Sizing system for functional clothing Uniforms for school children

Transcription

1 Indian Journal of Fibre & Textile Research Vol. 36, December 2011, pp Sizing system for functional clothing Uniforms for school children Norsaadah Zakaria a Department of Textile Technology, Faculty of Applied Sciences, Universiti Teknologi Mara, Malaysia In this study, a sizing system is proposed specifically for school-aged children in Malaysia. The sampling frame is based on the female population in the age group For this study, 1001girls have been selected randomly from 29 different schools in urban and rural districts of Malaysia. Principal component analysis is used for key dimensions determination. Data mining has been done to develop the sizing system using cluster analysis and classification tree technique. This study has successfully produced four main sizing systems for garments of girls aged 7-12 and covering upper and lower body. In total, 93 sizes have been developed for the girls of 7-17 years age. The sizing system coverage for 7-12 years old girls is found to be 99.6% for upper body and 99.2% for lower body. The coverage for girls of years age is 93.6% for upper body and 98.2% for lower body. This is the first comprehensive anthropometric survey conducted to develop a sizing system in Malaysia in order to design school uniforms locally. The benefit is an enhanced fit of school uniform and a guideline for a proper sizing system and sizing designation. Keywords: Anthropometric survey, Body dimensions, Sizing system, School uniform 1 Introduction The school uniform is an integral element of every child s school-going years. Children in different age groups have widely varying physical, social and psychological requirements for their clothing 1. The child's physical development and rapidly changing body shape and size can cause problems with the acceptability of school uniforms 2. Fit of clothing is a major factor affecting the physical and psychological comfort of the wearer 3. The reason that clothes often don t fit children well is that the sizing system used to manufacture their school uniforms is not based on a scientific understanding of body shapes and sizes of this group 4-6. Children s clothing needs to be functional in order to accommodate growth, provide comfort, promote safety, and foster a sense of independence 7,8. Norum 9 said regardless of how attractive an item is, how easy the garment is to care for or what value the clothing is to be, it is of no benefit if it does not fit the child. Gautam 10 found that factors affecting comfort of kids clothing include garment size, seasonally appropriate, and shoes and stockings of correct size. During childhood and adolescence, physical activity is promoted as a key component of energy balance and as a lifelong positive health behaviour 11. As a result, children are expected to wear comfortable clothing for various activities in order to be physically, socially and mentally active and fit 12. On the other hand, during a [email protected] this time children grow quickly in different ways and at different rates, therefore clothing size is significant in giving them the right fit which allows room for growth 13,14. Futhermore, there is a possibility that physical changes in children could cause complications in choosing clothing especially when it comes to fit. Basing the size system on age alone also results in poor representation of actual body dimensions and shapes 15,16. Several studies have revealed that children of similar age may have varying height, shape and body proportion 17,18. Otieno 19 demonstrated that 50% of children did not fit into clothes designed according to the age system. Methods of sizing nomenclature that do not have proper identification also mislead consumers in the selection of well fitted garments 20. Research has found that female children face the most problems when it comes to mass produced clothing as their body shape changes towards entering the adulthood 21. Thus, the present study was designed to generate baseline anthropometric data of female school aged children. The purpose of conducting this anthropometric survey is to develop a sizing system for upper and lower body for girls' school uniforms and propose a proper sizing designation. 2 Materials and Methods The study is divided into following four parts: (i) Anthropometric survey Anthropometric planning, anthropometric protocol (ii) Anthropometric data analysis Simple statistical, multivariate technique, data mining technique

