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Inequalities in child mortality in ten major African cities.

Quentin W, Abosede O, Aka J, Akweongo P, Dinard K, Ezeh A, Hamed R, Kayembe PK, Mitike G, Mtei G, Te Bonle M, Sundmacher L - BMC Med (2014)

Bottom Line: Significant inequalities were found in Kinshasa, Luanda, Abidjan, and Addis Ababa in the most recent survey.Nevertheless, inequalities appear to have increased in Abidjan, while they appear to have decreased in Cairo, Lagos, Dar es Salaam, Nairobi and Dakar.However, larger samples are needed in order to improve the certainty of our results.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Health Care Management and Berlin Centre for Health Economics Research (BerlinHECOR), Technische Universität (TU) Berlin, Straße des 17, Juni 135, Berlin 10623, Germany. wilm.quentin@tu-berlin.de.

ABSTRACT

Background: The existence of socio-economic inequalities in child mortality is well documented. African cities grow faster than cities in most other regions of the world; and inequalities in African cities are thought to be particularly large. Revealing health-related inequalities is essential in order for governments to be able to act against them. This study aimed to systematically compare inequalities in child mortality across 10 major African cities (Cairo, Lagos, Kinshasa, Luanda, Abidjan, Dar es Salaam, Nairobi, Dakar, Addis Ababa, Accra), and to investigate trends in such inequalities over time.

Methods: Data from two rounds of demographic and health surveys (DHS) were used for this study (if available): one from around the year 2000 and one from between 2007 and 2011. Child mortality rates within cities were calculated by population wealth quintiles. Inequality in child mortality was assessed by computing two measures of relative inequality (the rate ratio and the concentration index) and two measures of absolute inequality (the difference and the Erreyger's index).

Results: Mean child mortality rates ranged from about 39 deaths per 1,000 live births in Cairo (2008) to about 107 deaths per 1,000 live births in Dar es Salaam (2010). Significant inequalities were found in Kinshasa, Luanda, Abidjan, and Addis Ababa in the most recent survey. The difference between the poorest quintile and the richest quintile was as much as 108 deaths per 1,000 live births (95% confidence interval 55 to 166) in Abidjan in 2011-2012. When comparing inequalities across cities or over time, confidence intervals of all measures almost always overlap. Nevertheless, inequalities appear to have increased in Abidjan, while they appear to have decreased in Cairo, Lagos, Dar es Salaam, Nairobi and Dakar.

Conclusions: Considerable inequalities exist in almost all cities but the level of inequalities and their development over time appear to differ across cities. This implies that inequalities are amenable to policy interventions and that it is worth investigating why inequalities are higher in one city than in another. However, larger samples are needed in order to improve the certainty of our results. Currently available data samples from DHS are too small to reliably quantify the level of inequalities within cities.

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Under-five mortality rates by wealth quintiles for 10 African cities, development over time. a: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in ten African cities, more recent surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; * sample size <1,000 children; ** sample size <500 children. b: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in eight African cities, earlier surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; ** sample size <500 children.
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Figure 1: Under-five mortality rates by wealth quintiles for 10 African cities, development over time. a: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in ten African cities, more recent surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; * sample size <1,000 children; ** sample size <500 children. b: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in eight African cities, earlier surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; ** sample size <500 children.

Mentions: Figure 1a shows mean child (under-five years old) mortality rates and rates by wealth quintiles across the ten cities included in the more recent round of surveys. Mean child mortality rates range from about 39 deaths per 1,000 live births in Cairo (2008) to about 107 deaths per 1,000 live births in Dar es Salaam (2010). Because of relatively small sample sizes, point estimates of child mortality rates by wealth quintiles are associated with considerable uncertainty as indicated by large 95% confidence intervals. However, except for Dar es Salaam, where the sample size is particularly small, the richest quintiles always have the lowest child mortality rates, while poorer quintiles have considerably higher rates. In addition, it is clear that the size of the difference between rich and poor and the pattern of the distribution of child mortality rates across quintiles vary across cities, even when considering the large degree of uncertainty.Figure 1b shows child mortality rates calculated from the earlier surveys. Mean child mortality rates in most cities were even higher at the time of the earlier surveys. The degree of uncertainty around point estimates in several cities is even larger than in the later surveys. Nevertheless, the difference between rich and poor appears to have been even greater in these surveys.


Inequalities in child mortality in ten major African cities.

