human body’s dimensions also gradually change [27,30,31]. Thus, the difference in anthropometric data between various nations and the regional population is observed [29,32]. This means the anthropometric data are population-specific and difficult to use for different ethnic populations [23,24]. Therefore, exploring the differences in anthropometric data among different ethnicities or countries is valuable. Some studies have investigated the ethnic differences of body dimensions in the same country. For example, Widyanti et al. [33] and Hartono [26] measured Indonesian anthropometry data under different ethnicities (e.g., Minangkabau, Javanese, Sundanese, Drills, Chinese, and Non-Chinese). Moreover, Bhattacharjya and Kakoty [34] reported the ethnic differences in anthropometric data obtained from the Boro, Garo, Hira, Karbi, and Rabha living in India. Moreover, the same race coming from different countries might exhibit a dissimilarity in body dimensions. Lin et al. [29] first conducted a study to compare the anthropometric characteristics among four East Asian populations (the Taiwanese, Chinese, Japanese, and Koreans). Subsequently, Sadeghi et al. [23] compared the anthropometric data of Iranians with the previous Asian countries. Moreover, Chuan et al. [32] investigated the differences in anthropometric data between the Singaporean and Indonesian populations. Da Silva et al. [35] completed a comparison of anthropometry of Brazilian and US military populations and applied the results to a flight deck design. Rahman et al. [36] collected the anthropometric measurements of Malaysians and compared them to Indonesians, Filipinos, and Thai populations on sitting and standing body dimensions. All the mentioned studies showed that differences in ethnicity and countries were found in the anthropometric data.
However, due to the original human anthropometric data in different countries being measured by different research groups, most previous studies could only use the mean of the body dimensions and bodily proportions as parameters for comparing the body dimensions between different populations. This kind of comparison could only provide indirect evidence of the population differences in anthropometric data and the lack of statistical significance tests to support the fact. This may cause errors in practical applications. Hence, the current study was to conduct a cross-nation anthropometric data collection in Taiwan, Singapore, India, and China, and to compare the differences in the various body dimensions related to cycling design among the four Asian populations. The aim was divided into two objectives for better achievement as follows: (1) To present the descriptive analysis of Asian bicyclists’ anthropometric variables for bicycle design; (2) to compare the anthropometric variables of Asian bicyclist samples by using statistical techniques. The findings of this study can provide useful information for the ergonomics consideration of different countries during the bicycle design process. Further, it would be used in a CAD environment for the virtual ergonomics assessment of bicycles. In addition, the data could be processed further with statistical packages for developing a boundary-human model (virtual manikins) during the virtual ergonomics assessment of bicycles.

2. Materials and Methods

2.1. Participants

Since the bicyclist population of Asian countries (Singapore, Taiwan, India, and China) is still unknown, the minimum sample size was calculated (n ≥ 385) using the following parameters and Equation (1) [37]. Where the confidence level = 95% (Z = 1.96); with a sample proportion of 50% (p = 0.5) and the margin of error is 5% (e = ±0.05).
n = Z 2 p ( 1 p ) e 2
The cyclists’ body dimensions were measured among 413 randomly chosen males (aged between 18 to 60), which included 104 Indians, 106 Taiwanese, 100 Singaporeans, and 103 Chinese. These surveys were conducted in Singapore (Nanyang Technological University), Taiwan (Ming Chi University of Technology), China (South China University of Technology), and India (Karnavati University). Most of the subjects (bicyclists) were students or employees of these universities. We assumed that all the subjects of their individual countries were representatives of the bicyclist population with good health. The subjects with previous health issues (such as motor skills, bone fractures, etc.) were disallowed in the survey. All subjects were provided with a consent document for measuring their anthropometrics with an understanding of the research purpose. Due to a lack of manpower, the gender of investigators (all men), and time constraints, this study mainly measured the body dimensions of male samples.

2.2. Selection of Anthropometric Variables

We measured 17 anthropometrics (which included stature body height, buttock extension, shoulder height (sitting), shoulder-elbow length, elbow height (sitting), lower leg length, knee height, acromion-grip length, hand length, elbow-hand length, buttock-popliteal length, buttock-knee length, elbow-to-elbow breadth, hip breadth (sitting), foot breadth, BMI, and weight). These measurements were recognized from earlier research articles [14,28,38,39,40,41,42,43], which investigated/studied affairs related to ergonomics in bicycle/two-wheeler designs. According to the ISO 7250-1: 2008(E) standards, the anthropometric measurement procedures were followed to obtain the bicyclists’ body dimensions (see Figure 1).

2.3. Measuring Instruments

Manual anthropometric measuring apparatus and equipment were used due to the reason of accuracy/preciseness, ease of portability, and affordability [44]. Each piece of equipment was calibrated before obtaining the anthropometric measurements of bicyclists. In total, five pieces of equipment (see Figure 2) were used during the data collection process. One larger sliding caliper (make: Mitutoyo Corporation: Kawasaki, Japan; range: 0–700 mm; accuracy: 0.02 mm; resolution: 0.01 mm) was used to measure the length/height/width of body segments. A small sliding caliper (make: Mitutoyo Corporation- Kawasaki, Japan; 0–300 mm measurement range; 0.02 mm accuracy and 0.01 mm resolution), stadiometer-height measuring tape (Model: Gadget Hero, Beijing, China; Maximum 200 cm), nonstretchable plastic measuring tape (2000 mm), and portable weighing scale (138 kg maximum capacity, model: Crown Classic, New Delhi, India) were also used for collecting the anthropometric data.

2.4. Measurement Procedure

Before the measurement procedure started, the participants were informed regarding the measurement procedures and protocols for the data collection. Additionally, the participants were asked to provide their written consent for the data collection, which was prepared according to the Helsinki guidelines and approved by the committees from the four mentioned universities. The 15 measurements (see Figure 3), BMI, and body weight were carefully observed by well-trained anthropometrist, who are familiar with anthropometry and human-body landmarks for error-free and reliable measurements. Weight, stature, and buttock extension were measured in the standing position of the participants. During these measurements, the participants were asked to stand in an anatomical position on a flat floor. Similarly, the other thirteen measurements (shoulder height (sitting), shoulder-elbow length, elbow height (sitting), lower leg length, knee height, acromion-grip length, hand length, elbow-hand length, buttock-popliteal length, buttock-knee-length, elbow-to-elbow breadth, hip breadth (sitting), and foot breadth) were observed in the sitting position with adjustable stoles. During these measurements, the participants were asked to keep their torso in an erect manner (with their shoulders and head aligned with the same vertical plane), their knees together without any gaps, and their feet on the flat floor. All the measurements were recorded in the participant’s semi-nude clothing condition. Since the intra-/inter- reliability assessment anthropometry results were highly reliable, the measurements observed in the datasheet from a single trial were only for future analysis.

