# Categorizing individual Census Codes into NHIS Detailed Categories as described here: National Center for Health Statistics. # Dataset documentation 2018. Document Version Date: 25 July 2022. National Health Interview Survey (NHIS). # Available from: # https://ftp.cdc.gov/pub/health_Statistics/NCHs/Dataset_Documentation/NHIS/2021/Adult-codebook.pdf # See Industry Appendix page 623, and Occupation Appendix page 626.; # Please note: # NHIS 2018 INDUSTRY AND OCCUPATION GROUPINGS uses the 2012 Census codes; # NHIS 2021 INDUSTRY AND OCCUPATION GROUPINGS uses the 2018 Census codes; # # Mortality data starting with 2023 use 2018 census codes; # Email noms@cdc.gov with any questions on this program; # Code Created by Hannah Free at the National Institute for Occupational Safety and Health (NIOSH), United States Centers for Disease Control and Prevention. #Basic Setup------------------------------------------------------------------------------------------------------------ setwd() #Set working directory to your data by adding path library(summarytools) library(tidyverse) library(dplyr) library(data.table) #Read in your data. Reading in as a CSV or as a fixed width text file is recommended. Make sure that variables that start with 0 are not truncated. #If using a fixed width file for mortality text file, refer to the R mortality read-in code or clean data into a usable format before loading. #iotable <- read_fwf("Your_data_path_here") iotable <- df #Filter to only include 15-120 age range iotable <- dplyr::filter(iotable, Age_Recode_12 == "04" | Age_Recode_12 == "05" | Age_Recode_12 == "06" | Age_Recode_12 == "07" | Age_Recode_12 == "08" | Age_Recode_12 == "09" | Age_Recode_12 == "10" | Age_Recode_12 == "11" ) #Remove non-residents from sample iotable <- dplyr::filter(iotable, Resident_Status_US != "4") #Removing any blanks iotable <- iotable %>% drop_na(CensusOcc) iotable <- iotable %>% drop_na(CensusInd) # # Alternative option to read in full data set as a text file. For the text file, you must specify colClasses as character for this procedure. Make sure that variables that start with 0 are not truncated. # #iotable <- read.delim("Path_to_your_data", colClasses = "character") # #Filter by age range, resident status and missing values. # iotable <- dplyr::filter(iotable, Age_Recode_12 == "04" | Age_Recode_12 == "05" | Age_Recode_12 == "06" | Age_Recode_12 == "07" | Age_Recode_12 == "08" | Age_Recode_12 == "09" | Age_Recode_12 == "10" | Age_Recode_12 == "11" ) # iotable <- dplyr::filter(iotable, Resident_Status_US != "4") # iotable <- iotable %>% drop_na(CensusOcc) # iotable <- na_if(iotable, '') # iotable <- iotable %>% drop_na(CensusOcc) # iotable <- iotable %>% drop_na(CensusInd) # # Optional check to confirm that data cleaning worked # # freq(iotable$Age_Recode_12) # # freq(iotable$Age_Recode_12) # # freq(iotable$Resident_Status_US) #For this recode, you will need individual census occupation and industry code character variables named: #CensusOcc #CensusInd #------------------------------------------------------------------------------------------------------------------------ #2010 4-digit census occupation codes (from 2010 SOC) recoded to 2018 NHIS detailed recodes for occupation =occ_detailed #2007/2012 NAICS-based census industry codes recoded to 2018 NHIS detailed recodes for industry =ind_detailed #includes codes for 2007 since there was a one-to-one match for census codes see: # https://www.census.gov/topics/employment/industry-occupation/guidance/code-lists.html #includes industry code 2780 metal forgings and stampings, which was in the detailed recode but not the simple #includes NIOSH/NCHS non-paid worker codes and military codes see: # /niosh/topics/coding/nioccsuserdocumentation.html #----------------------------------------------------------------------------- #Code to change census occupation codes into NHIS detailed codes iotable <- iotable %>% mutate(occ_detailed = case_when( CensusOcc %in% c("0010", "0020", "0030") ~ "01", CensusOcc %in% c("0040", "0051", "0052", "0060") ~ "02", CensusOcc %in% c("0101", "0102", "0110", "0120", "0135", "0136", "0137", "0140", "0150", "0160") ~ "03", CensusOcc %in% c("0205", "0220", "0230", "0300", "0310", "0325", "0335", "0340", "0350", "0360", "0400", "0410", "0420", "0425", "0426", "0440") ~ "04", CensusOcc %in% c("0500", "0510", "0520", "0530", "0540", "0565", "0600", "0630", "0640", "0650", "0700", "0705", "0710", "0725", "0726", "0735", "0750") ~ "05", CensusOcc %in% c("0800", "0810", "0820", "0830", "0845", "0850", "0860", "0900", "0910", "0930", "0940", "0960") ~ "06", CensusOcc %in% c("1005", "1006", "1007", "1010", "1021", "1022", "1031", "1032", "1050", "1065", "1105", "1106", "1108") ~ "07", CensusOcc %in% c("1200", "1210", "1220", "1230", "1240") ~ "08", CensusOcc %in% c("1305", "1306", "1310") ~ "09", CensusOcc %in% c("1320", "1330", "1340", "1350", "1360", "1400", "1410", "1420", "1430", "1440", "1450", "1460", "1500", "1510", "1520", "1530") ~ "10", CensusOcc %in% c("1541", "1545", "1551", "1555", "1560") ~ "11", CensusOcc %in% c("1600", "1610", "1640", "1650", "1660") ~ "12", CensusOcc %in% c("1700", "1710", "1720", "1745", "1750", "1760") ~ "13", CensusOcc %in% c("1800", "1815", "1821", "1822", "1825", "1830", "1840", "1860") ~ "14", CensusOcc %in% c("1900", "1910", "1920", "1935", "1940", "1950", "1970", "1980") ~ "15", CensusOcc %in% c("2001", "2002", "2003", "2004", "2005", "2006", "2011", "2012", "2013", "2014", "2015", "2016", "2025") ~ "16", CensusOcc %in% c("2040", "2050", "2060") ~ "17", CensusOcc %in% c("2100", "2105", "2110") ~ "18", CensusOcc %in% c("2145", "2170", "2180") ~ "19", CensusOcc %in% c("2205") ~ "20", CensusOcc %in% c("2300", "2310", "2320", "2330") ~ "21", CensusOcc %in% c("2350", "2360") ~ "22", CensusOcc %in% c("2400", "2435", "2440") ~ "23", CensusOcc %in% c("2545", "2555") ~ "24", CensusOcc %in% c("2600", "2631", "2632", "2633", "2634", "2635", "2636", "2640") ~ "25", CensusOcc %in% c("2700", "2710", "2721", "2722", "2723", "2740", "2751", "2752", "2755", "2770") ~ "26", CensusOcc %in% c("2805", "2810", "2825", "2830", "2840", "2850", "2861", "2862", "2865") ~ "27", CensusOcc %in% c("2905", "2910", "2920", "2970") ~ "28", CensusOcc %in% c("3000", "3010", "3030", "3040", "3050", "3065", "3070", "3090", "3100", "3110", "3120", "3140", "3150", "3160", "3200", "3210", "3220", "3230", "3235", "3245", "3250", "3255", "3256", "3257", "3258", "3261", "3270") ~ "29", CensusOcc %in% c("3300", "3310", "3321", "3322", "3323", "3324", "3330", "3401", "3402", "3421", "3422", "3423", "3424", "3430", "3500", "3515", "3520", "3545") ~ "30", CensusOcc %in% c("3550") ~ "31", CensusOcc %in% c("3601", "3602", "3603", "3605") ~ "32", CensusOcc %in% c("3610", "3620") ~ "33", CensusOcc %in% c("3630", "3640", "3645", "3646", "3647", "3648", "3649", "3655") ~ "34", CensusOcc %in% c("3700", "3710", "3720", "3725", "3735") ~ "35", CensusOcc %in% c("3740", "3750") ~ "36", CensusOcc %in% c("3801", "3802", "3820", "3830", "3840", "3870") ~ "37", CensusOcc %in% c("3900", "3910", "3930", "3940", "3945", "3946", "3960") ~ "38", CensusOcc %in% c("4000", "4010") ~ "39", CensusOcc %in% c("4020", "4030") ~ "40", CensusOcc %in% c("4040", "4055", "4110", "4120") ~ "41", CensusOcc %in% c("4130", "4140", "4150", "4160") ~ "42", CensusOcc %in% c("4200", "4210") ~ "43", CensusOcc %in% c("4220", "4230", "4240") ~ "44", CensusOcc %in% c("4251", "4252", "4255") ~ "45", CensusOcc %in% c("4330") ~ "46", CensusOcc %in% c("4340", "4350") ~ "47", CensusOcc %in% c("4400", "4420", "4435") ~ "48", CensusOcc %in% c("4461", "4465") ~ "49", CensusOcc %in% c("4500", "4510", "4521", "4522", "4525") ~ "50", CensusOcc %in% c("4530", "4540") ~ "51", CensusOcc %in% c("4600", "4621", "4622", "4640", "4655") ~ "52", CensusOcc %in% c("4700", "4710") ~ "53", CensusOcc %in% c("4720", "4740", "4750", "4760") ~ "54", CensusOcc %in% c("4800", "4810", "4820", "4830", "4840") ~ "55", CensusOcc %in% c("4850") ~ "56", CensusOcc %in% c("4900", "4920", "4930", "4940", "4950", "4965") ~ "57", CensusOcc %in% c("5000") ~ "58", CensusOcc %in% c("5010", "5020", "5040") ~ "59", CensusOcc %in% c("5100", "5110", "5120", "5130", "5140", "5150", "5160", "5165") ~ "60", CensusOcc %in% c("5200", "5210", "5220", "5230", "5240", "5250", "5260", "5300", "5310", "5320", "5330", "5340", "5350", "5360", "5400", "5410", "5420") ~ "61", CensusOcc %in% c("5500", "5510", "5521", "5522", "5530", "5540", "5550", "5560", "5600", "5610", "5630") ~ "62", CensusOcc %in% c("5710", "5720", "5730", "5740") ~ "63", CensusOcc %in% c("5810", "5820", "5830", "5840", "5850", "5860", "5900", "5910", "5920", "5940") ~ "64", CensusOcc %in% c("6005") ~ "65", CensusOcc %in% c("6010", "6020", "6040", "6050") ~ "66", CensusOcc %in% c("6115") ~ "67", CensusOcc %in% c("6120", "6130") ~ "68", CensusOcc %in% c("6200") ~ "69", CensusOcc %in% c("6210", "6220", "6230", "6240", "6250", "6260", "6305", "6330", "6355", "6360", "6400", "6410", "6441", "6442", "6460", "6500", "6515", "6520", "6530", "6540") ~ "70", CensusOcc %in% c("6600") ~ "71", CensusOcc %in% c("6660", "6700", "6710", "6720", "6730", "6740", "6750", "6765") ~ "72", CensusOcc %in% c("6800", "6821", "6825", "6835", "6850", "6920", "6950") ~ "73", CensusOcc %in% c("7000") ~ "74", CensusOcc %in% c("7010", "7020", "7030", "7040", "7050", "7100", "7110", "7120", "7130") ~ "75", CensusOcc %in% c("7140", "7150", "7160", "7200", "7210", "7220", "7240", "7260") ~ "76", CensusOcc %in% c("7300", "7315", "7320", "7330", "7340", "7350", "7360", "7410", "7420", "7430", "7440", "7510", "7520", "7540", "7550", "7560", "7610", "7640") ~ "77", CensusOcc %in% c("7700") ~ "78", CensusOcc %in% c("7710", "7720", "7730", "7740", "7750") ~ "79", CensusOcc %in% c("7800", "7810", "7830", "7840", "7850", "7855") ~ "80", CensusOcc %in% c("7905", "7925", "7950", "8000", "8025", "8030", "8040", "8060", "8100", "8130", "8140", "8225") ~ "81", CensusOcc %in% c("8250", "8255", "8256") ~ "82", CensusOcc %in% c("8300", "8310", "8320", "8335", "8350", "8365", "8450", "8465") ~ "83", CensusOcc %in% c("8500", "8510", "8530", "8540", "8555") ~ "84", CensusOcc %in% c("8600", "8610", "8620", "8630") ~ "85", CensusOcc %in% c("8640", "8650", "8710", "8720", "8730", "8740", "8750", "8760", "8800", "8810", "8830", "8850", "8910", "8920", "8930", "8940", "8950", "8865", "8990") ~ "86", CensusOcc %in% c("9005") ~ "87", CensusOcc %in% c("9030", "9040", "9050") ~ "88", CensusOcc %in% c("9110", "9121", "9122", "9130", "9141", "9142", "9150") ~ "89", CensusOcc %in% c("9210", "9240", "9265") ~ "90", CensusOcc %in% c("9300", "9310", "9330") ~ "91", CensusOcc %in% c("9350", "9365", "9410", "9415", "9430") ~ "92", CensusOcc %in% c("9510", "9570", "9600", "9610", "9620", "9630", "9640", "9645", "9650", "9720", "9760") ~ "93", CensusOcc %in% c("9830", "9840", "9850") ~ "94", CensusOcc %in% c("9010", "9020", "9070", "9060", "9100", "9900") ~ "95", TRUE ~ "00")) #------------------------------------------------------------------------------------------------------------------------- #For Census codes, switch NIOSH NCHS military with: # CensusOcc %in% c("9800", "9810", "9820", "9830", "9840") ~ "23", #and add: # CensusOcc %in% c("9997") ~ "97", # CensusOcc %in% c("9998") ~ "98", # CensusOcc %in% c("9999") ~ "99", #------------------------------------------------------------------------------------------------------------------------- #Create recode for occupation titles iotable <- iotable %>% mutate(occ.names = case_when( CensusOcc %in% "01" ~ "01 Chief executives; general and operations managers; legislators", CensusOcc %in% "02" ~ "02 Advertising, marketing, promotions, public relations, and sales managers", CensusOcc %in% "03" ~ "03 Administrative services, compensation/benefits, human resources, training, production, purchasing, and transportion/distribution, and other operations managers", CensusOcc %in% "04" ~ "04 All other management occupations", CensusOcc %in% "05" ~ "05 Business operations specialists", CensusOcc %in% "06" ~ "06 Financial specialists", CensusOcc %in% "07" ~ "07 Computer specialists", CensusOcc %in% "08" ~ "08 Mathematical science occupations", CensusOcc %in% "09" ~ "09 Architects, surveyors, and cartographers", CensusOcc %in% "10" ~ "10 Engineers", CensusOcc %in% "11" ~ "11 Drafters, engineering, and mapping technicians", CensusOcc %in% "12" ~ "12 Life scientists", CensusOcc %in% "13" ~ "13 Physical scientists", CensusOcc %in% "14" ~ "14 Social scientists and related workers", CensusOcc %in% "15" ~ "15 Life, physical, and social science technicians", CensusOcc %in% "16" ~ "16 Counselors, social workers, and other community and social service specialists", CensusOcc %in% "17" ~ "17 Religious workers", CensusOcc %in% "18" ~ "18 Lawyers, judges, and related workers", CensusOcc %in% "19" ~ "19 Legal support workers", CensusOcc %in% "20" ~ "20 Postsecondary teachers", CensusOcc %in% "21" ~ "21 Primary, secondary, and special education school teachers", CensusOcc %in% "22" ~ "22 Other teachers and instructors", CensusOcc %in% "23" ~ "23 Librarians, curators, and archivists", CensusOcc %in% "24" ~ "24 Other education, training, and library occupations", CensusOcc %in% "25" ~ "25 Art and design workers", CensusOcc %in% "26" ~ "26 Entertainers and performers, sports and related workers", CensusOcc %in% "27" ~ "27 Media and communication workers", CensusOcc %in% "28" ~ "28 Media and communication equipment workers", CensusOcc %in% "29" ~ "29 Health diagnosing and treating practitioners", CensusOcc %in% "30" ~ "30 Health technologists and technicians", CensusOcc %in% "31" ~ "31 Other healthcare practitioners and technical occupations", CensusOcc %in% "32" ~ "32 Nursing, psychiatric, and home health aides", CensusOcc %in% "33" ~ "33 Occupational and physical therapist assistants and aides", CensusOcc %in% "34" ~ "34 Other healthcare support occupations", CensusOcc %in% "35" ~ "35 First-line supervisors/managers, protective service workers", CensusOcc %in% "36" ~ "36 Firefighting and prevention workers", CensusOcc %in% "37" ~ "37 Law enforcement workers", CensusOcc %in% "38" ~ "38 Other protective service workers", CensusOcc %in% "39" ~ "39 Supervisors, food preparation, and serving workers", CensusOcc %in% "40" ~ "40 Cooks and food preparation workers", CensusOcc %in% "41" ~ "41 Food and beverage serving working", CensusOcc %in% "42" ~ "42 Other food preparation and serving related workers", CensusOcc %in% "43" ~ "43 Supervisors, building and grounds cleaning and maintenance workers", CensusOcc %in% "44" ~ "44 Building cleaning and pest control workers", CensusOcc %in% "45" ~ "45 Grounds maintenance workers", CensusOcc %in% "46" ~ "46 Supervisors, personal care and service workers", CensusOcc %in% "47" ~ "47 Animal care and service workers", CensusOcc %in% "48" ~ "48 Entertainment attendants and related workers", CensusOcc %in% "49" ~ "49 Funeral service workers", CensusOcc %in% "50" ~ "50 Personal appearance workers", CensusOcc %in% "51" ~ "51 Transportation, tourism, and lodging attendants", CensusOcc %in% "52" ~ "52 Other personal care and service workers", CensusOcc %in% "53" ~ "53 Supervisors, sales workers", CensusOcc %in% "54" ~ "54 Retail sales workers", CensusOcc %in% "55" ~ "55 Sales representatives, services", CensusOcc %in% "56" ~ "56 Sales representatives, wholesale and manufacturing", CensusOcc %in% "57" ~ "57 Other sales and related workers", CensusOcc %in% "58" ~ "58 Supervisors, office and administrative support workers", CensusOcc %in% "59" ~ "59 Communications equipment operators", CensusOcc %in% "60" ~ "60 Financial clerks", CensusOcc %in% "61" ~ "61 Information and record clerks", CensusOcc %in% "62" ~ "62 Material recording, scheduling, dispatching, and distributing workers", CensusOcc %in% "63" ~ "63 Secretaries and administrative assistants", CensusOcc %in% "64" ~ "64 Other office and administrative support workers", CensusOcc %in% "65" ~ "65 Supervisors, farming, fishing, and forestry workers", CensusOcc %in% "66" ~ "66 Agricultural workers", CensusOcc %in% "67" ~ "67 Fishing and hunting workers", CensusOcc %in% "68" ~ "68 Forest, conservation, and logging workers", CensusOcc %in% "69" ~ "69 Supervisors, construction and extraction workers", CensusOcc %in% "70" ~ "70 Construction trades workers", CensusOcc %in% "71" ~ "71 Helpers, construction trades", CensusOcc %in% "72" ~ "72 Other construction and related workers", CensusOcc %in% "73" ~ "73 Extraction workers", CensusOcc %in% "74" ~ "74 Supervisors of installation, maintenance, and repair workers", CensusOcc %in% "75" ~ "75 Electrical and electronic equipment mechanics, installers, and repairers", CensusOcc %in% "76" ~ "76 Vehicle and mobile equipment mechanics, installers, and repairers", CensusOcc %in% "77" ~ "77 Other installation, maintenance, and repair occupations", CensusOcc %in% "78" ~ "78 Supervisors, production workers", CensusOcc %in% "79" ~ "79 Assemblers and fabricators", CensusOcc %in% "80" ~ "80 Food processing workers", CensusOcc %in% "81" ~ "81 Metal workers and plastic workers", CensusOcc %in% "82" ~ "82 Printing workers", CensusOcc %in% "83" ~ "83 Textile, apparel, and furnishings workers", CensusOcc %in% "84" ~ "84 Woodworkers", CensusOcc %in% "85" ~ "85 Plant and system operators", CensusOcc %in% "86" ~ "86 Other production occupations", CensusOcc %in% "87" ~ "87 Supervisors, transportation and material moving workers", CensusOcc %in% "88" ~ "88 Air transportation workers", CensusOcc %in% "89" ~ "89 Motor vehicle operators", CensusOcc %in% "90" ~ "90 Rail transportation workers", CensusOcc %in% "91" ~ "91 Water transportation workers", CensusOcc %in% "92" ~ "92 Other transportation workers", CensusOcc %in% "93" ~ "93 Material moving workers", CensusOcc %in% "94" ~ "94 NIOSH NCHS military", CensusOcc %in% "95" ~ "95 NIOSH NCHS Other--Misc", CensusOcc %in% c("0010", "0020", "0030") ~ "01", CensusOcc %in% c("0040", "0051", "0052", "0060") ~ "02", CensusOcc %in% c("0101", "0102", "0110", "0120", "0135", "0136", "0137", "0140", "0150", "0160") ~ "03", CensusOcc %in% c("0205", "0220", "0230", "0300", "0310", "0325", "0335", "0340", "0350", "0360", "0400", "0410", "0420", "0425", "0426", "0440") ~ "04", CensusOcc %in% c("0500", "0510", "0520", "0530", "0540", "0565", "0600", "0630", "0640", "0650", "0700", "0705", "0710", "0725", "0726", "0735", "0750") ~ "05", CensusOcc %in% c("0800", "0810", "0820", "0830", "0845", "0850", "0860", "0900", "0910", "0930", "0940", "0960") ~ "06", CensusOcc %in% c("1005", "1006", "1007", "1010", "1021", "1022", "1031", "1032", "1050", "1065", "1105", "1106", "1108") ~ "07", CensusOcc %in% c("1200", "1210", "1220", "1230", "1240") ~ "08", CensusOcc %in% c("1305", "1306", "1310") ~ "09", CensusOcc %in% c("1320", "1330", "1340", "1350", "1360", "1400", "1410", "1420", "1430", "1440", "1450", "1460", "1500", "1510", "1520", "1530") ~ "10", CensusOcc %in% c("1541", "1545", "1551", "1555", "1560") ~ "11", CensusOcc %in% c("1600", "1610", "1640", "1650", "1660") ~ "12", CensusOcc %in% c("1700", "1710", "1720", "1745", "1750", "1760") ~ "13", CensusOcc %in% c("1800", "1815", "1821", "1822", "1825", "1830", "1840", "1860") ~ "14", CensusOcc %in% c("1900", "1910", "1920", "1935", "1940", "1950", "1970", "1980") ~ "15", CensusOcc %in% c("2001", "2002", "2003", "2004", "2005", "2006", "2011", "2012", "2013", "2014", "2015", "2016", "2025") ~ "16", CensusOcc %in% c("2040", "2050", "2060") ~ "17", CensusOcc %in% c("2100", "2105", "2110") ~ "18", CensusOcc %in% c("2145", "2170", "2180") ~ "19", CensusOcc %in% c("2205") ~ "20", CensusOcc %in% c("2300", "2310", "2320", "2330") ~ "21", CensusOcc %in% c("2350", "2360") ~ "22", CensusOcc %in% c("2400", "2435", "2440") ~ "23", CensusOcc %in% c("2545", "2555") ~ "24", CensusOcc %in% c("2600", "2631", "2632", "2633", "2634", "2635", "2636", "2640") ~ "25", CensusOcc %in% c("2700", "2710", "2721", "2722", "2723", "2740", "2751", "2752", "2755", "2770") ~ "26", CensusOcc %in% c("2805", "2810", "2825", "2830", "2840", "2850", "2861", "2862", "2865") ~ "27", CensusOcc %in% c("2905", "2910", "2920", "2970") ~ "28", CensusOcc %in% c("3000", "3010", "3030", "3040", "3050", "3065", "3070", "3090", "3100", "3110", "3120", "3140", "3150", "3160", "3200", "3210", "3220", "3230", "3235", "3245", "3250", "3255", "3256", "3257", "3258", "3261", "3270") ~ "29", CensusOcc %in% c("3300", "3310", "3321", "3322", "3323", "3324", "3330", "3401", "3402", "3421", "3422", "3423", "3424", "3430", "3500", "3515", "3520", "3545") ~ "30", CensusOcc %in% c("3550") ~ "31", CensusOcc %in% c("3601", "3602", "3603", "3605") ~ "32", CensusOcc %in% c("3610", "3620") ~ "33", CensusOcc %in% c("3630", "3640", "3645", "3646", "3647", "3648", "3649", "3655") ~ "34", CensusOcc %in% c("3700", "3710", "3720", "3725", "3735") ~ "35", CensusOcc %in% c("3740", "3750") ~ "36", CensusOcc %in% c("3801", "3802", "3820", "3830", "3840", "3870") ~ "37", CensusOcc %in% c("3900", "3910", "3930", "3940", "3945", "3946", "3960") ~ "38", CensusOcc %in% c("4000", "4010") ~ "39", CensusOcc %in% c("4020", "4030") ~ "40", CensusOcc %in% c("4040", "4055", "4110", "4120") ~ "41", CensusOcc %in% c("4130", "4140", "4150", "4160") ~ "42", CensusOcc %in% c("4200", "4210") ~ "43", CensusOcc %in% c("4220", "4230", "4240") ~ "44", CensusOcc %in% c("4251", "4252", "4255") ~ "45", CensusOcc %in% c("4330") ~ "46", CensusOcc %in% c("4340", "4350") ~ "47", CensusOcc %in% c("4400", "4420", "4435") ~ "48", CensusOcc %in% c("4461", "4465") ~ "49", CensusOcc %in% c("4500", "4510", "4521", "4522", "4525") ~ "50", CensusOcc %in% c("4530", "4540") ~ "51", CensusOcc %in% c("4600", "4621", "4622", "4640", "4655") ~ "52", CensusOcc %in% c("4700", "4710") ~ "53", CensusOcc %in% c("4720", "4740", "4750", "4760") ~ "54", CensusOcc %in% c("4800", "4810", "4820", "4830", "4840") ~ "55", CensusOcc %in% c("4850") ~ "56", CensusOcc %in% c("4900", "4920", "4930", "4940", "4950", "4965") ~ "57", CensusOcc %in% c("5000") ~ "58", CensusOcc %in% c("5010", "5020", "5040") ~ "59", CensusOcc %in% c("5100", "5110", "5120", "5130", "5140", "5150", "5160", "5165") ~ "60", CensusOcc %in% c("5200", "5210", "5220", "5230", "5240", "5250", "5260", "5300", "5310", "5320", "5330", "5340", "5350", "5360", "5400", "5410", "5420") ~ "61", CensusOcc %in% c("5500", "5510", "5521", "5522", "5530", "5540", "5550", "5560", "5600", "5610", "5630") ~ "62", CensusOcc %in% c("5710", "5720", "5730", "5740") ~ "63", CensusOcc %in% c("5810", "5820", "5830", "5840", "5850", "5860", "5900", "5910", "5920", "5940") ~ "64", CensusOcc %in% c("6005") ~ "65", CensusOcc %in% c("6010", "6020", "6040", "6050") ~ "66", CensusOcc %in% c("6115") ~ "67", CensusOcc %in% c("6120", "6130") ~ "68", CensusOcc %in% c("6200") ~ "69", CensusOcc %in% c("6210", "6220", "6230", "6240", "6250", "6260", "6305", "6330", "6355", "6360", "6400", "6410", "6441", "6442", "6460", "6500", "6515", "6520", "6530", "6540") ~ "70", CensusOcc %in% c("6600") ~ "71", CensusOcc %in% c("6660", "6700", "6710", "6720", "6730", "6740", "6750", "6765") ~ "72", CensusOcc %in% c("6800", "6821", "6825", "6835", "6850", "6920", "6950") ~ "73", CensusOcc %in% c("7000") ~ "74", CensusOcc %in% c("7010", "7020", "7030", "7040", "7050", "7100", "7110", "7120", "7130") ~ "75", CensusOcc %in% c("7140", "7150", "7160", "7200", "7210", "7220", "7240", "7260") ~ "76", CensusOcc %in% c("7300", "7315", "7320", "7330", "7340", "7350", "7360", "7410", "7420", "7430", "7440", "7510", "7520", "7540", "7550", "7560", "7610", "7640") ~ "77", CensusOcc %in% c("7700") ~ "78", CensusOcc %in% c("7710", "7720", "7730", "7740", "7750") ~ "79", CensusOcc %in% c("7800", "7810", "7830", "7840", "7850", "7855") ~ "80", CensusOcc %in% c("7905", "7925", "7950", "8000", "8025", "8030", "8040", "8060", "8100", "8130", "8140", "8225") ~ "81", CensusOcc %in% c("8250", "8255", "8256") ~ "82", CensusOcc %in% c("8300", "8310", "8320", "8335", "8350", "8365", "8450", "8465") ~ "83", CensusOcc %in% c("8500", "8510", "8530", "8540", "8555") ~ "84", CensusOcc %in% c("8600", "8610", "8620", "8630") ~ "85", CensusOcc %in% c("8640", "8650", "8710", "8720", "8730", "8740", "8750", "8760", "8800", "8810", "8830", "8850", "8910", "8920", "8930", "8940", "8950", "8865", "8990") ~ "86", CensusOcc %in% c("9005") ~ "87", CensusOcc %in% c("9030", "9040", "9050") ~ "88", CensusOcc %in% c("9110", "9121", "9122", "9130", "9141", "9142", "9150") ~ "89", CensusOcc %in% c("9210", "9240", "9265") ~ "90", CensusOcc %in% c("9300", "9310", "9330") ~ "91", CensusOcc %in% c("9350", "9365", "9410", "9415", "9430") ~ "92", CensusOcc %in% c("9510", "9570", "9600", "9610", "9620", "9630", "9640", "9645", "9650", "9720", "9760") ~ "93", CensusOcc %in% c("9830", "9840", "9850") ~ "94", CensusOcc %in% c("9010", "9020", "9070", "9060", "9100", "9900") ~ "95", TRUE ~ "00")) #------------------------------------------------------------------------------------------------------------------------ #For Census codes, switch NIOSH military with: # occ_detailed %in% "23" ~ "23 Census: Military Specific Occupations", #And add: # occ_detailed %in% "97" ~ "97 Census: Refused, Classified", # occ_detailed %in% "98" ~ "98 Census: Not Ascertained", # occ_detailed %in% "99" ~ "99 Census: Do not know", #---------------------------------------------------------------------------------------------------------------------- #*2007/2012 4-DIGIT NAICS-BASED CENSUS INDUSTRY CODES RECODED TO 2018 NHIS DETAILED RECODES FOR INDUSTRY =IND_detailed #INCLUDES CODES FOR 2007 SINCE THERE WAS A ONE-TO-ONE MATCH FOR CENSUS INDUSTRY CODES: SEE # HTTPS://WWW.CENSUS.GOV/TOPICS/EMPLOYMENT/INDUSTRY-OCCUPATION/GUIDANCE/CODE-LISTS.HTML #INCLUDES INDUSTRY CODE 2780 Metal forgings and stampings, WHICH WAS IN THE DETAILED RECODE BUT NOT THE SIMPLE iotable <- iotable %>% mutate(ind_detailed = case_when( CensusInd %in% c("0170") ~ "01", CensusInd %in% c("0180") ~ "02", CensusInd %in% c("0190", "0270") ~ "03", CensusInd %in% c("0280") ~ "04", CensusInd %in% c("0290") ~ "05", CensusInd %in% c("0370") ~ "06", CensusInd %in% c("0380", "0390", "0470", "0480") ~ "07", CensusInd %in% c("0490") ~ "08", CensusInd %in% c("0570", "0580", "0590", "0670", "0680", "0690") ~ "09", CensusInd %in% c("0770") ~ "10", CensusInd %in% c("1070", "1080", "1090", "1170", "1180", "1190", "1270", "1280", "1290") ~ "11", CensusInd %in% c("1370", "1390") ~ "12", CensusInd %in% c("1470", "1480", "1490") ~ "13", CensusInd %in% c("1570", "1590", "1670") ~ "14", CensusInd %in% c("1691", "1770") ~ "15", CensusInd %in% c("1790") ~ "16", CensusInd %in% c("3770", "3780", "3790", "3875") ~ "17", CensusInd %in% c("1870", "1880", "1890") ~ "18", CensusInd %in% c("1990") ~ "19", CensusInd %in% c("2070", "2090") ~ "20", CensusInd %in% c("2170", "2180", "2190", "2270", "2280", "2290") ~ "21", CensusInd %in% c("2370", "2380", "2390") ~ "22", CensusInd %in% c("2470", "2480", "2490", "2570", "2590") ~ "23", CensusInd %in% c("2670", "2680", "2690", "2770", "2780", "2990") ~ "24", CensusInd %in% c("2790", "2870", "2880", "2890", "2970", "2980") ~ "25", CensusInd %in% c("3070", "3080", "3095", "3170", "3180", "3291") ~ "26", CensusInd %in% c("3365", "3370", "3380", "3390") ~ "27", CensusInd %in% c("3470", "3490") ~ "28", CensusInd %in% c("3570", "3580", "3590", "3670", "3680", "3690") ~ "29", CensusInd %in% c("3895") ~ "30", CensusInd %in% c("3960", "3970", "3980", "3990") ~ "31", CensusInd %in% c("4070", "4080", "4090", "4170", "4180", "4195", "4265", "4270", "4280", "4290") ~ "32", CensusInd %in% c("4370", "4380", "4390", "4470", "4480", "4490", "4560", "4570", "4580", "4585") ~ "33", CensusInd %in% c("4590") ~ "34", CensusInd %in% c("4670", "4680", "4690") ~ "35", CensusInd %in% c("4770") ~ "36", CensusInd %in% c("4780", "4795") ~ "37", CensusInd %in% c("4870", "4880", "4890") ~ "38", CensusInd %in% c("4971", "4972", "4980", "4990") ~ "39", CensusInd %in% c("5070", "5080") ~ "40", CensusInd %in% c("5090") ~ "41", CensusInd %in% c("5170", "5180", "5190") ~ "42", CensusInd %in% c("5275", "5280", "5295", "5370") ~ "43", CensusInd %in% c("5381", "5391") ~ "44", CensusInd %in% c("5470", "5480", "5490", "5570", "5580") ~ "45", CensusInd %in% c("5593", "5670", "5680", "5690", "5790") ~ "46", CensusInd %in% c("6070", "6080", "6090", "6170", "6180", "6190", "6270", "6280", "6290") ~ "47", CensusInd %in% c("6370", "6380") ~ "48", CensusInd %in% c("6390") ~ "49", CensusInd %in% c("6470", "6480", "6490") ~ "50", CensusInd %in% c("6570", "6590") ~ "51", CensusInd %in% c("6670", "6680", "6690") ~ "52", CensusInd %in% c("6672", "6695", "6770", "6780") ~ "53", CensusInd %in% c("6870") ~ "54", CensusInd %in% c("6880", "6890") ~ "55", CensusInd %in% c("6970") ~ "56", CensusInd %in% c("6991", "6992") ~ "57", CensusInd %in% c("7071", "7072") ~ "58", CensusInd %in% c("7080", "7181") ~ "59", CensusInd %in% c("7190") ~ "60", CensusInd %in% c("7270", "7280", "7290", "7370", "7380", "7390", "7460", "7470", "7480", "7490") ~ "61", CensusInd %in% c("7570") ~ "62", CensusInd %in% c("7580", "7590", "7670", "7680", "7690", "7770", "7780", "7790") ~ "63", CensusInd %in% c("7860", "7870", "7880", "7890") ~ "64", CensusInd %in% c("7970","7980", "7990", "8070", "8080", "8090", "8170", "8180") ~ "65", CensusInd %in% c("8191", "8192") ~ "66", CensusInd %in% c("8270", "8290") ~ "67", CensusInd %in% c("8370", "8380", "8390", "8470") ~ "68", CensusInd %in% c("8561", "8562", "8563", "8564") ~ "69", CensusInd %in% c("8570") ~ "70", CensusInd %in% c("8580", "8590") ~ "71", CensusInd %in% c("8660", "8670") ~ "72", CensusInd %in% c("8680", "8690") ~ "73", CensusInd %in% c("8770", "8780", "8790", "8870", "8891") ~ "74", CensusInd %in% c("8970", "8980", "8990", "9070", "9080", "9090") ~ "75", CensusInd %in% c("9160", "9170", "9180", "9190") ~ "76", CensusInd %in% c("9290") ~ "77", CensusInd %in% c("9370", "9380", "9390", "9470", "9480", "9490", "9570", "9590") ~ "78", CensusInd %in% c("9790", "9670", "9680", "9780", "9770", "9690", "9790") ~ "79", CensusInd %in% c("9890", "9880", "9990") ~ "80", TRUE ~ "00")) #------------------------------------------------------------------------------------------------------------------------- #Create recode industry titles iotable <- iotable %>% mutate(ind.names = case_when( ind_detailed %in% "01" ~ "01 Crop production", ind_detailed %in% "02" ~ "02 Animal production and aquaculture", ind_detailed %in% "03" ~ "03 Forestry and logging", ind_detailed %in% "04" ~ "04 Fishing, hunting, and trapping", ind_detailed %in% "05" ~ "05 Support activities for agriculture and forestry", ind_detailed %in% "06" ~ "06 Oil and gas extraction", ind_detailed %in% "07" ~ "07 Mining (except oil and gas)", ind_detailed %in% "08" ~ "08 Support activities for mining", ind_detailed %in% "09" ~ "09 Utilities Industries", ind_detailed %in% "10" ~ "10 Construction Industries", ind_detailed %in% "11" ~ "11 Food manufacturing", ind_detailed %in% "12" ~ "12 Beverage and tobacco product manufacturing", ind_detailed %in% "13" ~ "13 Textile mills", ind_detailed %in% "14" ~ "14 Textile product mills", ind_detailed %in% "15" ~ "15 Apparel manufacturing", ind_detailed %in% "16" ~ "16 Leather and allied product manufacturing", ind_detailed %in% "17" ~ "17 Wood product manufacturing", ind_detailed %in% "18" ~ "18 Paper manufacturing", ind_detailed %in% "19" ~ "19 Printing and related support activities", ind_detailed %in% "20" ~ "20 Petroleum and coal products manufacturing", ind_detailed %in% "21" ~ "21 Chemical manufacturing", ind_detailed %in% "22" ~ "22 Plastics and rubber products manufacturing", ind_detailed %in% "23" ~ "23 Nonmetallic mineral product manufacturing", ind_detailed %in% "24" ~ "24 Primary metal manufacturing", ind_detailed %in% "25" ~ "25 Fabricated metal product manufacturing", ind_detailed %in% "26" ~ "26 Machinery manufacturing", ind_detailed %in% "27" ~ "27 Computer and electronic product manufacturing", ind_detailed %in% "28" ~ "28 Electrical equipment, appliance, and component manufacturing", ind_detailed %in% "29" ~ "29 Transportation equipment manufacturing", ind_detailed %in% "30" ~ "30 Furniture and related product manufacturing", ind_detailed %in% "31" ~ "31 Miscellaneous manufacturing", ind_detailed %in% "32" ~ "32 Merchant wholesalers, durable goods", ind_detailed %in% "33" ~ "33 Merchant wholesalers, nondurable goods", ind_detailed %in% "34" ~ "34 Non-specified wholesale trade", ind_detailed %in% "35" ~ "35 Motor vehicle and parts dealers", ind_detailed %in% "36" ~ "36 Furniture and home furnishings stores", ind_detailed %in% "37" ~ "37 Electronics and appliance stores", ind_detailed %in% "38" ~ "38 Building material and garden equipment and supplies dealers", ind_detailed %in% "39" ~ "39 Food and beverage stores", ind_detailed %in% "40" ~ "40 Health and personal care stores", ind_detailed %in% "41" ~ "41 Gasoline stations", ind_detailed %in% "42" ~ "42 Clothing, shoe, jewelry, luggage, and leather goods stores", ind_detailed %in% "43" ~ "43 Sporting goods, camera, hobby, book and music stores", ind_detailed %in% "44" ~ "44 General merchandise stores", ind_detailed %in% "45" ~ "45 Miscellaneous store retailers", ind_detailed %in% "46" ~ "46 Nonstore retailers and non-specified retail trade", ind_detailed %in% "47" ~ "47 Transportation (including support activities for transportation)", ind_detailed %in% "48" ~ "48 Postal service, couriers, and messengers", ind_detailed %in% "49" ~ "49 Warehousing and storage", ind_detailed %in% "50" ~ "50 Newspaper, periodical, book, and software publishing industries", ind_detailed %in% "51" ~ "51 Motion picture, video, and sound recording industries", ind_detailed %in% "52" ~ "52 Broadcasting and telecommunications", ind_detailed %in% "53" ~ "53 Libraries and archives, internet publishing, web search portals, data processing and hosting services, and other information services", ind_detailed %in% "54" ~ "54 Monetary authorities -- central bank", ind_detailed %in% "55" ~ "55 Credit intermediation and related activities", ind_detailed %in% "56" ~ "56 Securities, commodity contracts, and other financial investments and related activities", ind_detailed %in% "57" ~ "57 Insurance carriers and related activities", ind_detailed %in% "58" ~ "58 Real estate", ind_detailed %in% "59" ~ "59 Automotive and other consumer goods rental and leasing services", ind_detailed %in% "60" ~ "60 Commercial, industrial, and other intangible assets (except copyrighted works)", ind_detailed %in% "61" ~ "61 Professional, Scientific, and Technical Services Industries", ind_detailed %in% "62" ~ "62 Management of Companies and Enterprises Industries", ind_detailed %in% "63" ~ "63 Administrative and Support and Waste Management and Remediation Services Industries", ind_detailed %in% "64" ~ "64 Education Services Industries", ind_detailed %in% "65" ~ "65 Ambulatory health care services", ind_detailed %in% "66" ~ "66 Hospitals", ind_detailed %in% "67" ~ "67 Nursing and residential care facilities", ind_detailed %in% "68" ~ "68 Social assistance", ind_detailed %in% "69" ~ "69 Performing arts, spectator sports, promoters, agents, artists, writers and related industries", ind_detailed %in% "70" ~ "70 Museums, historical sites, and similar institutions", ind_detailed %in% "71" ~ "71 Amusement, gambling, and recreation industries", ind_detailed %in% "72" ~ "72 Accommodation", ind_detailed %in% "73" ~ "73 Food services and drinking places", ind_detailed %in% "74" ~ "74 Repair and maintenance", ind_detailed %in% "75" ~ "75 Personal services (barber shops, beauty salons, nail salons, laundry, funeral homes and cemeteries)", ind_detailed %in% "76" ~ "76 Religious, grantmaking, civic, labor, professional, and similar organizations", ind_detailed %in% "77" ~ "77 Private households", ind_detailed %in% "78" ~ "78 Public Administration Industries", ind_detailed %in% "79" ~ "79 NIOSH NCHS military", ind_detailed %in% "80" ~ "80 NIOSH NCHS Other--Misc", TRUE ~ "00")) #------------------------------------------------------------------------------------------------------------------------ #For Census code, switch NIOSH NCHS Military code for: # ind_detailed %in% "21" ~ "21 Census Military", #And add: # ind_detailed %in% "97" ~ "97 CENSUS REFUSED CLASSIFIED", # ind_detailed %in% "98" ~ "98 CENSUS NOT ASCERTAINED", # ind_detailed %in% "99" ~ "99 CENSUS NOT ASCERTAINED", #------------------------------------------------------------------------------------------------------------------------ #Output #Check for number of codes that were not categorized into detailed categories #Are there any missing values that missed the recode? sum(is.na(iotable$occ.names)) sum(is.na(iotable$ind.names)) #Are there any values that were uncategorized based on our recode? sum(iotable$occ.names == "00") sum(iotable$ind.names == "00") #Table for count and percentage of Occupation and Industry categories freq(iotable$occ.names, cumul=FALSE, weights= NA, display.type = FALSE, report.nas = TRUE) freq(iotable$ind.names, cumul=FALSE, weights= NA, display.type = FALSE, report.nas = TRUE) #Optional: Find raw data values of any missing categories. If values are wrong, this table will show you which so you can fix or add them. # subset <- iotable %>% filter(iotable$occ_detailed == "00") # freq(subset$CensusOcc) # subset <- iotable %>% filter(iotable$ind_detailed == "00") # freq(subset$CensusInd)