Secondary Analysis of Archived Data  

Secondary Analysis of Archived Data

The total number of obese children between five to nineteen years in the world has risen by 10% within the past forty years. According to a study by the Imperial College in London and the world health organization, by the year 2022, obesity rates are likely to be very severe. A publication of the study was brought out in the world obesity day.

To validate the study, an analysis of height and weight measurements for up to 130 million persons whose age is above five years was done. A number amounting to more than 1000 people contributed to the study whose aim was to look into how obesity has been changing between 1975 and 2016. The rate of obesity among children and adolescents in the world increased from 1 % ( 5 million girls and 6 million boys) in 1975 to 6% (50million) among girls and 8 % ( 74 million) in boys by the year 2016. Between ages 5 to 19 years, the number rose from 124 million in 1975 to 337 million in 2016.

According to a lead professor at the imperial school, obesity rates are mostly experienced among low and middle-income communities.  The high trends are due to the high prices set for nutritious foods making it hard for poor communities and families to afford. This makes them prone to illnesses such as diabetes. The professor claims that it is important to have ways that will increase availability and affordability of food among the low-income communities, both in school and at home.

Children and adolescents are said to have made a transition from being underweight to being overweight in most of the low and middle-income countries. An example is East Asia, the Caribbean and Latin American regions.

My project is about childhood obesity in low income based communities and having the trends on the obesity rates gives the world the knowledge on where it stands on obesity.

According to Centers for disease and control prevention (2014), childhood obesity has been a serious health issue which highly affects children from families who earn a low income. By collaborating with a department of agriculture in the united states, CDC make use of data found in a special nutrition program for women and children as a means to replace data in pediatric nutrition surveillance system. They use it to make surveillance on obesity among young children who come from low-income families. As at 2014, 14.5% of children whose age was between 2 and four years were obese. Obesity rates were high among Hispanic and American Indians ranging from 17.3% and 18% respectively.

The set of data by the center for disease control and prevention relates to my final project in that the project is concerned with childhood obesity in low income based communities. By making surveillance in low-income communities, the organization can know the figures they are dealing with in controlling rates of obesity. The data is valid and reliable since the figures obtained were derived from the centre for disease and control prevention which is an internationally recognized organization.

To overcome the limitation of the secondary data, it is important to define the purpose of carrying out the study. This involves being able to understand the reason behind the collection of the data, knowing the kind of data one wishes to collect (Stage, 2015). In so doing, one can stay focused, and one is hardly overwhelmed by the volume of data. For example, in this case, the data I collected involved childhood obesity in low income based communities. The reason why I carried out data collection is to be able to know the rate of prevalence of childhood obesity over the past few years.

It is also important to possess an understanding of any possible strengths and weaknesses that the dataset might possess. This involves acquiring the right time frame within which the data was collected, having a detailed description of the population being studied and having the actual figures.

One should also have a research design which will assist in analysis and collection of data. In a secondary review of data, it may involve having an outline of how one wishes their final copy to look like, having a list of data type one wishes to collect and sources of data.

Selecting a dataset and determining its integrity involves several steps. The first step involves coming up with the identification of the purposes that the data is likely to fulfil. It is important to consider the likely purpose that the data is likely to serve that goes beyond the initial use it was collected for (Whyte, 2010). It may be used for academics in teaching, and other researchers may need to use it for further publication.

The second step involves identifying data which must be kept. This should be about priorities. It is important for one to seek advice from one’s institution’s data management and support staff services on the policies associated with keeping the data.

The next step involves putting into consideration the cost that accompanies keeping the data. It is very important to consider one’s budgets and possible constraints. If one has to fund for data management services which may come up in the course of the research and funding for storage, then they may consider using the data set.

References

Whyte, A. & Wilson, A. (2010). “How to Appraise and Select Research Data for Curation”. DCC How-to Guides. Edinburgh: Digital Curation Centre. Available online: http://www.dcc.ac.uk/resources/how-guides

Media centre (2017)Tenfold increase in childhood and adolescent obesity in four decades: new study by Imperial College London and WHO retrieved from http://www.who.int/mediacentre/news/releases/2017/increase-childhood-obesity/en/

Stage, F. K., & Manning, K. (Eds.). (2015). Research in the college context: Approaches and methods. Routledge.

  1. O (2014). Centers for Disease Control and Prevention retrieved from https://www.cdc.gov/obesity/data/childhood.html

 

 

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