91Ó°ÊÓ

Is a television (TV) in the bedroom associated with obesity? Researchers questioned 379 twelve-year old adolescents and concluded that the body mass index (BMI) of the adolescents who had a TV in their bedroom was significantly higher than the BMI of those who did not have a TV in their bedroom. Source: Christelle Delmas, Carine Platat, Brigette Schweitzer, Aline Wagner, Mohamed Oujaa, and Chantal Simon. "Association Between Television in Bedroom and Adiposity Throughout Adolescence," Obesity, \(15: 2495-2503,2007\) (a) Why is this an observational study? What type of observational study is this? (b) What is the response variable in the study? What is the explanatory variable? (c) Can you think of any lurking variables that may affect the results of the study? (d) In the report, the researchers stated, "These results remain significant after adjustment for socioeconomic status." What does this mean? (e) Can we conclude that a television in the bedroom causes a higher body mass index? Explain.

Step by step solution

01

- Identify why this is an observational study

An observational study observes individuals and measures variables of interest without influencing the response. Here, researchers only observed whether the adolescents had a TV in their bedroom and their BMI without manipulating who had a TV or not.

02

- Determine the type of observational study

This study is a cross-sectional observational study because it looks at data from a population at one specific point in time.

03

- Identify the response variable and the explanatory variable

The response variable is the Body Mass Index (BMI) of the adolescents. The explanatory variable is whether the adolescent has a TV in their bedroom.

04

- Consider potential lurking variables

Lurking variables could include factors like physical activity levels, diet, screen time from other devices, parental supervision, or genetics. These variables can influence the results independently of whether there is a TV in the bedroom.

05

- Explain the meaning of adjusting for socioeconomic status

Adjusting for socioeconomic status means that the researchers accounted for variations in BMI that might be due to differences in socioeconomic background (e.g., income, education) rather than the presence of a TV in the bedroom. This adjustment helps isolate the impact of the TV on BMI.

06

- Discuss the conclusion and causation

No, we cannot conclude that having a TV in the bedroom causes a higher BMI. The study shows an association but does not establish causation because it is observational and does not control for all possible confounding variables. Randomized controlled trials are needed to establish causation.

Unlock Step-by-Step Solutions & Ace Your Exams!

• Full Textbook Solutions

  Get detailed explanations and key concepts

• Unlimited Al creation

  Al flashcards, explanations, exams and more...

• Ads-free access

  To over 500 millions flashcards

• Money-back guarantee

  We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

Key Concepts

These are the key concepts you need to understand to accurately answer the question.

observational study

An observational study observes subjects and measures variables of interest without attempting to influence the responses. In our exercise, researchers observed whether adolescents had a TV in their bedroom and measured their Body Mass Index (BMI). They did not manipulate any conditions or assign TVs to bedrooms. This passive gathering of data without intervention makes it an observational study.

cross-sectional study

A cross-sectional study analyzes data from a population at a single point in time. It gives a snapshot of the current relationship between variables. In the example, researchers collected data at a specific moment, asking 379 twelve-year-olds if they had a TV in their bedroom and recording their BMI. There were no follow-ups or longitudinal tracking, making it a cross-sectional study.

response variable

The response variable is the outcome or the main factor we are trying to measure or explain in a study. In this example, the response variable is the Body Mass Index (BMI) of the adolescents. This is what the researchers are primarily interested in understanding and comparing between the two groups of subjects.

explanatory variable

The explanatory variable, also known as the independent variable, is what is being used to explain or predict changes in the response variable. For this study, the explanatory variable is the presence or absence of a TV in the bedroom. Researchers are looking to see if this variable could help explain the differences in BMI among the adolescents.

lurking variables

Lurking variables are hidden factors that can affect the results of a study without being explicitly measured or considered. They can confound the relationship between the explanatory and response variables. In our example, lurking variables might include:

• Physical activity levels
• Diet
• Screen time from devices other than a TV
• Parental supervision
• Genetics
These factors might influence BMI independently of whether the adolescent has a TV in their bedroom.

socioeconomic adjustment

Socioeconomic adjustment means controlling for the effects of socioeconomic factors, like income or education, to isolate the impact of the variable under study. In the TV and BMI example, researchers adjusted their results to account for socioeconomic status differences. This helps ensure that differences in BMI are more likely due to having a TV in the bedroom and not because of differing socioeconomic backgrounds.

causation vs correlation

Causation means one event is the result of the occurrence of another event, whereas correlation signifies a relationship or association between two variables without proving one causes the other. In the study, while researchers found a correlation between having a TV in the bedroom and higher BMI, this does not establish causation. Observational studies can show associations, but without experimental control and randomization, they cannot prove that one variable directly causes changes in another.