Introduction
Childhood obesity has reached an alarming level in both developed and developing nations. Childhood obesity and overweight issues have been shown to have a negative influence on both physical health and mental well-being. Overweight and obese children have higher chances of remaining overweight as adults and acquiring noncommunicable illnesses such as diabetes and cardiovascular problems at an earlier age. Obesity progression is not completely understood, and it is thought to be an illness with several roots. External conditions, lifestyle choices, and cultural context all play important roles in the global obesity epidemic. The studies that will be discussed further will illuminate the most essential factors of childhood obesity and provide recommendations.
Research Design
The first study under discussion is the study conducted by Fenin et al. (2021). An RCT was conducted in a pediatric hospital under the supervision of pediatricians and researchers. The RCT focused on early screening for obesity and the implementation of USPSTF standards. Fenin et al. (2021) experimented to determine whether doctors are following the USPSTF standards that are universally recommended for doctors. The study’s design is considered quasi-experimental, as the authors included the results of a survey of physicians in the conclusions of the study.
Another study, by Ward et al. (2017), stated that earlier research employed statistical approaches to anticipate the population-level predominance of obesity rates in the U.S., but they did not use individual-level longitudinal data. To address these problems, the scientists discovered a method for simulating individual-level height /weight patterns throughout a lifetime while controlling pattern changes. To examine the influence of a child’s present weight on the likelihood of adult obesity, Ward et al. (2017) modeled such patterns from childhood to the age of 35 years, during which the potential dangers of obesity are well-documented.
The study by Umer et al. (2017) stated that earlier observational studies on the association between childhood obesity and adult CVD produced contradictory findings. Their analysis aimed to bridge that gap using a cumulative data meta-analytic framework. The researchers reviewed previous studies that met certain criteria, such as being longitudinal or cohort studies that were published no earlier than 2015, and included various measures.
Two final studies, Burns et al. (2011) and Kumanyika et al. (2010) are part of a series of publications dedicated to the observation of childhood obesity. According to both parties, the literature in the field of such a topic lacks evidence-based obesity prevention strategies. As a result, Burns et al. (2011) and Kumanyika et al. (2010), in their works, expand the notion of childhood obesity and include innovative methods of using conventional or existing data. These studies include reviews of newly produced evidence, implementation, and effects of obesity prevention policies and programs.
Data Collection Methods
As for data collection methods, Fenin et al.’s (2021) research is eminently practice-oriented and includes observations of focus groups. From December 2018 to January 2019, pre-intervention record assessments were performed on 60 randomly chosen children ages 6 to 16 years at a pediatric medical center based in Atlanta, Georgia, to identify screening protocols for this age cohort. An education program based on the USPSTF’s suggested guidelines and findings of the preliminary clinical examination was carried out. A post-intervention record review was performed on participants between April and May 2019 to examine if the program resulted in a change and improvement.
In turn, Ward et al. (2017) combined five representative samples of U.S. large datasets with multiple measurements of individual-level height and weight. The aggregated set of data comprised 176,720 samples from 41,567 adults and children after excluding individuals with fewer than two recorded observations. The researchers used this data to create a simulation model that predicts development trajectories based on individual-level weight and height statistics.
Umer et al. (2017) also carried out observational research. Their investigation was carried out and published following the Cochrane Collaboration’s principles and criteria for conducting observational systematic reviews and meta-analyses. Three internet databases, along with citation monitoring, were used to discover studies. Random-effect models were used to generate pooled effect estimates, and the STROBE tool was used to weigh the risk of bias. Random-effects meta-regression was also used to try to uncover causes of variability.
Lastly, Burns et al. (2011) and Kumanyika et al. (2010) performed a theoretical analysis of the data and included documents and records to corroborate their statements. Burns et al. (2011) used one chart, 15 tables, 17 frameworks, and two graphs, whereas Kumanyika et al. (2010) used two charts, two tables, and three graphs to organize the data they found. Additionally, Burns et al. (2011) collected the data from 59 sources, while Kumanyika et al. (2010) used 58 sources. As a result, researchers urged that more user-friendly studies be written so that people may understand the disease and learn about obesity prevention.
