1 increase of comorbidities such as elevated blood

1                Introduction

2                Literature Review

a.      Childhood Obesity

                                               i.     Prevalence and Trend

                                             ii.     Consequences

b.     Determinant

                                               i.     Genetic

                                             ii.     Environmental influences

                                            iii.     Physical Activity

                                            iv.     Sedentary Behaviour

                                              v.     Parental Feeding Practices

                                            vi.     Snacking

c.      Childhood Obesity in Malaysia

d.     Rural and Urban

3                Methodology

a.      Intro

b.     Study Design

c.      Location

d.     Study Procedure

                                               i.     Recruitment

                                             ii.     Consent

e.      Sample Size Calculation

f.      Data Collection

                                               i.     Socio-Demographic

                                             ii.     Anthropometry

                                            iii.     Physical Activity

                                            iv.     Sedentary

                                              v.     Snacking

                                            vi.     Feeding Practices

g.     Data Analysis

h.     Ethical Consideration

 

 

Chapter 1 Introduction

The prevalence of childhood obesity has been increased over past several decades raising concern among the healthcare professionals and policy makers. According to World Health Organization (2015), an estimation of 43 million children (including 35 million from developing countries) were overweight and obese and this figure will reach 60 million in 2020. This epidemic not only affects developed countries, but also developing countries. With the current lifestyle that include popularity of fast food, soft drinks, sedentary lifestyle, physical inactivity, and increase use of technology related gadgets, many children were found to be less active and eat more, resulted with increase of body mass index and fat (Patricia and Kristin 2006). Such unhealthy trends contributed to the increase of comorbidities such as elevated blood cholesterol, type 2 diabetes mellitus, and hypertension in their adulthood. 

 

Physical inactivity and sedentary lifestyle contributed a substantial role in increasing the prevalence of obesity among children.  Accessible to electronic devices such as computer, television and technology related gadget has caused negative impact on physical activity (Jessica et al. 2013). A longitudinal study of Kelder et al., (1994) also confirmed that patterns of physical activity habits forms during childhood that can be tracked to adulthood.  Furthermore, unlike during 1970s, children nowadays depend on transportation to commute from home to school or any other location, which compromise the involvement of physical activity such as walking (Anderson and Butcher 2006).

 

Among the key recommendations by WHO, snacking is one of main area of concern as well. As defined by Johnson and Anderson (2013), snack is food that is eaten between habitual meal that provide less calories compared to typical meal. If it is taken appropriately to meet certain nutritional recommendation such as fruit can enhance the intake of vitamin C.  However, the popularity and availability of energy-dense, high calories foods and drinks serving at the schools and public areas has encourage the children to consume more of these unhealthy snacks, which eventually contributed to the high prevalence of obesity among children (Anderson and Butcher 2006).

 

The South East Asian Nutrition Surveys (SEANUTS) Malaysian data showed that the prevalence of overweight and obesity among preschool-aged children was 16.0% in urban areas and 17.1% in rural areas (Poh et al., 2013).  Moreover, Malaysian pre-schoolers reportedly had a lack of physical activity, with close to 60% of children not achieving the recommended 2 hours of daily active play, while 27% had daily screen time that exceeded the recommended 2 hours (Lee et al., 2016).

Although study on obesity among children was done but not many was found in this part of Malaysia, Sarawak, particularly among the indigenous communities.  This study aims to determine the association between physical activity, sedentary behaviour and snacking among KEMAS preschoolers in Bau and Samarahan , Sarawak, focusing on the Iban and Bidayuh communities.

 

 

 

Chapter 2 Literature Review

2.1 Childhood Obesity

            Childhood obesity has arisen as one of the biggest concern for public health study as it can greatly affect the health status of children and could be carried on to the adulthood (T1).

