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Full Paper The Effects of Public and Private Health Care Spending on Child Mortality in Developing Countries

First Author: Presenting Author Md Juel Rana PhD Research Scholar Population Studies Centre for the Study of Regional Development School of Social Sciences Jawaharlal Nehru University Email: jranajnu@gmail.com Second Author:

• Dr. Srinivas Goli

Assistant Professor Population Studies Centre for the Study of Regional Development School of Social Sciences Jawaharlal Nehru University Email: sirispeaks2u@gmail.com

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Abstract

Though, many developing countries made significant progress in achieving Millennium Development Goal-4 which is a reduction in child mortality to one- third by 2015 but, still numerous countries are lagged behind. In the post-2015 development agenda, the Sustainable Development Goals have the healthy lives to

• all. Hence, this study attempts to evaluate the effects of public and private health

care spending on child mortality in developing countries using World Bank’s

• database. The findings from Random Effects models suggest that the total health

care spending has significant negative effect on child mortality. The public spending is negatively associated with child mortality but the private spending is not associated, rather it becomes supplementary of the public care spending. The public spending on health care in both absolute and relative forms reduce the risk

• f child mortality. It provides universal and equitable health coverage, but the

private sector denies the poor. The public financing in health care system should be increased and the role of private sector should carefully be fixed so that universal and equitable health care utilisation which will result in the better health

• utcome in general and reduced child mortality in particular in developing

countries. Keywords: Public and private health care spending, Health outcome, Child mortality, Developing countries, Random effects.

Introduction

The developed countries experienced a dramatic decline in under-five mortality over the last

• century. The developing countries also followed the same trend after second World War but

the nature of these countries is less optimistic than that of the former one (Mason 1997; Kirk 1996). On the post-2015 development agenda, the United Nations Sustainable Development Goals (SDGs) have healthy lives for all by 2030. The Millennium Development Goal-4 (MDG- 4) had targeted to reduce the one-third child mortality between 1990 and 2015. However, the progress has been made; an estimation showed that only 10 countries out of 67 with high child mortality were on the track for meeting the MDG-4 while in total, only 60 countries out of 195 are on the track (You et al. 2015). World Health Organisation (WHO) estimated that about six million children died in the last year (WHO 2014). The majority of them are were from the

3 developing and lag behind countries of MDG-4 such as Caucasus and Central Asian, Southern Asian, Sub-Saharan African countries. The prevalence of child mortality in developing countries is very high compared to the developed. For instance, one in twelve and one in nineteen child death was in Sub-Saharan Africa and South Asia respectively while the same was one in one hundred and forty seven in developed countries (WHO 2014). The developing countries were poorly performed in curbing the child mortality. Adequate and efficient public health spending on the workforce and infrastructure are widely considered as inevitable to the improvement of child health status and under-five mortality (Ssozi and Amlani 2015; Turner 1991; Pritchard and Williams 2011). Higher public spending

• n health care does not always result in better health outcomes because of efficiency in

spending (Pritchard and Williams 2011). On the other hand, however, private health facilities are assumed to be better health care provider but many times, patients face fraud, over- medication, exploitative pricing and unnecessary surgery (Dreze and Sen 2013; Sreevidya and Sathyasekaran 2003). Studies also found that inaccurate diagnosis and inappropriate treatment are practiced under both public and private health care system (Das et al. 2012; Das and Hammer 2004). The efficient health care spending may translate better health outcome, and it must be reached to the poor particularly in developing countries. Use of private health care facilities increase with the increase in household income because studies found that health care facilities are necessary in the public sector but become luxury in the private sector (Khan and Manumud 2015; Gerdtham et al. 1992; Farag et al. 2012; Barros 1998; Parkin et al. 1987). However, one can argue that the public health care spending may translate better health