2.5. Intra-/Inter- Reliability Assessment of Anthropometry

Before the anthropometric measurements were conducted on the cyclists of each country, inter-observer and intra-observer reliability tests were conducted on 10 randomly chosen healthy cyclists to assess the precision of the linear and mass measurements. To ensure the precision and accuracy in the measurement of all the anthropometric data, the reliability of anthropometry was estimated as the technical error of measurement (%TEM) of the inter-/intra-observer. This % TEM helped us to understand the manual or instrumental errors.
During the inter-reliability assessment, anthropometrists-1 and anthropometrists-2 measured the anthropometrics for 10 cyclists on the same day. For the intra-reliability assessment, anthropometrists-1 measured all the anthropometrics during the first week. In the subsequent week, the same anthropometry was followed by the anthropometrists-1 to estimate the %TEM of the intra-reliability assessment.
The %TEMs of the intra-/inter- were calculated in a spreadsheet using a set of %TEM equations, as stated in a previous research article [28]. In Appendix A, Table A4 presents the intra-/inter- reliability assessment of the anthropometrics with respect to countries. The %TEM of intra-reliability ranged from 0.15% to 1.73% across four countries. For the %TEM of inter-reliability, the estimation ranged from 0.11% to 1.57% across four countries.

2.6. Data Analysis

Using the IBM SPSS version 25.0 software (IBM: Armonk, NY, USA), the anthropometric data of the counties were analysed for the mean, standard deviation, maximum, minimum, range, and percentile distributions (5th, 50th, and 95th). Since the Kolmogorov–Smirnov test was used for n ≥ 50, the Shapiro–Wilk test was more appropriate for the small sample sizes (50 samples). However, it can also handle larger sample sizes [45]. The Shapiro–Wilk test was performed to assess the data’s normality at a confidence level of p-values of <0.05. Due to various reasons (such as limited samples, anthropometric variability, etc.), the normality test results imply that the data were not normally distributed. Henceforth, the differences among the four Asian countries were determined using the non-parametric Kruskal–Wallis test for all anthropometric measurements. Moreover, non-parametric statistics analyses (i.e., Mann–Whitney U Test) were performed to understand the difference between every two countries’ cyclists’ body dimensions. The comparison was performed in the following manner: Singapore (SGD) vs. Taiwan (ROC); SGD vs. China (PRC); SGD vs. India (INR); ROC vs. PRC; INR vs. ROC; INR vs. PRC. The basic cyclist characteristics were calculated by the following equation and methods. The body-surface area was estimated based on the Fujimoto and Watanabe formula [46]. As per Nes et al. [47], the HUNT equation (HRmax (beats/min) = [211 − 0.64 × Age]) is the slightly more precise formula and is adjusted for generally active users. Therefore, we used the HUNT equation for the HRmax estimation instead of the Inbar equation. For estimating the performance level, (VO2) = 111.33 − 0.42 H, where H is the resting heart rate, as per Uth et al. [48].

3. Results

The descriptive statistics of 413 male cyclists’ anthropometric measurements were presented using the mean, standard deviation, maximum, minimum, range, and percentile distributions (h, 50th, and 95th) for four countries (India, China, Singapore, and Taiwan). The 413 male cyclists had a mean age of 32 years (SD 11.5 years). These cyclists had a mean riding experience of 5 years (SD 4 years). Table 1 presents the summary (mean, minimum, and maximum) of the cyclists’ characteristics from the four countries. Table A3 in Appendix A presents the individual country’s cyclist characteristics. Table 2 and Table A1 present the descriptive statistics for 18 anthropometric measurements (including BMI) among the four countries.
The Kruskal–Wallis test showed (Table 3) a statistically significant difference in the anthropometric measurements among these countries. The Kruskal–Wallis test’s H value is presented (Table 3), which indicates a 5% probability of summarizing that a difference presents when there is no actual difference. The mean Kruskal–Wallis test rank is shown (in Table 3), where the average of the ranks for all the anthropometric observations within each sample of the countries is displayed.
The Mann–Whitney U test results are summarized in Table 4 and Table A2. From the results in Table 4, the comparative analysis between the Singaporean and Taiwanese cyclists indicated that there is a significant difference (p < 0.05) among all anthropometric measurements, except for body weight. By comparing the median of the body weights between the Singaporeans and Taiwanese (see Table A2), the Mann–Whitney U test indicated that the cyclist’s weight was greater for Taiwanese (Mdn = 109.83) than for the Singaporeans (Mdn = 96.8). The comparative analysis between the Singaporean and Chinese cyclists indicates that there is a significant difference (p < 0.05) among all anthropometric measurements, except for foot breadth and BMI. Nevertheless, the test results indicate that the BMI of cyclists was greater for the Chinese (Mdn = 106.87) than for the Singaporeans (Mdn = 96.98), U = 4648, p = 0.23. In a comparison of the Singaporean cyclists with Indian cyclists, mostly the sitting-related anthropometric measurements (stature body height, shoulder height (sitting), elbow-to-elbow breadth, foot breadth, and BMI) were insignificant (p > 0.009) between the two counties. However, other anthropometric measurements were found to be significantly different (p < 0.05) from each other. The comparative analysis between the Taiwanese and Chinese cyclists indicated that there is a significant difference (p < 0.05) among most of the anthropometric measurements, except for weight, stature, elbow height (sitting), and lower leg length. The comparative analysis between the Indian and Taiwanese cyclists indicated that there is a significant difference (p < 0.05) among all anthropometric measurements, except for weight, buttock extension, and hand length. The test results indicated that the cyclists’ weight was greater for Taiwan (Mdn = 109.42) than India (Mdn = 101.65), U = 5104, p = 0.35. The results comparison between the Indian and Chinese cyclists indicated that there is a significant difference (p < 0.05) among most of the anthropometric measurements, except for acromion-grip length, foot breadth, BMI, and weight.