Quentin W, Abosede O, Aka J, Akweongo P, Dinard K, Ezeh A, Hamed R, Kayembe PK, Mitike G, Mtei G, Te Bonle M, Sundmacher L - BMC Med (2014)

Under-five mortality rates by wealth quintiles for 10 African cities, development over time. a: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in ten African cities, more recent surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; * sample size <1,000 children; ** sample size <500 children. b: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in eight African cities, earlier surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; ** sample size <500 children.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4066831&req=5

Figure 1: Under-five mortality rates by wealth quintiles for 10 African cities, development over time. a: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in ten African cities, more recent surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; * sample size <1,000 children; ** sample size <500 children. b: Mean under-five mortality rates (diamonds) and rates by wealth quintiles (with 95% confidence intervals) in eight African cities, earlier surveys. Notes: Quintile 1 = poorest; quintile 5 = richest; ** sample size <500 children.
Mentions: Figure 1a shows mean child (under-five years old) mortality rates and rates by wealth quintiles across the ten cities included in the more recent round of surveys. Mean child mortality rates range from about 39 deaths per 1,000 live births in Cairo (2008) to about 107 deaths per 1,000 live births in Dar es Salaam (2010). Because of relatively small sample sizes, point estimates of child mortality rates by wealth quintiles are associated with considerable uncertainty as indicated by large 95% confidence intervals. However, except for Dar es Salaam, where the sample size is particularly small, the richest quintiles always have the lowest child mortality rates, while poorer quintiles have considerably higher rates. In addition, it is clear that the size of the difference between rich and poor and the pattern of the distribution of child mortality rates across quintiles vary across cities, even when considering the large degree of uncertainty.Figure 1b shows child mortality rates calculated from the earlier surveys. Mean child mortality rates in most cities were even higher at the time of the earlier surveys. The degree of uncertainty around point estimates in several cities is even larger than in the later surveys. Nevertheless, the difference between rich and poor appears to have been even greater in these surveys.

Bottom Line: Significant inequalities were found in Kinshasa, Luanda, Abidjan, and Addis Ababa in the most recent survey.Nevertheless, inequalities appear to have increased in Abidjan, while they appear to have decreased in Cairo, Lagos, Dar es Salaam, Nairobi and Dakar.However, larger samples are needed in order to improve the certainty of our results.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Health Care Management and Berlin Centre for Health Economics Research (BerlinHECOR), Technische Universität (TU) Berlin, Straße des 17, Juni 135, Berlin 10623, Germany. wilm.quentin@tu-berlin.de.

ABSTRACT

Background: The existence of socio-economic inequalities in child mortality is well documented. African cities grow faster than cities in most other regions of the world; and inequalities in African cities are thought to be particularly large. Revealing health-related inequalities is essential in order for governments to be able to act against them. This study aimed to systematically compare inequalities in child mortality across 10 major African cities (Cairo, Lagos, Kinshasa, Luanda, Abidjan, Dar es Salaam, Nairobi, Dakar, Addis Ababa, Accra), and to investigate trends in such inequalities over time.

Methods: Data from two rounds of demographic and health surveys (DHS) were used for this study (if available): one from around the year 2000 and one from between 2007 and 2011. Child mortality rates within cities were calculated by population wealth quintiles. Inequality in child mortality was assessed by computing two measures of relative inequality (the rate ratio and the concentration index) and two measures of absolute inequality (the difference and the Erreyger's index).

Results: Mean child mortality rates ranged from about 39 deaths per 1,000 live births in Cairo (2008) to about 107 deaths per 1,000 live births in Dar es Salaam (2010). Significant inequalities were found in Kinshasa, Luanda, Abidjan, and Addis Ababa in the most recent survey. The difference between the poorest quintile and the richest quintile was as much as 108 deaths per 1,000 live births (95% confidence interval 55 to 166) in Abidjan in 2011-2012. When comparing inequalities across cities or over time, confidence intervals of all measures almost always overlap. Nevertheless, inequalities appear to have increased in Abidjan, while they appear to have decreased in Cairo, Lagos, Dar es Salaam, Nairobi and Dakar.

Conclusions: Considerable inequalities exist in almost all cities but the level of inequalities and their development over time appear to differ across cities. This implies that inequalities are amenable to policy interventions and that it is worth investigating why inequalities are higher in one city than in another. However, larger samples are needed in order to improve the certainty of our results. Currently available data samples from DHS are too small to reliably quantify the level of inequalities within cities.

Show MeSH