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Is there an association between level of happiness and the risk of heart disease? Researchers studied 1739 people over a 10 year period and asked questions about their daily lives and the hassles they face. The researchers also determined which individuals in the study experienced any type of heart disease. After their analysis, they concluded that happy individuals are less likely to experience heart disease. Source: European Heart Journal \(31(9): 1065-1070,\) February \(2010 .\) (a) What type of observational study is this? Explain. (b) What is the response variable? What is the explanatory variable? (c) In the report, the researchers stated that "the research team also hasn't ruled out that a common factor like genetics could be causing both the emotions and the heart disease." Use the language introduced in this section to explain what this sentence means.

Step by step solution

01

Identify the type of observational study

Determine whether the study observes indirect associations, uses past data, or collects data over a period to monitor outcomes over time. From the description, the researchers followed 1739 people for 10 years and observed the outcomes.

02

Define the response variable and explanatory variable

Identify the response variable and explanatory variable by understanding what is being measured and what factors are being suggested to influence the measured variable. Here, the rate of experiencing heart disease is measured in relation to the level of happiness.

03

Interpret the researchers' statement regarding genetics

Understand the statement by recognizing the possibility of confounding variables in the study. Explain how genetics might be a lurking variable that could influence both happiness and the risk of heart disease.

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Key Concepts

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

explanatory variable

In an observational study, an explanatory variable is a variable that explains or influences changes in another variable. It's sometimes called an independent variable. In our exercise, researchers wanted to see how the level of happiness influences the risk of heart disease.

Happiness is the explanatory variable here because the study investigates if it has an effect on the occurrence of heart disease. Researchers collected data about the participants' happiness levels over 10 years to evaluate this relationship.

By observing happiness levels, researchers attempted to assess their impact on the subsequent health outcomes.

response variable

A response variable, or dependent variable, is the variable researchers are trying to predict or explain. It changes in response to changes in the explanatory variable.

In this observational study, the response variable is the incidence of heart disease. Researchers monitored 1739 individuals over a 10-year period to see how many developed heart disease and compared this data to their levels of daily happiness.

The rate at which participants experienced heart disease is considered the outcome influenced by the levels of happiness observed in the study.

confounding variable

A confounding variable is an outside influence that can skew the results of a study. It is something not accounted for that could affect both the explanatory and response variables, making it difficult to determine a clear relationship between the two.

In the context of our exercise, scientists mentioned genetics as a potential confounding variable. If genetics influences both an individual's happiness and their risk of heart disease, it could confuse the direct impact happiness has on heart disease incidence.

This means that without controlling for genetics, we can't be sure whether happiness or an individual's genetic makeup is more responsible for the lower rates of heart disease.

association

Association in statistical terms refers to a relationship between two variables such that changes in one variable relate to changes in the other. However, association does not equal causation which means we cannot conclude that changes in one cause changes in the other.

In the described study, the researchers concluded that there is an association between being happier and having a lower risk of heart disease.

This means that based on their observations, happier people are less likely to develop heart disease, but this study does not prove that happiness directly prevents heart disease.

Other factors, such as genetics, cannot be ruled out and may contribute to the observed relationship.