Royal Air Force: How Body Mass Index and Waist Circumference Influence the Rising Rates of Obesity - Essay Example

How Body Mass Index (BMI) and Waist Circumference influence the rising rates of obesity within the Royal Air Force? Throughout this research proposal, the author aims to assess whether the prevalence of obesity is on the increase or whether the assessment criteria of Body Mass Index (BMI) and Waist Circumference measurements are influencing these rising rates of obesity within service personnel. The rationale for undertaking this research proposal is that the author has worked within Primary Health Care for the past 12 yrs and it appears that there has been a steady increase in the number of Royal Air Force (RAF) personnel being referred for weight management. Information on the prevalence of obesity within the military is limited and usually relies on reported data on height and weight or on unrepresented smaller samples. According to Rona et al (2010), BMI is the usual indicator to assess overweight and obesity among army personnel but its validity is questionable because some people may have huge bodies but not obese. As such, in this proposal the author will make reasoned judgements and draw conclusions from these findings along with evaluating the significance of the assessment criteria used in monitoring obesity. Furthermore, the proposal also seeks to highlight the reason why the prevalence rate of obesity at the time of recruitment is low and subsequently increases over the years. The problem of obesity affects the military personnel in many ways. According to the World Health Organisation (2000) ‘Obesity is diagnosed as having a body mass index of 25 and over’. Thus the Ministry of Defence has adopted the WHO BMI chart and all personnel have their measurements taken and calculated as above and classified according to this chart. This will be further reviewed within this proposal. CONCLUSION Prevalence rates of obesity from this study should be viewed with caution as the sample studied is not representative of the UK Armed Forces. The true percentage of obesity could be higher since the sample is drawn from a small number of people. This research proposal aims to use a quantitative research method to evaluate the use of BMI and waist circumference to monitor obesity levels within the RAF. In turn this research proposal will highlight how BMI and waist circumference monitoring negatively reflects the obesity statistics in RAF personnel. Consequently the results of this research proposal will be used to: Highlight the importance of accurate measurements to assess obesity. In turn it will provide evidence to HQ Air to rethink current policy and perhaps adopt a tri service approach to tackling this problem in the future. INTRODUCTION Preventing obesity is essential within the military, not only to decrease the risk of cardiovascular disease and other chronic conditions (Ogden, et al 2007) but also to increase fitness and operational preparedness. This is essential since it improves their performance and physical fitness. The prevalence of obesity in the United Kingdom Armed Forces has not previously been monitored. Military personnel undergo annual health examination dependent on trade/branch (Joint Service Publication, 346 Chapter 2, 2008 will be hereafter referred to as JSP). Despite these examinations, there appears to be a requirement for a more robust information system to estimate obesity within the military (Rona et al, 2011). According to the JSP 346 the assessment process appears to rely heavily on how healthcare staff interprets height and weight measurements in order to calculate Body Mass Index (BMI). BMI provides the most useful population-level measure of obesity as it is the same for both sexes and for all ages of adults (WHO, 2012). The notion that BMI should be used when assessing obesity is backed by US research (Rona, 2012). However, the drawback of this method is that an increase in BMI may not necessarily mean that a person is obese since military personnel have greater muscle mass than ordinary citizens. In 2006, the National Institute for Health and Clinical Excellence (NICE) produced guidelines on the prevention, identification, assessment and management of overweight and obesity in adults and children. The author of this proposal spent over 21 years in the RAF as a Registered General Nurse (RGN) and during the past 12 years he was employed as a Practice Nurse providing Primary Health Care in numerous RAF Medical Centres. During the past 5 years, the author has experienced an increase of service personnel being referred for weight management. Currently the practice provides a weight management clinic run by a Medical Officer and a Nurse. This clinic was established as a result of the fact that such a large number of our service personnel were failing their six monthly fitness test. Subsequently, on recording their height and weight, it can be observed that their BMI calculation was placing them within the obese category. Thus, this research proposal aims to use a quantitative research method to evaluate the use of BMI and waist circumference to monitor obesity levels within the RAF. In turn this research proposal will highlight how BMI and waist circumference monitoring negatively reflects the obesity statistics in RAF personnel. OBESITY Obesity is a medical condition in which excess body fat has accumulated to the extent that it may have an adverse effect on health (WHO, 2000). At an individual level, a combination of excessive food intake and a lack of physical activity are thought to explain most cases of obesity (NICE, 2006). 