2 ZAKARIA: SIZING SYSTEM FOR FUNCTIONAL CLOTHING 349 (iii) Development of sizing system Size range, size interval, size roll (iv) Sizing system validation Accommodation rate, aggregate loss, total number of sizes. The study can help apparel manufacturers and retailers effectively in developing the sizing system according to their target market's body size specifications and requirements. 2.1 Anthropometric Survey Anthropometric Planning A total of 1001 school-aged girls were randomly selected from 29 primary and secondary schools for the study. The sampling consisted of three ethnic groups, namely Malays, Chinese and Indians. The age range of the sample size was kept between 7 and 12 years for subjects from primary school and between 13 and 17 years for those from secondary schools. The entire sample was recruited using stratified random sampling. Approximately 51 body measurements were taken on each subject, including height and weight, as per the ISO 8559/1989 body measurements standard. Body weight was taken using a digital scale to the nearest 100g and height was taken to the nearest 0.1 cm using a Mentone height measurement scale with attached head piece. Out of 51 body dimensions, 33 were for the upper and whole body and 18 were for the lower body. 2.2 Anthropometric Data Analysis After conducting the anthropometric survey, the collected data were analysed using simple statistical methods like mean, median and standard deviation to describe the body size and growth of subjects overall. Subsequently, to develop the sizing system, factor analysis, non-hierarchical cluster and decision tree techniques were employed using the SPSS ver.13.0 statistical software. The objective of using each technique is as follows Principal Component Analysis (PCA) Method The objective of this method is to reduce the variables for the selection of key dimensions, which were then used to segment the sample population. The body dimensions of each sample group are extracted using PCA and Varimax rotation. The PCA technique is commonly used to analyse anthropometric data to describe variations in human body in a parsimonious manner. Parsimonious means the variation of body dimensions are described using the fewest principal components (PCs) possible. To identify the number of components to be retained, three criteria were considered, namely latent root criterion, percentage of variance criterion and Scree test criterion. Then, key dimensions were selected based on the relevant components and factor loadings Cluster Analysis Method The objective of cluster analysis is to segment the sample population into homogeneous groups by applying the non-hierarchical K-means cluster method. It is a simple clustering method and shows optimal results 22. However, all variables must be independent and normally distributed. Different body types were identified based on the clustering method in which the subjects were grouped according to similar body characters Decision Tree Method The objective of decision tree is to profile the cluster groups. In this study, regression tree was used to classify the variables since the data is continuous. The dependent variable was the cluster group and the independent variables were the variables from either the upper or the lower body. 2.3 Sizing System Development After obtaining the profile of cluster groups, a sizing system was developed based on the size interval. The main objective of a sizing system is to classify the sample population into sub-groups, with similar people within each group but significantly different people among different cluster groups. 2.4 Sizing System Validation The aim of the sizing system is to enumerate a set of sizes that can accommodate most of the population measured. Thus, the final step is to validate the sizing system based on cover factor (%), aggregate loss, and size roll Cover Factor For cover factor validation, the percentage of sample accommodated under each body type and each individual assigned size is calculated. Each established size is presented in the size table. The percentages in each size were added together to give the total percentage covered by the system as a whole for each sample group. The cover factor should typically range 65-80%, meaning that the sizing system is able to accommodate 65-80% of the population with the sizes given Aggregate Loss The next item of validation for the sizing system is to measure the aggregate loss. The goal of a good sizing

3 350 INDIAN J. FIBRE TEXT. RES., DECEMBER 2011 system is to produce sizes that are close to the wearer s actual body size and shape. This degree of closeness (aggregate loss) measures the goodness of fit of each size. It measures the Euclidian distance between assigned size (the size created) and the actual size (the real size of a given subject). If the assigned size is near to the actual size, it means the distance between the two sizes is small and thus the aggregate loss value is low. Consequently, this means that the goodness of fit of the assigned size is high Size Roll Size roll is simply the total number of sizes obtained for each sizing system, from the smallest to the largest, with fixed intervals between adjacent sizes. The size intervals can be the same throughout the sizing system or it can vary. In terms of practicality and economics for the manufacturers, the optimum size roll is neither too less nor too many. 3 Results and Discussion Values obtained from the anthropometric survey show that the data are normally distributed. The distributions of data for girls (7-12 years old) and teenage girls (13-17 years old) are shown in Table 1, giving the extreme values, mean, and standard deviation (SD). The growth of girls according to important body dimensions is discussed in the following sections. 