2.1.1Prevalence and Trend

2.1.2Consequences

2.2  Determinant

2.2.1 Genetic

2.2.2 Environmental influences

2.2.3 Physical Activity

2.2.4 Sedentary Behaviour

2.2.5 Parental Feeding Practices

2.2.6 Snacking

2.3 Childhood Obesity in Malaysia

2.4 Rural and Urban

 

Chapter 3 Methodology

3.1 Study Design

            The current study is a cross-sectional study which targeted to look into the nutritional status and lifestyle of preschool students in KEMAS kindergarten. All the participated kindergarten and subjects were selected from rural area with main ethnic of Iban or Bidayuh.

            The current study is a study under the program ToyBox Study Malaysia which focusing on improving the lifestyle of preschool students in order to prevent childhood obesity.

3.2 Location

            The participating kindergartens were all located at either Bau or Kota Samarahan area in the state of Sarawak which belongs to Malaysia.

 

3.3 Study Procedure

3.3.1 Recruitment

     The recruitment of subjects was done at selected kindergarten at Bau and Kota Samarahan area where the main population for the preschool student is Iban or Bidayuh. Permission to conduct the study was sought from KEMAS both at the Federal and state level. 

 

3.3.2 Consent

Informed consent was obtained from the parents or guardians of the respondents.

 

3.4 Sample Size Calculation

            The calculation of sample size was based on the formula developed by Daniel (1999):

n = Z 2 p (1-p) / d2

where: n          = estimated sample size

Z          = standard value at Confidence Level of 95%

= 1.96

p          = Estimated prevalence of obese and overweight school children

= 8.1 % (obese) and 7.9% (overweight)

D         = margin error set at 5% = 0.05

Thus,

n (obese)           = 1.962 (0.081) (1-0.081) / (0.05)2

                                    = 114.38

                        = 114

n (overweight) = 1.962 (0.079) (1-0.079) / (0.05)2

                                    = 111.80

                        = 112

n (total)            = n (obese) + n (overweight)

                        = 114 + 112

                        = 226

Based on a dropout rate of 10%, the estimated sample size was 251 subjects. The estimated prevalence of obesity and overweight are based on a study conducted by Nasir et. al. (2012) with preschool students as study subjects.

 

3.5 Data Collection

3.5.1 Socio-Demographic

            A questionnaire constructed in Bahasa Malaysia to obtain socio-demographic information from parents or guardians of child subjects. Child subjects were asked to bring back the socio-demographic form to be filled by their parents or guardians and to return to their teacher after one week from the day of form distribution.

 

3.5.2 Anthropometry  

     Anthropometry data such as height (cm), weight (kg) and waist circumference (cm) of subjects were taken based on the standard of International Standards for Anthropometric Assessment by International Society for the Advancement o Kinanthropometry (ISAK) to generate information on the nutritional status of the respondents including BMI-for-age and waist circumference.

 

 Child’s weight was measured by using Omron electronic scale (xxx). Child subject was requested to be measured in the condition of light clothing with removed socks and shoes and the same time. Subjects were requested to stand on the center of scales with weight evenly distributed on both legs and without any support. The weight of subjects in this study was measured to the nearest 0.1kg.

 

Child’s height was measured by using Seca 213 Portable Stadiometer Height-Rod and was requested to be in a condition of lighting clothing with removed socks and shoes. Height was taken using the Stretch stature method which requires subject to stand with heels together and with the heels buttock and upper part of the back touching the scale. Head of subjects was positioned in the Frankfort plane in order to allow Vertex to be the highest point on the skull as according to ISAK standards. The height of subjects was measured to be the nearest 0.1cm.

 

The waist circumference was measured using Lufkin tape. Child subjects were requested to be in light clothing. Subjects were then requested to fold their arm across the thorax to open up the waist area. Measurer then looks for the narrowest point between lower rib costal border and iliac crest. The measurement of the midpoint between the lower costal rib and iliac crest was taken when there is no obvious narrowing on the child subject. After the positioning to the narrowest point or mid-point as according to condition stated above, subjects were requested to breathe normally and the measurement was taken at the end of a normal expiration. Waist Circumference of subjects was measured to be the nearest 0.1cm.

