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Chapter 8: Problem 20

The National Health and Nutrition Examination Study (NHANES) had a random sample of 9317 participants recall their diet over the last 24 hours. The information in this sample was used in a recent study that found that, on average, \(57.9 \%\) of the calories eaten by participants were obtained from ultraprocessed foods, which include substances not used in culinary preparations such as flavors, colors, sweeteners, emulsifiers, and other additives. One of the limitations of the study reported by the authors was the dependence on the dietary recall of individuals. \({ }^{20}\) The authors were concerned with (a) response bias. (b) undercoverage. (c) overstratification.

Short Answer

Expert verified
The authors were concerned with response bias.

Step by step solution

01

Identify Key Terms

First, let's understand the meaning of the terms provided: response bias, undercoverage, and overstratification. - **Response Bias**: This occurs when participants answer questions inaccurately due to the phrasing of the question, memory errors, or the desire to give socially acceptable answers. - **Undercoverage**: This happens when some members of the population are inadequately represented in the sample. - **Overstratification**: This involves dividing the sample into too many strata, which reduces statistical power.
02

Assess the Study Context

The study utilizes dietary recall from participants, which is a self-reported method. The authors expressed concerns about the dependence on self-reported data, which might lead to inaccuracies in remembering or reporting dietary intakes.
03

Determine Relevant Bias

Given the authors' concern about the reliance on dietary recall, we need to consider which type of bias might arise from self-reported data. Recall often involves memory errors or biases towards socially desirable reporting, which is indicative of response bias.
04

Compare Terms with Study Concerns

- **Response Bias**: A high probability due to reliance on recall could lead to inaccuracies from memory error or social desirability. - **Undercoverage**: This is less relevant here since the study sample is relatively large (9317 participants) and does not mention missing segments of the population. - **Overstratification**: There is no indication that the study divides participants into too many categories, as it's a straightforward dietary recall.
05

Conclusion

The concern about reliance on dietary recall aligns primarily with the definition of response bias.

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Key Concepts

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

Understanding Undercoverage
Undercoverage is a term used in survey sampling that refers to a situation where some members or segments of the population are inadequately represented in the sample. This can lead to biased results as the sample does not reflect the true diversity or distribution of the entire population.
In the context of the NHANES study, undercoverage would mean that certain groups within the overall population might not have been included, or were underrepresented in the sample of 9317 participants.
  • If certain demographics, such as various age groups, ethnicities, or geographical regions, are missing or poorly represented, the study's findings might not be generalizable.
  • Large studies are often designed to minimize undercoverage by carefully choosing a sample that mirrors the population in important ways. This does not seem to be a primary issue for NHANES due to the size and variety of its sample.
  • However, undercoverage concerns could arise if certain lifestyle or dietary habits are only prevalent in non-sampled groups, potentially skewing the findings about ultraprocessed food consumption.
Exploring Overstratification
Overstratification occurs when the sample is divided into too many strata, or subgroups. This process is intended to ensure that various subgroups are appropriately represented, but excessive stratification can lead to practical and statistical issues.
  • When a sample is overly stratified, the complexity makes it difficult to manage and analyze effectively since each stratum must be well-represented.
  • While stratification generally improves estimates by controlling for certain variables, overstratification can diminish statistical power, making it harder to detect significant trends or differences.
  • In the NHANES study context, the researchers did not overly stratify the participant data, which focused straight on dietary recall from the entire population group rather than dividing participants into numerous subgroups based on specific characteristics.
It's crucial to find a balance between having too many and too few strata in order to maximize the reliability and accuracy of the research findings.
Grasping Dietary Recall
Dietary recall is a common method used in nutritional studies to gather information about an individual's food intake over a certain period, typically through self-reporting. Participants are often asked to recall everything they consumed over the past 24 hours or more extended periods.
  • This method relies heavily on the participants' memory and honesty, which may lead to errors or biases in the data collected.
  • Issues like underreporting or overreporting certain food types can skew results. For example, someone may forget to mention a snack or beverage or might exaggerate the portion sizes of healthier food choices to seem more health-conscious.
  • The authors of the NHANES study have noted this potential limitation, highlighting the risk of response bias鈥攚here inaccuracies stem from faulty memory or a tendency to report what's socially desirable rather than what's accurate.
To improve dietary recall, researchers often guide participants with prompts or food models and encourage them to take notes of their consumption, which can reduce errors effectively.

