Corruption is a complex problem which threatens the impact of public investments, health care access and services, equity and outcomes [1], [2]. Increasingly, health sector leaders, and citizens of all countries, are recognizing the pernicious effects of corruption both at micro and macro levels, and the need to take action [1], [3], [4]. At the level of individuals and households, there is mounting evidence of the negative effects of corruption on the health and welfare of citizens [5], [6]. The 2006 report of transparency International asserts that the corruption level undermines the achievement of the Millennium Development Goal (MDGs) and that the corruption is one of the primary causes of the fact that the global community is already off target to meet the MDGs [1]. Based on literature and previous works, Vian et al. [2] distinguished 7 areas in the health sector where corruption could have pejorative health consequences: construction and rehabilitations of health facilities, purchase of equipment and supplies, distribution and use of drugs, regulation of qualities in products, education of health professionals, medical research, and provision of services by medical personnel.

Health impacts of corruption can not be only summarized as those acting directly on health access and services. For example, nearly 1.2 billion people in the world do not have guaranteed access to water and more than 2.6 billion are without adequate sanitation, with devastating consequences for development and poverty reduction. In developing countries, about 80 per cent of health problems can be linked back to inadequate water and sanitation [7]. The human consequences of this water crisis are devastating and affect the poor and women most of all. Experts concur that the water crisis is a crisis of water governance where, as suggested elsewhere, corruption could be one of the main cause and catalyst for this crisis and that it could affect all aspects of the water and sanitation sector, from resources management to services [8]. More globally corruption was shown to affect all domains of life from education to economic performances [4] and thought these ways could also impact health outcomes.

Among major health problems, child mortality is one of the most preoccupying. In 2006, for the first time since records have been kept, the number of children dying before their fifth birthday fell below 10 million, to 9.7 million. In 2008, it was estimated that 8.795 million deaths under 5 years of age occurred worldwide (figure 1). This milestone follows a long-term decline in the global under-five mortality rate since 1960. However, many countries still have high levels of child mortality, particularly in sub-Saharan Africa and South Asia, and in recent years have made little or no progress in reducing the number of child deaths. This global progress is insufficient to achieve MDGs in which reduction of mortality is crucial. The United Nations aim to decrease the child mortality rate by two-thirds between 1990 and 2015 [9], [10]. By its influences on health, water/sanitation services, education and economic development, corruption could potentially have a great impact on the dynamics of child mortality. However quantitative data on this subject at a population scale are poor. To our knowledge, the most recent study quantifying the specific link between these two variables was the one realised by Abed and colleagues [3]. This study, in 2002, observed a significant link between corruption level and child mortality but only incorporated a limited set of adjustment variables and was made using 10 years old data. A more recent vision of current global impacts of corruption on child mortality is needed to implement efficient programs and improve children survival.

In this perspective, data on national under five mortality rates, the classical risk factors of child mortality, and corruption level were gathered circa 2008. By using linear regressions, this ecological study aimed to 1) assess at a country scale the current impacts of corruption on global children mortality rate after adjusting with a large set of variables, and 2) roughly calculate the number of children deaths attributable to corruption.

National data on under five years deaths per 1000 live births and CPI in 2008 are shown in figure 1. Variables that can potentially explain inter-country variation in the child mortality rate were summarized in table 1. In 2008, the child mortality rate varied from 1.027 (Slovenia) to 195.188 (Afghanistan) per 1000 live births with a world median at 11.789.

A synthesis of Pearson's correlations between all quantitative variables used in this analysis was presented in figure 2 (obtained with a Focused Principal Components Analysis). The six variables the most correlated with log of mortality rate in children were: the log of health expenditure per capita (r = −0.87), the log of GDP per capita (r = −0.86), the percentage of people with access to improve sanitation (r = −0.84), the dependency ratio (r = 0.81), the food supply (r = −0.78) and the perceived corruption (r = −0.76). The six variables the most correlated with the perceived corruption index were: the health expenditure per capita (r = 0.82), the GDP per capita (r = 0.78), civil liberties index (r = −0.69), the food supply (r = 0.66), the political rights index (r = −0.64) and percentage of rural people (r = −0.58).

In the univariate analysis, all predictor variables (excepted battle-related deaths/person) were significantly associated (p<0.001) with child mortality (Table 2). The coefficient for the corruption perception index [β = −0.2482; 95% C.I: −0.2482; −0.1906] in the univariate model would mean that an increase in 1 point of the CPI would decrease the logarithm transformation of children deaths per 1000 live births by 0.2482.