'By 2050 half the UK adult population will be obese with only 1 in 10 adults having a 'normal' BMI,’ predicted by Foresight Report (2007) ‘Tackling Obesities: Future Choices’ highlighted the importance of tackling the growing obesity trend along with aiming to provide a fresh insightful analysis to help manage the growing social, economic and medical threat of obesity. Importantly, the study introduced new analytical methods and approaches to tackling this major health challenge. Subsequently Foresight (2007) commissioned a quantitative analysis of the future trends in the prevalence of obesity, including the consequences for cardiovascular risk and other co-morbidities. This work yielded some stark messages on the size and nature of the condition by concluding that if no new strategies were developed to stem the rise in prevalence of obesity and if the current trends were to continue, by 2050, 50% of women and 60% of men will be obese (Tackling Obesities: Future Trends – Project Report, 2007). These statistics are too high for comfort hence the need to monitor the problem of obesity. The author seeks to investigate if the strategies of using BMI and waist circumference are reliable for measuring obesity among the military personnel in UK. Information on the prevalence of obesity in the military is somewhat limited and has previously relied on reported data on height and weight or on unrepresented small samples (Bray, 2010). This in turn may suggest that obesity rates have been underestimated within the military (Mullie, P., et al, 2009). However, according to the outcome of two quantitative studies on military personnel which have been undertaken by Sudan et al (2011) and Rona et al (2011) both agree that the prevalence of obesity could become a serious problem in the future within the UK Armed Forces. The most common method of measuring obesity is the Body Mass Index (BMI). BMI is calculated by dividing a person’s weight measurement (in kilograms) by the square of their height (in metres) (WHO, 2000). In adults, a BMI of 25 to 29.9kg/m2 means that person is considered to be overweight and a BMI of 30kg/m2 or above means that person is considered to be obese (WHO, 2000). For the purpose of this research proposal, we will be looking at BMI above 30kg/m2. Basically, BMI is one of the effective ways of measuring the prevalence of obesity at the population level (WHO, 2000) whereby there is no specialised equipment needed and therefore it is easy to measure accurately and consistently across large populations (Department of Health, 2012). BMI is also used in other countries around the world, not just in England, which enables comparisons between countries, regions and population sub-groups (Department of Health, 2012). Height and weight data have been used to calculate BMI and waist circumference has been used to assess central obesity (NICE, 2006). BMI is used widely within the military but its accuracy has been questioned as you can have a huge individual but not obese (Friedl, 2004). Within the military, such lack of specificity may be a drawback because muscle mass may be a greater component of BMI than in the general population (Rona, 2011). This drawback may be greater in younger than in older service personnel as muscle mass decreases with age. Rona et al (2011) has shown that BMI does not distinguish between fat-free mass and fat mass yet this distinction is important as a clinical tool especially within the military and occupations for which physical fitness is important. Sundin et al (2011) agree that Body Mass Index should not be used in isolation and waist circumstance and skin fold thickness should also be recorded and standardised throughout the military in order that we accurately collect data on the prevalence of obesity. Military personnel would be expected to have a lower risk of obesity than the general population due to the emphasis on physical fitness (Sundin, 2011). There are currently only two published quantitative studies that have been undertaken by the Kings Centre for Military Health Research which are related to this area of study. These studies will be used as the theoretical framework of the study. However, there is a vast amount of literature available from the Department of Health which deal