4. Discussion

This study collected anthropometric data from four different populations (Indian, Singaporean, Taiwanese, and Chinese). The body dimensions were summarized. The presented percentile values can be applied as a guide for product design, especially in the sitting-related activities (e.g., cycling) among the four groups, in general. According to the statistical results, most of the body dimensions were significantly different among the selected ethnic populations.
Table 2 shows the descriptive statistics for the 17 body dimensions for the Indian, Singaporean, Taiwanese, and Chinese populations. Among the four Asian populations, the Chinese males had the highest stature, while the Singaporean males presented the shortest stature. For the Taiwanese males, the smallest body dimensions were obtained on shoulder height (sitting), shoulder-elbow length, acromion-grip length, elbow-hand length, buttock-popliteal length, buttock-knee length, and elbow-to-elbow breadth when compared with the other three populations. Moreover, the five largest (lower leg length, knee height, elbow-hand length, buttock-popliteal length, and buttock-knee length) and three most minor (buttock extension, elbow height (sitting), hand length) body dimensions were found in the Indian population compared to the others. The Singaporeans had the greatest buttock extension and acromion-grip length but the smallest lower leg length, knee height, hip breadth (sitting), and foot breadth. The Chinese males presented with the most significant body size for shoulder height (sitting), shoulder-elbow length, hand length, and body weight among the four Asian populations. The differences in the body dimensions among the four Asian populations can be contributed to geographical factors, such as ethnicity, nutrition, economic development, and lifestyle [21,29]. These results support the previous studies [27,33] that reported on the geographic factors influencing genetic differentiation in ethnic populations, especially for stature and body weight. The geographical condition was related to unique socioeconomic statuses, activity, and nutrition intake and generated the different levels of medical and social services, which impacted the differences in body dimensions [21]. The mentioned specific body characteristics between the four populations should be considered as valuable information for bicycle designers to adequately satisfy the differences in overseas customers. For example, when designing a bike to be imported to Singapore, a redesign process is needed for a better fitting based on the Singaporean males’ specific body dimensions (e.g., a shorter lower leg length and knee height).
While comparing Singaporean, Indian, Chinese, and Taiwanese cyclists’ anthropometric measurements, there is a significant difference. Specifically, the Taiwanese cyclists’ weight is greater than that of Singaporeans. The Chinese cyclists’ BMI is greater than that of Singaporeans. Perhaps, these differences might be due to the different food diets, years of practice, and so on. In a comparison of the Singaporean cyclists with Indian cyclists, mostly sitting-related anthropometric measurements were insignificantly different from each other. Regarding the comparison of the Taiwanese cyclists with cyclists from other countries (China/India), the anthropometric measurements were significantly different from each other. However, a few of the anthropometric measurements (weight, stature, elbow height (sitting), lower leg length, buttock extension, and hand length) were insignificantly different from each other. Perhaps, these could be the same ethnicity or migration of cyclists from their native country.
Anthropometric data vary based on many factors, such as age and gender [27,31,32]. In the current study, we selected similar age groups among the four populations and limited the study to male subjects to avoid other influences. Apart from the geographical differences, it should be noted that there are cultural differences between the four populations. Many pieces of research focused on the body morphological differences among various ethnic populations. Moreover, lifestyle, occupation, genetics, social environment, labor structure, and economic levels play an important role in affecting the anthropometric body measurements of a population group [29]. For a global marketing business, it is essential for product designers to consider the anthropometric differences of nations in the design process. When realizing the differences between populations and applying them to a product design, the products are then designed in accordance with the user’s body characteristic requirements.
The descriptive statistical outcomes could be applied to bicycle design. For instance, the 95th percentile of weight can be used in the bicycle’s seat design. This application could facilitate the weight-carrying capacity of a bicycle seat for up to 95% of the bicyclists. Similarly, the 50th percentile value applications in bicycle design would be facilitated to cover 50% of the bicyclist population. In particular, range (5th to 95th percentile) values could be applied in the seat-height adjustment system to cover 95% of the bicyclist population.
A validation was applied to evaluate the margin of errors in the selected body dimensions among the four populations. Across all data for the four populations, the %TEM test results reported that the intra- and inter-reliability of the current study was 0.15% to 1.73% and 0.11% to 1.57%, respectively. Based on the study of Arunachalam et al. [28], this research agreed that the %TEMs of an intra-/inter- less than 2% were considered to be highly reliable. Hence, our results suggested that anthropometry (i.e., anthropometrists-1, measurement protocol, instrument) is a trustworthy method for further data collection and comparisons. Meanwhile, all measurements in the current study were performed with rational precision and reliability during the collection of the body dimensions and were verified.
As per the literature survey, there was no any comparative investigation performed for the cyclists’ anthropometric measurements in these countries (Singapore, India, Taiwan, and China). The current investigative study is a first-of-its-kind to carry out this approach. Overall, the current study’s findings, from the qualitative analyses, could lead to performing large-scale anthropometric surveys by researchers and ergonomists. Further, an individual country’s anthropometric database for cyclists could be developed to improve the betterment of bicycle designs.
The current study considered only males and the age groups between 18 to 60. Considering both female and male cyclists, the male population was supposed to be greater. Thus, this study was conducted with male cyclists. However, a similar line of study has been planned for females from these countries in the future. Due to limited resources, a comparative analysis was performed for these countries (Singapore, India, Taiwan, and China) only. Due to the time constraints, the sample sizes were marginally small, which arose as a limitation in the parametric statistical analyses to generalize the results. However, the study sample size matches the minimal sample size. A large-sample study may include each country’s ethnicity, etc., which may also affect the cyclist’s anthropometric measurements.

5. Conclusions

This study was conducted to characterize male cyclists from India, Taiwan, China, and Singapore through an anthropometric study. Seventeen body dimensions were studied using anthropometric kits. Based on the statistical analysis, it has been established that most of the standing anthropometric measurements were different from each other. However, the weight and sitting-related anthropometrics did not differ much. This is the first study of its kind to present a descriptive analysis of four different countries’ (Singapore, India, Taiwan, and China) anthropometric measurements for cyclists. The involvement of the percentile values in bicycle design will improve the ergonomic benefits for the bicyclist. Therefore, this study acts as a dataset for performing bicycle ergonomic design in these countries (Singapore, India, Taiwan, and China).