3.1 Descriptive Analysis As shown in Table 1, the shortest girl aged between 7 and 12 years is about cm and the tallest is about cm. The mean height of these girls is cm. The SD for all dimensions is quite large, showing great variation in the measurements. The thinnest girl in this group weighs only 13.4 kg while the average is 29.8 kg and the heaviest is about 78.8 kg. The descriptions of the other three body dimensions, namely bust, waist and hip girth are given in Table 1. On the other hand, the study on the body size of teenage girls (13-17 years) according to height, weight, bust, waist and hip girth indicates that the shortest height of teenage is cm and the tallest is cm (Table 1). The thinnest weighs only 13.4 kg and the heaviest girl is about 78.8 kg. Thus, the average height and weight are cm and 47.9 kg respectively. The spread is lower in the height dimension as compared to the other dimensions Growth Distribution for Girls Aged 7-17 It can be seen from Fig.1 that the growth trend in girls between the age of 7 and 12 is very rapid, especially in height. Compared to year old Table 1 Anthropometric measurements of 7-12 and years old females Body dimension Height cm Weight kg Bust girth cm Waist girth cm Hip girth cm 7-12 years Minimum Maximum Mean SD years Minimum Maximum Mean SD Fig. 1 Growth trend for critical body dimensions (7-17 years) girls, the overall graph shows growth in every dimension. It has been shown that females start their growth spurt between ages 10 and 12, which is the onset of puberty 24. After the age of 14, their height changes very little; it is relatively unchanging for females from 15 to 17 years 25. In girth measurements, growth occurs in three obvious phases. Overall, there is a continuous increment in measurements for all body dimensions with age. The increment rate differs in age groups 7-12, and There is rapid growth from age 7 to 12, then growth seems to increase but at a slower rate from age 12 to 14 and finally becomes almost stationary from age 14 to 17. As a result, the total growth of key body measurements for age is much lower than for age The spread of height is greater between ages 7 and 12 as compared to ages between 13 and 17. This finding is consistent with those of A Hearn et al. 26

4 ZAKARIA: SIZING SYSTEM FOR FUNCTIONAL CLOTHING 351 who found that differences in height by age are the largest between the ages 9 and 13. Other studies also show that height is affected by age, nutrition, lifestyle and health 27. Therefore, it is assumed that more sizes will be needed for age 7-12 as compared to age due to the larger size range in the younger group. 3.2 Factor Analysis The factor loadings of each component were thoroughly selected using the three criteria as mentioned in the methodology section. Results are compiled in Table Step 1 Factor Analysis For factor analysis, two important data of the Kaiser-Meyer-Olkin (KMO) and Bartlett test values are shown in Table 2. Both the values of KMO and Bartlett test statistics are used to predict if the data is likely to factor well, and in this study the KMO measure is found to be equal to (7-12 years old) and (13-17 years old) and Bartlett s test for both groups shows p<0.01. This reading is suitable for factor analysis as KMO is supposed to be > 0.5 and Bartlett test is < As a result, all the dimensions are suitable for factor analysis Step 2 Retaining the Factor Components The results of the extracted components from PCA technique showed that 50 components are extracted for each sample group (aged 7-12 and 13-17) which explains 100% of the variance in the data. The current study shows that 76% of the variance in the 50 body dimensions for female (aged 7-12) is explained in component 1, while for female samples of the age between 13 and 17, less percentage value is observed (54%). In addition, from this finding, 90% variance is explained by seven principal components for female samples age 7 12, and for female samples (age 13-17), 14 components show 90% of variance. In order to reduce the numbers of components for a more parsimonious solution which is the goal of using the PCA technique, the criterion of retaining components are applied which are: latent root, scree plot and percentage of accumulated variance. Table 2 shows Age years Kaiser Meyer Olkin (KMO) Table 2 KMO and PCA results for girls aged 7-12 and Bartlett s tests Component extracted (PCA) Factor 1 Factor Factor 1 Factor 2 that the criterion of Eigen value >1 is first used to retain three components for female aged 7-12 and six components for females aged Next, using Scree plot criterion, two factors are retained, resulting to Components 1 and 2. The third criterion for retaining values depends on the percentage of accumulated variance on Eigen value. For females aged 7-12, Component 1 (PC1) shows Eigen value of 76.3 and Component 2 (PC2) shows Eigen value of 7.2. Thus, the cumulative % variance from initial Eigen values is 83.5%. For females aged 13-17, Component 1 (PC1) shows Eigen value of 54.0 and Component 2 (PC2) shows Eigen value of Thus, the cumulative % variance from initial Eigen values is 69.0%. After choosing the numbers of components need to be retained, all factor loadings of each variable in each component are examined which will clearly distinguish those variables that correlate highly with each component. In general, similar body dimensions are accumulated into its own component which can be interpreted as one type of measurements such as the length, girth, or width Step 3 Result of PCA Anthropometric variables with factor loadings > 0.5 are mostly clustered within Components 1 (PC 