 

All anthropometric measurement involved in the paper was taken by taking the mean value of 2 measurements on the same subject at the same session. In any case that the Technical Error of Measurement (TEM) exceeds (xx), a third measurement was taken and the median of 3 value will be considered as the output of the measurement.

 

Body Mass Index (BMI) of subjects was obtained by following the equation:

BMI = Weight/ (Height)2

            Comparison of BMI to age was based on the classification of WHO 2007 stated in the figure below.

       

 

Classification of the anthropometric indicator is based on a standard set by WHO.

 

3.5.3 Physical Activity and Sedentary Behaviour

            Physical activity of subjects was measured using accelerometer Actigraph (xx). The accelerometer is light in weight and was proven to be practical to capture physical activity on children based on the previous studies (Jackson et. al. 2003, Basterfield et. al. 2011). According to previous studies by Basterfield et. al. (2011) and Penpraze et. al. (2006), 3-4 days of accelerometry is able to provide high reliability for assessment of physical activity in young children. Accelerometry data for 3 weekdays and 1 weekend are taken as data for the present study if subjects are wearing for at least 10 hours for the stated 3 weekdays and 1 weekend. Subjects were advised to wear it for 6 days for data collection of the accelerometer was to allow the compensation of an extra weekday or weekend to any possible missing date of wearing the accelerometer.

            Every accelerometer used in this study were calibrated and initiated with corresponded subject information. The accelerometers were set to record activity in 15 seconds epoch. All subjects were carefully briefed on the proper way to wear the accelerometer (with an elastic band), which is around waist area above of hips as explained in the previous study and outside of clothing of subjects to prevent any rashes or skin allergy problems on child subject (Hughes et. al. 2006). A simple log form was given to all parents and guardians in order to assist their children in recording activities such as when it is put on and off and what is the reason behind such action.

            Besides accelerometer, parents and guardians of child subjects were requested to complete a questionnaire from ToyBox Study Malaysia which consists of 7 question regarding physical activities for parents and guardians and 30 question regarding physical activities for their children.

            Data for the sedentary behaviour of child subject were obtained from two part which is accelerometer and ToyBox Study Malaysia Questionnaire.

            Data from accelerometers were retrieved at the same time from the measurement of physical activities. As opposed to physical activity, sedentary behaviour looking at the count per minute (CPM). The categorization of CPM will be based on a previous study by Wafa et.al. (2011) on children subjects where:

Categorization

CPM

Sedentary behaviour

<1100 cpm Light intensity physical activity 1100 – 3200 cpm Intensive physical activity >3200 cpm

 

            Besides that, parents and guardians of child subjects were requested to complete a questionnaire from ToyBox Study Malaysia which consists of 7 question regarding sedentary behaviours for parents and guardians and 30 question regarding sedentary behaviours for their children

 

3.5.4 Snacking

            While for snacking practices of child subjects, parents and guardians of child subjects were requested to complete a questionnaire from ToyBox Study Malaysia which consists of 7 question regarding snacking practices for parents and guardians and 30 question regarding snacking practices for their children

 

3.5.5 Feeding Practices

            Parental feeding practices of child subjects were assessed through the Children Feeding Questionnaire (CFQ) which was developed by Birch et. al. (2001). Due to the locality of present study conducted, most participants of the study were not fluent in English as a language for questionnaires, therefore a translated version of the questionnaire in Bahasa Malaysia was used in this study. The translation was done by Prof. Wan Manan from the University of Science Malaysia and was validated. Child subjects were requested to bring the CFQ home to be filled by their parents or guardian and return to their kindergarten teacher on week after CFQ was distributed.

 

3.6 Data Analysis

            Statistical analysis of the study was performed using SPSS version 22.0 (SPSS Inc., Chicago, IL., USA). Descriptive and inferential statistics were carried out based on a p-value of <0.05.   3.7 Ethical Consideration Ethical approval was obtained from the university ethical committee. Permission to conduct the study was sought from KEMAS both at the Federal and state level.