setwd(“/home/leandro/Downloads/duke/TF/”)
title: “Exploring the BRFSS data” output: html_document: fig_height: 4 highlight: pygments theme: spacelab —
## Setup
### Load packages
library(ggplot2)
library(dplyr)
library(ggrepel)
library(ggpmisc)Load data
load("DATA.RData")Part 1: Data
The Behavioral Risk Factor Surveillance System (BRFSS) is the nation’s premier system of health-related telephone surveys that collect state data about U.S. residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. Established in 1984 with 15 states, BRFSS now collects data in all 50 states as well as the District of Columbia and three U.S. territories. BRFSS completes more than 400,000 adult interviews each year, making it the largest continuously conducted health survey system in the world.
Data Collection
Interviewing Procedures
In 2013, 53 states or territories used Computer-Assisted Telephone Interview (CATI) systems. The CDC supports CATI programming using the Ci3 WinCATI software package. This support includes programming the core and module questions for data collectors, providing questionnaire scripting of state-added questions for states requiring such assistance, and contracting with a Ci3 consultant to assist states. Following guidelines provided by the BRFSS, state health personnel or contractors conduct interviews. The core portion of the questionnaire lasts an average of 18 minutes. Interview time for modules and state-added questions is dependent upon the number of questions used, but generally, they add 5 to 10 minutes to the interview.
Interviewer retention is very high among states that conduct the survey in-house. The state coordinator or interviewer supervisor conduct repeated training specific to the BRFSS. Contractors typically use interviewers who have experience conducting telephone surveys, but these interviewers are given additional training on the BRFSS questionnaire and procedures before they are approved to work on BRFSS.
BRFSS protocols required evaluation of interviewer performance. In 2013, all BRFSS surveillance sites had the capability to monitor their interviewers. Interviewer-monitoring systems vary from listening to the interviewer only at an on-site location to listening to both the interviewer and respondent at remote locations. Some states also use verification callbacks in addition to direct monitoring. Contractors typically conducted systematic monitoring of each interviewer a certain amount of time each month. All states had the capability to tabulate disposition code frequencies by interviewer. These data were the primary means for quantifying interviewer performance.
States conducted telephone interviews during each calendar month; they made calls seven days per week, during both daytime and evening hours. They followed standard BRFSS procedures for rotation of calls over days of the week and time of day. Detailed information on interview response rates is available in the BRFSS 2013 Summary Data Quality Report.
Part 2: Research questions
Research quesion 1:
Which of the categorical variables from this category dataset with more correlations or associations with other categorical and discrete variables, respectively.
It was found 14 variables that have a correlation or association with more than 80 of out 330 varibles of this data set.
## [1] "grenday_" "vegeda1_" "menthlth" "sleptim1" "joinpain" "metvl21_"
## [7] "wtkg3" "children" "htm4" "X_age80" "fc60_" "maxvo2_"
## [13] "physhlth" "poorhlth"We observed that the variables associated with mental and physical health are included within this group. Both mental health and physical health are studied every day by different research groups or hospitals, and even by NGOs. It is public knowledge that food, sleep quality and physical exercise and among other variables help to increase the quality of life. Also, it is widely known that excesses in some of these items can affect the quality of life.
Therefore, we decided to identify what would be the effect of the mental and physical health of a person, who although has a healthy life in the terms of physical exercise, does not sleep well.
Research quesion 2:
Which is the probability that a person has a bad sleep and exercises a lot have physical problems or mental problems?
Based on recent studies, sleep less than 7 hours can affect health. Therefore, we classify poor quality of dreams people who sleep daily this amount of time.
We also select the variable of how many times you walk, run, play or nothing. It was considered as high when some of these activities are done 2 or more times per week.
Similarly, it was classified as poor or low mental and physical health when people spend more than 5 sick days per year
Male physhlth
## [1] 0.3333528Male menthlth
## [1] 0.3267993Female physhlth
## [1] 0.3475371Female menthlth
## [1] 0.3750462Next we calculated probabilities of people who do a lot of physical exercise and sleep very well have a mental or physical health problem.
When we compare these results with bad sleep, there is a reduction of almost half or one third part in the possibility of having a poor mental or physical health.
Male physhlth
## [1] 0.2780967Male menthlth
## [1] 0.1909537Female physhlth
## [1] 0.2629596Female menthlth
## [1] 0.2246869Research quesion 3:
According to the last result, we have tried to identify this in youngest and oldest people in this dataset. Which is the probability that a person (youngest and oldest) has a bad sleep and exercises a lot have physical problems or mental problems if this ?
For so much, we have decided to classify the jovones all those who are less than 30 years old and those who are older than 65.
What is the percentage of young and old adults who have a high estimate of oxygen consumption and high estimated functional capacity, but who sleeps badly, a lot of weight and who does not have any mental or physical health problems?
Youngest people
Male physhlth
## [1] 0.1734398Male menthlth
## [1] 0.3991292Female physhlth
## [1] 0.229255Female menthlth
## [1] 0.4730466Oldest people
Male physhlth
## [1] 0.4801013Male menthlth
## [1] 0.2221418Female physhlth
## [1] 0.4366276Female menthlth
## [1] 0.2438117After this analysis, there is evidence that indicates that sleeping poorly affects people differently, depending on whether they are young or older.
Younger people were less likely to have physical problems and more likely to have mental problems when they have poor sleep but exercise a lot. The opposite was seen in older people.
As a conclusion, sleeping poorly affects a lot even though a lot of physical exercise is done. But sleeping poorly affects the mental health of young people while this physical health is affected in the older persons.
Part 3: Exploratory data analysis
To carry out this study, the first step was to carry out an exploration of all the variales. The first question was part of the exploration phase. This phase showed us that the quality of mental and physical health was significantly correlated with many categorical variables, which led us to think that it could be an interesting starting point.
Next, we show the graphs of the physical health being significantly correlated with all the caterogoric variables. The above being just 5% of the entire exporatory phase of this study
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