1) and 2 (PC 2). For female samples aged 7-12, 46 variables are loaded on two components while for female samples aged 13-17, 42 variables are loaded on two components. In PC 1, all variables are girth dimensions and therefore the first component retained is the girth factor. PC 2 consists mainly of length dimensions. It is thus known as the length factor. For the sample group aged 7-12 years, 30 variables (15 variables each for upper and lower body) are found to have high factor loadings ( 0.70). However, in Table 3 only eleven variables for upper and lower body are shown, with the highest factor loading. Dimensions shown in bold are those which show high factor loading and are used most frequently in pattern making. Height and bust are identified as the key dimensions for upper body 28, 29, while height and hip girth are chosen for the lower body 30, 31. Height is Factor Eigen values Scree plot criterion Cumulative total variance, % Components Components 69.0

5 352 INDIAN J. FIBRE TEXT. RES., DECEMBER 2011 Table 3 Principal component analysis with Varimax rotation (7-12 year olds) Parameter Value PC 1 (girth) Upper body Upper arm girth Bust girth Neck girth Lower body Waist girth Hip girth PC 2 (length) Upper body Under arm length Cervical height Height Lower body Inside leg length Hip height Outer leg length considered the best representative of length 32. Bust and hip girths are considered representative of weight 33,34. For female aged years, the result of PCA shows that 26 variables are correlated to the girth and length components with a factor loading of Fifteen variables are loaded on girths while another 11 variables are loaded on lengths. From Table 4, only the highest factor loading variables are shown which consists of eleven variables for upper and lower body. Referring to Tables 3 and 4, only five variables that have the highest factor loading from PC 1 and PC 2 are listed, with the exception of the height variable, which is considered crucial for key dimensions in sizing system. Furthermore, height shows high factor loading ( 0.75) for both groups. 3.3 Cluster Analysis Two key dimensions namely the height and chest girth for upper body and height and waist girth for lower body, selected from the previous PC analysis, have been used to cluster the subjects. Six separate cluster analyses are run, generating participant cluster membership from 2 to 9 grouping categories. Each k- means of the the cluster results is evaluated to determine the ideal number of grouping categories. The ideal cluster result will mean that each cluster group shows distinction among each other. Three groups are chosen for its distinctive characters and considered practical for size clustering of school-aged children, due to the familiarity of three basic sizes (S, M and L) in the local industry. Table 4 Principal component analysis with Varimax rotation (13-17 year olds) Parameter Value PC 1 (girth) Upper body Bust girth Upper arm girth Neck girth Lower body Waist girth Hip girth Thigh girth PC 2 (length) Upper body Arm length Under arm length Height Lower body Inside leg length Outer leg length Fig. 2 Clusters according to height and bust girth in cm for (a) 7-12 and (b) years old girls Clustering of 7-12 Years Old Females Clusters obtained for the upper body for 7-12 year old females and their analysis are shown in Fig. 2 and Table 5 respectively. As can be seen, Cluster 1 is made up of subjects with short height and small bust. Cluster 2 includes tall subjects with large busts and Cluster 3 lies in between the two covering subjects having medium bust and average height. For the lower body too, three distinct clusters were obtained (Fig. 3). A large majority of subjects are clustered under Cluster 2 which represents the medium size covering subjects having average height and small to medium size hip girth. Cluster 3 for large size includes subjects which are tall with wide hip girths. Cluster 1 covers subjects with narrow hips and short height. Details of each cluster are given in Table Clustering of Years Old Females Clusters obtained for this group show a different character from those obtained for younger girls

6 ZAKARIA: SIZING SYSTEM FOR FUNCTIONAL CLOTHING 353 Table 5 Clusters for upper body of 7-12 and years old girls Parameter 7-12 years years Cluster 1 Cluster 3 Cluster 2 Cluster 2 Cluster 3 Cluster 1 N (197) (194) (134) (120) (101) (80) Mean height, cm Range, cm Mean bust girth, cm Range, cm Body type Small Medium Large Small Medium Large Table 6 Clusters for lower body of 7-12 and years old girls Parameter 7-12 years years Cluster 1 Cluster 2 Cluster 3 Cluster 1 Cluster 2 Cluster 3 N (176) (196) (142) (126) (102) (64) Mean height, cm Range, cm Mean hip girth, cm Range, cm Body type Small Medium Large Small Medium Large Trend obtained is similar to that seen for the upper body classification. While cluster 1 (small) and cluster 2(medium) are distinct in height categories, the range of hip measures for them is overlapping. Cluster 3 (large) covers the women with a large bust but across the entire range of height. Table 6 shows the profile of each cluster for years according to key lower body dimensions. The majority of the subjects fall into Cluster 1 (the small size). The second largest sample size is Cluster 2 (the medium size). Cluster 3 