The extent of obesity is assessed by classification in adults. However, it is difficult to assess the same in case of children by such classifications. For studies and research, given the problems in children, the prevalence is an important parameter to study. In research studies, classically this is measured in percentiles. Although there are legitimate criticisms, research literature has conventionally used body mass index. Consequently, there is a prescribed body mass index (BMI) for all ages, and 85th to 95th percentile of the standard BMI has been used as the landmark. This means children within this range will be considered at risk for being overweight. On the other hand, children who are beyond 95th percentile would be regarded overweight. It is evident that studies that involve at risk children as target population for intervention, would attempt to identify them, and in that context, these benchmarks could serve as effective identifiers. Once identified, these affected children may be intervened through designed public health measures with the objective and outcomes being prevention of future or existing obesity and reduction of complications and implications of obesity in them (Gibson et al., 2006). The global nature of this problem has already been mentioned, but the important parameter that this study attempts to address is launching the public health intervention at young age when the exposure to life style related risk factors are just beginning to occur. This would not only provide an opportunity to modify the behaviour, but it can also modify the metabolic syndromes and other complications that these children are exposed to in their future lives. Implemented in a large scale the trend towards the intensified prevalence locally, regionally, and globally may be controlled in an effective manner. The impact of this hypothesis will be evident when the review of studies indicates that increased obesity in childhood is often the forerunner of obesity and its consequences in the adulthood. These interventions may this eliminate or downsize the other health risks or other medical consequences in the future lives. Obesity per se in childhood has been implicated in serious medical illnesses and related mortality in children. As a result, the best way to intervene would be preventing them early on, and without monitoring the prevalence this is impossible (Fox, 2004).
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Research has also indicated repeatedly that prevention is the best intervention in childhood obesity. Therefore, a public health intervention would address the risk factors as measures of prevention. Therefore, identification of the risk factors associated with childhood obesity and overweight remains the best strategy (Hawkins et al., 2009). Current evidence further indicates idiopathic or primary childhood obesity can be linked with dietary and nutritional factors. Many routes of such nutritional abnormalities have been recognised. These are formula feeding, caloric intake, nutritional imbalance, physical activity, food groups, and many such other factors (Ness, 2004). Therefore, there is a rationale of such interventions in these noted areas may help curb these risk factors, and evidence again suggests, these could be capable of improving the obesity problem of the children in the family and community levels.
Research Question: An appropriate study and public health intervention measure can be designed. Thus study will investigate the effects of these risk factor interventions in children with obesity. This study would thus attempt to question whether risk factor modification interventions can be effective in reducing obesity in children selected as the study population.
Aims: To investigate and examine the long and short-term effects of risk factor modification interventions on obese children.
Objectives: The study design will be prospective. The objective will be to examine the effects of risk factor modification interventions as a public health measure against obesity in childhood within the study population determined to be obese children in a community. As indicated earlier, the literature review has identified the risk factors. These will be enlisted. Literature review has also identified the indicative parameters of childhood obesity, which may be modified and altered favourably through these public health interventions. Many of these interventions will take longer time to demonstrate effects. However, some interventions can modify immediately some factors. Therefore, the effect size should be investigated both on short and long-term basis. Safely, as indicated in other studies, a 6-month intervention through a combined dietary, behavioural, and physical activity regimen could demonstrate both parameters on the anthropometric and other indicators of childhood obesity (Robertson et al., 2008).
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Plan of Investigation
Methodology: There is a paucity of studies reporting public health intervention programme with obese children as study subjects. This study is required moreover due to the fact that current literature provides limited information on long-term effects of public health intervention programme on these children with obesity. Literature also reports that analysis of body composition, analysis of anthropometric indices, description of food habits, taking into account the activities related to dietary and leisure time, scales of fitness, and most importantly, lipid profiles have been acknowledged to be acceptable indicators of obesity in childhood (Saunders, 2007). Therefore public health measures should be designed in such a way that dietary-habit modification and interventions related to physical activity promotions can have effect on these obesity parameters such as body weight, BMI percentile, BMI, body composition. These should also have effects on activity parameters and fitness scales among these children. The biochemical parameter of lipid profile may have also a positive effect with such interventions. In the short run, these also are known to deliver adequately effective results; however, the long-term effects of these interventions have not been demonstrated in literature. This justifies further investigation into the matter. Thus the prospective study design is justified since it may be capable of elucidating the effects of these factors (Balakrishnan et al., 2008).