• utcomes in developing countries as the public sector may provide universal and equitable

health care facilities to all irrespective of paying capability of service seekers. Economic instability of a country affects changes in the key areas of public funding particularly health, education and infrastructure (Williams and Maruthappu 2013; Horton 2009). The effects of economic crisis on human health are evident with a broad range of health outcome including child health (Ensor et al. 2010; Maruthappu et al. 2015). After the recent global recession and economic crisis, the public health care spending has decreased in many countries (Maruthappu et al. 2015). The lower and lower-middle income countries are more vulnerable to the economic fluctuations (Garenne and Gakusi 2006). The overall public health spending has decreased in many countries while the private health expenditure has grown in developing countries (World Bank 2015). In this backdrop, an analysis of effects of public and private

4 health care spending on health outcome in required in developing countries as these countries are more vulnerable to the economic shocks. A number of studies were carried out to find out the relationship between health expenditure and health outcomes. Some studies found a strong association between an increase in health care spending and health outcome while others find a weak link between them. Novignon et

• al. (2012) shown both public and private health expenditure have a significant effect on

reducing child mortality while the public has stronger effects than the private. Evidence from Lesotho suggests that along with female literacy, availability of physicians and child immunisation, health expenditure significantly improved the status of child health (Akinkugbe and Mohanoe 2009). Another study using panel data analysis and fixed effects model estimated that 10% rise in health expenditure contributes about 21% and 22% fall in child and infant mortality respectively in 47 African countries during 1990-2004 (Anyanwu and Erhijakpor 2007). Other previous studies also came with similar findings that there is a positive association between health spending and health outcome (Gupta et al. 2003; Khan and Mahumud 2015). Baldacci et al. (2008) draw a channel connecting social spending and human capital to economic growth. They found that health spending has a significant positive effect on human capital and economic growth. They advocated that good governance may accelerate the effects

• f health spending on health outcome.

On the contrary, several studies documented that the effects of health spending on health

• utcomes are weak or insignificant and even negative. Gupta et al. (2002) investigated the

cross-sectional data of 50 countries and found that public spending has a weak effect on health

• utcome particularly infant and child mortality. Filmer and Pritchett (1999) found a weak

relationship between the increase in health spending and reduction in mortality. Rather, 95% country level variation in mortality can be explained by some other factors such as country’s per capita income, unequal income distribution, female education, religion and ethnic

• fragmentation. Evidence from 91 countries during 1990-2003 shown that the public health

spending has a weak association with child mortality but the association is more effective in well governed countries while it is insignificant in poorly governed countries (Rajkumar and Swaroop 2008). Other literatures advocate that some socioeconomic and technological factors such as the level of education, income, cultural variation, technological changes make a difference in health outcomes rather than direct health spending (Geweke et al. 2003; Glied and Lleras-Muney 2008). Wagstaff and Cleason (2004) noted that the effects of public health

5 spending on health outcomes are depends on upon the institutional performance and policy interventions in a country. Some researchers argued that the reason behind the weak relationship between health spending and health outcome may be the efficiency of health expenditure and quality of service delivery (Devarajan 1996; Filmer and Pritchett 1999). Yaqub et al. (2012) argued that the reduction in corruption may increase the effectiveness of health spending on health outcomes. Earlier studies widely investigated the effects of health expenditure, especially spending in public sector on health outcome and found a diverse results. Some studies found a strong effect while some found a weak or no significant effect. Some studies also quantified the effectiveness

• f health care spending on health outcomes. No any studies examines the effects of public and

private health spending on health outcomes in comparing manner. This study attempts to evaluate the absolute and relative effects of public health care spending compared to the private in developing countries.

Conceptual Framework

The total health care facilities are availed by both public and private sector in any country with the different percentage of share. The public health care spending is a major concern in low and middle-income countries as people with low income are more likely to choose public health care services because of lower out-of-pocket payment. On the contrary, the households with higher income level have freedom to choose the private health care facilities and services as it is expected that the private facilities (clean facilities, shorter waiting time etc.) might result better than the public. Hence, the private health care facilities deny the poor because of high