Author Contributions

Conceptualization, Y.-C.L.; methodology, A.M. and Y.-C.L.; validation, A.M. and Y.-C.L.; formal analysis, Y.-C.L.; investigation, Y.-C.L.; resources, Y.-C.L.; data curation, Y.-C.L.; writing—original draft preparation, A.M. and Y.-C.L.; writing—review and editing, A.M. and Y.-C.L.; visualization, A.M. and Y.-C.L.; supervision, Y.-C.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of National Tsing Hua University, ref. 10311HE039.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table A1. Additional descriptive statistics. Note: All measurements are in mm unless specified.
Table A1. Additional descriptive statistics. Note: All measurements are in mm unless specified.
Anthropometric VariablesConfidence IntervalChineseIndianTaiwaneseSingaporeans
Stature body height95% Confidence Interval for MeanLower Bound1710.741680.811710.381668.51
Upper Bound1734.101707.561731.551698.75
Std. Deviation59.7868.7854.9576.20
Buttock extension95% Confidence Interval for MeanLower Bound872.56832.64854.58956.57
Upper Bound903.09856.15869.84975.97
Std. Deviation78.1060.4339.6348.90
Shoulder height (Sitting)95% Confidence Interval for MeanLower Bound613.47571.20509.94570.42
Upper Bound630.42583.23523.66589.00
Std. Deviation43.3830.9235.6246.84
Shoulder-elbow length95% Confidence Interval for MeanLower Bound360.76350.09251.22325.55
Upper Bound375.36358.79258.40346.45
Std. Deviation37.3522.3818.6352.66
Elbow height (Sitting)95% Confidence Interval for MeanLower Bound243.91217.00256.62237.40
Upper Bound259.17227.50267.37250.02
Std. Deviation39.0327.0127.9031.81
Lower leg lengthMean425.69447.60419.97413.90
95% Confidence Interval for MeanLower Bound417.77439.58414.84408.37
Upper Bound433.62455.61425.10419.43
Std. Deviation40.5541.1926.6227.88
Knee height95% Confidence Interval for MeanLower Bound527.47542.67503.37493.31
Upper Bound538.43559.79512.91509.09
Std. Deviation28.0444.0324.7639.74
Acromion-grip length95% Confidence Interval for MeanLower Bound623.07621.17563.71639.99
Upper Bound638.88637.18574.21663.81
Std. Deviation40.4541.1427.2660.04
Hand length95% Confidence Interval for MeanLower Bound181.13175.03176.09180.49
Upper Bound189.67180.23179.93183.85
Std. Deviation21.8313.389.988.47
Elbow-hand length95% Confidence Interval for MeanLower Bound443.44469.51362.80456.79
Upper Bound454.49479.59370.34467.33
Std. Deviation28.2625.9119.5926.58
Buttock-popliteal length95% Confidence Interval for MeanLower Bound430.79490.09350.04449.87
Upper Bound446.01505.37359.62460.57
Std. Deviation38.9539.2924.8826.96
Buttock-knee length95% Confidence Interval for MeanLower Bound534.05588.29447.78556.45
Upper Bound561.01602.02459.74568.05
Std. Deviation68.9735.2931.0429.21
Elbow-Elbow breadth95% Confidence Interval for MeanLower Bound442.06422.84394.65429.26
Upper Bound461.10437.78403.56440.64
Std. Deviation48.7038.4123.1528.67
Hip breadth (Sitting)95% Confidence Interval for MeanLower Bound352.53331.53371.65302.97
Upper Bound367.68342.24381.84311.37
Std. Deviation38.7627.5426.4421.19
Foot breadth95% Confidence Interval for MeanLower Bound98.69100.11103.4099.73
Upper Bound105.27103.33105.21102.39
Std. Deviation16.828.274.706.70
Weight (kg)95% Confidence Interval for MeanLower Bound68.2666.1565.9464.47
Upper Bound72.4570.3269.2467.41
Std. Deviation10.7210.728.567.42
BMI (kg/m2)95% Confidence Interval for MeanLower Bound23.0823.0921.8722.84
Upper Bound24.3324.5122.8723.69
Std. Deviation3.223.672.612.13
Table A2. Mean rank of Mann–Whitney test.
Table A2. Mean rank of Mann–Whitney test.
Anthropometric VariablesSingaporean
vs.
Taiwanese
Singaporean
vs.
Chinese
Singaporean
vs.
Indian
Taiwanese
vs.
Chinese
Indian
vs.
Taiwanese
Indian
vs.
Chinese
Stature body height86.785.6798.62104.2291.5890.66
119.35117.85106.24105.81119.16117.47
Buttock extension150.74136.49149.6488.4597.5482.55
58.9468.5157.18122.03113.31125.66
Shoulder height (Sitting)140.4577.13102.7656.46147.4671.41
68.65126.15102.25154.9664.33136.91
Shoulder-elbow length152.4885.8292.0453.51158.4695.04
57.3117.71112.56157.9953.54113.04
Elbow height (Sitting)85.6693.02122.27111.3468.8579.18
120.33110.7283.4998.47141.46129.06
Lower leg length95.8387.3175.1297.28128.69119.18
110.74116.27128.83112.9582.7588.67
Knee height92.6673.6967.9579.04140.23118.74
113.73129.49135.73131.7171.4389.12
Acromion-grip length145.83112.9711462.12146.92104.88
63.5791.3591.44149.1364.86103.12
Hand length116.8492.29113.685.53104.9686.42
90.92111.4391.83125.03106.03121.75
Elbow-hand length156.14116.7990.654.84158.49130.43
53.8487.64113.94156.6253.5177.31
Buttock-popliteal length155.69117.5970.158.14158.43141
54.2686.86133.66153.2253.5766.64
Buttock-knee length155.48112.8375.8157.13158.45133.39
54.4791.49128.16154.2653.5574.33
Elbow-to-elbow breadth139.1184.22105.0963.21132.7587.87
69.91119.26100.01148.0178.76120.29
Hip breadth (Sitting)52.5760.5970.25122.267.6182.98
151.55142.2133.5187.3142.68125.23
Foot breadth88.42106.8398.71123.3397.18109.5
117.7397.32106.1486.13113.6798.45
BMI116.2396.9895.490.93119.86106.53
91.49106.87109.33119.4891.42101.44
Weight96.887.7493.2996.95109.42100.73
109.83115.84111.36113.28101.65107.3
Table A3. Summary of cyclists’ characteristics (n = 406).
Table A3. Summary of cyclists’ characteristics (n = 406).
CharacteristicSingapore (SGD)India (INR)Taiwan (ROC)China (PRC)
MeanRangeMeanRangeMeanRangeMeanRange
MinMaxMinMaxMinMaxMinMax
Age (Yrs.)272056251837302049321959
Body surface area (m2)1.761.462.201.781.332.111.791.542.331.831.332.33
HRmax (beats/min)194175198195187199192180198191173199
Performance level (VO2)797882797880797881797882
Years of practice923871191223114141
Weekly training load (km)265024522978278521253250270019852985252020852920
Note: The body surface area has been estimated based on the Fujimoto and Watanabe (1969) formula; HRmax (beats/min) = [211 − 0.64 × Age]; performance level (VO2) = 111.33 − 0.42 H, where H is resting heart rate, as per Uth et al. [48].
Table A4. Technical Error of Measurement for 16 Anthropometrics (n = 10).
Table A4. Technical Error of Measurement for 16 Anthropometrics (n = 10).
Anthropometric VariablesIntra-Observer Technical Error (%TEM)Inter-Observer Technical Error (%TEM)
Singapore (SGD)India (INR)Taiwan (ROC)China (PRC)Singapore (SGD)India (INR)Taiwan (ROC)China (PRC)
Stature body height0.470.510.350.490.110.240.340.45
Buttock extension0.320.340.280.300.350.480.540.54
Shoulder height (Sitting)0.940.930.860.841.201.091.240.59
Shoulder-elbow
length
1.111.240.921.010.981.091.321.45
Elbow height (Sitting)1.731.681.451.641.201.541.050.95
Lower leg length1.21.230.890.980.890.970.851.57
Knee height0.400.540.650.350.680.780.561.25
Acromion-grip length0.640.790.680.540.600.630.701.01
Hand length1.331.351.211.011.211.511.241.32
Elbow-hand length0.910.930.780.890.780.880.780.85
Buttock-popliteal length1.101.391.561.230.680.870.740.65
Buttock-knee length0.860.660.980.780.650.730.690.95
Elbow-to-elbow breadth0.640.800.750.740.850.890.941.02
Hip breadth (Sitting)0.950.960.980.91.011.181.251.35
Foot breadth0.640.780.850.540.940.980.860.89
Weight0.230.150.30.250.230.340.320.35