with issues related to obesity. National Institute for Health and Clinical Excellence (NICE) produced guidelines on the prevention, identification, assessment and management of obesity in adults and children (2006). LITERATURE REVIEW The aim of a literature review is to look at relevant evidence on a given subject and evaluate these documents in order to help to highlight areas that need further research (Hart, 2005). A literature review was conducted using the following keywords: Obesity, British Military, Prevalence, Increase, Body Mass Index (BMI) from 2006 to the current period. Computerised databases were accessed via the Athens Access Management System using the search engines CINAHL, COCHRANE, Medline, and Defence Medical Library Service (DMLS), Army Primary Health Care via Defence Intranet and also Royal Air Force Primary Health Care via Defence Intranet. Internet search was undertaken using Google and Google Scholar accessing Department of Health and National Institute of Clinical Effectiveness (NICE) evidence. Inclusion Criteria for Literature Search The keywords used initially presented a vast array of evidence and literature on obesity. This search was refined to include the UK only as the majority of the studies were undertaken by United States Military and various other Military services around the world. The search criteria was refined to include the British Military and it soon became apparent that there is an extreme lack of data available which focuses on Obesity Trends within the UK Military. Exclusion Criteria for Literature Search Studies that involved the United States Military were excluded. However, the literature that the author will be reviewing does refer and also compare the UK Military to the US Military. The remainder of the literature available was therefore refined in order to include relevant data that is up to date. As there were only two key UK related military studies available, the author appraised this using Critical Appraisal Skills Programme for Quantitative Research (CASP, 2002). The majority of the literature was again refined so as to be able to critically analyse their relevance to this research proposal. The literature reviewed includes the following studies: ‘Agreement between body mass index, waist circumference and skin-fold thickness in the United Kingdom Army’ by Rona et al (2011) and ‘Obesity in the UK Armed Forces: Risk Factors’ by Sundin et al (20011). Both studies appeared to have a clearly defined question and that the population they were studying was clearly laid out within the abstract. Rona et al (2011) assessed whether Body Mass Index (BMI), waist circumference and skin-fold thickness within the United Kingdom Army would provide sufficient quantitative data to prove their hypothesis. Overall it was whether these measures are acceptable in assessing obesity. In contrast Sundin et al (2011) assessed whether the prevalence of obesity based on self reported is caused by an increase in BMI. The outcomes of both studies were the same. It was generally agreed that BMI and Waist circumference appear to be an acceptable method of assessing obesity. However, it appeared that comparisons were made to the general population and US military which may have influenced the outcome. The comparison of obesity between the two studies is limited as the samples were not selected in the same way and the sampling approaches used by the studies differed. One of the researchers used random sampling and other used quota sampling whereas probability sampling was used for the population studies. It is evident from the data that the majority of the subjects were taken from the army which may subsequently not have provided a true cross section of data from the UK Armed Forces. Therefore, these studies are not truly randomised though the researchers generally agreed and concluded that the consistency of the results justified these sampling methods. Rona (2011) sampled 386 male army personnel which would appear to make this study too gender specific and suggested that it is therefore not truly randomised. On the other hand, Sundin (2011) sampled a larger population of both male and females concluding that the sample size was still insufficient to truly assess the prevalence of obesity. Given this information, it is widely accepted that larger samples provide more statically relevant data. Polit and Hungler (1997) agree that the larger the sample, the more representative of the population it is likely to be. However, Egger (1998) suggests the significance of smaller studies and argues that smaller studies are systematically biased towards the effectiveness of the intervention they are testing. Given this information, it can be concluded that either study would provide the relevant data for analysis to assess the prevalence of obesity. Sundin (2011) used self reported data that were obtained via questionnaires sent out to randomly selected regular and reserve personnel. According