In order to analyze the presented data, it is imperatively important to conceptualize and internalize the above statistical terms: Sampling is defined as the process that involves selecting units from a given population that a researcher is intending to study, while confidence interval is an interval estimate in a population to be studied and is used to show the reliability of the defined sample.
In the study which was carried out in United States in 2009 amongst the children and adults to show the prevalence of Asthma, a sample of 38,815 and confidence interval of 95% was used. Asthma is a serious common chronic respiratory disorder which affects persons of all ages. This inflammatory chronic disease whose exact cause is not known is characterized by shortness of breath, wheezing, breathlessness coughing and chest pain. With the level of danger it imposes, public health professionals must always access the kind of data on prevalence to ensure that those affected get the right medication. (Centre for Disease Control 2011)
The data presented shows the results and summary of a survey dubbed the National Health Housing Survey, (NHIS) which was conducted by phone on the prevalence of Asthma in the US between 2001- 2009. In the study a total sample of 38,815 with a 95% confidence interval was used. The above sample was used because it is not possible to interview everyone within US and also helped in getting rid of the bias. The sample was randomly picked from the entire estimated geographical coverage. The sampling error which is always provided in statistics covered for any unrepresented group within the estimated study. The confidence level used shows that the researchers are 95% confident that the parameter falls within the interval. In other words the result is having 95% probability of representing the whole value.
In the given data the prevalence was defined using characteristics such as, adults by sex, race/ethnicity poverty and region. From the data, there was a significant increase in Asthma patients during 2009 to 2011 at 12.3%.Amongst children Asthma increased during the period from 8.7% to 9.6% while within the adults’ fraternity the proportional increase was from 6.9% to 7.7%.The above proportions marked an increase in prevalence amongst males from 6.3% to 7.1% while in females it was 8.3% to 9.2%.
The report further indicated that the prevalence was greater amongst children as compared to adults at 9.6% against 7.7% and was remarkably high in boys at 11.3% against 7.9% of the girls population. Amongst adults, the prevalence was noted to be high within women folk at 9.7% against 5.5% for men, the report further indicated that in the preceding one year there was a reported great attack amongst children than adults at 57.2% against 50.7 %.( Centre for Disease Control 2011)
Confidence interval is important in health studies because it identifies those values that will recur such that there is high probability that given figures within the population is likely to have a similar trend. The confidence interval gives a plausible range of values within a population because when we estimate different statistics in a population there will be a sampling variability making the entire samples to differ. In a nutshell, confidence intervals are recommended in these studies because they give concrete description in the range of values that should be used to ensure an exact data interpretation. With the sensitivity that health data brings with it, it is necessary that high level of accuracy is encouraged and therefore the application of confidence interval.
Reference
Centre for Disease Control. (2011) Vital signs: asthma prevalence, disease characteristics, and self-management education — United States, 2001–2009. Web.