Background and Significance of the Problem
As stated in the research performed by Ogden, Carrol, Kit, and Flegal (2014), the number of obese people in the United States (US) exceeded one-third of the population in 2011-2012. However, between 2003-2004 and 2009-2010 obesity rates were stable. Another research performed by Ogden, Carrol, Fryar and Flegal (2015) concludes that obesity is prevalent mostly for people of age 40-59 with no significant difference between older adults and middle-aged adults. 40.2% of the middle-aged population of the US suffers from obesity. Thus, the situation does not deteriorate any further, while remaining severe as it is.
The main factors that contribute to obesity in the US are the unhealthy diet, sedentary lifestyle, and social changes. According to Altman (2014) Douglas L. Coleman, 82 also include genetics in this list. However, there is almost no scientific evidence of genetic predisposition to obesity. Taking all of the factors mentioned above into account, one could argue that the most crucial one is a pernicious diet with sedentary lifestyle being the second. The diet that an average citizen of the US follows is most harmful not only to the digestive system.
It also worsens the condition of the cardiovascular system and creates a possibility of obesity. Sedentary lifestyle, in turn, allows the unhealthy diet to damage the organism even further. Without regular exercises to keep a person fit, the risks of receiving a number of diseases that are caused by obesity results are ever-growing (Hruby, et al., 2016).
Finally, social changes also contribute to the problem. Television, video games, cellular devices are the technologies that make it easier to follow a sedentary lifestyle which, again, leads to increasing the risk of becoming obese (Altman, 2014). These changes are regarded as social because they are mostly prevalent in highly-developed countries such as the US where bigger part of the population is gaining access to advanced technology such as the devices mentioned above. These factors combined create an environment in which obesity rates have become extremely severe over the course of last decade (Hruby, et al., 2016).
Statement of the Problem
The current rates of obesity among the adult population of the US have drastically increased during the last decade (Dwyer-Lindgren, et al., 2013). This issue is of utmost importance and, therefore, requires intervention in the form of finding ways to decrease obesity rates. Thus, there is also a need to improve the healthcare system by incorporating practices that will contribute to treating patients suffering from obesity. The problem of this study is to evaluate the current rates of obesity and practices that will assist in solving the problem the most. Purpose of the research is therefore, to determine education as intervention can reduce the rates of obesity cases seeking medical care. Information on obesity rates will support this statement (Hruby, et al., 2016).
Obesity in adults (particularly parents) is not only likely to have an impact on them but also sways the possibility of obesity in their children due to common genes or environmental aspects (Simmonds, Llewellyn, Owen, & Woolacott, 2016). The perception that obesity runs in the family has been backed by Simmonds et al. (2016) and other studies present a proof that parental obesity is a considerable risk aspect for obesity in their children. Facts from researches indicate that maternal Body Mass Index (BMI), particularly, was a considerable predictor of BMI in children from six to thirteen years of age.
After attaining the age of six, the possibility of the child turning into an obese adult in later life exceeds 50% in obese children when judged against approximately 10% for non-obese children (Simmonds et al., 2016). The risk for obesity in adulthood was considerably high when either the father or mother of the child was obese (Simmonds et al., 2016). This illustrates that parental obesity increases the risk of childhood obesity and obesity in later life of their children. Obesity signifies a risk aspect for related co-morbidities, for instance, type II diabetes, heart diseases, and other illnesses (Simmonds et al., 2016).
Similar to Simmonds et al. (2016), Bouret, Levin, and Ozanne (2015) established that both genetic and nongenetic impacts lead to the parental transmission of obesity to their children with environmental determinants like the feeding practices of adults in addition to the development of eating habits and lifestyle perpetuating obesity. Parental consumption patterns could as well alter genetic inclinations to preferring or disliking some foods and assist in shaping food tastes in children.