References

  1. World Health Organization. Physical Activity. Available online: https://www.euro.who.int/en/health-topics/environment-and-health/Transport-and-health/data-and-statistics/physical-activity2 (accessed on 20 March 2021).
  2. Pucher, J.; Buehler, R.; Seinen, M. Bicycling renaissance in North America? an update and re-appraisal of cycling trends and policies. Transport. Res. Part A Pol. Pract. 2011, 45, 451–475. [Google Scholar] [CrossRef]
  3. Young, M.; Savan, B.; Manaugh, K.; Scott, L. Mapping the demand and potential for cycling in Toronto. Int. J. Sustain. Transport. 2021, 15, 285–293. [Google Scholar] [CrossRef]
  4. Assunçao-Denis, M.; Tomalty, R. Increasing cycling for transportation in Canadian communities: Understanding what works. Transport. Res. A Pol. Pract. 2019, 123, 288–304. [Google Scholar] [CrossRef]
  5. Aldred, R.; Woodcock, J.; Goodman, A. Does more cycling mean more diversity in cycling? Transp. Rev. 2016, 36, 28–44. [Google Scholar] [CrossRef]
  6. Chen, C.F.; Chen, P.C. Estimating recreational cyclists’ preferences for bicycle routes—Evidence from Taiwan. Transp. Policy 2013, 26, 23–30. [Google Scholar] [CrossRef]
  7. Hsieh, L.Y.; Lin, Y.C.; Lee, Y.H.; Lee, S.T. Relationship between bikeway image, tourism value and intention to revisit bikeways in Taiwan. J. Inf. Optim. Sci. 2021, 42, 235–248. [Google Scholar] [CrossRef]
  8. Goel, R.; Goodman, A.; Aldred, R.; Nakamura, R.; Tatah, L.; Martin, L.; Garcia, T.; Zapata-Diomedi, B.; De Sa, T.H.; Tiwari, G.; et al. Cycling behaviour in 17 countries across 6 continents: Levels of cycling, who cycles, for what purpose, and how far? Transp. Rev. 2022, 42, 58–81. [Google Scholar] [CrossRef]
  9. Streisfeld, G.M.; Bartoszek, C.; Creran, E.; Inge, B.; McShane, M.D.; Johnston, T. Relationship between body positioning, muscle activity, and spinal kinematics in cyclists with and without low back pain: A systematic review. Sports Health 2017, 9, 75–79. [Google Scholar] [CrossRef]
  10. Brand, A.; Sepp, T.; Klöpfer-Krämer, I.; Müßig, J.A.; Kröger, I.; Wackerle, H.; Augat, P. Upper Body posture and muscle activation in recreational cyclists: Immediate effects of variable cycling setups. Res. Q. Exerc. Sport. 2020, 91, 298–308. [Google Scholar] [CrossRef]
  11. Garimella, R.; Peeters, T.; Parrilla, E.; Uriel, J.; Sels, S.; Huysmans, T.; Verwulgen, S. Estimating cycling aerodynamic performance using anthropometric measures. Appl. Sci. 2020, 10, 8635. [Google Scholar] [CrossRef]
  12. Menaspa, P.; Rampinini, E.; Bosio, A.; Carlomagno, D.; Riggio, M.; Sassi, A. Physiological and anthropometric characteristics of junior cyclists of different specialties and performance levels. Scand. J. Med. Sci. Sports 2012, 22, 392–398. [Google Scholar] [CrossRef] [PubMed]
  13. Brunkhorst, L.; Kielstein, H. Comparison of anthropometric characteristics between professional triathletes and cyclists. Biol. Sport 2013, 30, 269–273. [Google Scholar] [CrossRef] [PubMed]
  14. Grainger, K.; Dodson, Z.; Korff, T. Predicting bicycle setup for children based on anthropometrics and comfort. Appl. Ergon. 2017, 59, 449–459. [Google Scholar] [CrossRef] [PubMed]
  15. Wadsworth, D.J.S.; Weinrauch, P. The roel of a bike fit in cyclists with hip pain. A clinical commentary. Int. J. Sports Phys. Ther. 2019, 14, 468–486. [Google Scholar] [CrossRef]
  16. Holliday, W.; Swart, J. Anthropometrics, flexibility and training history as determinants for bicycle configuration. Sports Med. Health Sci. 2021, 3, 93–100. [Google Scholar] [CrossRef]
  17. Scoz, R.D.; Amorim, C.F.; Espindola, T.; Santiago, M.; Mendes, J.J.B.; De Oliverira, P.R.; Ferreira, L.M.A.; Brito, R.N. Discomfort, pain and fatigue levels of 160 cyclists after a kinematic bike-fitting method: An experimental study. BMJ Open Sport Exerc. Med. 2021, 7, e001096. [Google Scholar] [CrossRef]
  18. Wang, E.M.Y.; Wang, M.J.; Yeh, W.Y.; Shih, Y.C.; Lin, Y.C. Development of anthropometric work environment for Taiwanese workers. Int. J. Ind. Ergon. 1999, 23, 3–8. [Google Scholar] [CrossRef]
  19. Del Prado-Lu, J.L. Anthropometric measurement of Filipino manufacturing workers. Int. J. Ind. Ergon. 2007, 37, 497–503. [Google Scholar] [CrossRef]
  20. Klamklay, J.; Sungkhapong, A.; Yodpijit, N.; Patterson, P.E. Anthropometry of the southern Thai population. Int. J. Ind. Ergon. 2008, 38, 111–118. [Google Scholar] [CrossRef]
  21. Iseri, A.; Arslan, N. Estimated anthropometric measurements of Turkish adults and effects of geographical regions. Int. J. Ind. Ergon. 2009, 39, 860–865. [Google Scholar]
  22. Khadem, M.M.; Islam, M.A. Development of anthropometric data for Bangladeshi male population. Int. J. Ind. Ergon. 2014, 44, 407–412. [Google Scholar] [CrossRef]
  23. Sadeghi, F.; Mazloumi, A.; Kazemi, Z. An anthropometric data bank for the Iranian working population with ethnic diversity. Appl. Ergon. 2015, 48, 95–103. [Google Scholar] [CrossRef] [PubMed]