• ut-of-pocket payment (Khan and Mahumud 2015; Gupta et al. 2003). However, the more

public health care spending may translate into better health outcome in developing countries as it has universal health coverage than the private (Figure 1). Some socioeconomic, demographic and Water, Sanitation and Hygiene (WASH) factors affect the health status and mortality in childhood (Granados & Sánchez 2014; Filmer and Pritchett 1999; Geweke et al. 2003; Glied and Lleras-Muney 2008). The level of income and economic status of a country is positively associated with the health outcomes, as higher-income people live longer lives than the lower-income (Cutler et al. 2006). A lack of income or household poverty can restrict the supply of food and water in the household and deteriorate the health

6 status of children, as Preston estimated income alone may lift about 15% life expectancy (Preston 1975). A study estimated that the children born to a literate mother are 50% more likely to survive than the illiterate. Increase in the educational level of mothers reduce the risk

• f mortality among their children, further; it is also observed that the child vaccination rate and

nutritional status is significantly higher among the educated mothers than their counterpart (UNESCO 2010; Semba et al. 2008; Blunch 2013). Figure 1: Conceptual Framework Besides, age at marriage and childbearing of women are the crucial component of the health status of mothers as well as their children. Marriages of women during the adolescent period not only restrict the linear and ponderal growth among them but also it adversely affect the physical growth of their children. Those women are more likely to face intrauterine growth retardation (IUGR) and deliver premature birth and with low birth weight (Goli et al. 2015; Rah et al. 2008). These poor delivery outcomes enhance the risk of childhood growth restriction, frequent illness and infectious diseases (Winkvist et al. 1992). Literatures also established the linkage between WASH status and child health. In detail, the poor WASH condition increase the water-sanitation related diseases which are the most significant health problems for children worldwide. Among them, diarrhoea is the most severe disease that increases the mortality rate and opportunistic diseases like acute respiratory infections (ARI) (Arifeen et al. 2010; UNICEF 2015). Globally, ARI and diarrhoea together contribute around GDP per capita Female literacy Adolescent fertility Improved water Public health care Child mortality WASH status Health outcome Socioeconomic factors Demographic factors Health expenditure

Private health care facilities

Universal coverage

Denying access to the poor

7 two third child deaths (Arifeen et al. 2010). Infectious diseases and malnutrition have a vicious cycle between them, and both of them are the major contributor of childhood mortality (Lopez et al. 2006; Black et al. 2008; Arifeen et al. 2010; UNICEF 2015). However, universal health coverage with efficient health care spending can reduce the pervasiveness of worsening the child health and mortality in developing countries.

Data and Methods

Data and Variables The study pooled cross-section and time-series data for the two different time points viz. 1995 and 2013 for 146 developing countries. In the case of unavailability of data in the variables for the study years, the recent score from preceding four years was lifted to replace the missing values in the respective variables. The data used in this empirical analysis were collected from the World Bank, World Development Indicators (WDI). The data on child mortality rate per thousand was used as the dependent variable of this study. The predictor variables viz. the public and private health expenditure were collected in the percentage of Gross Domestic Product (GDP). The three groups of covariates viz. socioeconomic, demographic and WASH variables were considered in the analysis as their relationships with child mortality are mentioned in the conceptual framework. Specifically, three variables from the socioeconomic status of a country were captured particularly GDP per capita in current US$, poverty headcount ratio at 1.25 US$ (percentage of population) and female literacy rate (percentage of the adult female aged 15 years and above). The demographic variables include adolescent fertility rate (births per thousand women aged 15-19 years) and low birth weight (percentage of low weighted births). The adolescent fertility rate capture the nature of early marriage and early childbearing as well as their fertility behaviour. The WASH variables include the percentage of the population accessing improved water source and sanitation facility, as water and sanitation are the leading cause of many diseases and mortality. Initially, all the factors were taken into consideration in the enquiry but during multivariate analysis, one variable from each factor was selected based on theoretical and empirical

• multicollinearity. In particular, GDP per capita (economic factor), female literacy (social

factor), adolescent fertility (demographic factor) and improved water (WASH factor) have been included in the multivariate modelling.