Sample Size: To generate reliable and valid findings, any significant study should include adequate subjects to qualify the sample size. Randomization and control are other two most important parameters. The most significant variable would be the weight change of the participants after the intervention. A power calculation of the sample size will be mandated in such situations. Statistically, with a two-sided 0.05 level of significance, at least 25 children should be included in the intervention group. For application of the control, an equal number of children would be included in the control group. In any study, there is a possibility of attrition. Thus to compensate for the reduction in the effect size, another 5 children would be added to each group. This makes the total sample size of 60, with 30 children in the intervention group and 30 children in the control group (Westwood et al., 2007).
Children in both the groups will be monitored regularly. A nutritional consultation will be arranged. These children will also be instructed on physical activity and exercise. To modify the habit, these exercises would be performed on their own with a frequency of at least 3 times a week during the whole of this 6-month period. The study group will similarly participate in a 6-month combined dietary and comprehensive exercise programme designed to this end. A computer generated randomisation schedule will be used for randomisation of these participant children. The inclusion criteria will include children who have been self referred to the obesity clinic where this researcher works. They will be recruited through a period of 1 year. The age of these recruited children would be within the range of 6-16 years. A physician administered clinical examination will be done for all children to ascertain clinical obesity. Presence of other organic diseases causing obesity will be the exclusion criteria. The other exclusion criteria would be presence of any medication that may cause weight gain (Edwards et al., 2009).
Design: A multimedia lecture on childhood obesity will be prepared. All interested parents and prospective participants of the intervention group will attend this series of 8 lectures. These would also comprise discussion on concepts of general nutrition with an overview of therapeutic approach based on nutritional control and relationship of physical activity and exercise with reduction of obesity during this 6 months' time. These lectures will be delivered by physicians and dieticians (James et al., 2007).
During the 6-month period of time, customised and age-appropriate dietary interventions will be designed and offered to the participants by the dieticians. Whenever possible, families will be involved in this process. There would be diet interviews based on 24-hour dietary recall. These will be recorded. Dieticians will deliver education about appropriate diet. Information will be shared about the problem of childhood obesity. From these interviews, information will be acquired about dietary habits and cooking patterns. The motivation about weight loss, food labels, food choices, food preparation and cooking, regular meals, food pyramid, and measures that control situations promoting overeating will be assessed (Kipping et al., 2008). Dietary information will be provided through leaflets and worksheets on relevant issues involving nutrition. These will comprise methods to deal with greed and tendencies to larger intakes. The strategies to control eating in big celebrations, restaurants, vacations, and holidays will be taught. Information about balanced diet such as food pyramid, importance of taking fruits and vegetables in the daily diet; calcium intake and needs will also be provided. For regulating the food intake at the family level, an individualized dietary chart will be provided to the family in order to ensure a caloric deficit of 30% or intake less than 15% of the required daily intake (Maynard et al., 2009).
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For the intervention group, an exercise programme will be designed. During this 6-month period of intervention, they would participate in a supervised thrice weekly exercise programme appropriate for each age group. This would be 1 hour per training session. A graded exercise programme will be incorporated within the schedule ensuring gradual increase in exercise with progress in the intervention schedule. These exercise regimens would comprise of endurance activities of 50% team sports and 50% running games. These would improve coordination and flexibility skills of the participants. There should be measures to improve habit and imbibe responsibility at a personal level, so after three months into the programme, they may increase the time of exercise and frequency when instructed with personal choices. Instruction on importance of avoiding sedentary habits and activities will be done, and they will avoid television and computer games and will be encouraged to use stairs and involve themselves in outdoor games (Kipping 2008a).