  24. Dawal, S.Z.M.; Ismail, Z.; Yusuf, K.; Abdul-Rashid, S.H.; Shalahim, N.S.M.; Abdullah, N.S.; Kamil, N.S.M. Determination of the significant anthropometry dimensions for user-friendly designs of domestic furniture and appliances—Experience from a study in Malaysia. Measurement 2015, 59, 205–215. [Google Scholar] [CrossRef]
  25. Vyavahare, R.T.; Kallurkar, S.P. Anthropometry of male agricultural workers of western India for the design of tools and equipment. Int. J. Ind. Ergon. 2016, 53, 80–85. [Google Scholar] [CrossRef]
  26. Hartono, M. Indonesian anthropometry update for special populations incorporating Drillis and Contini revisited. Int. J. Ind. Ergon. 2018, 64, 89–101. [Google Scholar] [CrossRef]
  27. Lee, Y.C.; Chen, C.H.; Lee, C.H. Body anthropometric measurements of Singaporean adult and elderly population. Measurement 2019, 148, 106949. [Google Scholar] [CrossRef]
  28. Arunachalam, M.; Singh, S.P.; Karmakar, S. Determination of the key anthropometric and range of motion measurements for the ergonomic design of motorcycle. Measurement 2020, 159, 107751. [Google Scholar] [CrossRef]
  29. Lin, Y.C.; Wang, M.J.J.; Wang, E.M. The comparisons of anthropometric characteristics among four peoples in East Asia. Appl. Ergon. 2004, 35, 173–178. [Google Scholar] [CrossRef]
  30. Yap, W.S.; Chan, C.C.; Chan, S.P.; Wang, Y.T. Ethnic difference in anthropometry among adult Singaporean, Malay and Indians, and their effects on lung volumes. Respir. Med. 2001, 95, 297–304. [Google Scholar] [CrossRef]
  31. Mohammad, Y.A. Anthropometric characteristics of the hand based on laterality and sex among Jordanian. Int. J. Ind. Ergon. 2005, 35, 747–754. [Google Scholar] [CrossRef]
  32. Chuan, T.K.; Hartono, M.; Kumar, N. Anthropometry of the Singaporean and Indonesian populations. Int. J. Ind. Ergon. 2010, 40, 757–766. [Google Scholar] [CrossRef]
  33. Widyanti, A.; Susanti, L.; Sutalaksana, I.Z.; Muslim, K. Ethnic differences in Indonesian anthropometry data: Evidence from three different largest ethnics. Int. J. Ind. Ergon. 2015, 47, 72–78. [Google Scholar] [CrossRef]
  34. Bhattacharjya, R.B.; Kakoty, S.K. A survey of the anthropometric data relating to five ethnic groups in Assam considering gender and ethnic diversity: Application of the data in designing an improvised pedal-operated Chaak. Int. J. Ind. Ergon. 2020, 76, 102927. [Google Scholar] [CrossRef]
  35. Da Silva, G.V.; Gordon, C.C.; Halpern, M. Comparison of anthropometry of Brazilian and US Military population for flight deck design. Int. J. Ind. Ergon. 2018, 64, 170–177. [Google Scholar] [CrossRef]
  36. Rahman, N.I.; Dawal, S.Z.; Yusoff, N.; Kamil, N.S.M. Anthropometric measurements among four Asian countries in designing sitting and standing workstations. Sādhanā 2018, 43, 10. [Google Scholar] [CrossRef]
  37. Krejcie, R.V.; Morgan, D.W. Determining sample size for research activities. Educ. Psychol. Meas. 1970, 30, 607–610. [Google Scholar] [CrossRef]
  38. McLean, B.D.; Parker, A.W. An anthropometric analysis of elite Australian track cyclists. J. Sports Sci. 1989, 7, 247–255. [Google Scholar] [CrossRef]
  39. Hsiao, S.W.; Chen, R.Q.; Leng, W.L. Applying riding-posture optimization on bicycle frame design. Appl. Ergon. 2015, 51, 69–79. [Google Scholar] [CrossRef]
  40. Foley, J.P.; Bird, S.R.; White, J.A. Anthropometric comparison of cyclists from different events. Br. J. Sports Med. 1989, 23, 30–33. [Google Scholar] [CrossRef]
  41. Donkers, P.C.M.; Toussaint, H.M.; Molenbroek, J.F.M.; Steenbekkers, L.P.A. Recommendations for the assessment and design of young children’s bicycles on the basis of anthropometric data. Appl. Ergon. 1993, 24, 109–118. [Google Scholar] [CrossRef]
  42. Laios, L.; Giannatsis, J. Ergonomic evaluation and redesign of children bicycles based on anthropometric data. Appl. Ergon. 2010, 41, 428–435. [Google Scholar] [CrossRef] [PubMed]
  43. Christiaans, H.H.; Bremner, A. Comfort on bicycles and the validity of a commercial bicycle fitting system. Appl. Ergon. 1998, 29, 201–211. [Google Scholar] [CrossRef]
  44. Lee, Y.C.; Lin, G.; Wang, M.J.J. Comparing 3D foot scanning with conventional measurement methods. J. Foot Ankle Res. 2014, 7, 44. [Google Scholar] [CrossRef]
  45. Mishra, P.; Pandey, C.M.; Singh, U.; Gupta, A.; Sahu, C.; Keshri, A. Descriptive statistics and normality tests for statistical data. Ann. Card. Anaesth. 2019, 22, 67. [Google Scholar] [PubMed]
  46. Fujimoto, S.; Watanabe, T. Studies on the body surface area of Japanese. Acta Med. Nagasaki 1969, 13, 1–13. [Google Scholar]
  47. Nes, B.M.; Janszky, I.; Wisløff, U.; Støylen, A.; Karlsen, T. Age-predicted maximal heart rate in healthy subjects: The HUNT Fitness Study. Scand. J. Med. Sci. Sports 2013, 23, 697–704. [Google Scholar] [CrossRef]
  48. Uth, N.; Sørensen, H.; Overgaard, K.; Pedersen, P.K. Estimation of VO2max from the ratio between HRmax and HRrest—The heart rate ratio method. Eur. J. Appl. Physiol. 2004, 91, 111–115. [Google Scholar] [CrossRef]
