Data
Data for this study included health, income, education, and structural indicators, openly available on the Direction of Statistics and Census of the City of Buenos Aires’ web page25. We also used 2020 data of mortality from the National Statistics and Health Information Direction National Health Minister, and COVID-19 Mortality in people 60 years or above40.
Geographical units
The City of Buenos Aires is administratively divided in 15 Comunas. Each Comuna has several neighborhoods within its boundaries. The Comunas are the minimal geographical unit with systematic data through the years and it is the unit chosen for this analysis41.
Several statistics reports nucleate the Comunas in four larger regions42. South Region: Comunas 4, 7, and 8; Center East Region: Comunas 1, 3, 5, 6, and 15; West Region: Comunas 9, 10, and 11; North Region: Comunas 2, 12, 13, and 14.
Selection of core indicators
Core indicators are summary measures of specific domains that help monitor and assess social and health related trends over time. We used demographic, socioeconomic, health and environmental indicators across “Comunas” to characterize social and health inequities. The indicators were chosen considering direct or indirect relevance to health outcomes and systematic data availability. Due to the pandemic, there are almost no updated indicators in 2020, so we chose data from 2019 and 2021. Ideal indicators had sufficient variability to reflect the distribution of the risk factor in the population as well as to discriminate between areas of high and low inequities.
Population over 25 years old with incomplete high school degree or less
The educational level attained has traditionally been selected as a socioeconomic indicator because it is a predictor not only of the quality and condition of employment but also of income and the social and cultural context. It is also considered a structural indicator that remains stable with economic fluctuations. It is widely known that adults with higher education levels live healthier and longer lives when compared to less educated peers43. We used 2021 data44.
Adolescent birth rate (live birth to females aged 15–19 per 1000 females aged 10–19 years)
Much has been discussed about the association between pregnancy and poverty. This is certainly an indicator that behaves differently according to socioeconomic levels. In adolescent pregnancy, the reproductive behavior of adolescent mothers and the socioeconomic conditions in which they live determine the sexual practices, endorsed, and reinforced by the context45. The characteristics make this indicator eligible. We used 2021 data42.
Percentage of households with income lower to total living expenses
This is an indicator of deprivation, it is also an indicator sensitive to the economic situation of a country and specifically refers to the ability of a household to meet the cost of food that satisfies their food needs and some non-food goods and services such as clothing, transportation, education, health, housing, etc46. We used 2021 data42.
Households without sewage connection
The sewage system is the urban means of elimination of excreta. Disposal through sewerage is considered a basic need. The lack of connection to this system is an indicator of deprivation that is associated with structural poverty, and it is directly related to negative health outcomes including mortality47. We used 2021 data48.
Age-standardized mortality rate
This indicator was selected to account for the risk of dying that the inhabitants of each Comuna have regardless of the influence of its population structure. The age-standardization of death was done following Pan American Health Organization (PAHO) Guidance49. We used 2020 data of mortality from the National Statistics and Health Information Direction, National Health Minister, and Argentinian population 2010 for age standardization40,50.
Population with public health system only
Argentina’s health system is divided into three subsectors: public, private, and social security that coexist and overlap. The private subsector is paid out of pocket voluntarily. The social security sector is financed through regular fixed contributions from employees and employers in the formal working force. Finally, people living in Argentina, regardless of their Nationality or if they are covered under any of the other subsectors, can access the public subsector51. Due to this, the public health system has long waiting lists. Most of the population using exclusively the public subsector cannot afford private health insurance and are not covered through the social security sector assured by a formal job52. Like many indicators, it has socioeconomic characteristics, since it is directly related with employment status and salary. We used 2021 data42.
Health inequity composite index (HICI)
We developed a Health Inequity Composite Index including six indicators to assess the overall magnitude and the relative Health inequities between the Comunas. The indicator value for each of the fifteen Comunas was first standardized to a Z-score: Z=\(({\mathrm{x}}_{\mathrm{i}}- \overline{\mathrm{x} })/\)s, where x_i = Communas-specific values, x = overall mean of the values, s = standard deviation. Indicators for which a high value reflects a higher health or lower social inequity were multiplied by + 1, whereas indicators for which a high value reflects a lower health or higher social inequity were multiplied by − 1. All six Z-scores for each Comuna were summed into a final composite Z-score to rank the 15 Comunas from lowest to highest health inequity.
We calculated the mean, standard deviation, and coefficient of variation of each indicator. One of the indicators, “percentage of households without sewage connection”, was log-transformed due to a coefficient of variation equal or greater than 100%. Other indicators were approximately normally distributed. Using mean and standard deviation, we obtained each Z-score and the cumulative Z-score. A higher HICI index indicates a higher level of socioeconomic deprivation. We used the Comuna with lower cumulative Z as the reference to compare the HICI within Comunas. Measures of absolute health inequity were calculated as the difference between indicator values in each Comuna and the reference Comuna (with the lowest cumulative HICI Z-score) to characterize the overall burden of inequity for each indicator. Measures of relative health inequity were also calculated as the ratio of each indictor values and the reference Comuna to compare inequities across health outcomes that use different scales. Using these two measures of inequity can help track both the reduction in inequity between groups and the overall elimination of the inequity altogether.
COVID-19 mortality in people 60 years or above
The target population mortality in people 60 years or above as evidence shows older adults were at higher risk of mortality due to COVID-19 during pandemic months of 20201. We used age-standardized mortality rate in 60 years or above (%).
To assess the correlation between mortality from COVID-19 and the HICI we calculated the specific mortality rates (COVID-19) in people 60 years or above by Comuna. We used official secondary data sources from statistical mandatory death certificates with a cause of death labeled as COVID-19 (U07 of the ICD-10), and 2020 population projections53. We age-standardized the mortality rate using Argentina 2010 Census population40.
Ethical considerations
The study did not require evaluation by the ethics committee because it used secondary, publicly available data with no identifiable information54.