Factors like too much time watching TV, spending most of the free time each day playing computer games, and lack of physical activity among others are some causes of obesity. On the contrary, Nguyen, Shuval, Bertmann, and Yaroch (2015) affirm that early initiation to healthy food and habits has the capacity to determine proper consumption patterns and alter genetic inclinations as well (for example, neophobia, the fear of consuming new kinds of foods), which could translate to positive food intake approaches.
The means of avoiding obesity among children and the adult population encompass changes in the nutritional habits at home to ensure consumption of healthy foods (Nguyen et al., 2015). The evaluation of childhood obesity is hard since children develop in irregular intervals. The assessment can only be effectively conducted by a health care expert with the use of the height and weight of the child in relation to the child’s earlier growth account.
The loss of weight for the majority of young adults is a negative pointer because their bodies are maturing and developing; similarly, overweight is a bad indicator. However, overweight people must not be put on diet except when a doctor directs so for health purposes. A limiting diet might fail to offer the nourishment required for normal development. It is thus advisable for the majority of overweight young adults and the ones with obesity to engage in regular exercise and consume healthy foods.
Just like Nguyen et al. (2015), Geiss et al. (2017) affirm that the most significant practices to avoid are unhealthy eating behaviors, lack of exercise, and increased sedentary activities like too much of watching TV or playing video games. The avoidance of the aforementioned practices forms a section of a healthful lifestyle that ought to be followed in both childhood and adulthood. Parents and guardians are in a better position to prevent both their obesity and that of their children through ensuring consumption of healthy foods, daily exercise, nutrition edification, and avoidance of junk foods. Healthy foods offer the required nutrients for the growth of children and form a healthy consumption behavior and approach in adults while increased exercise decreases medical risks and assists in managing weight.
Nutritional education assists adults to gain the knowledge of proper nutrition and healthful consumption behaviors; it aids them by persuading them to take up healthful eating habits (Geiss et al., 2017). Adults should avoid focusing on weight objective and concentrate on good health. They should also avoid inadequate time for the family or ignoring overweight in themselves or their children. Instead, adults (especially parents) should involve every member of the family and make efforts towards bettering the family’s consumption practices and observing the time for exercise. Such adults should avoid cases of the family or their children eating out as much as possible and strive to take food together at home at all times. This way, they will ensure consumption of healthy foods, decide which food is eaten when, and facilitate monitored healthy consumption behavior.
For clinical evaluation, every obese person ought to know his or her entire history and have physical examination carried out (An & Xiang, 2016). Everyone’s weight and height ought to be regularly measured and fitness test done. The variation of body mass index all through childhood ought to be plotted on BMI charts, and waist perimeter could be used as a parameter for obesity.
Problems that ought to be addressed on fitness test encompass high blood pressure, keratosis nigricans (a disease characterized by thick pigmented skin denoting insulin resistance), and fatty liver to mention a few (Perez et al., 2013). Cautionary indications of other uncommon causes of obesity encompass short height, use of drugs like corticosteroids, in addition to the developmental setback. In parents and children with grievous obesity, particularly when there is a family record of illnesses linked to insulin resistance, examination for liver problems, dyslipidaemia, insulin resistance, and glucose intolerance to mention a few should be conducted.
Backing the affirmations of other studies, Perez et al. (2013) assert that the success of treatment will entail non-weight associated results, in addition to weight-associated outcomes, which encompass advancement in confidence, an augment in healthful lifestyle habits for the entire family, addressing the co-morbidities of obesity, and parental and children understanding that lasting behavior modification is needed.
Nonetheless, Bouret et al. (2015) establish that weight loss objectives are usually not set when addressing obesity among the adult population since the principal objective ought to be behavioral change. Families have an impact on feeding and other activities hence successful treatment of obesity has to be family centered. Change of lifestyle practices with the adults being on the frontline marks a significant aspect in successful treatment. Numerous visits to nutritionists at the beginning (for example, one time a week or after every two weeks) could be needed to talk about advancement in making minor modifications and as well set new attainable targets. Advice from a professional dietitian for added support in realizing lifestyle modifications could offer great assistance.