Figure 1. Sample picture captured during measurements. Note: (A) shoulder-elbow length; (B) knee height.
Figure 1. Sample picture captured during measurements. Note: (A) shoulder-elbow length; (B) knee height.
Ijerph 19 10078 g001
Figure 2. Measuring instruments used in the survey. Note: (A) larger sliding caliper; (B) small sliding caliper; (C) plastic measuring tape; (D) stadiometer and (E) weighing scale.
Figure 2. Measuring instruments used in the survey. Note: (A) larger sliding caliper; (B) small sliding caliper; (C) plastic measuring tape; (D) stadiometer and (E) weighing scale.
Ijerph 19 10078 g002
Figure 3. Anthropometric measurements.
Figure 3. Anthropometric measurements.
Ijerph 19 10078 g003
Table 1. Summary of cyclists’ characteristics (n = 406).
Table 1. Summary of cyclists’ characteristics (n = 406).
CharacteristicMeanRange
MinMax
Age (Yrs.)281850
Body surface area (m2)1.791.472.20
HRmax (beats/min)193179199
Performance level (VO2)797881
Years of practice10132
Weekly training load (km)266421623033
Table 2. Descriptive statistics of cyclists’ anthropometric measurements. Note: All measurements are in mm unless specified.
Table 2. Descriptive statistics of cyclists’ anthropometric measurements. Note: All measurements are in mm unless specified.
S. NoAnthropometricCountriesMedianMeanStd. DeviationMinimumMaximumInterquartile RangeRangePercentiles
5th50th95th
1Stature body heightIndia16801694.1868.781540.001875.0099.25335.001599.001680.001823.75
Singapore16771683.6376.201521.001900.00102.75379.001552.401677.001820.00
Taiwan1715.81720.9754.951587.401855.2083.52267.801634.161715.801813.36
China17201722.4259.781600.001933.4080333.401630.001720.001818.70
2Buttock extensionIndia855844.3960.43575.00980.0070405.00725.00855.00935.00
Singapore971966.2748.90820.001073.0057253.00877.10971.001039.95
Taiwan859.35862.2139.63775.00955.0055.92180.00797.28859.35930.62
China891887.8378.10470.001099.3074629.30775.10891.001000.00
3Shoulder height (Sitting)India572.2577.2230.92507.10654.0044.48146.90522.38572.20632.60
Singapore569.5579.7146.84493.00711.0054218.00512.10569.50653.95
Taiwan515.6516.8035.62435.30599.3053.6164.00460.91515.60580.50
China622.5621.9443.38450.00740.0044.5290.00555.26622.50700.00
4Shoulder-elbow lengthIndia352.85354.4422.38301.70410.1027.52108.40315.85352.85393.53
Singapore317.5336.0052.66263.00432.0032.75169.00268.15317.50419.95
Taiwan253.85254.8118.63210.00312.1024.92102.10222.52253.85285.33
China358368.0637.35310.00500.0033190.00323.14358.00450.00
5Elbow height (Sitting)India224.2222.2527.01160.60284.9039.25124.30175.38224.20270.93
Singapore243243.7131.81190.00358.0045.5168.00198.00243.00292.95
Taiwan261.05262.0027.90201.30321.8043.85120.50219.68261.05311.06
China257251.5439.03140.00320.0053180.00179.20257.00309.78
6Lower leg lengthIndia444.6447.6041.19373.80710.3050.3336.50393.05444.60498.05
Singapore410413.9027.88356.00493.0035.5137.00370.15410.00464.75
Taiwan417.3419.9726.62362.60477.0034.6114.40375.66417.30465.67
China428.5425.6940.55160.00500.0040340.00366.94428.50480.00
7Knee heightIndia551.6551.2344.03463.10835.4047.5372.30492.00551.60603.63
Singapore491.5501.2039.74425.00680.0053.75255.00453.25491.50572.95
Taiwan506.85508.1424.76458.60560.1038.57101.50469.15506.85549.68
China534532.9528.04430.00601.0035.1171.00490.00534.00590.20
8Acromion-grip lengthIndia627.55629.1741.14528.60750.0051.2221.40561.85627.55702.58
Singapore650651.9060.04542.00800.0054258.00553.70650.00764.75
Taiwan566.825568.9627.26491.50635.8033.67144.30521.44566.83617.38
China625630.9740.45550.00750.0052200.00580.00625.00716.00
9Hand lengthIndia177.95177.6313.38150.90209.3021.5858.40155.60177.95199.80
Singapore183182.178.47160.00205.001145.00168.00183.00196.95
Taiwan178.1178.019.98148.00200.5010.9752.50159.38178.10195.49
China185185.4021.8376.00300.0015.9224.00170.00185.00209.20
10Elbow-hand lengthIndia475.05474.5525.91420.30538.9035.65118.60433.50475.05523.68
Singapore461.5462.0626.58386.00520.0036.75134.00413.10461.50497.00
Taiwan367.15366.5719.59317.00420.6024.43103.60340.24367.15408.84
China450448.9628.26270.00500.0029230.00406.80450.00490.00
11Buttock-popliteal lengthIndia497.95497.7339.29398.30569.8057.82171.50436.25497.95563.18
Singapore458455.2226.96356.00508.0029.75152.00400.15458.00497.00
Taiwan353.05354.8324.88289.30416.0033.55126.70307.97353.05398.92
China440438.4038.95330.00524.0041.5194.00360.00440.00508.00
12Buttock-knee lengthIndia596.65595.1535.29497.70675.4051.4177.70538.95596.65655.03
Singapore568.5562.2529.21470.00624.0032.5154.00491.70568.50596.85
Taiwan455453.7631.04351.70517.1040.67165.40393.27455.00499.90
China549.4547.5368.97478.56671.0047.5671.00480.00549.40630.80
13Elbow-to-elbow breadthIndia434430.3138.41330.00533.0060203.00357.75434.00488.75
Singapore430.5434.9528.67379.00533.0040.5154.00399.10430.50489.50
