Introduction
The article gathers and relies on information collected by the National Healthcare and Nutritional Examination Survey (NHANES). The above-mentioned program was generally of studies coded to apprise haleness and nutritional conditions of the American population. The NHANES program was launched and approved by the National Center for Healthcare Statistics research and review board which specializes in epidemiological studies and health science research (Ogden et al., 2020). This was part of research by public healthcare surveillance after the realization that a big number of the population is under the threat of obesity-related consequences. The program was narrowed down to focus on individuals of Hispanic origin in comparison to other races in American society. The anlysis will focus on the essential aspects of the article including data type, methodology, research design and hypothese for the model to give insight on the reserchers view about the topic.
Available Data
The survey involved a cross-sectional analysis of the United States civilian nutrition where people of all age groups participated with consent; for the minors, permission from their guardians was prioritized. As mentioned earlier, it is crucial to consider the source of the data, if it is reliable, and whether or not the research board has the responsibility of provision of and strictly observing guidelines for ethical research practices. This document will forcuse on analyzing the reliability of the aticle as well as the information it has gathered.
Type of Data
The article provides valuable information about the trends in obesity prevalence by race and Hispanic origin. The level of measurement of the data used in the piece is nominal, as the data is classified into different categories according to race and Hispanic origin. The above-mentioned information category is estimated to generate radical results when configuring statistical ratios and percentages in the human population. Since the method relies on establishing a relationship between variables, the correct use of correlation coefficients is key (Islam & Rizwan, 2020). At first, the survey recorded an attendance rate of approximately 80% but the response rates eventually decreased barely recording the 50% mark since the year 2000 (Ogden et al., 2020). To efficiently record captured information, it had to have specific definitions. For infants, their scale was termed as a weight for length at or above the 97.7th percentile, for the period between childhood and teenage, it was body mass index (Ogden et al., 2020). Obesity and severe fatness among adults were characterized by a body mass index above the 40 mark.
Some of the assumptions that can be made from the data used in the article include, the prevalence of plumbness is higher among people of certain races and Hispanic origins than others. From the piece of work, research indicates that young ones of age 2-5 of non-Hispanic origin had increased overweight conditions between the years 2000-2005. For children of age 6-11, obesity rates increased to 19.3% with neither of the American races being severely affected (Ogden et al., 2020). Among the mature males, the Spaniards were the only race to record high weight disorders averaging at 43% after increasing from 27.5% (Ogden et al., 2020). However, despite these records, on aggregate, it can be assumed that the prevalence of plumbness has increased over time.
There are a variety of statistics that can be calculated from the data in the article. As illustrated above, they include the percentages of people in each racial and Hispanic origin group who are obese, the prevalence of obesity in each group from 1999 to 2016, and the percentage increases in fatness in each group from 1999 to 2016. Overall, the quality of the data used in the Ogden et al., 2020 piece is quite high. The data comes from the NHANES, which is a large, nationally representative dataset. The column is careful to note that the data is subject to certain limitations such as potential misclassification and missing data. This indicates that the authors are aware of the limitations of the data, and have taken steps to ensure that the data is as accurate as possible.
Study Design
The data from the column indicates that a bio-statistical study was conducted to determine trends in bulkiness prevalence by race and Hispanic origin. The writer sought to investigate the hypothesis that racial and ethnic disparities in plumbness prevalence have increased over time. The authors used a descriptive study design to analyze the data from the NHANES survey. The study design is used to describe the characteristics of a population in terms of trends, frequencies, and correlations. The program is unique because of its strict guidelines in terms of the schedule and obligations of the research (Siedlecki, 2020). The columnist used descriptive statistics such as mean, median, and standard deviation to summarize the data and compare the results across racial and ethnic groups.
The analysist used the chi-square tests and logistic regression models to further explore the associations between stoutness prevalence and race/ethnicity. For instance, although a 2-year trend cycle was more accurate for evaluating the linear and quadratic trend, the researchers considered a change to a 4-year pole estimate to be more realistic (Ogden et al., 2020). Racial and ethical disparities in obese was the issue under observation according to information in the article. Forcusing the synopsis has its reference rase as the Spaniards, not much would have changed where the focus samples are general American population.
However, the emphatic setting of society influences the direction of the research; despite all the negativity, the survey generates rather convincing rational regarding race and obesity. In the expository configuration, quantitative methods are used when collecting quantifiable information before it is analyzed and described statistically (Mihas, 2019). Quantitative methods that showed the progress in weight matters across different age groups provide further proof that the design was applied in the survey. The ratio of length to weight among adults is relatively higher and it is practically easy to misinterpret weight for obesity. The research results managed to categorize obese and severely-obese adults with a body mass index of 30 and above or 40 and above.
Overall, the piece used a descriptive study design and descriptive and inferential statistics to investigate the trends in stoutness prevalence by race and Hispanic origin. The authors used chi-square tests and logistic regression models to test this hypothesis and found that there have been significant increases in overweight prevalence among certain racial and ethnic groups over time (Siedlecki, 2020). A statistical assessment of the survey indicates that a very little portion of the children population faced weight problems during the 1999-2018 period.