Like Geiss et al. (2017), Foster‐Schubert et al. (2012) assert that increase in exercise and healthy eating habits for the entire family are some of the changes that could prevent the development of obesity. All adults ought to be persuaded to set some free time for physical activities. Engaging the whole family in arriving at a change to ensure sustainable and healthful consumption is normally crucial. This is attributable to the reality that transformations in cooking and shopping patterns and modified approaches to the time for consumption and avoidance of junk foods are all needed.
Fundamentally, great concentration ought to be on behavioral modification instead of a prearranged diet. Some of the susceptible consumption behaviors in the family that should be changed could encompass missing lunch or breakfast, consuming high-fat foods, eating junk foods, taking a lot of soft drinks and fruit juice, and frequently having takeaway foods from eateries or eating out. Healthy consumption practices might encompass increased vegetables and fruits, taking food together for the whole family, taking plenty of water each day, organizing non-food rewards for performance of the children such as toys and outings, and carrying lunch to school or place of work.
In conclusion, obesity among the adult population is liable of swaying the likelihood of obesity in children due to genetic and environmental factors. Obesity signifies a great risk aspect for connected co-morbidities such as type II diabetes amid other illnesses and its growing occurrence expresses a great public medical problem. Ways that could prevent or treat obesity successfully encompass modification of dietary practices at home to ensure consumption of healthy foods and frequent physical activities.
However, with all that it is vivid that the likelihood of children becoming obese is greatly affected by parents’ obesity condition. Therefore, it is notable that precautionary measures ought to be determined to ensure that parents are involved in education the probability of their children being obese because of their obesity. Since the literature illustrates that transmission of obesity is through environmental factors such as eating behaviors, lack of exercise, and increased sedentary activities like too much of watching TV or playing video games then adults need to be taught on nutrition and exercise early in advance to find out if the levels of obesity among children consequently decreases. Involvement of the entire family in realizing an effective change for the prevention of obesity is valuable.
Research Questions, Hypothesis, and Variables with Operational Definitions
According to the problem of this study, the research question is as follows:
- In adults’ ages 20-65 diagnosed with obesity, will an educational intervention decrease the rates of obesity?
- The variables for either RQ are:
- Educational intervention
- Obesity rates
- Standard medical care
Hypothesis: Research and Null
Research by Fallah-Fini et al., (2014) states that “The energy imbalance gap (EIG) is a major factor in the development of obesity and a key target of public health interventions to reduce obesity” (p. 1230). The EIG is related to another important concept – maintenance energy gap or MEG. Both of these factors may be considered as the most important in evaluating, reducing, and preventing obesity. However, many researchers have begun to question the effectiveness of EIG because of its models that may be too simplified to accurately assess the levels of obesity and design the needed interventions.
On the other hand, improvement of the healthcare system would reduce the amount of biased and unfounded prejudices towards patients suffering from obesity (Dietz et al., 2015). The current problematic state of obesity rates is further worsened by the fact that medical professionals receive almost no necessary training to work with the obese patients.
This concludes in various misconceptions and ineffective treatment that does not solve the patient’s problem and in some cases may lead to further complications such as depression. Therefore, by improving practices that are prevailing in the healthcare system, the US government will contribute to solving the problem on many levels. Firstly, a more professional and efficient approach would be implemented to treat obese patients. Secondly, there would be a need to adjust the used practices to fight more effectively which will significantly contribute to decreasing obesity rates.
Identifying Study Variables
The dependent variables of this study are the practices that help to treat obesity. The independent variable is the obesity rate in the United States (US) and its changes across the decade.
The practices that help to treat obesity must be considered as a number of methods that is used in the healthcare system to treat obesity using specialized equipment. Obesity, in turn, is a medical condition that is characterized by the negative effect that excessive body fat has on the human health.
Obesity rate is a statistic measurement of the amount of US citizens that suffer from obesity, their race, age, and social status.
