Strengths and Limitations of Secondary Data Sources

Introduction
Population health issues are the significant factors affecting or impacting a group of people based
on various characteristics, including personal characteristics such as age, sex, race, immune
status, marital status, occupation, use of drugs, and socioeconomic status. Other determinants of
health include the population’s geographical location and place of residence relevant to disease
occurrence and time variations as they influence disease processes (Gomez et al., 2021). The
population health issues often relate to the very structure of the society and expand beyond
healthcare and medical practices, including political income inequality and social and economic
state. The selected population health problem is Type II Diabetes Mellitus.
Description of the Population Health Problem
Type II Diabetes Mellitus is a chronic metabolic disease affecting how the body processes and
utilizes blood sugar (Goyal & Jialal, 2021). In Type II diabetes, the boy either resists insulin or
does not produce enough insulin. The common symptoms include frequent urination, increased
thirst, fatigue, hunger, slow healing wounds, hunger, blurred vision, or no symptoms in other
patients. In 2017, about 6.28% or 462 million people in the world were affected by type II
diabetes, with most of the population (22%) being those over 70 years (WHO, 2021).
Approximately 8.7%, or 28.7 million people of the United States population, had been diagnosed
with the condition in 2019 (CC, 2022). According to the Center for Disease Control and
Prevention, type II diabetes is the most common type as it affects 90 to 95% of the cases, with
only about 5% of cases representing type 1 (CDC, 2022). The CDC indicates that people with
other conditions, such as pancreatitis, Chasing’s syndrome, malignant neoplasm, and other

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genetic disorders, are at an increased risk of developing diabetes. Environmental factors have
also been linked to diabetes in various patients.
Identification of the Selected Data Sets
The selected data sets were retrieved from the Centers for Disease Control and Prevention
(CDC), Word Health Organization (WHO), and Walden’s Office of Research and Doctoral
Services. The data sets were retrieved after searching the databases using keywords and limiting
the publication dates to five years. The keywords used in the search include diabetes, type II
diabetes mellitus, diabetes mellitus, and age. Additionally, the journal articles used from
Walden’s Office of Research and Doctoral Services were peer-reviewed information published
in various journal databases (Walden University, LLC., 2021).
Variables in Each Data Set of Interest
The variables of interest in these data sets include the age prevalence and incidence rates of
diabetes mellitus according to age, gender, and other personal characteristics of the populations
at high risk of infection. Additionally, the data includes details about the risk factors, disease
causes, diagnostic methods and tests, comorbidities according to age, and treatment methods.
Moreover, the data set from Walden’s Office of Research and Doctoral Services includes
evidence from previous studies, including randomized controlled trials, systematic and meta-
analyses, and case controls or cohort studies. The experiment results from these studies or
findings from previous literature are essential in evaluating the effectiveness of the data
presented in the secondary data sources.
Validity of Each Data Set. Has it Been Used in Prior Studies?
Data validity refers to the measurement accuracy of the method used in the intended results.
High validity in research demonstrates the findings produced results corresponding to the real

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properties, variations, and characteristics in the physical or social world. The Center for Disease
Control and Prevention and the World Health Organization have numerous experts in various
fields and a global presence on every continent. Therefore, they have studied various patient
populations, including primary research and experimentation, to understand population dynamics
associated with disease processes and properties over time. The data sets for the identified
population health problem have been used in prior studies by professionals, professional
organizations, and government institutions for various functions, including research and
development, policy and funding, and resource mobilization.
Challenges that Might be Faced in Identifying a Proper Data Set or Securing Permission to
Use it
The challenges that might be faced in identifying or securing permission to use data sets include
data storage and fast retrieval, uncertainty in the data management landscape, and gaining
meaningful insights using extensive data analysis (Sivarajah et al., 2016). Secondly, secondary
data may fail to answer the researcher’s specific research questions or contain specific
information that the researcher would like to use in the current scenario. Secondly, identifying
the proper data sets may be challenging if the existing data sets may not have the currency
required to be used (Largan & Morris, 2019). The ethical concerns, especially in presumed
consent of study subjects, de-identification of data before release, preventing damage or distress
in the use of the data, and lack of re-identification of the participants in the outcomes of the
analysis should be observed. The selected data sets from the World Health Organization, Center
for Disease Control and Prevention, and the Office of Research and Doctoral Services were
freely and readily accessible without specific permissions.

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References

CDC. (2022). Type 2 diabetes. https://www.cdc.gov/diabetes/basics/type2.html
Gomez, C. A., Kleinman, D.V., Pronk, N., Gordon, G. L., Ochiai, E., Blakey, C., Johnson, A., &
Brewer, K. R. (2021). Addressing health equity and social determinants of health through
healthy people 2030. Journal of Public Health Management and Practice, 6, 249-257.
doi: 10.1097/PHH.0000000000001297
Goyal, R., & Jialal, I. (2021). Diabetes mellitus type 2. StatPearls Publishing.
Largan, C., & Morris, T. (2019). Qualitative secondary research: A step-by-step guide. SAGE.
Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2016). Critical analysis of big data
challenges and analytical methods. Journal of Business Research, 70, 263-286.
WHO (2021). Diabetes. https://www.who.int/news-room/fact-sheets/detail/diabetes
Walden University, LLC. (2021). Theoretical models—One Health and socioecological model
[Interactive media]. Walden University Blackboard. https://class.waldenu.edu