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Most popular questions from this chapter

Student Archaeologists. An archaeological dig turns up large numbers of pottery shards, broken stone implements, and other artifacts. Students working on the project classify each artifact and assign it a number. The counts in different categories are important for understanding the site, so the project director chooses \(2 \%\) of the artifacts at random and checks the students' work. What are the population and the sample here?

Sampling Greemville County. The rails to trails program refers to the conversion of old rail corridors into multipurpose trails for recreation and transportation. Researchers were interested in obtaining information on characteristics of users and nonusers of a 10-mile-long paved greenway trail in Greenville, South Carolina, that connects residential areas to both a university campus and the commercial downtown area of the city. Random digit dialing of residential numbers was done using a database of exchanges. A total of 2461 persons were contacted, of which 726 completed the survey. When a household was reached, surveyors asked to speak to the adult over 18 with the next birthday. No cell phone numbers were included in the sample. 23 (a) What is the population of interest? What is the response rate for the survey? (b) The following table gives the number of adults between 18 and 64 , and 65 or older in both the sample and the county (only 689 of the 726 respondents to the survey provided data on their ages). The county counts were obtained from the U.S. Census Bureau: What percent of the sample is between 18 and 64? What percent of the population is between 18 and 64? Does this difference surprise you given the sampling method described? Explain briefly. (c) Among the 726 respondents, 181 or \(24.9 \%\) reported using the trail in the last six months. Do you think this sampling method gives biased information about the percent of Greenville County adults who have used the trail in the last six month? What is the likely direction of bias? Explain briefly.

A sample of households in a community is selected at random from the telephone directory. In this community, \(4 \%\) of households have no telephone, \(10 \%\) have only cell phones, and another \(25 \%\) have unlisted telephone numbers. The sample will certainly suffer from (a) nonresponse. (b) undercoverage. (c) false responses.

Systematic random samples. Systematic random samples go through a list of the population at fixed intervals from a randomly chosen starting point. For example, a study of dating among college students chose a systematic sample of 200 single male students at a university as follows. \({ }^{33}\) Start with a list of all 9000 single male students. Because \(9000 / 200=45\), choose one of the first 45 names on the list at random and then every 45 th name after that. For example, if the first name chosen is at position 23 , the systematic sample consists of the names at positions, \(23,68,113,158\), and so on up to 8978 . (a) Choose a systematic random sample of five names from a list of 200 . If you use Table B, enter the table at line \(127 .\) (b) Like an SRS, a systematic sample gives all individuals the same chance to be chosen. Explain why this is true, then explain carefully why a systematic sample is nonetheless not an SRS.

A survey of Chicago, continued. The sample for the survey described in Exercise 8.28 included 477 non-Hispanic black adults, 304 non-Hispanic whites, and 263 Hispanics. Results for the entire sample are considered to be accurate within \(\pm 4 \%\), the margin of error for non-Hispanic blacks was \(\pm 5 \%\), and for non-Hispanic whites and Hispanics, the margin of error is \(\pm 7 \%\). (a) Why is the accuracy greater for non-Hispanic blacks than for non-Hispanic whites and Hispanics? (b) The poll details indicate For purposes of analysis, block and Hispanic respondents were oversampled. This irvolved (additional) random dialing in fandline exchanges and cell phone areas with high proportions of minority residents. What would have been true of the margin of error for blacks and Hispanics if they were not oversampled? If we want to compare the responses of different ethnic groups, explain briefly the purpose of oversampling these groups.
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