to Burns and Groves (1999), a good questionnaire is one with content and structure that meet the research objectives. Denscombe (2003) agrees that a questionnaire should be clear and unambiguous and concluded that if the respondent understands exactly what is being asked, they are more likely to answer accurately. Sundin (2011) used closed questions like: “How tall are you without clothes on? And what’s your weight without clothes on? These questions are firmly rooted within quantitative research and it is evident that these questions obtain the exact data. Rona (2011) undertook their data collection by measuring their heights and waist circumferences in order to demonstrate high reliability and validity of data collected. It is evident from this that both of these studies were undertaken by researchers from Kings College for Military Health Research and it appears that the same researchers were involved in both studies which might have introduced an element of Observer Bias. According to Angrosino (2012), although researchers may strive for objectivity in the recording and analysis of data, social researchers who use observational methods are aware of the possibility that bias arising out of the nature of observation itself may compromise their work. Observer bias may arise out of unconscious assumptions or preconceptions harboured by the researcher. Egger (1998) agrees that a potential problem that arises in meta-analysis of observational data is that the findings may appear to be very precise but they are simply reinforcing biases present in individual studies. It is evident that Rona et al (2011) acknowledge that this study may be seen as observer biased though they concluded that there was a positive outcome as it minimised the margin for error. Considering this fact, the author agrees that accurate measurements are essential in this study. However, the time taken to measure the participants may again be seen as biased. Both studies considered the results that were undertaken on men and women using BMI as the usual indicator to assess obesity in population studies. However, its validity has been questioned because the index does not measure fat mass. Friedl (2004) and Sundin (2011) agree that lack of specificity may be a drawback because muscle mass may be a greater component of BMI than in the general population. Ford, (2003) support the use of waist circumference as a measure of obesity to predict health risk. Their arguments posit to the effect that waist circumference has been shown to be a good or better predictor than body mass index since it provides information about health risk. In addition, waist circumference is conceptually easy to measure and it does not require training and standardization. However, others have noted that substitution of body mass index by waist circumference as an indicator of risk for cardiovascular disease and diabetes may be an oversimplification (Janssen, et al, 2002). Furthermore Ford (2003) argues that waist circumference is strongly correlated to body mass index and waist circumference does not differentiate between subcutaneous fat and visceral fat. Therefore, it has not been shown that an association exists between waist circumference after adjustment of age and body mass index concluding that body fat distribution is different across race, sex and age (Jensen, 2006). It is evident from the results that response rates from self reported data were quite satisfactory at 60% with a possibility of personnel avoiding being measured and some of them were reluctant since they were already obese (Rona, 2011). The study by Sundin et al (2011) which was carried out during a period of unprecedented activity in which the main concerns were related to overstretching of the UK Armed Forces in preparation for Iraq and Afghanistan which could possibly affect the results. However, it was generally agreed that the results were precise enough to make a decision on the assessment of obesity. In conclusion, all the important outcomes were considered and the results can be applied to be our population in ways that would produce the same or similar results. The literature suggests that the prevalence of obesity increases with age and this is similar to the general population. Both studies concluded that the true percentage of obesity could be higher and that the trend may be on the increase. Subsequently, they both agree that prevention of obesity is of paramount importance for occupational and health reasons. METHODOLOGY FOR RESEARCH PROPOSAL Research Method The literature review has demonstrated the relevance of the links between these two studies. They weigh up the importance that the prevalence of obesity within the Armed Forces may well be on the increase and that the three armed services may need to reconsider their policies on how they record data along with evaluating the significance of recording height, weight, BMI in conjunction with waist measurement. Sundin (2011) and Rona (2011) agreed in their conclusion that the overall management of obesity in the future may become a problem. The literatures reviewed have both used quantitative research methods in order to gather their data. Denscombe (2003) suggests that Quantitative research looks to discover answers to questions through the application of scientific procedures whereby it starts with the collection of data, based on the hypothesis or theory. According to Cormack (1996), quantitative research is usually viewed as the more scientific approach for which it usually gains more credibility. In contrast qualitative researchers aim to gather an in-depth understanding of human behaviour and the reasons that govern such behaviour. The qualitative method investigates the why and how of decision making not just what, where, when. Hence, smaller but focused samples are more often needed than large samples. No research method is perfect since qualitative and quantitative research methods have advantages and disadvantages (Cormack, 1996). Therefore, in order to carry out this research proposal, the author has opted for a quantitative research method. The advantage of this method is that data can be scientifically calculated to show a true reflection of the results of the subjected being studied. According to Newell and Burnard (2011), a hypothesis requires that there should be variables to test and assumptions to prove or disprove. Thus, the hypothesis for this study is: An increase in BMI and wait circumference causes obesity. The research has designed to find out if the score on a particular measure or a test result corresponds with the other behaviour of interest. For example, the author intends to predict that the findings from the research will be that BMI and waist circumference positively reflects the rising obesity prevalence for service personnel. Holloway & Wheeler (1996) believe that quantitative results which are grounded in evidence and rooted in objective reality rather than personal belief will provide a strong argument. Therefore, this research proposal will provide some evidence that can be used to influence or change the implementation of RAF policies along with introducing new strategies to assess and monitor the increasing rise in obesity within the service population. DATA COLLECTION Quantitative research is often viewed as the more scientific approach, for which it gains more credibility (Denscombe, 2007). The data collected during quantitative research is reliable on variables and looks to discover answers to questions through the application of scientific processes, and to prove or disprove a hypothesis. Therefore, the author has chosen to use an observational quantitative survey to obtain data as opposed to using a qualitative method. The advantage of undertaking this observational survey is that it will provide more statistically accurate data and does not require the researcher to engage in thoughts and feelings of the participants. However, the researcher is well aware that there may be an element of observational bias in undertaking this proposal. Procedures such as electing every third person regardless of their gender /age/trade should help to reduce this bias. .According to Polit and Hungler (1997), a survey is a non-experimental, systematic approach in which the researcher investigates data from subjects so that new information can be obtained. Davies (2007) agrees that the advantage of this method of data collection is that the researcher can capture and input the data, along with standardization where similar data can also be collected from other groups then interpreted comparatively (Davies, 2007). However, there may also be disadvantages of using this method in that it may not be flexible since it requires the initial study design to remain unchanged throughout the data collection process (Davies, 2007). Throughout this proposal, the author will ensure that standardisation is maintained and data recorded is accurate. For the purpose of this research proposal, the author has chosen to obtain the height, weight and Body Mass Index (BMI) data concurrently over a 4-6 week time scale. RAF personnel that attend the medical centre within the stipulated time scale will be invited to have their height/weight and BMI recorded. Posters and information sheets will be made available to inform participants of the research that they will be participating in. Informed verbal consent will be obtained from each participant. It is important to ensure that consent is obtained and that the participants are made aware that any data obtained will be anonymous and confidentiality will be maintained and used for the purpose of this research only. Participants will be asked additional information such as age, sex and trade. This is to determine whether there is any given trade for example aircrew/sedentary workers such as administrators or regiment personnel at a higher risk of obesity The