This research theory on obesity in the United States of America proposes those health beliefs together with unhealthy foods and a sedentary lifestyle as the key factors that have contributed to the increased obesity cases in the past decade. This theory proposes that unless people, especially in America change their health beliefs, fighting and preventing obesity will get harder. This proposition clearly relates to our research by highlighting the need for a change in attitude and adoption of better health beliefs that will help fight obesity in the American adult population. The theory recommends exercise as the basic factor to consider in fighting the disease as it facilitates psychological needs satisfaction. There is a schedule to be followed as prescribed for a period, which shows the progress in proportion variation.
Health Belief Model
This theory is grounded on the concept of the effect of personal belief on the health of an individual. The principal constructs of this theory are based on perceptions such as the seriousness, susceptibility, perceived benefits, as well as the perception of barriers. These health perceptions can individually or in a group determine the health behaviour of an individual.
The Obese Adults in America are also mainly affected by these constructs. Increased seriousness on the susceptibility of an individual to the likelihood of obesity can actually fasten the rate of contracting the lifestyle disease. It is believed that, an increase in belief in health belief model and theory based health education can lower the chances of increased body weight and prevalence to obesity. An assumption that physical behaviour is that proximal mediator of bodyweight is the foundation of the theory.
Application of Theory
The propositions of this research theory can be applied to the healthcare system to help the obese patients change the opinions they hold regarding the treatment and prevention of this disease. Thus, reducing the general obesity cases is as a result of an all-inclusive health care system whose treatment and prevention principles are grounded on the health belief theory. The application of the scientific approach in identifying the key health belief practices that lead to obesity and implementing alternative lifestyle and dietary options are some of the key ways in which the outcomes of this research can be applied to solve the problem of obesity in America (Rahmandad, 2014).
These theory can be applied to the study methods to establish the available options for consideration when setting up the health care system such as the maintenance energy gap (MEG) and the energy imbalance gap (EIG) which are deemed as some of the most effective ways to evaluate, reduce prevalence cases that result from the health beliefs of individuals, and even prevent future obesity cases. Having a friendly environment is recommended as it helps reduce stress and boredom among people which facilitates obesity. Also, work setting can facilitate obesity. Self-efficiency an environmental constructs have to be watched carefully in curbing overweight.
The investigation of the problem implies a specific setting. Considering the hypothesis which states that the improvement of the healthcare will contribute to the better outcomes related to obesity rates, the most common approaches used in the given sphere could be considered the main aspects of the investigation. These become a crucial element that should be included in the investigation because of the character of the research question and the obvious necessity to determine the character and impact of the approaches that are explored in the healthcare today (Fallah-Fini et al., 2014).
About 10 medical care units across the state are chosen in terms of stratified, cluster-sampling survey design. The medical care units are the clusters in the study whilst it is important to note that they were sampled from strata issued by the government. However, before engaging in the research in these hospitals, the researcher will sought for permission from the patients through administering consent forms to those willing to take part in the exercise. Some of the participants will be assigned to the intervention group. Those assigned to the intervention group will participate in duration of 3 months before their consequent assessment. Those not involved in the intervention groups will be given questionnaires.
Considering the aim of the research, it is necessary to trace the correlation between the level of the suggested services, workers competence and obesity rates. For this reason, such variables educational intervention, obesity rates and standard medical care are chosen. These are dependent and independent variables correspondingly. In other words, a set of methods that are today used in the healthcare sector along with the specific equipment becomes crucial for the research (Dietz et al., 2015). The chosen medical care units are located in different regions and are characterized by different environment. The additional training to improve the care delivery and admit its impact on population is common to all units.
As for the type of the research, it could be considered quantitative study that is focused on the investigation of a causal impact of an intervention on a target population. In the suggested study, alteration of the quality of care preconditions quantitative changes in obesity rates. For this reason, it is crucial to apply this study design to calculate basic alterations.