Findings
Given the present prevalence of overweight, the models of Ward et al. (2017) anticipated that the vast majority of children (57.3 percent) will struggle with obesity by the age of 35, with almost 50% of the anticipated prevalence occurring during adolescence. The possibility that a child with extreme obesity will not be obese at age 35 dropped from 21% at the age of 2 years to 6.1% at the age of 19. According to the simulation model of Ward et al. (2017), childhood obesity will remain a serious public health issue in the U.S. Obesity in childhood predicts overweight in adulthood, particularly in obese children.
Additionally, according to the findings of Umer et al. (2017), childhood obesity could be a contributing factor to adult cardiovascular disease risk variables. A total of 23 papers were systematically reviewed and 21 were included in the meta-analysis of the 4840 references analyzed. Childhood obesity was found to be strongly and strongly linked with adult spontaneous bacterial peritonitis, as well as substantially and inversely correlated with adult HDL. Before any conclusive findings can be drawn, though, more, higher-quality studies that include crude and unadjusted variables such as BMI are required.
Fenin et al. (2021) discovered a notable increase in screening rates from pre-intervention to post-intervention, from 36.7% to 91.7%, respectively. As a result, the researchers found that educating children and adolescents about USPSTF guidelines for obesity screening enhanced screening rates in a pediatric medical center. Consequently, Fenin et al.’s (2021) approach to screening and educational intervention proved to be beneficial in increasing the rate of preventing and treating the disease.
In turn, Burns et al. (2011) and Kumanyika et al. (2010) in their findings provide recommendations and preventive measures. The researchers assert that environmental variables can have a significant impact on children’s well-being and risk of obesity in their first years of life, as patterns of eating, activity level, and sleep are established. Approximately 17% of children and adolescents aged 2 to 19 have obesity, while nearly 32% struggle with overweight health issues. Such data shows an epidemic that creates significant issues for policymakers, public health experts, and other key figures. For a long time, public health officials have advocated for strong action to combat this pandemic, and their requests have grown more urgent in recent years. Their concern stems from the severe health consequences of obesity and being overweight, including possible negative impacts on well-being and longevity.
Hence, five studies focused on illuminating childhood obesity, its effect on children, and preventive measures. Five studies included both quantitative and qualitative data to provide the most objective information. Moreover, four of the studies were focused on research reviews, while only one study by Fenin et al. (2021) focused on data analysis and also included participant observation. Consequently, two of the studies, those by Ward et al. (2017) and Umer et al. (2017), provided a prognosis for the development of childhood obesity and its roots. Meanwhile, Burns et al. (2011) and Kumanyika et al. (2010) provided recommendations and policy advancements for this issue.
References
Burns, A., Parker, L., & Birch, L. L. (Eds.). (2011). Early childhood obesity prevention policies. National Academies Press.
Fenin I.A., Norris, C.L., Barnby, E., & Hammock, M.B. (2021). Adoption of clinical guidelines to improve childhood obesity screening. Pediatric Nursing, 47(3), 114-123.
Kumanyika, S. K., Parker, L., & Sim, L. J. (Eds.). (2010). Bridging the evidence gap in obesity prevention: A framework to inform decision making. Institute of Medicine.
Umer, A., Kelley, G. A., Cottrell, L. E., Giacobbi, P., Innes, K. E., & Lilly, C. L. (2017). Childhood obesity and adult cardiovascular disease risk factors: A systematic review with meta-analysis. BMC Public Health, 17(1). Web.
Ward, Z. J., Long, M. W., Resch, S. C., Giles, C. M., Cradock, A. L., & Gortmaker, S. L. (2017). Simulation of growth trajectories of childhood obesity into adulthood. New England Journal of Medicine, 377(22), 2145–2153. Web.