Taiwan401.55399.1123.15349.20449.8035.65100.60361.62401.55435.73
China450451.5848.70150.00600.0040450.00393.00450.00518.94
14Hip breadth (Sitting)India340336.8827.54270.00425.0034.75155.00290.00340.00380.00
Singapore306307.1721.19250.00371.0026.75121.00273.00306.00347.75
Taiwan376.95376.7526.44321.90445.6034.05123.70327.20376.95421.18
China360360.1138.76250.00550.0040300.00299.20360.00413.54
15Foot breadthIndia100101.728.2785.00115.001530.0090.00100.00115.00
Singapore102101.066.7082.00114.00832.0090.05102.00112.90
Taiwan104.05104.314.7091.60120.306.1328.7096.65104.05111.90
China100101.9816.8276.00240.0010.7164.0088.40100.00121.60
16BMI (kg/m²)India23.8123.803.6713.7131.745.7118.0318.4823.8129.25
Singapore22.823.272.1318.9431.632.8312.6919.9622.8027.22
Taiwan22.1822.372.6117.9631.143.0513.1818.4322.1827.29
China23.5323.713.2217.0434.843.5317.8018.6223.5329.26
17Weight (kg)India68.568.2410.7238.0096.0016.1358.0051.0068.5083.50
Singapore6465.947.4250.0095.009.7545.0058.0064.0079.95
Taiwan67.567.598.5653.0092.0011.2539.0055.0067.5085.00
China7070.3610.7252.00110.001258.0055.0070.0090.80
Table 3. Results of the Kruskal–Wallis test.
Table 3. Results of the Kruskal–Wallis test.
Anthropometric VariablesKruskal–
Wallis Test
p-ValueGroup’s Mean Rank
HpSingapore (SGD)India (INR)Taiwan (ROC)China (PRC)
Stature body height26.360.0001169.98183.48235.73237.13
Buttock extension178.650.002335.86132.27153.7212.2
Shoulder height (Sitting)199.90.002219.33216.1382.43314.01
Shoulder-elbow
length
235.150.004229.34261.0657.34284.74
Elbow height (Sitting)79.010.0001199.94126.52266.14234.25
Lower leg length52.290.004157.25271.71183.76213.88
Knee height117.670.003133.29289.69157.2246.33
Acromion-grip length157.640.0001271.79238.2483.55239.6
Hand length31.070.0001221.73178.21175.48254.21
Elbow-hand length254.180.0001262.53297.8755.19217.57
Buttock-popliteal length278.970.002242.38328.158.97202.72
Buttock-knee length259.740.0001243.1231558.15216.07
Elbow-to-elbow breadth123.450.003227.42215.63104.88283.56
Hip breadth (Sitting)206.550.000182.4179.1309.43250.73
Foot breadth19.910.004192.96207.82247.73177.9
BMI18.140.0001207.61230.72166.84223.79
Weight11.970.0001176.82216.51201.43232.43
Table 4. Results of Mann–Whitney U test.
Table 4. Results of Mann–Whitney U test.
Statistical ParametersSGD vs. ROCSGD vs. PRCSGD vs. INR
Mann–Whitney USig (2-Tailed)
p-Value
Mann–Whitney USig (2-Tailed) p-ValueMann–Whitney USig (2-Tailed)
p-Value
BMI40270.00346480.2344900.09
Weight4629.50.1137240.0014278.50.02
Stature body height3619.50351704811.50.35
Buttock extension576.5017010486.50
Shoulder height (Sitting)1605.502662.505174.50.95
Shoulder-elbow length402.503532041540.01
Elbow height (Sitting)3515.504251.50.0332230
Lower leg length4532.50.073680.502461.50
Knee height42160.012318.501744.50
Acromion-grip length1067.504053.50.00940500.006
Hand length3966.50.00241790.0240900.008
Elbow-hand length36.503671040100.005
Buttock-popliteal length810359101959.50
Buttock-knee length102.5040670.0125310
Elbow-to-elbow breadth1739.503372049410.53
Hip breadth (Sitting)206.50100901974.50
Foot breadth379204667.50.2448210.36
Statistical ParametersROC vs. PRCINR vs. ROCINR vs. PRC
Mann–Whitney USig (2-Tailed)
p-Value
Mann–Whitney USig (2-Tailed) p-ValueMann–Whitney USig (2-Tailed)
p-Value
BMI39680.00140190.0015092.50.54
Weight46060.05151040.3550160.43
Stature body height53760.8494064.50.0013968.50.001
Buttock extension370504684.50.063125.50
Shoulder height (Sitting)313.50114801966.50
Shoulder-elbow length10404424.50.03
Elbow height (Sitting)4786.50.1241700.5027750
Lower leg length4640.50.0613100037770
Knee height2707.501900.503823.50
Acromion-grip length91401204052650.83
Hand length3395.5054560.8935280
Elbow-hand length14201026070
Buttock-popliteal length4920701507.50
Buttock-knee length3850502299.50
Elbow-to-elbow breadth102902677.5036780
Hip breadth (Sitting)3635.50157103169.50
Foot breadth3515.504646.50.044784.50.18
Note: Singaporean (SGD); Taiwanese (ROC); Chinese (PRC); Indian (INR).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Muthiah, A.; Lee, Y.-C. Comparative Analysis of Male Cyclist Population in Four Asia Countries for Anthropometric Measurements. Int. J. Environ. Res. Public Health 2022, 19, 10078. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191610078

AMA Style

Muthiah A, Lee Y-C. Comparative Analysis of Male Cyclist Population in Four Asia Countries for Anthropometric Measurements. International Journal of Environmental Research and Public Health. 2022; 19(16):10078. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191610078

Chicago/Turabian Style

Muthiah, Arunachalam, and Yu-Chi Lee. 2022. "Comparative Analysis of Male Cyclist Population in Four Asia Countries for Anthropometric Measurements" International Journal of Environmental Research and Public Health 19, no. 16: 10078. https://0-doi-org.brum.beds.ac.uk/10.3390/ijerph191610078

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop