Week Two discussion 2 replies. 1-2 paragraphs

Respond to at least two of your fellow students discussion posts. These responses must include a journal, news, or website article that critically reflects and pertains to the points of the initial post. You can either agree, disagree, or elaborate using these sources.

Week 2 Discussion 2

Lateshia Tubman-Armstrong (student’s name)

The epidemiology of congenital heart disease (CHD) has changed in the past 50 years because of an increase in the prevalence and survival rate of CHD (Moons et al, 2022). Mortality in patients with CHD has changed dramatically since the latter half of the twentieth century as a result of more timely diagnosis and the development of interventions for CHD that have prolonged life. As patients with CHD age, the disease burden shifts away from the heart and towards acquired cardiovascular and systemic complications. Wong (2023) tells us that the prevalence of cigarette use in the past 30 days among middle and high school students in the United States was 1.0% and 1.9%, respectively, in 2021. 

A few measures used to gain information and track heart disease are as follows:

The risk ratio compares the risk of developing heart disease between two groups. It is calculated by dividing the risk of heart disease in the exposed group by the risk in the unexposed group. A risk ratio greater than 1 indicates an increased risk, while a risk ratio less than 1 indicates a reduced risk.

The odds ratio is another measure of association that compares the odds of exposure to a risk factor in individuals with heart disease to the odds of exposure in individuals without heart disease. It is commonly used in case-control studies. An odds ratio greater than 1 indicates an increased odd, while an odds ratio less than 1 indicates a decreased odds.

The hazard ratio is often used in survival analysis, where the time to the occurrence of a heart disease event is considered. It compares the hazard (or risk) of developing heart disease in the exposed group to the hazard in the unexposed group. A hazard ratio greater than 1 indicates an increased risk, while a hazard ratio less than 1 indicates a reduced risk.

The correlation coefficient measures the strength and direction of the linear relationship between two continuous variables. In the context of heart disease research, it can be used to assess the association between variables such as blood pressure, cholesterol levels, or body mass index (BMI) and the presence or severity of heart disease.

Measurable changes in the prevalence of congenital heart disease (CHD) in the past decades are the result of evolving trends in birth prevalence and survival of patients over time.

 

References

 

Moons et al (2022). Changing epidemiology of congenital heart disease: effect on outcomes and

quality of care in adults. Retrieved from:  https://www.nature.com/articles/s41569-022-

00749-y

 

Woodcock (2020). Non-Occupational Physical Activity and Risk of Cardiovascular Disease,

Cancer and Mortality Outcomes: A Dose–Response Meta-Analysis of Large Prospective

Studies. Retreieved from: https://bjsm.bmj.com/content/early/2023/01/23/bjsports-2022-105669?s=09

 

Wong (2023). Heart Disease and Stroke Statistics—2023 Update: A Report From the American

Heart Association. Retrieved from:

https://www.ahajournals.org/doi/full/10.1161/CIR.0000000000001123

Week 2 Discussion 2

Rebecca Shelton (student’s name) 

When studying and analyzing all 3 different peer review data on Meta-Analysis of alcohol consumption and the results of said consumption, they all seem to analyze things differently, and they use different variables. I think more specifically there are a plethora of things you can look at in determining the outcomes of what alcohol can do to your body and overall health.

One study did a systematic review and a meta-analysis of 107 cohort studies. This study in particular looked at over 4.8 million participants and found that they see no significant reductions in risk of all causes for mortality for drinkers who drank less the 25G of Ethanol per day. But when they adjusted characteristics such as median age, and sex of the cohorts, they found that it actually can increase the risk of mortality if it was a woman who drank more than 25 or more grams of ethanol per day.

Now looking at another study, I found that they also used meta-analyses to track their data. But they found that when they, took non-drinkers as the reference group and used the random-effect model to recalculate the pooled relative risks and 95% CIs of different alcohol consumption levels. Cochran's Q test and the I2 statistics are the tools to evaluate the heterogeneity between studies. I2 values equal to or exceeding 50% are usually judged to represent large heterogeneity. The Egger's test in which a p < 0.1 is taken as statistical evidence of the presence of small-study effects was used to calculate the publication bias. For all tests (except for the heterogeneity and small-study effects), p < 0.05 was considered statistically significant. All calculations were conducted with Stata 16.0 (Zhong, Chen, Wang, et al, 2022).”

Moreover, while reviewing all three studies, regardless of the way they choose to analyze the data, the results where typically the same. They can make inferences, or hypothesis on this date, but due to the inconsistency in what they were running, there was no precise way verify their data 100 percent, and because of this they can only make assumptions, or possible determinations on what the outcomes may be.

Reference

Zhong, L., Chen, W., Wang, T., Zeng, Q., Lai, L., Lai, J., Lin, J., & Tang, S. (2022). Alcohol and Health Outcomes: An Umbrella Review of Meta-Analyses Base on Prospective Cohort Studies.  Frontiers in public health,  10, 859947.  https://doi.org/10.3389/fpubh.2022.859947.

Zhao, J., Stockwell, T., Naimi, T., Churchill, S., Clay, J., & Sherk, A. (2023). Association Between Daily Alcohol Intake and Risk of All-Cause Mortality: A Systematic Review and Meta-analyses.  JAMA network open,  6(3), e236185.  https://doi.org/10.1001/jamanetworkopen.2023.6185

Giovanni Corrao, Vincenzo Bagnardi, Antonella Zambon, Carlo La Vecchia. (2004).

A meta-analysis of alcohol consumption and the risk of 15 diseases, Preventive Medicine,

Volume 38, Issue 5, Pages 613-619,ISSN 0091-7435,  https://doi.org/10.1016/j.ypmed.2003.11.027.

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