Wafa Aldhaleei, MD, MSc, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205
Sungmin Park, MD, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205
Background: The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to evaluate the health and nutritional status of adults in the United States. We are developing skills that allow us to access publicly available large databases that may be queried to answer fundamental questions about public health. These datasets might exist in formats unfamiliar to Stata users or in sizes that cripple ones workflow.
Methods: For Stata/BE or IC users this current program outputs an NHANES dataset with 22 pre-specified variables. We curated a dataset with all the mortality records in the United States from 1959-2017 and wrote a basic Stata script that output a two-way plot showing annual trends in number of deaths during this period. We wrote a Stata program, mortality, that allows the user to define the time-period of interest, plus other parameters such as cause-of-death, and ultimately produce a similar two-way plot with the convenience of a Stata command.
. qui do https://raw.githubusercontent.com/jhustata/book/main/nhanes-alpha.ado
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Results: We can see from the graph that poor and bad nutrition groups are associated with a higher mortality rate over time.
. use nh3andmort, clear
(NHANES 1988-1994, survey & mortality)
. di "obs: `c(N)' & vars: `c(k)'"
obs: 19599 & vars: 22
. set scheme s2color
. nhanes
This shows a flexible program for univariate logistic regression using STATA 17.
capture program drop unilogit
program define unilogit
syntax varlist [if], [outcome(string)]
quietly foreach var of varlist `varlist' {
logistic `outcome' `var' `if', nolog
lincom `var'
local sig_p: di %4.3f `r(p)'
if `sig_p' < 0.05 {
noi di "`var'" _col(15) "`sig_p'"
noi di "Significantly associated with `outcome':"
noi di "`var' (p=`sig_p')"
noi di ""
}
}
end
noi unilogit
Conclusion: Poor and bad nutrition is associated with higher mortality rates and are increasing with each decade.
References:
Acknowledgments:
We initially published our Stata output in a Jupiter-book hosted by Github. All the .html content of the book was produced in a Python environment; however, Stata .html output will gradually replace the Python-based output of the book as we truly become advanced Stata users!
VS Code terminal is our IDE choice for committing and pushing our git content to our hub and have established a seamless process for updating our publication.