pertains to the large size. Fig. 3 Clusters according to height and hip girth in cm of girls of (a) 7-12 and (b) years old (Fig. 2). In this case, a huge overlap in dimensions of the three cluster groups is observed. While clusters 1 and 2 are distinct in terms of height measurement, their range of bust measures is overlapping. Cluster 3, which may be termed as large size, has subjects across all height categories with a large bust measurement. Thus, the spread of measurements is seen to increase markedly, indicating the emergence of distinct body shaping in this age group. Majority of the sample population falls under Cluster 1, which makes up the small size. Cluster 3 (large body type) contains samples that are short to tall with large bust measurements. Cluster 1 samples belong to the small body type, with short to average height and small to average bust. In Cluster 2 (medium body type), the samples are average to tall with small to average size bust. Figure 3 shows the clusters obtained for teenage girls on the basis of height and hip measurements. 3.4 Classification Based on Gender and Age Groups Table 7 depicts the characteristics of small, medium and large sizes. As can be seen, in the small size, height is always less than in the other two sizes, which means that the length of skirts for school uniforms should be shorter for this group as compared to the other two sizes. However, for the large size the attributes are different, i.e. for age 7-12 height alone is significant, while for age only hip measurement needs to be considered. 3.5 Sizing System Development The sizing system was developed according to the design limit, which accommodated 90% of the sample population. It can be seen that height is the determining factor for size in girls aged 7-12 years. In comparison, girth is the determining factor for size in girls aged years. Applying the classification rule of IF/THEN (Table 7), the three body types namely small, medium and large for upper and lower body are developed

7 354 INDIAN J. FIBRE TEXT. RES., DECEMBER 2011 Table 7 Classification tree profiles of key dimensions (cm) Body types 7-12 years years Upper body Small Height / bust <129.4 /<65.3 <153.9 / < 86.3 Medium Height/ bust / > 65.3 >86.3/ >153.9 Large Height >139.7 Bust >86.3 Lower body Small Height/hip <139.7/ < 67.4 <153.3 / 93.8 <126.5 / >67.4 Medium Height/hip / Hip > 67.4 < /< 93.8 Large Height >139.7 Hip >93.8 using different size interval for different key dimensions. The interval for key dimensions can be chosen based on the total range in order to develop the size table. It is therefore, the goal of any sizing system to find the best size interval to signify the best coverage of the target population while having not so many size rolls. Table 8 shows that the entire samples are highly accommodated with appropriate numbers of size rolls which proves the size intervals selected are correct. However, it is also noted in some of the sizing system that there are some sizes which are not densely accommodated, e.g. for height the total range is 40 cm, therefore to obtain 5 sizes, each interval is set at 8cm, meanwhile for girth key dimensions, if the range is 35 cm, then choosing interval of 5 cm will result to 7 sizes. Development of the upper body size table for 7-12 year old girls is discussed here. For the development of size system, the decision to classify the female samples according to the classified rules, as shown in Table 7, are applied. Basically, there are three major sizes namely small, medium and large allocated for females aged 7-12 years old for upper body. Table 7 shows the rules to classify each size, and therefore the control variables for upper body are height and bust girth. Table 8 depicts the total sample size of females age 7-12, which shows 24 size rolls, divided into three sizes small, medium and large. There are two key dimensions used height and bust girth. The range for height in this sample size is 40 cm (from 114cm to cm), which is divided into five subgroups, namely 114cm, 122cm, 130 cm, 138cm and 146cm. This range is divided using an interval of 8 cm. The size interval is chosen based on the best coverage for these samples. For the bust, the total range is 36 cm Size roll Table 8 Size distribution for upper body for girls 7-12 years Body type Key dimension cm Accommodation rate Height Bust girth N % Aggregate loss, cm 1 Small Medium Large Total (from 54 cm to 89.9 cm); this range is divided into six subgroups using an interval of 6 cm; 54 cm, 60 cm, 66 cm, 72 cm, 78 cm and 84 cm. Using the classifying rules in Table 7, the sizing system for upper body (age 7-12) is divided according to small, medium and large size which consists of four small sizes, ten medium sizes and ten large sizes. For the small size category, four sizes are provided with height between cm and cm bust girth measurement (Table 8). For the medium size category, ten sizes are provided with variations of height from 114 cm to cm with bust measurements of cm. Ten sizes are provided for the last group (large size) for tall children measuring from 138 cm to cm with bust measurement between 60cm and 89.9cm. The number of samples accommodated for each size is shown and the total accommodation rate for the whole sample size is found to be 99%. However, in Malaysia the school uniforms are available in eleven different sizes to accomodate children in the schooling age range (7-17 years old). This means that for each