researcher may not be able to carry out all measurements alone therefore additional medical personnel such as nurses, medics or health care assistants will be provided with the training in order to try to maintain consistency throughout the research. METHOD Height will be measured using calibrated Leicester stadiometer. Personnel will be asked to remove shoes and instructed to stand up straight with eyes looking horizontal and the vertex of the skull in the centre of the upper measuring platform. Their height will be recorded to the nearest one millimetre. Weight will be measured with calibrated SECA to the nearest 200 grams. Participants will be asked to remove their outer jacket and jumpers along with removing shoes and emptying pockets. Ideally, all personnel will be weighed in their number two blue uniforms comprising of trousers or skirt and blue shirt. BMI will be calculated using WHO BMI chart. SAMPLING The sample of individuals should be representative of the population being studied, or ideally the total population being studied (Higginbottom, 2004). For the purposes of this research proposal, the total population will be all RAF service personnel currently registered within our region. The region constitutes 5 medical centres with varying population strengths. However, the author expects to capture approximately 5,000 personnel. Due to limited time nor funding available to study the total population of the RAF (currently approx 40,000), a sample population will be selected. Probability sampling will be used as everyone in the sample will be a serving member of the RAF. Probability sampling is a sampling technique where the samples are gathered in a process that gives all the individuals in the population equal chances of being selected and this probability can be accurately determined (Davies, 2007). The author proposes to use systematic sampling for this research proposal as the target population has been identified (RAF personnel). The sampling process will commence randomly and proceed by selecting every third person that attends the medical centre and will continue for the allocated timescale. The advantages of using systematic random sampling for this research proposal is that it is fairly easily to manage therefore it is likely to produce more accurate results. The disadvantage that may be encountered during this proposal is that there may be an element of observer bias as the researcher has control over the process. However, as the researcher is aware of this, certain measures can be put in place to try to reduce the occurrence of bias. Exclusion Criteria Pregnant females will be excluded from the sampling process as the data captured will not be a true reflection of their current BMI. Cadets, trainees, will be excluded from this process as the prevalence of obesity at recruitment into the military is expected to be low due to strict entry and fitness criteria (Yamane, 2007). Army and Navy personnel will also be excluded as they will not appear as a true reflection of their service as there are only very low numbers within the regions therefore preventing false results. RELIABILITY AND VALIDITY Reliability and validity are measures used to assess the quality of quantitative research (Davies, 2007). Shuttleworth (2009) describes reliability as something that is dependable and that it will give the same outcome each time. Reliability is an essential component of validity but on its own is not a sufficient measure of validity. Reliability describes the repeatability and consistency of a test. This can be demonstrated by consistently using the same equipment to record the height, weight of the participants within this research proposal. Validity defines the strength of the results and whether they can be recorded accurately. These may affect the research proposal if the results are entered incorrectly by the person recording them, or if the researcher becomes biased in any way. Therefore, the author intends to monitor the process and go for additional training if the need arises in order to reduce the margin for error. ETHICAL CONSIDERATIONS Ethics is not an option but a fundamental feature of good research (Davies, 2007). All researchers should be ethical and participants should not suffer as a consequence of their involvement in a research study (Denscombe, 2007). Therefore, as part of this research proposal, it is imperative to ensure that no distress is caused to the participants during the monitoring process. According to Denscombe, (2007) it is particularly important to seek the approval of an ethics committee before commencing a research study involving the collection of data from people. The ethics committee is responsible for scrutinising the design of the research. It ensures that the research design includes the appropriate elements to protect the interests of the research participants (Burns and Groves, 1999). Therefore, prior to commencing this research study, the author