Observational studies are utilized to come up with treatments when dealing with new diseases or unanswered questions about ailments that have plagued humanity. These types of studies observe and compare subjects in real-life situations.
Part of the subject population receives some type of medication or remedy, while the other acts as a control group. The end goal is to establish a cause-and-effect relationship between two variables. One factor that differentiates observational studies from controlled experiments is that they do not decide the treatment each subject uses. Below are three most common examples of the following observational study:
1. Cross-Sectional Studies
A 2003 study published in the European Journal of Clinical Nutrition wanted to determine if there was a relationship between drinking beer and obesity. A sample of 1,989 men and women from the Czech Republic were given questionnaires and a quick examination at a local clinic. The subjects were asked about their alcohol intake frequency, type and other factors. The study focused on those who drank no alcohol and those who solely drank beer and no other hard alcoholic beverages. The study concluded, while controlling for confounding variables, that drinking beer had little effect on overall body mass index (BMI) and waist-hip ratio in (WHR) in neither men nor women.
The previous is an example of a cross-sectional study: those that draw comparisons among different subject groups at a single time-point without manipulating the environment. No actual experiment takes place in cross-sectional studies. Rather data is recorded and analyzed to provide researchers information regarding a given question. Developmental psychologists, for example, use cross-sectional studies to compare reading comprehension skills of children who are all the same age, but from different socio-economical and ethnic backgrounds.
Advantages of Cross-Sectional Studies:
- Cost Effective Execution: Cross-sectional studies are advantageous in several sectors because they require no follow-up on test subjects and are thus less expensive to execute.
- True Representative Samples of Populations: Since researchers cannot completely control the testing environment, true representations of the sample populations will exist.
2. Cohort Studies
The world has known for a long time that smoking cigarettes leads to many deadly diseases, particularly lung cancer and emphysema. A 2015 study published in the New England Journal of Medicine found that smoking also increases the risk of kidney disease, intestinal disease and several other heart and lung ailments that were previously unlinked to smoking cigarettes.
The study followed five cohort groups - people who share some common characteristic. In this case the cohorts were people who had participated in previous studies that measured their smoking frequency. A total of 954,029 men and women were followed for 10 years. It was concluded that 83% of the participants who smoked died from diseases known to be caused by smoking. The study also found smokers were six times more likely to die from a rare blood disease and twice as likely to die from respiratory infections and hypertensive disease that were not previously linked to tobacco.
Advantage of Cohort Studies:
- Clarity of Temporal Sequence: Cohort studies are particularly advantageous for establishing clarity of temporal sequence, or observing otherwise disease-free people upon entrance into the study. These studies also allow researchers to establish absolute and relative risk, along with attributable proportion of a given ailment.
Disadvantages of Cohort Studies:
- Expensive Execution: The biggest disadvantage of cohort studies is the need for very large subject population and thus high costs. Unreliable: Prospective (forward-looking) cohort studies are unreliable for rare disease and those with long latency periods. Additionally, retrospective (backward-looking) cohort studies cannot account for confounding variables since the data has already been recorded and can no longer be measured.
3. Ecological Studies
Dr. John Snow of York, England, is generally regarded as the first researcher to use an ecological study to answer a health-related question. A cholera outbreak in London in 1831 got the young physician interested in the cause of the disease. He did not believe the miasmas theory - that cholera was caused by toxic gases emitted from sewer, swamps and graves.
Another outbreak struck London in 1848 and Dr. Snow pinpointed the first subject case. The man had arrived in London from Germany via merchant ship. He and another man rented the same London hotel room and died of cholera within days. Most physicians at the time rejected the idea that living organisms (germs) caused disease. Dr. Snow discovered that people living on the same side of London streets, where waste water came in contact with their drinking water, were in contact with the disease most often.
He gathered data from various government resources on where large outbreaks of cholera happened. He eventually convinced city officials to shut down a particular water pump in a town of Soho that many residents drank from because he determined the water was contaminated. Cholera cases slowly tricked to a halt thereafter in the town.
Advantages of Ecological Studies:
- Ease of Disease Outbreak Research: All ecological studies measure at least one area in a given group base on geographic location or a given time period. These studies are particularly useful in areas where disease is rampant among the locals.
- Hypothesis Testing: Since existing data sets are used, ecological studies are advantageous for quickly testing a hypothesis.
Disadvantages of Ecological Studies:
- Ecological Fallacies: Inferring results on individuals with different levels of exposure based on group data is one of the major drawbacks. Regardless, ecological studies provide solid foundations for investigating various medical issues so long as the limitations are taking in consideration by the respective researchers.
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