8 Statistical Analysis In this study, univariate, bivariate and multivariate analyses were carried out to draw the

• inferences. In the univariate analysis, mean, standard deviation, minimum, maximum and

number of observation were computed in developing and developed countries separately to describe the characteristics of the study variables. Pearson’s correlation coefficient formula was applied to show the bivariate relationship among the variables. For multivariate analyses, Ordinary Least Square (OLS), Random Effects and Fixed-Effects Models were applied, as these models are widely used to analyse the panel data based on certain assumptions (Maddala 1971; Chamberlain 1982). The adjusted and unadjusted effects of health expenditures on child mortality were estimated. The multivariate regression coefficients have been adjusted for social (female literacy), economic (GDP per capita), demographic (adolescent fertility) and WASH (improved water) factors. Four different set of models were executed to assess the differences in the effects of public and private health spending on child mortality with adjusted for same controlling factors. In model 1, the effects of total health care spending on child mortality were estimated while the same of public and private spending were assessed in model 2 and 3

• respectively. To evaluate the robustness of the effects of public spending compared the private,

the effects of a share of public spending in total health care expenditure were computed in model 4. During the multivariate analysis, Breusch-Pagan LM test was implemented to select the models between Random effects and OLS regression estimation (Breusch and Pagan 1997) and Housman’s specification test were applied to choose the appropriate models between Fixed Effects and Random Effects models (Hausman 1978). All the analysis in this study were carried

• ut using the statistical software Stata version 13 (StataCorp 2013). Breusch-Pagan LM test

and Housman’s specification test suggested choosing the random effects model for all the models of multivariate analyses. Random effects model include the weighted average of the estimates produced by the between and within estimators (Maddala 1971; Chamberlain 1982; StataCorp 2013). The statistical description of Random Effects model is follows 𝑍

𝑗𝑢 = 𝛽𝑗 + 𝛾𝑌𝑗𝑢 + 𝜑𝑗 + 𝜁𝑗𝑢

Where, Yit is the observation on the dependent variable for cross-sectional unit i in a period t, Xit is an independent variable observed for unit i in period t, β is the coefficients of the independent variables, υi is an error between entities and εit is an error within the entity.

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Results

Table 1 presents the summary statistics of the study variables used in this study including 146 developing for the two periods viz. 1995 and 2013. The overall child mortality rate was 30 per thousand, but it ranges from 2 to 208 in different developing countries. Around 6.4% of GDP were spent in health care facilities while public and private sector shared 4.0% and 2.4% of GDP respectively. Public sector shares about 61% of total health care spending. The average female literacy rate was 85%. On an average, 45% women in developing countries delivered their first birth before the age of 18 years and around average 90% households were availed improved water sources in the selected developing countries. Table 1: Descriptive statistics of the study variables in developing countries for 1995 and 2013 Variables Mean SD Min Max Obs Child mortality

• verall

29.94 32.42 2.00 208.50 N = 292 between 29.84 3.65 162.95 n = 146 within 12.81

• 15.61

75.49 T = 2 Total health expenditure (% of GDP)

• verall

6.42 2.63 1.95 17.10 N = 285 between 2.41 2.51 16.16 n = 143 within 1.05 2.84 10.00 T-bar = 1.99 Public health expenditure (%

• f GDP)
• verall

4.00 2.21 0.27 13.81 N = 285 between 2.09 0.89 13.44 n = 143 within 0.70 1.81 6.19 T-bar = 1.99 Private health expenditure (%

• f GDP)
• verall

2.41 1.48 0.21 10.09 N = 285 between 1.31 0.40 8.14 n = 143 within 0.70

• 0.86

5.69 T-bar = 1.99 Public health expenditure (%

• f total health expenditure)
• verall

61.19 18.29 5.22 95.20 N = 285 between 17.29 13.37 92.73 n = 143 within 5.97 44.46 77.92 T-bar = 1.99 GDP per capita (log)

• verall

8.67 1.43 5.36 12.00 N = 288 between 1.30 5.80 11.77 n = 147 within 0.60 6.59 10.75 T-bar = 1.96 Female literacy

• verall

85.63 16.84 28.48 100.00 N = 168 between 15.67 29.47 100.00 n = 107 within 5.45 68.59 102.68 T-bar = 1.57 Adolescent fertility

