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South American Children’s Quality of Life: Intra-Urban Disparities along Life-Cycle Indicators

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Abstract

By 2015, 80% of the population in South America was living in urban areas. Although children in urban areas, on average, enjoy better conditions than children in rural areas, millions of urban children struggle to overcome poverty. There is no “urban advantage” in terms of Quality of Life for them. In this context, understanding the inequalities affecting urban children is imperative. Although there is a large body of quantitative analysis on urban-rural disparities, inequities within cities are under-explored. This knowledge is crucial for promoting and designing policies to promote Quality of Life among children and adolescents in the region. This article describes evidence on intra-urban inequalities affecting children’s and adolescents’ Quality of Life and the full realization of their rights in South America. These results stem from Household Surveys covering the last 10 years. Based on housing characteristics, income level and parents’ educational status, households were classified in three groups: experiencing highly deprived, moderately deprived or non-deprived living conditions. Relative and absolute gaps for several indicators were analyzed to compare children living in highly deprived and non-deprived households. In most countries, intra-urban disparities are larger than urban-rural ones. Also, urban children in highly deprived living conditions fare worse than the average rural child. Thus, it is important to focus on highly deprived urban children. Local/municipal governments have plenty of authority to design and implement policies specifically addressing urban children and their Quality of Life.

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Fig. 1

Source: Own calculations based on household surveys

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Notes

  1. Household surveys from the last 10 years were analyzed. For some countries, when available, several surveys were used.

  2. All Countries (except Venezuela) are reviewed.

  3. Which explains why SDG 11 is about sustainable cities and that the United Nations adopted the New Urban Agenda in 2016 which unequivocally emphasizes the importance of equity for livable cities.

  4. Following the Convention of the Rights of the Child, children are defined up to 18 years of age. When needed, for instance depending on the indicators being discussed we differentiate children from adolescents.

  5. Inequalities, which like disparities refer to quantitative differences, should be distinguished from inequities, which refer to value judgements about the differences being unfair and avoidable. From a social justice perspective, we deem all the quantitative differences described in this paper as inequities. Nevertheless, as we concentrate on their measurement we will refer to them (interchangeably, in order to avoid repetition) as inequalities and disparities.

  6. Very good exceptions are the studies by Martinez (2016) and Linares et al. (2016), albeit they focus only on one and two cities respectively.

  7. These are not subjective measures but they do include external components of Quality of Life (Diener 2006).

  8. National household surveys (homogenized by SITEAL): Argentina (2010), Bolivia (2007), Brazil (2009), Colombia (2010), Chile (2009), Ecuador (2009), Paraguay (2009), Peru (2009), and Uruguay (2009). With the exception of Argentina, this study uses databases homogenized provided by SITEAL.

    Demographic and Health Survey (DHS): Bolivia (2008), Colombia (2010), Peru (2008).

    Multiple Indicators Cluster Surveys (MICS): Guyana (2006–2007) and Suriname (2006). Results for these two countries are included in all the totals but sometimes are not shown separately due to the small sample size.

  9. This paper uses UN Habitat operational definitions for housing deficiency. Some variations have been incorporated due to data limitations. For example, information on sanitation and tenure has not been included. The information on access to water is measured by access to public water supply, while UN Habitat considers access to nearby drinking water at a low cost. These indicators, albeit with some exceptions are also used to measure multi-dimensional child poverty (Gordon et al. 2003, Minujin et al. 2006, and CONEVAL 2010, 2011).

  10. Nor do we distinguish among non-poor and rich for households earning income above the poverty line. This is done for simplicity and ease of exposition.

  11. For Ecuador, the database did not include information on housing conditions. Therefore, only poverty and level of education were used (and poverty was further divided using a threshold of half of the poverty line to approximate high deprivation).

  12. Birth registration is also included. Although it is not usually considered an Output indicator, it is a fundamental child right. Also, it is a “gate-keeper” – as it helps to determine age, it allows access to school, family/child subsidies, juvenile justice system, etc. Moreover, it would be difficult to place it either as an Input or Throughput. However, it could be considered loosely related to the Strength of the Local Community. In addition, Johansson (2002) also mentions housing and amenities which we have used to classify the type of households so we cannot use them as dependent variables.

  13. Thus, we do not need to define it. We also avoid the issue of choosing between hedonistic, objectivistic, or other types of lists (Brey 2012).

  14. Calculations were based on the aggregate number of individuals in each of the independent variables categories. These were considered for each of the countries with available data.

    In countries with DHS and MICS calculations were based on the original weights (not expanding the total population) using the population data from the year in which the survey was conducted.

    There are no available data for rural areas of Argentina. In this case, urban data were used for both the total results at the national level as well as for the results within urban areas.

  15. Also, due to the sample size, it is not possible to reliably disaggregate the rural population to measure intra-rural disparities. Nevertheless, this is an area worth exploring.

  16. When we indicate “Half of the countries”, we are referring to those with data from MICS and DHS (because the other surveys did not include these indicators): Bolivia, Colombia, Guyana, Peru, and Suriname. Otherwise, information for all the countries (except Venezuela) is available.

  17. For lack of space we do not address deficiency of micronutrients, nor obesity which is a growing problem in the region (Rivera et al. 2013, Caballero et al. 2017, Corvalán et al. 2017)

  18. Physical Access for students with disabilities is more of a school design issue (ECLAC and UNICEF 2013) but in many cases providing transportation for students with certain disabilities should be the competency of municipal governments.

  19. Although this estimate is lower than other existing ones (e.g. Espejo and Espindola 2015, Minujín et al. 2016), the distribution (e.g. across countries or in terms of urban-rural differences), which is the concern of this paper, is similar.

  20. However, it is important to unpack the difference between adolescent girls and boys within the NEETs. When the type of labor participation of many adolescent boys and the household chores carried out by adolescent girls (at home of for other families) are taken into account, a very strong element of gender discrimination is found (Minujín et al. 2016).

  21. In addition, providing early child care could also free up time of adolescent girls (who usually have to look after their younger siblings) to study and participate in activities with their peers.

  22. Child and adolescent participation, important elements for Quality of Life, are among the central elements of Child Friendly Cities and Urban Planning for Children promoted by UNICEF (UNICEF 2012).

  23. For all indicators with estimates from more than half of the countries, the correlation between intra-urban relative gaps and Gini Coefficients hovers only around 0.55.

  24. This results is similar to Binswanger’s (2006) but in terms of inequalities instead of levels of income.

  25. The New Urban Agenda establishes a “vision of cities for all, referring to the equal use and enjoyment of cities…without discrimination of any kind…where all persons are able to enjoy equal rights and opportunities” (United Nations 2017).

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Authors and Affiliations

  1. University of Buenos Aires and Equity for Children, Buenos Aires, Argentina

    Diego Born

  2. UNICEF Cuba, Habana, Cuba

    Victoria Colamarco

  3. UNICEF, New York, NY, USA

    Enrique Delamónica

  4. Equity for Children, The New School, New York, NY, USA

    Alberto Minujín

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  1. Diego Born
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  2. Victoria Colamarco
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  3. Enrique Delamónica
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  4. Alberto Minujín
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Correspondence to Diego Born.

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Born, D., Colamarco, V., Delamónica, E. et al. South American Children’s Quality of Life: Intra-Urban Disparities along Life-Cycle Indicators. Applied Research Quality Life 14, 799–817 (2019). https://doi.org/10.1007/s11482-018-9607-2

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