will seek approval from the RAF’s Ethics Committee. Confidentiality will be maintained in order to protect the interests of the participants. The consent of research participants will be needed before they can take part in the research study (Denscombe, 2007). To allow research participants to make this decision, they are provided with information about the research study, their rights, and how these rights will be protected. These rights are varied but for the purposes of this research proposal, they include the right to full disclosure, the right to self determination, and the right to anonymity and confidentiality (Parahoo, 2006). Furthermore any clinical concerns that may arise from this data collection will be appropriately referred using the correct practice referral process. DATA ANALYSIS Analysis of data collected by quantitative research usually involves some more of statistical analysis (Floyd and Fowler, 2002). Polit and Hungler (1997) stress the use of the appropriate statistical analysis stating that it provides a systematic means of assessing, summarising and presenting the findings of the research. Statistical analysis is classified as either descriptive or inferential (Clegg, 1982). Descriptive statistics provide a quick picture of a set of numbers – averages and percentages are examples of descriptive statistics (Cormack, 1996). Interferential statistics are concerned with making judgements and the testing of hypotheses (Clegg, 1982). Considering this, the author will use a predictive hypothesis within this research proposal. Therefore, descriptive statistics will be used to analyse the data. In order to gain an appropriate quantitative view of the service population a data analysis tool incorporated within a software package called Statistical Package for Social Service (SPSS) will provide the most accurate view of the use of BMI and Waist Circumference to measure obesity in order that the results can be formatted and presented in order to prove or disprove the hypothesis on whether the incidence of obesity is on the increase within the RAF. CONCLUSION This research proposal has addressed the key literature surrounding whether BMI and Waist Circumference have an influence on the rising rates of obesity within the RAF. Furthermore this proposal has highlighted that prevention of obesity is of paramount importance for occupational and health reasons. There is a greater need for health promotion particularly raising awareness to adjust diet especially in a group that may need high energy food intake during demanding periods of training. Subsequently there is a requirement for a more robust assessment of obesity using BMI and waist circumference in service personnel that have a BMI threshold above 30 to include an element of health promotion. Furthermore, this proposal has highlighted the need for more extensive research within the Armed Forces in relation to obesity as the two key studies mentioned within this proposal do not complement each other which creates a gap in the data surrounding obesity within the UK Armed Forces. REFERENCES ARMED FORCES WEIGHT MANAGEMENT POLICY (2009). Defence Instructions and Notices 2009DIN001-18 ANGROSINO, M. V., (2012). Observer bias. The Sage Encyclopaedia of Social Science Research Methods. Available at: < http://srmo.sagepub.com/view/the-sage-encyclopedia-of-social-science-research-meThe SAGE Encyclopedia of Social Science Research Methods Michael S. Lewis-Beck& Alan Bryman& Tim Futing Liao thods/n651.xThe SAGE Encyclopedia of Social Science Research Methods Michael S. Lewis-Beck& Alan Bryman& Tim Futing Liao ml> (Accessed 19th July 2012). ASSOCIATION FOR THE STUDY OF OBESITY (2004). The prevalence of obesity in the UK. Association for the Study of Obesity. Available at: ASO Website. (accessed 16th December 2011). BRAY, R.M., HOURANI, L.L., OLMSTEAD, K.L. (2006). Department of Defence survey of health related behaviours among active duty personnel. accessed (11th December 2011). BURNS, N., GROVE, S.K. (2007). Understanding Nursing Research. 4th Ed. Saunders :Philadelphia. CLEGG, F. (1982) Simple Statistics: A course book for the Social Sciences. Cambridge, Cambridge University Press. CORMACK, D.F.S. (2000). The Research Process in Nursing. 4th Ed. Blackwell Scientific: Oxford. CRITICAL APPRAISAL SKILLS PROGRAMME (CASP) (2002) Making Sense of Evidence. Milton Keynes: MKPCT: Available at: Solutions for Public Health website. (updated, 2010) accessed (12th December 2011) DAVIES, M., (2007). Doing a Successful Research Project. Palgrave MacMillan. UK. DENSCOMBE, M., (2007). The Good Research Guide For Small Scale Research Projects. 3rd Ed. Open University Press: Buckingham. DEPARTMENT OF HEALTH (2012).Available at: dh (accessed 19th July 2012). EGGER, M., (1998). Meta-analysis bias in location and selection of studies. British Medical Journal, 316 (61). The Foresight Report. Tackling Obesities: Future Trends – Project Report. (2007) Available at: (accessed 12th December 2011). FORD, E.S., MOKDAD, A.H., GILES, W.H., (2003). Trends in waist circumference among US adults. Obesity Research. (11): 1223-31 FLOYD, J., FOWLER, J. (2002). Survey Research Methods. 