• verall

45.15 35.50 0.62 168.65 N = 280 between 33.57 1.04 140.98 n = 140 within 11.71 7.94 82.36 T = 2 Improved water

• verall

90.78 12.74 33.60 100.00 N = 280 between 12.30 36.65 100.00 n = 144 within 4.33 75.08 106.48 T-bar = 1.94 Note: SD: Standard deviation; Min: Minimum, Max: Maximum, Obs: Number of observation

10 Table 2 shows the bivariate relationships between child mortality and health expenditures (Figure 2) including its other predictor variables. The results show that the total health care spending is negatively correlated with child mortality (r=-0.34, p<0.01). Specifically, the public spending alone is significantly associated with child mortality (r=-0.43, p<0.01) but the correlation between private health care spending and child mortality (r=0.04) is not significant. As a percentage share of public health care spending increased, the child mortality decreased (r=-0.34, p<0.01). Besides, GDP per capita, female literacy and improved water have a significantly negative association with child mortality while adolescent fertility has a positive relation with it. Figure 2: Relationship between child mortality and health expenditures in developing countries

11 Table 2: Correlation matrix of the study variables of pooled sample of developing countries for 1995 and 2013 Variables Child mortality Total (%

• f GDP)

Public (%

• f GDP)

Private (%

• f GDP)

Public (%

• f total)

GDP per capita Female literacy Adolescent fertility Improved water Child mortality 1 Total expenditure (% of GDP)

• 0.340***

1 Public expenditure (% of GDP)

• 0.433***

0.826*** 1 Private expenditure (% of GDP) 0.044 0.538***

• 0.031

1 Public expenditure (% of total health expenditure)

• 0.419***

0.157*** 0.639***

• 0.676***

1 GDP per capita (log)

• 0.720***

0.326*** 0.481***

• 0.142**

0.481*** 1 Female literacy

• 0.671***

0.362*** 0.467*** 0.018 0.390*** 0.470*** 1 Adolescent fertility 0.680***

• 0.302***
• 0.424***

0.083

• 0.359***
• 0.606***
• 0.484***

1 Improved water

• 0.780***

0.369*** 0.426*** 0.015 0.332*** 0.662*** 0.496***

• 0.610***

1 Note: *** p < 0.01, ** p < 0.05, * p < 0.1

12 Table 3: Results from panel data regression estimation (Random effect model) showing unadjusted and adjusted effects of health expenditures on child mortality in developing countries during 1995-2013 Model 1 Model 2 Model 3 Model 4 Variables Total expenditure (% of GDP) Public expenditure (% of GDP) Private expenditure (% of GDP) Public expenditure (% of Total health expenditure) Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Health expenditure

• 4.13(1.53)***
• 0.99(1.09)*
• 6.24(2.21)***
• 1.31(1.42)*
• 1.15(1.98)
• 0.69(1.67)
• 0.64(0.26)***
• 0.10(0.11)*

GDP per capita

• 9.08(3.45)***
• 8.90(3.42)***
• 9.14(3.16)***
• 8.74(3.54)***

Female literacy

• 0.52(0.29)***
• 0.52(0.28)***
• 0.55(0.28)***
• 0.54(0.26)***

Adolescent fertility

• 0.18(0.13)***
• 0.18(0.13)***
• 0.18(0.13)***
• 0.16(0.13)**

Improved water

• 0.53(0.50)**
• 0.55(0.50)**
• 0.57(0.50)**
• 0.60(0.49)**

Constant 55.80(12.42)*** 197.74(52.32)*** 54.27(10.99)*** 196.75(53.34)*** 32.08(7.24)*** 201.28(53.82)*** 68.51(18.15)*** 203.26(54.03)*** Observations (N) 285 151 285 151 285 151 285 151 R square Within 0.1121 0.6959 0.1068 0.6926 0.0318 0.6939 0.0291 0.6879 Between 0.1163 0.7261 0.203 0.7269 0.0091 0.7232 0.2087 0.7279 Overall 0.1155 0.7341 0.1878 0.7338 0.002 0.731 0.1753 0.7327 Wald Chi2 27.74 119.18 30.64 118.71 1.30 116.36 23.82 126.92 Note: *** p < 0.01, ** p < 0.05, * p < 0.1; The 95% confidence interval (±CI) is reported in the parentheses

