Setup

Load packages

library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.5.3
library(dplyr)
## Warning: package 'dplyr' was built under R version 3.5.3

Load data

Make sure your data and R Markdown files are in the same directory. When loaded your data file will be called brfss2013. Delete this note when before you submit your work.

load("brfss2013.RData")

Part 1: Data

The Behavioral Risk Factor Surveillance System (BRFSS) is a project supported by 50 Federal States belonging to the USA, including the District of Columbia, Guam, and the Commonwealth of Puerto Rico. It is run by Population Health Surveillance Branch, under the Division of Population Health at the National Center for Chronic Disease Prevention and Health Promotion. It was framed to measure behavioral risk factors for population over 18. The BRFSS data collects information on preventive health practices and risk behaviors that are linked to chronic diseases. It includes tobacco use, HIV/AIDS knowledge and prevention, exercise, immunization, health status, healthy days - health-related quality of life, health care access, inadequate sleep, hypertension awareness, cholesterol awareness, chronic health conditions, alcohol consumption, fruits and vegetables consumption, arthritis burden, and seatbelt use. It has the following number of variables:

Part 2: Research questions

Research quesion 1: what gender predominates under veternas?

brfss2013 %>%
  group_by(sex,veteran3) %>%
  summarise(count =n())
## Warning: Factor `sex` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `veteran3` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `sex` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## # A tibble: 9 x 3
## # Groups:   sex [3]
##   sex    veteran3  count
##   <fct>  <fct>     <int>
## 1 Male   Yes       55938
## 2 Male   No       144940
## 3 Male   <NA>        435
## 4 Female Yes        5507
## 5 Female No       284642
## 6 Female <NA>        306
## 7 <NA>   Yes           1
## 8 <NA>   No            1
## 9 <NA>   <NA>          5

The graph shows that veterans smoke at least 100 cigarretes more than those who are not veterans and the table shows that there are 55938 males veterans and only 5507 females veterans

Research quesion 2: who have better general health conditions, men or women?

brfss2013 %>%
  group_by(sex,genhlth) %>%
  summarise(count =n())
## Warning: Factor `sex` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `genhlth` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## Warning: Factor `sex` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## # A tibble: 15 x 3
## # Groups:   sex [3]
##    sex    genhlth   count
##    <fct>  <fct>     <int>
##  1 Male   Excellent 35741
##  2 Male   Very good 65135
##  3 Male   Good      62998
##  4 Male   Fair      25882
##  5 Male   Poor      10713
##  6 Male   <NA>        844
##  7 Female Excellent 49740
##  8 Female Very good 93940
##  9 Female Good      87557
## 10 Female Fair      40844
## 11 Female Poor      17238
## 12 Female <NA>       1136
## 13 <NA>   Excellent     1
## 14 <NA>   Very good     1
## 15 <NA>   <NA>          5

The graph shows that the less you earn, the higher the probability to be be Diagnosed With Angina Or Coronary Heart Disease An we see that 35741 men have excellent general health whereas 49740 women have excellent general health. That means, women are better off than men and maybe that´s why they live longer

Research quesion 3:

Are those Who smoke at least 100, men or women? and who are in better health conditions based on Number Of Days Physical Health Not Good

ggplot(brfss2013, aes(x=sex, fill=smoke100)) +geom_bar(position = "fill")

brfss2013 %>%group_by(sex,physhlth) %>%
  summarise(count =n())
## Warning: Factor `sex` contains implicit NA, consider using
## `forcats::fct_explicit_na`
## # A tibble: 68 x 3
## # Groups:   sex [3]
##    sex   physhlth  count
##    <fct>    <int>  <int>
##  1 Male         0 131861
##  2 Male         1   8106
##  3 Male         2  10403
##  4 Male         3   6016
##  5 Male         4   3176
##  6 Male         5   4977
##  7 Male         6    971
##  8 Male         7   3080
##  9 Male         8    536
## 10 Male         9    130
## # ... with 58 more rows

The graph shows that males smoke at least 100 cigarrets more than females and that women are in better shape than men

In conclusion, women are better off than men.