OVERVIEW
Each student will complete 4 case studies responding to the questions posed in the instructions. The case study provides the learner with the opportunity to analyze current epidemiological data for management, evaluate various determinants and measures of health, and to synthesize this information to make management decisions based on Christian principles.
Case studies also provide the future professional with a glimpse into the real-world application of writing briefs or actual case studies for use in management or leadership decision making. These assignments provide a framework for how niche-specific, social proofs may be used to inform decisions in health care administration. Leaders will utilize these types of case studies to determine how to best serve populations or at-risk demographics when delivering health care.
INSTRUCTIONS
Each student will individually respond to 4 case studies in the course. ·
Each case study response should be at least 250 words in length but not to exceed 2 pages of content.o
If utilized, the title page and abstract are excluded from the page limitation.o
The reference page is exclusive of the page limitation.·
All citations should be formatted in current APA style. ·
At least 2 scholarly or peer-reviewed sources are must be included in the case study response. o
While use of scripture is encouraged, the Bible does not contribute to the necessary 2 scholarly resources.·
Acceptable sources include scholarly articles published within the past 5 years, the Bible, the course text, or other epidemiological texts pertinent to the case study.
Case Study: Prospective Cohort Study Assignment
Read/Review:Chapter 14, Case Study 14.2Respond to the following question sets. Include a description of how you derived the response.
- What research question was addressed in this study, or what hypothesis was tested?
- Why are incidence rates of DM in this study reported per 1,000 person-months rather than per 100 per 1,000 women, and what does person-months mean?
- What do hazard rations in Table 14.14 indicate? Are these results statistically significant? Explain your answer.
Why in this study were the estimates of the health outcome (DM) statistically adjusted for variables such as age, maternal risk factors, neonatal outcomes, and postpartum maternal lifestyle?
Note: Your assignment will be checked for originality via the Turnitin plagiarism tool.
Note each questions has to have a response of 250 words. I didn’t realize it and my grade truly reflected it in the previous case studies. thanks
Case Study: Prospective Cohort Study Assignment
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- What research question was addressed in this study, or what hypothesis was tested?
The hypothesis that was tested for the study was whether there was a relationship between breastfeeding and the occurrence of diabetes mellitus within two years after delivery for women who had gestational diabetes mellitus during pregnancy.
Gestational diabetes mellitus affects approximately 5 to 9 percent of all pregnant women in the U.S. and is a predictive risk factor for developing diabetes mellitus after giving birth. However, there is evidence that lactation or breastfeeding is a postpartum behavior that can prevent women from developing diabetes mellitus after they give birth (Khaliq, 2020). According to Shub et al. (2019), breastfeeding helps to reduce the levels of fasting glucose during the postpartum period hence it may play a significant role in mitigating glucose intolerance among women with gestational diabetes.
The study had to be assessed using a cohort study design because according to Khaliq (2020), cohort studies examine hypotheses about the causation of specific diseases. However, since it is difficult to determine if there is a causal relationship between a risk factor and a disease, the main aim of cohort studies is to refute or reveal whether there is a statistical association between a specific disease and a specific risk factor. Just like cohort studies, the Bible also describes the cause and effect relationship. Luke 6:38 states, “Give, and it will be given to you. Good measure, pressed down, shaken together, running over, will be put into your lap. For with the measure you use it will be measured back to you” (English Standard Version Bible, 2001).
- Why are incidence rates of DM in this study reported per 1,000 person-months rather than per 100 per 1,000 women, and what does person-months mean?
In epidemiology, incidence refers to a measure that determines the frequency of occurrence of a specific disease among a specified population group. Incidence measures the risk of a specified population contracting a specific disease within a specified time period (Spronk et al., 2019). In cohort studies, incidence is calculated using the person-time estimate where the frequency of occurrence of a disease is calculated based on an actual time-at-risk that can either be days, months, or years (Khaliq, 2020). Therefore, in the case study, the incidence rates were reported using a person-time estimate instead of a person-population estimate because the cohort study was measuring incidence of diabetes mellitus among women over a specific time period (two years after giving birth). Since the time unit for measuring incidence should always be tied to the length of the study, it was more reasonable to measure incidence in person-months rather than person-years.
Person-months means that the incidence was reported according to the number of women who developed diabetes mellitus within a month. Modig et al. (2017) explain that it is important to note that incidence changes over time because it can either increase or decrease and is one of the factors that influences resource allocation for specific diseases. In the Bible, some diseases such as leprosy seemed to have high incidence. Numbers 5:2 states, “Command the people of Israel that they put out of the camp everyone who is leprous or has a discharge and everyone who is unclean through contact with the dead” (English Standard Version Bible, 2001).
- What do hazard rations in Table 14.14 indicate? Are these results statistically significant? Explain your answer.