Measures: Anthropometric measurements will be conducted. The parameters recorded will be weight, height, and BMI. Percentile BMI for ages will be calculated given by the equation, C = M(1+ LSZ)2 (1/L) with C indicating age in months adjusted percentile for BMI, M indicating age-related median, S representing age-related standard deviation, Z indicating the z score, and L standing for age-related power in the Box-Cox transformation (Wake et al., 2009). The age-adjusted z score that corresponded to the percentile for physical measurement parameters will be calculated by the equation Z = [(X/M)2L - 1]/LS, where X indicates the weight, height, head circumference, stature, or calculated BMI value. These measurements will be done at baseline, every week during this 6-month programme, at 1 year, and at 2 years following the programme. Triceps and subscapular skin folds will be measured to the nearest 0.1 mm on the right side of the body, and all measurements will be taken by the same observer (Wake et al., 2009).
A 2-day food record will be used for baseline nutritional assessment. A pilot evaluation will be done for accuracy through a 24-hour dietary recall done at the beginning of the study. A nutritionist will analyse the 2-day food record data which will be instructed earlier, at the end of 6-month programme, and at 1 year from the beginning of the study. A computer programme will analyse the intake of energy (Lobstein and Baur, 2005).
The changes in food and exercise behaviour will be assessed through questionnaires designed for dietary habit and physical activity assessments. Each type of physical activity will be scored with a MET score resulting in a weighted score. Assessment of fitness will be done through endurance tests, and baseline data will be compared with outcome data at 6 months and at 1 year and at 2 years. Endurance time will be from the end of warm-up until the point of exhaustion with a 2-minute enhancement in speed and inclination. Fasting serum lipid profile will also be measured at baseline and following the 6-month period. These will include testing for total cholesterol, triglycerides, high-density lipoprotein, and low-density lipoprotein, with the normal range of the machine indicating the cut-off points (Gordon et al., 2003).
Data Analysis: Statistically, two-sample t-tests will analyse the differences between the control and the intervention groups. To determine the effect sizes on BMI, body weight, body fat %, habitual indices, fitness data, and serum lipid profiles and to compare them between these groups, a two-way analysis of repeated measures of variance will be used. The data will be presented as mean Â± standard deviation, and statistical significance will be indicated by a P value of less than 0.05 (Sandhu et al., 2006).
Key Deliverables and Outcomes: To substantiate the hypothesis, a 6-month intervention would lead to significant decrease of all negative parameters in the intervention group. Thus BMI, body weight, and % body fat will decrease considerably in comparison to control group. As expected there would be similar changes in habitual physical activity, fitness, and sedentary habits. In the intervention group the expected outcome parameters would include increased endurance. Regular dietary and nutritional interventions will lead to increased awareness about diet with changes in food habits, and the control group would demonstrate no such changes. In the intervention group after a 6-month period, serum lipid parameters will reduce significantly. Since this programme has been designed to engender behavioral changes in the intervention subjects, these changes will be maintained, and if maintained and continued, these may as well culminate into permanent reversal of obesity (Viner and Cole, 2005).
Ethical Issues: Following submission of the proposal, ethical clearance will be sought from the appropriate review board and authority. Following ethical committee clearance, consents of both family and the children will be sought from each of the prospective recruits. The purpose, objectives, and procedure of the study will be explained in laymanâ€™s language, and both verbal and written informed consent will be taken. It is evident that no participant will be coerced, and their identities will remain undisclosed. All subjects will have freedom to opt out of the study anytime they feel like. A followup for 2 years would be suitable for the study; however, due to reasons for holding treatment in the control group for such a long period in case they develop any problems would not be ethical, hence would be quashed (Stamatakis et al., 2005).
Potential Risks and Disadvantages: There are potential risks and disadvantages in this study. Motivation of the families and children not to purse and change habits immediately would be very difficult. Behavioural and dietary modifications are crucial for the methodology of the study, and with failure, the study may fail to produce results. This indicates an inherent fault in the design. To assess long-term effects, followup is very important. Give the time of two years, there is a potential risk of attrition leading to a loss to followup, thus reducing the number of participants. This may compromise internal validity and reliability. This may in turn compromise generalizability of the study. Two years of followup time may be unethical for the participants in the control group participants, leading to compromise in the outcomes.
Beneficiaries: If this study is able to produce the results anticipated, this could generate a public health intervention measure to control risks and obesity in children along with its health hazards.
