Strengths and Limitations of Secondary Data Sources
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Asthma as a population health problem
Introduction
Secondary data have been collected intentionally by another researcher for a research project other than the current research. Such sources are helpful because they assist the researcher in obtaining ready-made data that the researcher can use to offer recommendations without struggling to gather primary data (Stewart et al., 2021). In this paper, we will get a brief identification of asthma as a population health problem, three data sets used to describe the population and magnitude of asthma, the variables in each of these data sets, their validity, and the challenges a researcher might encounter while identifying proper data sets.
Identification of population health problem
Asthma is a chronic respiratory disease where one experiences episodes of reversible airway obstruction, increased sensitivity of the smooth muscles of the bronchi to various stimuli, and inflammation. It is seen in all age groups, but most health concerns stem from pediatric cases of the condition. For asthma, there is a reduction in quality of life, increased use of health care services, significant financial costs in terms of medical care, and loss of productivity. This is because its occurrence is occasioned by environmental factors, genetic makeup, and social or demographic factors, to mention but a few.
Selected data sets
The three selected data sets include the National Health Interview Survey (NHIS), The Behavioral Risk Factor Surveillance System (BRFSS), and the National Environmental Public Health Tracking Network. The National Health Interview Survey is one of the significant sources of health information about the United States of America population, and it is conducted by the Centers for Disease Control and Prevention every year. It has acquired extensive information on various health categories by conducting personable household interviews and provides broader information concerning asthmatic occurrences, risk factors, and ethnicity (Frey et al., 2023).
The BRFSS, or the Behavioral Risk Factor Surveillance System, is the most extensive longitudinal health surveying system on the earth; it contacts respondents over the telephone. Operated by the CDC, this examines population health behaviors, chronic diseases, and preventive practices at a state level, greatly helpful in establishing regions of asthma occurrence and correlated behaviors (Osei et al., 2019). The National Environmental and Public Health Tracking Network connects data from environmental and health-related systems with a focus on services to understand how the environment affects the public’s health. They pertain to ecological factors that can precipitate asthma and the epidemiological information on air quality, which is crucial for planning actions to control exposure to asthma triggers.
The variables in data sets
Certain variables useful from each dataset are required to compare and analyze the impact of asthma and its factors. For asthma diagnosis status, age, sex, race/ethnicity, income and education level, healthcare accessibility, and presence of any existing co-morbidity, the NHIS contains relevant data (Frey et al., 2023). Demographic and social variables used here assist in studying the patterns of asthma and how it is controlled. The BRFSS offers various questions on asthma, smoking, physical activity, BMI, availability of health care, and socio-demographics, including age, sex/revenue, and education. These enable the measurement of the likelihood of displaying certain behavioral risk factors and how these are related to asthma (Osei et al., 2019). The NENVHT was able to provide variables on air quality indices (for example, levels of PM2. 5 and ozone), location, and time trends on air quality. These environmental variables can be connected to asthma prevalence. They can assist in explaining the effects of the environment on asthma severity and occurrences, allowing for the formulation of tailored public health interventions that seek to reduce these risks.
The validity of each data set
The NHIS is widely acknowledged as a highly valid data collection instrument since it incorporates several measures into its datasets and covers a vast scope of health-related topics. It has been used in many peer-reviewed papers to examine diverse health states, such as asthma, and has offered accurate and nationally representative data (Frey et al., 2023). Another important aspect is that the BRFSS is somewhat valid and reliable, using a large, random sample to gather information on behavior and chronic illnesses. The MPRS has been used in many publications and public health reports, making it a valid source of data on the prevalence of asthma and associated risk factors. The National Environmental Public Health Tracking Network, although relatively younger, has proved its worth due to the diverse and high-quality data sources included. It has also been used in research on the relationship between environmental factors and health effects, respiratory diseases, asthma, etc. The preponderance of these data sets in previous studies supports the validity and reliability of such data sets in public health research.
Challenges a researcher might face in identifying proper data sets
One of the challenges that a researcher may encounter is locating a proper data set for the study or gaining permission to use the suitable data set. It might be hard to determine the validity and accuracy of the data set collected about the aspects of the research question being addressed, which involves reviewing the various variables and the sample size and coverage of the population. Further, accessing the data may require a lot of paperwork, formalities, and IRB approvals. In the case of reviewing data that includes health information of the patients, it is an even more tedious process. Acquisitions typically involve signing elaborate data usage consent, compliance with the privacy rules, and, sometimes, high data access costs (Portier, 2011). Also, there could be issues of data compatibility and integration, thus posing a technical challenge in the analytical skills and resources necessary for integration. Researchers must also pay attention to possible methodological biases and constraints in the data sources, including self-report measures and samples, which can be selected in a limited and non-probabilistic manner that may affect the validity and applicability of the results obtained.
References
Frey, S. M., Rowe, R. K., & Halterman, J. S. (2023). The prevalence of childhood asthma: interpreting falling rates in the context of shifting measurement and the COVID-19 pandemic. Current opinion in pulmonary medicine, 29(3), 197–201. https://doi.org/10.1097/MCP.0000000000000959
Osei, A. D., Mirbolouk, M., Orimoloye, O. A., Dzaye, O., Uddin, S. M. I., Dardari, Z. A., DeFilippis, A. P., Bhatnagar, A., & Blaha, M. J. (2019). The association between e-cigarette use and asthma among never combustible cigarette smokers: behavioral risk factor surveillance system (BRFSS) 2016 & 2017. BMC pulmonary medicine, 19(1), 180. https://doi.org/10.1186/s12890-019-0950-3
Portier C. J. (2011). Comprehensive environmental public health. Public health reports (Washington, D.C. : 1974), 126 Suppl 1(Suppl 1), 3–6. https://doi.org/10.1177/00333549111260S102
Stewart, J., Kee, F., & Hart, N. (2021). Using routinely collected primary care records to identify and investigate severe asthma: a scoping review. NPJ primary care respiratory medicine, 31(1), 1. https://doi.org/10.1038/s41533-020-00213-9
TO PREPARE
Consider a variety of population health problems and then select one of professional interest on which to focus for this Assignment.
Explore three data sources (data sets) presented in the Learning Resources that could aid you in describing the population and magnitude of the problem you selected. Consider the strengths and limitations of each data source.
THE ASSIGNMENT
In 3–4 pages (not including title page and references), analyze the data sources you selected by addressing the following:
Briefly identify the population health problem you selected.
Identify each data set you selected.
Identify the variables in each data set you would need to examine the association of interest.
Assess the validity of each data set. Has it been used for prior studies/publications?
Explain challenges you might face as a researcher in identifying a proper data set or securing permission to use it.
Strengths and Limitations of Secondary Data Sources Essay