3rd ed., USA, Sage Publications Limited. FRIEDL, K.E. (2004). Can you be large and not obese? The distinction between body weight, body fat and abdominal fat in occupational standards, Diabetes Technol Ther 6:732-749. HART, (2005) Doing a Literature Review. Releasing the Social Science, Research, Imagination. Sage: London. HEALTH SURVEY FOR ENGLAND (2009). Health and Lifestyles. The NHS Information Centre, 2010: Available at: . (accessed:10th December 2011). Healthy Lives, Healthy People: A call to action on obesity in England. Available at: (accessed: 16th December 2011). HIGGINBOTTOM, G. (2004). Sampling issues in Qualitative Research. Nurse Researcher, 12(1), pp 7 – 19 HOLLOWAY, I and WHEELER, S. (1996) Quantitative Research for Nurses. Oxford. Blackwell Science. JANSSEN, L.,HEYMSFIELD, S.B., ALLISON, D.B., (2002). Body mass index and waist circumference independently contribute to the prediction of nonabdominal , abdominal subcutaneous, and visceral fat. The American Journal of Clinical Nutrition. 25(4), pp 683 - 688 Joint Service Publication (JSP) 346. Chapter 2: Medical Assessment , 2008 MULLIE, P.,VANSANT, G.,GUELINCKX, I.,HULENS,M.,CLARYNS, P.,DEGRAVE,E., (2009). Trends in the evolution of BMI in Belgian army men. Public Health Nutrition 2009; Vol. 12, pp 917- 21. NEWELL, R. and BURNARD, P. (2011). Research for Evidence-Based Practice in Healthcare. 2nd Ed. Oxford Wiley-Blackwell. NHS information centre 2009 (health survey). Available at: (accessed 10th 2011). NATIONAL INSTITUTE FOR CLINICAL EXCELLENCE (2006). Obesity, the prevention, identification, assessment and management of overweight and obesity in adults and children. Available at: (accessed 12th December 2011). NATIONAL OBESITY OBSERVATORY. Available at: (accessed 19th July 2012). OGDEN, C.I., YANOVSKI, S.Z., CARROLL, M.D., FLEGAL, K.M., (2007). The epidemiology of obesity. Gastroentology 132:2087-2102 PARAHOO, K. (2006). Nursing Research: Principles, Process and Issues. 2nd Ed. Macmillan: London. POLIT, D., and HUNGLER, B. (1997). Essentials of Nursing Research Methods, Appraisal and Utilization. 5th ed. Philadelphia. Lippincott. QUALITY AND OUTCOME FRAMEWORK (2009/10). The NHS Information Centre. Available at: (accessed 16th December 2011). Rona J.R., Sundin J.,Wood P., (2011) Agreement between body mass index, waist circumference and skin-fold thickness in the United Kingdom Army. Kings Centre for Military Health Research. Annals of Human Biology. May-June 2011:38(3):257-264. Rona J.R., Sundin J., Fear N.T., (2011) Obesity in the United Kingdom Armed Forces: Prevalence Based on Measured and Self-Reported Data. Military Medicine, Vol 176, 1:44 RONA, R.J., SUNDIN, J., WOOD, P., FEAR, N.T. (2010). Agreement between body mass index, waist circumference and skin fold thickness in the United Kingdom Army. Annals of Human Biology, May-June 2011; 38(3): 257-264 SHUTTLEWORTH, M. (2009). Definition of Reliability. Accessed 14th December 2011 SUNDIN, J., RONA, R.J., FEAR, N.T., (2011). Obesity in the UK Armed Forces: Risk Factors. Military Medicine. May 2011, 176(5):507-12 Statistical Package for Social Sciences. Available at: Accessed 19th July 2012 TACKLING OBESITIES: Future Choices 2nd Edition – Modelling Future Trends in Obesity and their Impact on Health Foresight. Government Office for Science, 2007. Available at . Accessed 16th December 2011. World Health Organisation (2000). Obesity: Preventing and Managing the Global WHO Technical Report Series – 894..Geneva. YAMANE, G.K. (2007). Obesity in civilian adults: potential impact on eligibility for US military enlistment. Military Medicine. 172 pp 1160-5. Britain's Future Armed Forces - Fit to Fight or Fall Briefing Paper: A Case for the Ministry of Defence to Develop and Implement 'Nutrition for Health and Performance' Education Programme for the New Recruits Curriculum. North Yorkshire Specialist Health Promotion Services. Aug 2001.The SAGE Encyclopedia of Social Science Research Methods Michael S. Lewis-Beck& Alan Bryman& Tim Futing Liao The SAGE Encyclopedia of Social Science Research Methods Michael S. Lewis-Beck& Alan Bryman& Tim Futing Liao Pub. date: The SAGE Encyclopedia of Social Science Research Methods Michael S. Lewis-Beck& Alan Bryman& Tim Futing Liao Pub. date: The SAGE Encyclopedia of Social Science Research Methods Michael S. Lewis-Beck& Alan Bryman& Tim Futing Liao Pub. date: PROJECT PLAN PHASE DESCRIPTION TIME 1 Literature Search 2 weeks 2 Write Literature Review 3 weeks 3 Write Research Proposal 4 weeks 4 Obtain MODREC approval 3-6months 5 Data Collection 6-8 weeks 6 Data Analysis 2 months 7 Presentation of Research 3 months RESOURCES RESOURCE COST Medical Weighing Scales ?265 Height Measure ?52.25 Paper ?40 Petrol ?300 Loan of DMICP laptop from DMS NIL Read More