Dissemination: The findings from this research will be tabulated and synthesized in the form of a research paper and will be published in reputed journal of nutrition, dietetics, pediatrics, and obesity.
Timetable: It will take 3 months to get approval from the ethical body, and after 1 month of initial preparation, the recruitment will begin. Depending on patient inflow to the department, a period of 6 months will be provided for recruitment, and for the sake of uniformity, all interventions will be started at the same time. Thus another 2 years 6 months would be added to the study time. Another 1 month will be necessary to compute, synthesize, and analyze data, and in the following month the paper will be written. The total time required thus will be 31/2 years.
Criticism on Methodology
BMI has been assigned as the variable for study the prevalence of obesity and overweight in the children and the adolescent. For the convenience of calculation, the epidemiologic definition of prevalence is the proportion of subjects in the zenith of the BMI distribution curve. As indicated in the methodology, subjects above the 95th percentile for gender and age adjusted rates, have been included. However, this may be conceptual error since actually for certain individuals such as in children younger than 2 years, there are no accepted, universal, or references of optimum BMI in these individuals. Therefore there is a possibility of loss of validity in this study; however, this also validates the need for future research exploring these relationships so age-adjusted risks for other parameters of physiological and psychological morbidities associated with higher BMIs may be well elucidated. The diagnosis and definition of childhood obesity are controversial. There are considerable ethnic and racial variables in this population. Moreover, gender, stage of development, and age also are acknowledged determinants of body fat mass in these subjects. The established clinical measures are body mass index, skin-fold thickness at different locations, and circumference of the waist. While assessing the upper body, waist-to-hip ratio is helpful. But it has been argued that these measures do not allow measurement of intra-abdominal fat. This has been attempted to be solved by suggesting cut-off points related to BMI in children and adolescents leading to list of age and gender related BMI values. Standard values for 2 to 18 years can be accessed. For children younger than 2 years, this is not applicable due to unavailability of data. Moreover, weight status may not correlate well with the level of adiposity. Although this is also true for adults, in case of children and the young, given their growth and rapid development, this can be a wrong tool to use due to rapid changes in body composition. Therefore classification of obesity based on this single measure may be inappropriate. It has also been stated that national standards may not be applicable in regions, since there is notable regional variation even within a geographic region due to mix of different races and ethnicity among the children. While doing this study, the definition of obesity only captures children with excessive adiposity by weight, while accurately, the estimation of the level of fat in the body should be effective, and unfortunately, this is only one of the measures. To avoid this problem, anthropometric measures have been used in studies involving obesity. While there may be innate flaws in that, a precise measure of the status of overweight is through calculation of Z score, derived by subtraction of the reference value from the measured data and by division by the standard deviation data from the reference population, with a Z score of +2 or above is indicative of obesity by convention. The advantage of this measure is that it can generate continuous values and is independent of age and gender. This validates its use in this research project (Polit and Beck 2005).
There is a need for quantitative design to enumerate the results of interventions. A rigorous design would increase the reliability and validity of the study. It is also important that the public health intervention would practically be able to apply these findings in actual (Polit and Beck 2005). There is clear definition of inclusion and exclusion criteria in this study defining the study population (Polit and Beck 2005). This has practical implications when a public health intervention measure bases on research findings due to resultant generalizability of the findings. The prospective design of this study limits the representativeness of participants as applicable in a quantitative design, thus close approximation of actual individuals in a community might have been compromised. Due to use of computer generated randomisation, there is no appreciable bias in this study (Polit and Beck 2005).
The sample size was determined through power analysis. Adequate investigation of hypothesis may need a minimally adequate number. Although power analysis can effectively estimate sample size needs, the appropriate number of the subjects may never be accurately known. This suggests the need for a large number which was not possible in this study (Polit and Beck 2005). In a prospective design, analysis of presumed causes is done. In this study, an intervention has been designed which tends to counteract these presumed causes or risk factors and then goes forward in time to observe presumed effects (Polit and Beck 2005). True experiments possess a high degree of internal validity because the use of manipulation, randomization, and a control group usually enables the researcher to rule out most alternative explanations for the results. These have been utilised in this study design to improve reliability so a definite conclusion can be reached. Thus this study has considerable internal validity (Polit and Beck 2005).