compare binomial outcomes for (1) and (2) (z tests with the normal approximation or contingency tables), and conduct a t test on ages for (3).

Since 1971, the National Center for Health Statistics had been assessing the health and nutritional status of both children and adults in the United States, through periodic National Health and Nutritional Examination Survey (THANES) surveys. These surveys are an invaluable resource to epidemiological and public health research; the surveys can be used to determine the prevalence of major diseases and risk factors, to assess nutrition and health promotion, and to guide public health policy.

All initial and peer postings should be at least 250-500 words in SPA format supported by scholarly sources.

In 2012, the THANES National Youth Fitness Survey (SUNNY) was conducted in conjunction with THANES to obtain physical activity and fitness levels of U.S. youths aged 3 through 15. Initial data from the SUNNY were released in 2013 and serve as the basis for this discussion problem.

Begin by downloading the Excel file MHA610_Week 6_Discussion_SUNNY_working This workbook was created by merging two data sets from the SUNNY: the demographic variables data set, and the body measures data set. For the purposes of this discussion, many variables were eliminated from the original data sets, as well as observations with missing data on height and weight. The Excel workbook thus consists of one worksheet, with 1576 rows (the first row contains headers, and the next 1575 rows are observed values for the participants), and 11 columns of variables. The columns in the Excel file are the following:

SEWN the respondent sequence number (index for all the files)
DRAINAGE gender of the participant, 1 = male, 2 = female
RIDRETH1 race/Hispanic origin:

1 = Mexican American

2 = other Hispanic

3 = non-Hispanic white

4 = non-Hispanic black

5 = other

RIDGY age in years at time of physical exam
INDHHIN2 annual household income, categorized
INDFMIN2 annual family income, categorized
INSPIRED ratio of family income to poverty, 0 to 5
B M X W T weight, in kg
B M X H T height, in cm
SUBMIT body mass index (kg/m^2)
B M DB M I C BI category:

1 = underweight

2 = normal weight

3 = overweight

4 = obese

. = missing

More detailed descriptions of these variables are given at the data documentation web pages for the SUNNY, at and at
For purposes of this discussion, you are asked to answer the three following questions:

  • Does BI vary significantly between boys and girls?
  • Does BI vary significantly among the racial/ethnic groups?
  • Is there any trend to BI with age?
  • Comments:

There are several ways to address these questions. For example, you might take SUBMIT as your outcome variable of interest: it is continuous, so you could then perform a two-sample t test for (1), a one way analysis of variance for (2), and a simple regression analysis (with age as the predictor variable) for (3). Alternatively, you might reduce the problem to consideration of binomial probabilities: for example, you could classify everyone as obese or not obese (or maybe, overweight/obese vs underweight/normal), then compare binomial outcomes for (1) and (2) (z tests with the normal approximation or contingency tables), and conduct a t test on ages for (3).
Neither approach is wrong—the key is interpreting your findings!

If you prefer to do the analyses in Stat disk, there is a file, SUNNY_working data.cs, ready to be read into Stat disk. (It’s the original Excel workbook, saved as cs.) No need to go through any additional steps, unless you wish to restructure the data in Excel.
Incidentally, the income variables are not needed for these questions, but as a bonus, you might want to investigate whether obesity is related to socioeconomic status (as reflected by family income).

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