Research Statists
Considering the survey generated nominal data after a descriptive analysis, statistical variables were used in the analysis. As mentioned earlier, there was a general increase in the percentage of severe weight conditions among the American races, especially the Spaniard race which was under observation. Among Hispanics’ children below the age of 9 years faced no sloutness issues, however, from 1999 to 2018, adolescent children with cases of weight problems increased by approximately 5% to nearly 21% (Ogden et al., 2020). The surge in stoutness among teenagers was attributed to the growth of the non-Hispanic white population in the United States. Among Spaniards and whites, obesity levels increased to 43%, but among the blacks not much change was realized (Ogden et al., 2020). Americans needed to be aware of proper physical fitness and the benefits it provides. The author provides a comprehensive report about stoutness but does not recommend any initiatives regarding the issue.
Recommended Changes
The authors did an excellent job of analyzing the data and presenting the results. They used appropriate statistical methods to analyze the data. Furthermore, they discussed important limitations of the study, such as the fact that NHANES data do not include individuals who are homeless or in institutional care (Ogden et al., 2020). Overall, the authors did not make any major statistical errors in their analysis. However, there are a few areas where the authors could have made changes to improve the article.
The authors could have included more information about the differences between racial and ethnic groups in terms of other health outcomes, such as diabetes and hypertension. Finally, the authors could have included more information about potential interventions to reduce stoutness among different racial and ethnic groups. By providing information about potential interventions, the authors could have helped to provide readers with a better understanding of the steps that can be taken to reduce the prevalence of plumbness among different racial and ethnic groups. Although there are some areas where the authors could have made changes to improve the piece, there are no major statistical errors.
Use of Correct Data
Based on the information available in the column, the statistical information provided could be interpreted as credible. The description and analysis of the statistical values have been done correctly. All the necessary observations have been monitored, hence, the analysis being accurate and reliable. The data source has a justifiable background as well as a guaranteed vastness of research material and archives from which to reference its results. Besides the above-stated facts, the results generated from the study can also be computed through a different survey hence justifying the legitimacy of the information and the resulting data. As stated earlier, the author is aware of the shortcomings of his work, and as an effort towards making amends, there is a section describing their failures.
Data Resourcefuness and Efficiency
Overall, the authors had access to the correct data to answer the research question. The survey data allowed the authors to get a comprehensive picture of prevalence of heaviness among adults in the US. By comparing the prevalence of plumbness among different racial and ethnic groups, the authors were able to identify any disparities that exist in stoutness prevalence. However, there are a few issues with the data that should be noted.
The data only reflects adults aged 20 and up, which may not be representative of the entire population. The survey data is self-reported, which means there is potential for bias. Finally, the data only covers the last two decades, which may not be enough to make long-term conclusions about trends in stoutness prevalence. The article used the correct data to assess trends in obesity prevalence by race and Hispanic origin. However, there are a few limitations to the data that should be kept in mind when interpreting the findings. Despite these limitations, the data is still useful in understanding how different racial and ethnic groups fare in terms of overweight prevalence.
Statistical Accurecy
As expected of NJANES, the ultimate goal of any scientific survey is to generate radicle and reliable information as part of observing the ethical responsibility. The period of the project was relatively enough to generate reliable readings that when properly integrated with the right models would generate realistic statistical assumptions. The samples under observation were reliable in providing feedback hence the success of the survey. Most of what a researcher would be investigating is available, and the statistical terms and stipulations have been strictly utilized. The chances of the error have not been eliminated. As mentioned earlier, despite the study showing possibilities of biases, the statistical assumptions and the process of developing them are reliable hence overpowering the shortcomings.
Conclusion and Recommendations
Conclusively, the article provides reliable facts and figures in support of the argument that obesity is prevailing more among Americans with Spaniard origins. However,the author failed to capture some sections like for recomentations, readesr are left with a problem at hand withought gauidance on imminent solutions. Furthermore, other than collecting individuals reports, the survey could be more time-preserving by using the healthcare facility records on infection records that are highly related to stoutness. Cases of hypertension, type 2 diabetes, gallbladder disease, and coronary heart disease are part of the symptoms of weight issues. Collecting records from hospitals and then statistically interpreting them concerning geographical setting and age could also help to develop information regarding the matter of stoutness in the American population. During the Covid-19 infection, numerous young energetic individuals passed on overweight-related diseases (Kompaniyets et al., 2021). These support the article on a drastic increase in plumbness percentages among American citizens.
References
Islam, T. U., & Rizwan, M. (2020). Comparison of correlation measures for nominal data. Communications in Statistics-Simulation and Computation, 51(3), 698-714. Web.
Kompaniyets, L., Goodman, A. B., Belay, B., Freedman, D. S., Sucosky, M. S., Lange, S. J., Gundlapalli, V. A., Boehmer, K, T. & Blanck, H. M. (2021). Body mass index and risk for COVID-19–related hospitalization, intensive care unit admission, invasive mechanical ventilation, and death—United States, March–December 2020. Morbidity and Mortality Weekly Report, 70(10), 355. Web.
Mihas, P. (2019). Qualitative data analysis. In G. Noblit et al. (eds.), Oxford research encyclopedia of education. Web.
Ogden, C. L., Fryar, C. D., Martin, C. B., Freedman, D. S., Carroll, M. D., Gu, Q., & Hales, C. M. (2020). Trends in obesity prevalence by race and Hispanic origin—1999-2000 to 2017-2018. Jama, 324(12), 1208-1210. Web.
Siedlecki, S. L. (2020). Understanding descriptive research designs and methods. Clinical Nurse Specialist, 34(1), 8-12. Web.