Children under 18 and elderly over 65 living in household [33_179_DF_DCCV_ABITAFFOLL_2]

Updated on DBnomics on November 7, 2023 (7:56 AM)

Frequency [FREQ]
Territory [REF_AREA]
Indicator [DATA_TYPE]
Measure [MEASURE]
Tenure status [TENURE_STATUS]
Household number of components [NUMBER_HOUSEHOLD_COMP]
Household typology [HOUSEHOLD_TYPOLOGY]
Number of children [NUMB_OF_CHILDREN]
Number of elderly [NUMB_OF_ELDERLY]
Fifth of equivalent household income [FIFTH_EQUIV_HOUSE_INC]
Sex of main income earner [SEX_MAIN_PERCEPTOR]
Age of main income earner [AGE_MAIN_EARNIER]
Educational level of main income earner [EDU_LEV_MAIN_EARN]
Professional status of main income earner [LABPROF_STATUS_C_MAIN_EARNER]

Dataset has 8 series. Add search filters to narrow them.

Dimension codes and labels
[FREQ] Frequency
  • [A] annual
[REF_AREA] Territory
  • [IT] Italy
[DATA_TYPE] Indicator
  • [ABITAZ_AFFOLL_MED] household crowding index (number of components of household per square meter)
[MEASURE] Measure
  • [10] per hundred values
[TENURE_STATUS] Tenure status
  • [99] total
[NUMBER_HOUSEHOLD_COMP] Household number of components
  • [99] total
[HOUSEHOLD_TYPOLOGY] Household typology
  • [99] total
[NUMB_OF_CHILDREN] Number of children
  • [1] 1 minor child
  • [2] 2 minor child
  • [3] 3 minor child and over
  • [5] no minor child
  • [9] total
[NUMB_OF_ELDERLY] Number of elderly
  • [1] 1 elderly
  • [2] 2 elderly or more
  • [4] no elderly
  • [9] total
[FIFTH_EQUIV_HOUSE_INC] Fifth of equivalent household income
  • [9] total
[SEX_MAIN_PERCEPTOR] Sex of main income earner
  • [9] total
[AGE_MAIN_EARNIER] Age of main income earner
  • [9] total
[EDU_LEV_MAIN_EARN] Educational level of main income earner
  • [99] total
[LABPROF_STATUS_C_MAIN_EARNER] Professional status of main income earner
  • [99] total
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