Hazard ratios refers to the ratio estimate of the hazard rate for the treatment or experimental group versus the control group. This estimate is the probability that the event under examination will occur within the next time interval if it has not already occurred (Stensrud et al., 2018). When calculating hazard rates, the time interval is usually very short such that the rate is instantaneous. The hazard ratio is also assumed to be constant hence in a clinical trial, the ratio is an indicator of the relative likelihood that a disease will be resolved among the treatment group in comparison to the control group at a specific time (George et al., 2020).
The hazard ratios in table 14.14 illustrate that women who exclusively breastfed their children were less likely to develop diabetes mellitus as illustrated by their lower hazard ratios. On the other hand, those who mostly used formula and were inconsistent with the lactation were more likely to develop diabetes. The group that exclusively used formula served as the reference group hence the hazard ratio was 1 meaning that this was the null hypothesis value. The confidence interval values that did not contain the value 1 were statistically significant. Therefore, only the hazard ratios for mostly lactation and exclusively lactation groups were statistically significant. The hazard ratios for the mostly formula and inconsistent lactation group were not significant.
The hazard ratios illustrate that lactating reduces the risk of diabetes hence all pregnant women with gestational diabetes should be encouraged to breastfeed. Proverbs 22:3 states, “The prudent sees danger and hides himself, but the simple go on and suffer for it” (English Standard Version Bible, 2001).
- Why in this study were the estimates of the health outcome (DM) statistically adjusted for variables such as age, maternal risk factors, neonatal outcomes, and postpartum maternal lifestyle?
In the study, the estimates of the health outcomes for the mothers were adjusted according to variables such as age, neonatal outcomes, maternal risk factors, and the mother’s lifestyle because these variables also influence outcomes. According to Bellou et al. (2018), age is a significant factor associated with high risk of developing diabetes mellitus because aging impairs pancreatic function. Therefore, mothers who give birth at an older age are more likely to develop diabetes than those who do so at a younger age. Lee et al. (2018) add that maternal risk factors include sociodemographic factors, family history, and physiologic factors that may predispose the mother to developing gestational diabetes and diabetes mellitus at the post-partum period. Neonatal outcomes such as s severe health conditions for the infant may increase the risk of diabetes for the mother while postpartum maternal lifestyle can either be a protective or risk factor for diabetes. Mothers who lead healthy lifestyles after delivery are less likely to develop diabetes.
The main variable being examined in the study is breastfeeding and is association with diabetes mellitus development in the post-partum period hence adjusting for other factors isolates their effects and allows the researchers to focus only on breastfeeding. Adjusting for other variables made the findings of the study more accurate. The Bible encourages Christians to be truthful and accurate when presenting information. Acts 1:25 states, “He had been instructed in the way of the Lord. And being fervent in spirit, he spoke and taught accurately the things concerning Jesus, though he knew only the baptism of John.” (English Standard Version Bible, 2001).
References
Bellou, V., Belbasis, L., Tzoulaki, I., & Evangelou, E. (2018). Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses. PLOS ONE, 13(3), e0194127. https://doi.org/10.1371/journal.pone.0194127
English Standard Version Bible. (2001). ESV Online. https://esv.literalword.com/
George, A., Stead, T., & Ganti, L. (2020). What’s the Risk: Differentiating Risk Ratios, Odds Ratios, and Hazard Ratios? Cureus. https://doi.org/10.7759/cureus.10047
Khaliq, A. A. (2020). Managerial epidemiology. (1st ed.). Burlington, MA: Jones & Bartlett Publishers. ISBN: 9781284082173.
Lee, K., Ching, S., Ramachandran, V., Yee, A., Hoo, F., & Chia, Y. et al. (2018). Prevalence and risk factors of gestational diabetes mellitus in Asia: a systematic review and meta-analysis. BMC Pregnancy and Childbirth, 18(1). https://doi.org/10.1186/s12884-018-2131-4
Modig, K., Berglund, A., Talbäck, M., Ljung, R., & Ahlbom, A. (2017). Estimating incidence and prevalence from population registers: example from myocardial infarction. Scandinavian Journal of Public Health, 45(17), 5-13. https://doi.org/10.1177/1403494817702327
Shub, A., Miranda, M., Georgiou, H., McCarthy, E., & Lappas, M. (2019). The effect of breastfeeding on postpartum glucose tolerance and lipid profiles in women with gestational diabetes mellitus. International Breastfeeding Journal, 14(1). https://doi.org/10.1186/s13006-019-0238-5
Spronk, I., Korevaar, J., Poos, R., Davids, R., Hilderink, H., & Schellevis, F. et al. (2019). Calculating incidence rates and prevalence proportions: not as simple as it seems. BMC Public Health, 19(1). https://doi.org/10.1186/s12889-019-6820-3
Stensrud, M., Aalen, J., Aalen, O., & Valberg, M. (2018). Limitations of hazard ratios in clinical trials. European Heart Journal, 40(17), 1378-1383. https://doi.org/10.1093/eurheartj/ehy770