Extraneous variables are those that are unnecessary for the experiment and cannot be predicted in advance in the majority of cases. Unless their influence on the relationship between dependent and independent variables is neutralized or minimized, they produce an undesirable effect on the outcomes of the experiment adding error (Grove, Burns, & Gray, 2014). The research question I am going to answer in my proposed study runs as follows: In adults’ ages 20-65 diagnosed with obesity, will an educational intervention decrease the rates of obesity?
Experimenter effects: The results of the experiment may be affected by the researcher’s subjectivity (e.g. positive or negative perception of the region, hospital staff, etc.). The researcher must be able to separate his/her personal attitude from objective results to eliminate these variables.
- Demand characteristics: Hospitals that are aware of the experiment may present their statistics in a more positive light than it actually is. However, in fulfillment of the Institutional review board (IRB) requirements; the hospital management has to be informed prior to conducting the experiment.
- Participant variables: Some of obesity cases may be exposed to other diseases such as hormonal deregulations, heart conditions. Such patients must be excluded from statistics to make the picture more objective.
- Situational variables: Since all health care units are located in different regions, obesity rates may be affected by ecological, economic, social, etc. factors specific for the community. It is hard to minimize the influence of these variables but it is possible to take some of the factors (not related to health care) into consideration while comparing the statistics. Random assignment and random sampling can control extraneous variables.
Instruments: Validity and Reliability Testing
About 10 medical care units across the state have been chosen to trace the correlation between adults’ ages 20-65 diagnosed with obesity and nutrition and exercise knowledge. While choosing an appropriate instrument, the preference should be given to those than ensure higher validity and reliability. That is why this study will rely upon survey, with closed ended and scale questions. The survey reliability and validity shall however, be tested through a pilot test. To determine the construct validity, the surveys are to be issued to two groups, one that has knowledge on nutrition and exercise than the other. Fir reliability test, Cronbach’s alpha becomes r=0.7 or greater the instrument will be reliable to use for the research (Macharia et al., 2016).
Description of the Intervention
The selected health care units are located in different regions and are characterized by different environment. Yet, the additional training to improve the care delivery and admit its impact on population is common to all units. The research will be a quantitative study focusing on the investigation of a causal impact of an intervention on a target population, which is supposed to precondition quantitative changes in obesity rates. A health intervention will be administered within the course of the research by the researcher. The researcher will provide information on nutritional education to the respondents assigned to an intervention group. The intervention will take a period of 3 months and after the group will be examined if they are obese or not to know if the education interventions are effective.
Data Collection Procedures
Data collection procedures for the research are as follows:
In this particular research, stratified, cluster-sampling survey design will be adopted. The medical care units are the clusters in the study whilst it is vital to know that they were sampled from strata issued by the government. However, before engaging in the research in these hospitals, the researcher will sought for permission from the patients through administering consent forms to those willing to take part in the exercise. Through the assistance of trained health care professionals we shall seek to determine the weight of the participants and measure their height.
Consequently, these professionals will calculate sex-specific, body mass index (BMI) based on Centres for Disease Control and Prevention growth charts. Some of the participants will be assigned to the intervention group. Those assigned to the intervention group will participate in duration of 3 months before their consequent assessment through a survey will be undertaken to determine if educational intervention is effective. Those not involved in the intervention groups will be given questionnaires to fill so that the outcome would be compared with that of those in the intervention groups.
Data Analysis Plans
In the present study, the data analyses section will comprise of two components: demographic variable and the research variables analysis.
Descriptive Plan for Data Analysis for Demographic Variables
The analysis of demographic variables is targeted at comparing the demographic variables with the main variables studied in the research for identifying whether there are potential confounding relationships between the two (Alspelmeier, 2010). In order to determine whether there is an association between the demographic variable primarily age and the primary variables of interest in the present study (BMI and the success of the medical intervention), the following plan will be followed:
Conducting a series of univariate analyses, such as:
Descriptive Plan for Data Analysis for Demographic Variables
In the case of age which is the demographic variable of interest in this study, age 20-65 of those diagnosed with obesity will be analysed using central tendency such as mean, mode, median. Mean will show the weighting average of the ages of all those involved in the study. Mode on the contrary will indicate the age with the most respondents in the study while median will show the most central age in the study (Alspelmeier, 2010).