8 ZAKARIA: SIZING SYSTEM FOR FUNCTIONAL CLOTHING 355 age, there is one size, e.g. for the primary school ages 7-12 (which covers six years), there are six different sizes to choose from. To propose a system similar to the currently prevailing one, the two sizes that best accomodate a majority of subjects from each height group are chosen since height is the determining factor for this age group. This shows that the total of number of sizes recommended is nine (Table 9). The selection of the best sizes for constructing uniform is based on sizes that have accommodation coverage of more than 2%, which is considered as good accommodation Application Size Table for School Uniform for Upper Body Table 9 lists the representative standard size chart for school uniform of the upper body for female aged 7-12 years old using height and bust girth as the determining factors for sizes. For functional clothing such as school uniforms worn by active growing children, the sizes need to fit them well and to give comfort. Therefore, in Table 9 the new sizing system is recommended for designing school uniforms for upper body. For primary school children, the top garment usually consists of a short sleeve collared shirt or a long sleeve tunic. There are nine new sizes for school uniforms to accomodate those with heights between 114 cm and 154 cm and with busts from 54 cm to 84 cm. Table 9 shows the new size designation size S , which refers to girls with a height cm and bust girth cm. Three small, two medium and four large sizes are recommended for school uniforms as compared to six sizes in the current local market. From Table 9, it can be seen that the size designation denotes the key Table 9 Sizes for school uniforms based on height and bust girth Size designation S S S M M L L L L Height range, cm Bust girth range, cm Height, cm Bust girth, cm Neck girth, cm Shoulder width, cm Upper arm girth, cm Arm scye girth, cm Upper arm length, cm Arm length, cm Elbow girth, cm Wrist girth, cm Waist girth, cm Hip girth, cm Cervical to breast point, cm Neck shoulder to breast point, cm Accommodation, % Aggregate loss, cm Table 10 Sizing system validation Parameter 7-12 years years Upper body Lower body Upper body Lower body Control Height/bust Height/hip Height/bust Height/hip dimensions girth girth girth girth Population coverage, % Aggregate loss No of sizes Cluster Cluster Cluster Total number of sizes dimensions which clearly shows the exact measurements for consumers. In order to avoid confusion, size designation should be neither alphabetic nor numeric but should include proper label identification which states the key dimensions on which it is based on. As it can be seen, the sizes are not based on age but on key body dimensions which informs consumers the right sizes to choose from and thus will enhance the fit of the clothing. The normal practice of school uniform sizes in Malaysia is based on age and sometimes numerical alphabets which has no information on the real body dimensions, based on which the size system is created. 3.7 Size Validation Table 10 summarizes the validation for the entire sizing system built for the sample populations. It is significant that sizing systems for both age groups successfully accommodated 99% of the sample

9 356 INDIAN J. FIBRE TEXT. RES., DECEMBER 2011 population measured and have minimal total sizes between 22 and 27. The aggregate loss is between 2.5cm and 2.6 cm, well below the ideal value of 3.6 cm. If two key dimensions are used to cluster the population then the ideal aggregate loss is given as 2 ½ = This value is in inch. Since all measurements are taken in metric (cm), the aggregate loss is calculated as 1.41 * 2.54 cm = 3.58 cm. This value is the ideal aggregate loss regarded as the benchmark for an accurate size. Hence, the goodness of fit for this system and efficiency of the size system is found to be high, as the average coverage factor is above 90%. 4 Conclusion This paper has presented the analysis of body characteristics of school aged children. It is worth noting that the multivariate analysis using PCA technique proves that the height, bust and hip girth are most influential in size determination. Through data mining techniques, the different body shapes existing among female children have been identified. In essence, the current study contributes towards the development of a new sizing system for the clothing industry in Malaysia focusing specifically on schoolaged girls. With the new sizing system, the fit of school uniforms for girls in the age group 7-17 will be enhanced as it is based on anthropometric data which integrates the right size designation. It is evident that the comfort of this functional clothing will be much better as the students will be able to get the right sized clothes appropriate for their body shape and size based on the right size designation. Acknowledgement The author would like to express her sincere appreciation to the Research Management Institute and Faculty of Applied Sciences from Universiti Teknologi MARA and Jerasia Sdn Bhd for their financial support to carry out this project. 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