In nutritional research, meta-analysis aims to integrate results from multiple investigations on the effects of nutrients, or a food item on a particular health parameter. Studies selected for the procedure can be on a single nutrient or a combination of nutrients. In addition, meta-analysis provides statistical evidence for several other health and nutrition components, such as the following:
To identify the valuable and harmful impacts of dietary supplements in a specific sub-population. For example, whether vitamin E supplements boost performance ability in athletes. Another example is the effects of vitamin D supplementation on infants.
To correlate nutrient consumption with the reduced risks of acquiring a medical disorder. For example, several meta-analysis studies have investigated the impact of vitamins and minerals in mitigating the risks of cardiovascular disease. Another example, whether oral administration of vitamin B12 improves mood disorders such as depression.
To estimate the overall effect of dietary or meal patterns, including timings, position size, and composition, concerning a particular study outcome and identify the health outcomes of a diet rich in fructose corn syrup.
To compare the benefits between two dietary substances. For example, saturated fats vs. unsaturated fats.
To understand the impacts of nutrient deficiency on a particular age group or any other well-defined parameter.
Methods in Meta-Analysis Studies
There is no one methodology for meta-analysis studies, and researchers can choose from several variations on the nature and availability of primary research reports. Regardless of the method, every single procedure begins with the formulation of the research question. For example, what is the impact of consuming fish thrice a week on the overall well-being of pregnant women? The PICO method, which stands for population, intervention, comparison, and outcomes is a commonly employed strategy for framing the primary research question. Other components of a meta-analysis study are as follows:
Before doing a review of the literature, it is vital to define a search strategy. For example, a meta-analysis study can use aggregate data from primary research papers or use individual participant datasets. The latter has several advantages as it helps to standardize the statistical analysis process gives quality assurance and determines the cause of any variations.
The study design is a standard parameter that is filtered. For example, randomized clinical trials are often preferred due to their higher standard of research integrity.
It is vital to set the inclusion and inclusion criteria. The inclusion criteria identify the study groups in a way that will provide consistent, reliable, and objective results. Examples include the disorder or aspect of health investigated in the study, the participantsâ€™ weight and age, and treatment characteristics. The exclusion criteria are the factors that might influence or bias the population in a way, that makes them unsuitable for the study.
After data extraction and quality assurance, the statistical method is determined depending on the nature of the analysis. In choosing the variables, researchers can choose continuous or discrete measures. The two frequently used methods are the fixed effects method and the random effects method.
Heterogeneity in meta-analysis studies refers to variability or differences among the studies and study findings. There exist three types of heterogeneity, clinical, methodological, and statistical. Determining the underlying reasons for this variation is an essential component of meta-analysis.
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