Descriptive Plan for Data Analysis for Study Variables
The main analysis of variables will test the formulated hypotheses with the use of the univariate approach. Association between the participants BMI and the success of the medical intervention implementation will be tested through Pearson’s correlations, which measures the linear relationship between two variables. The second set of data analyses will compare the changes in BMI among participants that have been exposed to three different types of interventions. For the second set, we will divide the participants in three groups, those with alterations in the quality of care, those with diet interventions, and those with exercise interventions. We will compare the BMI in those three groups using ANOVA procedures.
Overall, the presented data analysis plan will be focusing on measuring the effectiveness of healthcare and lifestyle interventions’ implementation for reducing the BMI of adults diagnosed with obesity. BMI is the key variable on which the present study will focus since it allows for a reliable and quick measurement of an individual weight status. The issue of obesity has never been as important as today (Hruby, 2015); therefore, the present study will aim to measure whether obese adults could improve their health through integrating better quality of care or lifestyle interventions into their everyday lives.
Reduction of moral inequalities and promotion of justice is one of the ethical issues. Public health is grounded on drawing attention to any social structure that has adverse effects on the health if individuals. Its interventions are rooted interventions that alter the well-being of individual’s health. Also, ensuring fair procedures and accountability is important.
Public health programs are mandated to make sure that the health of individuals is publicly made clear to everyone. Finally, minimization of burden and harm should accrue. Public health sector is obliged to minimizing risks such as stigma and opportunity cost by setting up strategies such as public closure and confidentiality protections as well as withdrawal of financial subsidies. The researcher sought to meet all these standards and therefore, they consequently sought for approval from the Research Evaluation Committee of the Department of Nutrition and Dietetics of the university that consequently approved it.
Limitations of Proposed Study
The study was faced with some challenges such ,enough data could not collected from telephone conversations as compared to face to face conversation as it is a costly method and also limited to some area and people. The information may not be accurately being presented to the researcher as it may be biased. This will lead to inaccurate data being analyzed hence wrong results. Language barrier may also be a problem to the researcher will have hard time in tapping the intended information from the source or misinterpretation may accrue. Secondly, the only information collected was in the elderly men and women (Falconer et al., 2014).. There should have been a general view of the effect of the of the disease on each age group. This has limited the researcher on the effect on middle aged hence the results lack consistency.
Also, as per the view that men are more prone to obese than women, there should have been a clear perspective way showing the experiences of men other than women. Finally, it is clear that there is lack of attention on how the interviewer characteristics influence data collection. Obesity stigma has not been viewed of its impact on data collection. There has to be a good communication flow between the interviewee and the interviewer to maintain comfort and non-judgmental approach which is essential in information collection. Since obesity stigma is a psych-social phenomenon, the interviewer has to be cautious not to prolong the interview session so as to avoid impacting stress on the interviewee as it may alter the data generated.
Implications of the Practice
Education is seen to play a greater role in constraining the effects of obesity. Educated people are seen to be less prone the disease as they adjust to all recommendations that are recommended by physicians as compared to uneducated who may be neglectors to the prescription. Also less schooled people do not adjust to dietary regulations which contributes to obesity.Research has shown that ,people schooling for long time have limited time to smoke and enjoying other luxurious life styles thus exempting them from the risk. The positive information can be attributed to having information on health measures and improved ability to handle such information as opposed to uneducated.
Alspelmeier, J. (2010). How to write methods, results, and discussion.
Altman, L. (2014). Douglas L. Coleman, 82, dies; Found a Genetic Cause of Obesity. New York Times, 12, 2429–2430.
An, R., & Xiang, X. (2016). Age–period–cohort analyses of obesity prevalence in US adults. Public Health, 141, 163-169.