For child mortality rates, the final multivariable model (adjusted R² = 0.890) included the following significant variables: percentage of people with improved sanitation (p.value<0.001), logarithm of total health expenditure (p.value = 0.006), CPI score (p.value<0.001), presence of an arid climate on the national territory (p = 0.006), and the dependency ratio (p.value<0.001). In this model, presence of a warm temperate climate on the national territory and DTP vaccination coverage were also found as almost significant (p<0.1). Incorporation of the CPI in the model increased the adjusted R² from 0.8736 to 0.8897 (+1.61%). The coefficient for the corruption perception index [β = −0.0644; 95% C.I: −0.0954; −0.0334] in the final multivariate model would mean that a decrease in 1 point of the CPI score would increase the log of child deaths per 1000 live birth by 0.0644.

Plot of residuals versus predicted values and qqplot did not revealed particular pattern and indicated that homoscedasticity and normal hypothesis were respected in the final linear model. Variance inflation factors of variables included in the final model were also found to be lower than 5 showing that the magnitude of multicollinearity was low.

Ecological studies have their limitations (i.e. bias, confounding) [33]. The available data in a country may not have been sufficient to reflect the local variations of all the studied variables. This study was limited to a one year period (2008) and, due to the lack of data, some important variables to explain child mortality (as breastfeeding for example [34]) could not be included in the present analysis. Furthermore, several variables were based on estimations made by the United Nations and their quality could vary greatly compared to other objective data used in this analysis. However, all the data used in this analysis is the only available to study the problem at this scale. Although there are limitations, the fact that the present analysis came to similar observations on suspected and described phenomenon acting on child mortality rates is unlikely to have been due to a statistical artefact.

The linear regression analysis presented here, after taking into account known significant predictors of children deaths (mainly health expenditure, sanitation level, dependency ratio and arid climate) seems to point towards a significant pejorative link between perceived corruption and death rate at national level. In this model, a decrease in CPI of one point (i.e. a more important perceived corruption) was associated with an increase in log of national child mortality rate of 0.0644. The adjustment of the final model was very good (Pseudo R² = 0.89) meaning that 89% of the data variability was captured by modelisation. Incorporation of CPI in the final model made a rise in the Pseudo R² of 1.61%. According to this result, it could be hypothesized that roughly 1.6% of world deaths in children could be explained by corruption meaning that, of the annual 8.795 million children deaths, more than 140000 annual children deaths could be indirectly attributed to corruption.

By its simplistic nature, the model constructed here, has probably a non negligible tendency to underestimate the effects of corruption on children deaths. As shown elsewhere, across different country contexts, corruption has been a cause and consequence of poverty and so could possibly directly impacts the others significant parameters retrieved by the analysis, especially the percentage of population with adequate access to sanitation [35] and the public health expenditure [36]. Growing evidence from around the world indicates that corruption, fraud, and abuse are also resulting in significant losses of public money and denial of good quality health and sanitation services to millions of people [1], [2], [4], [7]. The diversity of health and water/sanitation systems worldwide, the multiplicity and complexity of parties involved make it difficult to determine the overall impacts of corruption in children deaths around the globe. Local studies have to be made to elucidate the underground complexity of the relation between child health, socio-economic conditions, and corruption.

This study is a first step in the quantification of the current global impact of corruption on child deaths in human populations and shows that annually at least 140000 children deaths could be related to corruption, a total that largely exceeds the conspicuous pooled total of cholera, rabies, Ebola and combat-related deaths. But still, because the equation corruption = deaths is seldom explicit, corruption only seems like a nuisance.

The global response to child deaths must involve a necessary increase in funds available to 1) develop water and sanitation access and 2) purchase new methods for prevention, management, and treatment of major diseases killing children around the globe (principally pneumonia, diarrhoea and malaria). However, without paying attention to the anti-corruption mechanisms needed to ensure their proper use, it will also provide further opportunity for corruption. In practice, donors and governments still treat health, water/sanitation access and corruption as separate rather than integral components of the same strategy. To address these obstacles, designing dedicated indicators at micro and macro levels which monitor efficiently corruption impacts on health and heath related services, is urgently needed. Policies and interventions supported by governments and donors must integrate initiatives that recognise how health and corruption are inter-related.