clean_economic_status: Economic status

In dosgillespie/hseclean: Health Survey Data Wrangling

Description

Process the data on employment and occupation.

Usage

clean_economic_status(data)

Arguments

data	Data table - the Health Survey for England dataset.

Details

The classifications considered are:

• Employed / in paid work or not.

• The NS-SEC measure, which was constructed to measure the employment relations and conditions of occupations (i.e. it classifies people based on their employment occupation). It is therefore not that good at classifying people who are not employed for various reasons.

• The NRS social grade system. This measure is the one used in the Tobacco and Alcohol Toolkit studies, but is not reported in the Health Survey for England. We create this variable by recategorising the NS-SEC 8 level variable. This is important to facilitate the link of analysis to the Toolkit Study.

• Manual vs. non-manual occupation. In the 2017 Tobacco control plan for England, there was a specific target to reduce the difference in rates of smoking between people classified with a manual or non-manual occupation. We create this variable from the 3 level NS-SEC classification by grouping Managerial and professional with intermediate occupations to give the non-manual group.

• Economic status - retired / employed / unemployed.

• Activity status for last week that adds more detail such as 'in education' and 'looking after home or family'.

Value

• employ2cat: "employed", "unemployed"

• nssec3_lab: "Managprof", "Intermediate", "Routinemanual", "Other". Social class/occupation based on the NS-SEC system. A four level variable for managerial and professional occupations, intermediate occupations and routine and manual occupations. The fourth level is 'other' that includes anyone (young/old/unemployed) who do not have an occupation.

• social_grade: "ABC1", "C2DE". 2 level social grade classification.

• man_nonman: "Manual", "Non-manual", "Other"

• activity_lstweek: "Managprof" (employed), "Intermediate" (employed), "Routinemanual" (employed), "Unemployed", "In education", "Looking after home or family", "Sickness, injury or disability", "Retired"

Examples

## Not run: 

data <- read_2016(root = "/Volumes/Shared/")

data <- clean_economic_status(data = data)


## End(Not run)

dosgillespie/hseclean documentation built on May 2, 2020, 1:15 a.m.