Bouret, S., Levin, B. E., & Ozanne, S. E. (2015). Gene-environment interactions controlling energy and glucose homeostasis and the developmental origins of obesity. Physiological Reviews, 95(1), 47-82.
Dietz, W. H., Baur, L. A., Hall, K., Puhl, R. M., Taveras, E. M., Uauy, R., & Kopelman, P. (2015). Management of obesity: Improvement of health-care training and systems for prevention and care. The Lancet, 385(9986), 2521–2533.
Dwyer-Lindgren, L., Freedman, G., Engell, R., Fleming, T., Lim, S., Murray, C., et al. (2013). Prevalence of physical activity and obesity in US counties, 2001-2011: a road map for action. Population Health Metrics, 7-17.
Fallah-Fini, S., Rahmandad, H., Huang, T. T. K., Burens, R. M., & Glass, T. A. (2014). Modeling US adult obesity trends: A system dynamics model for estimating energy imbalance gap. American Journal of Public Health, 104(7), 1230-1239.
Falconer, C., Park, M., Croker, H., Kessel, A., Saxena, S., Viner, M., & Kinra, S. (2014). Can the relationship between ethnicity and obesity-related behaviors among school-aged children be explained by deprivation? A cross-sectional study. BMJ Open, 4, 1-10.
Foster‐Schubert, K. E., Alfano, C. M., Duggan, C. R., Xiao, L., Campbell, K. L., Kong, A., & McTiernan, A. (2012). Effect of diet and exercise, alone or combined, on weight and body composition in overweight‐to‐obese postmenopausal women. Obesity, 20(8), 1628-1638.
Geiss, L. S., Kirtland, K., Lin, J., Shrestha, S., Thompson, T., Albright, A., & Gregg, E. W. (2017). Changes in diagnosed diabetes, obesity, and physical inactivity prevalence in US counties, 2004-2012. PloS One, 12(3), 1-10.
Grove, S. K., Burns, N., & Gray, J. (2014). Understanding nursing research: Building an evidence-based practice. Amsterdam, Netherlands: Elsevier Health Sciences.
Hruby, A. (2015). The epidemiology of obesity: A big picture. Pharmacoeconomics, 33(7), 673-689.
Hruby, A., Manson, J., Lu, Q., Malik, V., Rimm, E., Qi, S., et al. (2016). Determinants and Consequences of Obesity. American Journal of Public Health, 1656-1662.
Macharia, W. M., Muteshi, C. M., Wanyonyi, S. Z., Mukaindo, A. M., Ismail, A., Ekea, H.,… Ngugi, A. K. (2016). Comparison of the prevalence and characteristics of inpatient adverse events using medical records review and incident reporting. South African Medical Journal, 106(10), 1021-1036.
Nguyen, B. T., Shuval, K., Bertmann, F., & Yaroch, A. L. (2015). The supplemental nutrition assistance program, food insecurity, dietary quality, and obesity among US adults. American Journal of Public Health, 105(7), 1453-1459.
Ogden C. L., Carroll M. D., Fryar C. D., & Flegal K. M. (2015). Prevalence of obesity among adults and youth: United States, 2011–2014. NCHS Data Brief, 219. Retrieved from http://c.ymcdn.com/sites/www.acutept.org/resource/resmgr/Critical_EdgEmail/0216-prevalence-of-obesity.pdf
Ogden, C. L., Carrol, M. D., Kit, B. K., & Flegal K. M. (2014). Prevalence of childhood and adult obesity in the United States, 2011-2012. Journal of the American Medical Association, 311(8), 806-814
Perez, L. G., Arredondo, E. M., Elder, J. P., Barquera, S., Nagle, B., & Holub, C. K. (2013). Evidence-based obesity treatment interventions for Latino adults in the US: A systematic review. American Journal of Preventive Medicine, 44(5), 550-560.
Simmonds, M., Llewellyn, A., Owen, C. G., & Woolacott, N. (2016). Predicting adult obesity from childhood obesity: A systematic review and meta‐analysis. Obesity Reviews, 17(2), 95-107.