This dataset contains sample data for computing non-ordered summary measures of health inequality. It contains data from a household survey for the proportion of births attended by skilled health personnel disaggregated by subnational region.
Format
NonorderedSample
A data frame with 34 rows and 11 columns:
- indicator
indicator name
- dimension
dimension of inequality
- subgroup
population subgroup within a given dimension of inequality
- estimate
subgroup estimate
- se
standard error of the subgroup estimate
- population
number of people within each subgroup
- setting_average
indicator average for the setting
- favourable_indicator
favourable (1) or non-favourable (0) indicator
- ordered_dimension
ordered (1) or non-ordered (0) dimension
- indicator_scale
scale of the indicator
- reference_subgroup
reference subgroup
Source
WHO Health Inequality Data Repositoryhttps://www.who.int/data/inequality-monitor/data
Details
The proportion of births attended by skilled health personnel is calculated as the number of births attended by skilled health personnel divided by the total number of live births to women aged 15-49 years occurring in the period prior to the survey.
Skilled health personnel include doctors, nurses, midwives and other medically trained personnel, as defined according to each country. This is in line with the definition used by the Countdown to 2030 Collaboration, Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS) and Reproductive Health Surveys (RHS).
Subnational regions are defined using country-specific criteria. Subnational region is a non-ordered dimension (meaning that the subgroups do not have an inherent ordering).
This dataset can be used to calculate non-ordered summary measures of health inequality, including: between-group variance (BGV), between-group standard deviation (BGSD), coefficient of variation (COV), mean difference from mean (MDM), index of disparity (IDIS), Theil index (TI) and mean log deviation (MLD). It can also be used to calculate the impact measures population attributable risk (PAR) and population attributable fraction (PAF).
Examples
head(NonorderedSample)
#> indicator dimension
#> 1 Births attended by skilled health personnel (%) Subnational region
#> 2 Births attended by skilled health personnel (%) Subnational region
#> 3 Births attended by skilled health personnel (%) Subnational region
#> 4 Births attended by skilled health personnel (%) Subnational region
#> 5 Births attended by skilled health personnel (%) Subnational region
#> 6 Births attended by skilled health personnel (%) Subnational region
#> subgroup estimate se population setting_average
#> 1 aceh 95.11784 1.5384434 230.20508 91.59669
#> 2 bali 100.00000 0.0000000 149.46272 91.59669
#> 3 bangka balitung 97.41001 1.2676437 55.66533 91.59669
#> 4 banten 80.35694 3.5440531 451.26550 91.59669
#> 5 bengkulu 94.25756 2.7740061 70.17540 91.59669
#> 6 central java 98.56168 0.6476116 1221.94446 91.59669
#> favourable_indicator ordered_dimension indicator_scale reference_subgroup
#> 1 1 0 100 1
#> 2 1 0 100 0
#> 3 1 0 100 0
#> 4 1 0 100 0
#> 5 1 0 100 0
#> 6 1 0 100 0
summary(NonorderedSample)
#> indicator dimension subgroup estimate
#> Length:34 Length:34 Length:34 Min. : 64.20
#> Class :character Class :character Class :character 1st Qu.: 86.76
#> Mode :character Mode :character Mode :character Median : 91.20
#> Mean : 89.67
#> 3rd Qu.: 96.56
#> Max. :100.00
#> se population setting_average favourable_indicator
#> Min. :0.000 Min. : 26.33 Min. :91.6 Min. :1
#> 1st Qu.:1.468 1st Qu.: 79.20 1st Qu.:91.6 1st Qu.:1
#> Median :2.551 Median : 156.93 Median :91.6 Median :1
#> Mean :2.678 Mean : 297.19 Mean :91.6 Mean :1
#> 3rd Qu.:3.428 3rd Qu.: 307.36 3rd Qu.:91.6 3rd Qu.:1
#> Max. :7.201 Max. :1979.52 Max. :91.6 Max. :1
#> ordered_dimension indicator_scale reference_subgroup
#> Min. :0 Min. :100 Min. :0.00000
#> 1st Qu.:0 1st Qu.:100 1st Qu.:0.00000
#> Median :0 Median :100 Median :0.00000
#> Mean :0 Mean :100 Mean :0.02941
#> 3rd Qu.:0 3rd Qu.:100 3rd Qu.:0.00000
#> Max. :0 Max. :100 Max. :1.00000