National Health Interview Survey
The National Center for Health Statistics has different data collection systems, such as the National Health Interview Survey (NHIS), which has been monitoring the health of the nation annually since 1957 (Centers for Disease Control and Prevention, 2018). NHIS offers data on different parameters such as family, household, injuries and poisoning episodes, a person, sample child, sample adult, imputed income files, and family disability. Under each category, different information is gathered. For instance, under the data file named “family” recorded demographic and general health information. Similarly, under the “sample adult” and “sample child”, health behavior, risk behavior, and health condition data is recorded (Martinez, Galinsky, & Clarke, 2015). The NHIS core data focuses on health conditions, health care access, and utilization, health behaviors and risk factors, and socio-demographic characteristics (Martinez et al., 2015). This data is in line with the role of epidemiology, which is to give insights into the changes that occur in health care problems presenting in a given community (Gordis, 2014).
specifically for you
for only $16.05 $11/page
The data captured under NHIS has evolved, and it changes from time to time to address new topics, meet departmental goals, or highlight more details on core topics (Martinez et al., 2015). For instance, in 1963, the core topics included person, condition, hospital, household, family, and health expenditures. However, in 1964, the core topics on household and health expenditures were replaced by X-ray. Similarly, in 2015, data on imputed income was collected, but it was missing in 2016 and 2017 records. In addition, the number of participants used for the surveys differs from year to year. For example, in 2016, the number of participants was more as compared to 2017. In 2016, 33,028 sample adults were interviewed, but that number dropped to 26,742 in 2017. The same trend was followed in all other core topics (Centers for Disease Control and Prevention, 2018).
Health Problem in Delaware
The health problem chosen for this task is substance use and abuse in Delaware. According to the available data, drug use and abuse vary between state counties (The University of Delaware Center for Drug and Alcohol Studies & State Partners, 2016). The commonly used drugs include marijuana, alcohol, and cigarettes. The focus will be on excessive alcohol consumption.
Substance use varies by age, race, and sex. For instance, 20.7 percent of male binge drink as opposed to 13.7 percent of females (Delaware Health Tracker, 2018). The disparity is also reflected in age. While 30.9 percent of young adults between the ages of 18 and 24 binge drink, only 28.1 percent, 16.9 percent, and16.5 percent of their counterparts in age brackets of 25-34, 35-44, and 25-54 respectively engage in the habit (Delaware Health Tracker, 2018). Racially, 18.5 percent of whites and non-Hispanics binge drink as compared to 13.8 percent and 12.9 percent of Hispanics and blacks/non-Hispanics respectively (Delaware Health Tracker, 2018).
Some of the possible explanations of why young adults are likely to drink more than their counterparts in other age groups include peer pressure and self-presentational reasons, such as attractiveness or advanced status (Vincke & Vyncke, 2017). This assertion explains why binge drinking rates decrease as individuals grow older with only 11.3 percent of adults aged between 55 and 64 years engaged in the habit. In terms of gender, Wilsnack, Wilsnack, and Kantor (2014) note that alcohol consumption plays an important social role in men as opposed to women. Additionally, women who quit drinking after becoming pregnant may not resume binge drinking after childbirth. In terms of race, Klima, Skinner, Haggerty, Crutchfield, and Catalano (2014) established that young white adults are more likely to binge drink as compared to their black counterparts due to religiosity, ethnic identity, and delinquency.
The Objective of the Study
This study sought to establish the relationship between spousal smoking status and the probability of quitting smoking among adults in the United States (US). Additionally, the researchers wanted to determine whether the effect of spousal smoking status on quitting differs by sex in 4,500 spouse pairs over 9 years of follow-up in the Atherosclerosis Risk in Communities (ARIC) Study cohort” (Cobb et al., 2014, p. 1183).
The Study Design
A population-based cohort study design was used for this research work.
100% original paper
on any topic
done in as little as
Advantages and Disadvantages of the Study Design
One of the advantages of the cohort study design is that it allows the calculation of incidence of disease in the exposure group. Additionally, selection bias is avoided during the enrollment of participants. On the other hand, this study design has the disadvantage of having to follow large numbers of participants for a long time.
Selection of Participants
Probability sampling was used to identify households for the study. The researchers then visited the selected households to establish eligibility. For participants to be included in the study were required to be married and at least one of them to have smoked in the past or a smoker at that time.
The authors hypothesized that individuals married to smokers are less likely to quit smoking. The measure of association is estimated to include physiological and social factors that influence smoking.
The researchers concluded that individuals married to a smoker are less likely to quit smoking as compared to their counterparts married to non-smokers. Women married to former smokers were more likely to quit the habit as compared to their counterparts married to never smokers.
Limitations of the Study
I agree with the authors that restricting the definition of marriage to heterosexual partners was a limitation of the study.
Cobb, L. K., McAdams-DeMarco, M. A., Huxley, R. R., Woodward, M., Koton, S., Coresh, J., & Anderson, C. A. M (2014). The association of spousal smoking status with the ability to quit smoking: The atherosclerosis risk in communities study. American Journal of Epidemiology, 179(10), 1182-1187.
Delaware Health Tracker. (2018). Disparities dashboard. Web.
Gordis, L. (2014). Epidemiology (5th ed.). Philadelphia, PA: Elsevier.
Klima, T., Skinner, M. L., Haggerty, K. P., Crutchfield, R. D., & Catalano, R. F. (2014). Exploring heavy drinking patterns among black and white young adults. Journal of Studies on Alcohol and Drugs, 75(5), 839-849.
Martinez, M. E., Galinsky, A. M., & Clarke, T. C. (2015). The National Health Interview Survey (NHIS): An overview of survey design, data access, and applications to public health. Web.
The University of Delaware Center for Drug and Alcohol Studies & State Partners.
(2016). 2016 community profile for Delaware: Data by sub-state planning area. Web.
Vincke, E., & Vyncke, P. (2017). Does alcohol catch the eye? Investigating young adults’ attention to alcohol consumption. Evolutionary Psychology, 15(3), 1-13. Web.
Wilsnack, S. C., Wilsnack, R. W., & Kantor, L. W. (2014). Focus on women and the costs of alcohol use. Alcohol Research, 35(2), 219-228.
100% original paper
written from scratch
specifically for you?