Week 8 Assignment: Meta-Analyses
Introduction
Meta-analyses is a broadly used methodology that combines results from two or more independent studies to determine overall trends (Friis & Sellers, 2021). In this assignment, the selected article is titled “Risk factors for gestational diabetes: An umbrella review of meta-analyses of observational studies” by Giannakou et al. (2019). The article uses meta-analyses to examine the risk factors of gestational diabetes. The authors argue that gestational diabetes mellitus (GDM) is highly prevalent globally, and its prevalence is projected to continue increasing, given the rise in the number of overweight people and obese pregnant women.
Characteristics of Meta-Analysis
Giannakou et al.’s (2019) study comprises unique characteristics of a meta-analyses methodology. First, the meta-analysis includes observational studies that explore the risk factors for gestational diabetes. This inclusion criteria is specific, with the researchers considering only the observational studies that examine the risk factors of gestational diabetes. Second, the meta-analyses uses statistical methods to allow researchers to analyze data across multiple studies. Thus, the end product of this study is a quantitative review of multiple observational studies. Third, Giannakou et al.’s (2019) meta-analyses is highly objective and synthesize findings from multiple meta-analyses of observational studies that examine the risk factors for GDM. In addition, the meta-analyses clearly state the study’s population, intervention, comparison, and specific outcome. The target population is pregnant women with obesity; the intervention is diet and lifestyle modifications; comparison is no diet and lifestyle changes; and the outcome is a reduction of instances of gestational diabetes. These are the key attributes that make Giannakou et al.’ (2019) study a meta-analyses.
Inclusion and Exclusion Criteria
The meta-analyses clearly state the inclusion and exclusion criteria. The authors searched ISI Web of Science and PubMed to select the relevant articles. Only articles published from inception to December 2018 were included. This helped Giannakou and others to accurately identify meta-analyses exploring the relationship between known risk factors for GDM. In each identified meta-analyses, the authors estimated the summary effect size, the 95% prediction interval and confidence interval, evidence of small-study impacts, and evidence of excess-significance bias and between-study heterogeneity. I agree with the approach used by the researchers, for they employed a comprehensive search strategy, used approved nursing databases, and emphasized validity and reliability (Friis & Sellers, 2021). Also, the researchers clearly address potential biases and confounders, highlighting their commitment to limiting methodological limitations and improving the quality and reliability of the study findings.
Evaluation of Conclusions
Giannakou et al.’s (2019) meta-analyses reviewed 62 studies and identified 61 key risk factors for GDM. Out of these, the authors identified and examined four risk factors that had strong epidemiological evidence and credibility about BMI and hypothyroidism. The researchers concluded that during pregnancy, diet and lifestyle changes should be assessed in large and controlled randomized trials. The study concludes that in pregnancy, women with history of thyroid conditions or known obese conditions should be given earlier screening for GDM (Zehravi et al., 2021). This conclusion is significant, insightful, relevant, and reliable in promoting quality care and improving patient outcomes. To synthesize evidence, it is important to comprehensively identify risk factors for diabetes mellitus in pregnant women. This helps recommend and apply evidence-based interventions for prevention and control (Friis & Sellers, 2021). Besides, the conclusions emphasize the need to strengthen the validity and reliability of study findings. Therefore, early screening for GDM in pregnancy supports targeted treatment interventions and quality care outcomes for both mothers and infants.
Applying Study Implications to Nursing Practice
There are various ways that I would apply the implications of Giannakou et al.’s (2019) study to nursing practice. First, I would implement this evidence-based strategy by collaborating with endocrinologists and obstetricians to create early screening protocols in high-risk populations (Lewandowska et al., 2020). This will enable pregnant women get appropriate interventions and monitoring. Also, I would educate pregnant women on diet and lifestyle modifications, including regular physical activity, balanced diet, and weight management. Group counseling sessions will empower pregnant women to make informed health decisions that optimize maternal health and fetal outcomes (Friis & Sellers, 2021). In addition, I would embrace patient-centered care through holistic patient assessments, collaboration with other nurses, and constant communication with pregnant women to create an individualized care plan that effectively addresses the specific risk factors while promoting the patient’s overall health and well-being.
Conclusion
In epidemiological research, researchers have conducted meta-analyses on different population health topics, including obesity, heart disease, diabetes, and other cardiovascular conditions. This paper has examined Giannakou et al.’s (2019) meta-analyses and identified the use of observational studies, statistical or quantitative methods, synthesis of findings, and evidence of PICO as the characteristics that justify the study to be a meta-analysis methodology. The inclusion criteria of the meta-analyses included peer-reviewed articles published in ISI Web of Science and PubMed between the start to December 2018. The meta-analyses concludes that during pregnancy, diet and lifestyle changes should be assessed in large randomized trials.
References
Friis, R. H., & Sellers, T. A. (2021). Epidemiology for public health practice (6th Ed.). Jones & Bartlett.
Giannakou, K., Evangelou, E., Yiallouros, P., Christophi, C. A., Middleton, N., Papatheodorou, E., & Papatheodorou, S. I. (2019). Risk factors for gestational diabetes: An umbrella review of meta-analyses of observational studies. PloS one, 14(4), e0215372. https://doi.org/10.1371%2Fjournal.pone.0215372
Lewandowska, M., Wieckowska, B., & Sajdak, S. (2020). Pre-pregnancy obesity, excessive gestational weight gain, and the risk of pregnancy-induced hypertension and gestational diabetes mellitus. Journal of Clinical Medicine, 9(6), 1980. https://doi.org/10.3390/jcm9061980
Zehravi, M., Maqbool, M., & Ara, I. (2021). Correlation between obesity, gestational diabetes mellitus, and pregnancy outcomes: an overview. International Journal of AdolescentMedicine and Health, 33(6), 339-345. https://doi.org/10.1515/ijamh-2021-0058