13 The results from random effect models assessing unadjusted and adjusted effects of public and private health expenditure on child mortality in developing countries were presented in Table

• 3. Findings demonstrate that the effects of total health care spending on child mortality were

significant after controlling the effects of socioeconomic, demographic and WASH factors (Model 1). It shows that 1% decrease in the GDP in total health care spending would increase 1 child death per thousand (β=-0.99, p<0.1). Individually, the public spending on health care has significant negative effect on child mortality, but the private spending does not (Model 2 and 3). About 1% increase in public spending reduce the risk of 1.3 child death per thousand (β=-1.31, p<0.1). In support of the results from model 2, model 4 reveals that the decrease in public spending as a percentage of total health care expenditure significantly increase the chance of child death (β=-0.10, p<0.1). Along with the public and private health care spending, the other socioeconomic, demographic and WASH factors significantly affects in reducing child mortality in developing countries (Table 3). For instance, results show that the increase in GDP per capita, female literacy, improved water availability significantly reduce the child mortality while the rise in adolescent fertility rate raises the mortality.

Discussion

In this study, an empirical analysis has been made for assessing the effects of the public and private health care expenditure on child mortality in developing countries during the last two

• decades. The findings suggest that the total health care spending including both public and

private significantly reduce child mortality. The public health care spending alone has significant effects on child mortality while the private spending individually does not have, rather it becomes supplementary of the public spending for health outcomes. The public spending on health care in both absolute and relative forms reduce the risk of child mortality as an increase in the public share of total health care spending significantly reduce the child mortality. Studies found that the reduced public health expenditure translates into lesser hospital budgets, which results into scarcity of resources in the hospitals including the health workers (Martin et

• al. 2011; Maruthappu et al. 2015). For instance, the decline in medical supplies and drugs and

salaries for health personnel due to reduced health care spending in the 1970s led to increasing

14 in child mortality (Garenne and Gakusi 2006). It can also worsen health outcomes in several dimensions: poor delivery outcome particularly prematurity of the baby is one of the main cause of new-born death and child mortality. About two-third of these deaths can be prevented if skilled health personnel take care of the baby at the time of birth and in early few days of life (WHO 2015). Public health awareness campaign to recognise the illness and to promote the effective measures of infections, asphyxia, prematurity and low birth weight needs public health findings (Darmstadt et al. 2005). High technological health care infrastructure, in fact, assisted ventilations for neonates is very costly (Darmstadt et al. 2005). Prematurity and low birth weight may lead to malnutrition in the early life (Victora et al. 2008; Winkvist et al. 1992). Infectious diseases particularly ARI and diarrhoea and malnutrition contribute to post- neonatal death sharing around half of the child death (Lopez et al. 2006; Black et al. 2008; Arifeen et al. 2010). Studies found that increase in health care spending especially in vaccination, have significant effects on reducing child mortality (Ssewanyana and Younger 2008). Probably the most cost effective and influential intervention, 100% vaccination of children is considered to reduce 16 per thousand infant deaths (Ssewanyana and Younger 2008). The other quick and efficient interventions like the appropriate treatment of ARI and diarrhoea; and reduction of malnutrition among children translate into a reduction in mortality (Amouzou et al. 2012; Lopez et al. 2006; Black et al. 2008). The private health care spending, mostly spent as out-of-pocket payments, was the most common mechanism for healthcare funding in developing countries. The fundamental component of universal health coverage is to reduce the out-of-pocket payment to the affordable level of common citizens in the country. The universal health coverage needs redistribution of health care facilities and services across poor and rich, healthy and sick people (WHO 2013). It requires political encouragement and policy interventions. The extent of redistribution depends on the distribution of healthcare utilisation across different groups of people (Khan and Mahmud 2015). The health care seeking behaviour often differs across different socioeconomic groups of people. The private health seeking behaviour is mostly pro- rich as compared to the public sector is to the pro-poor (James and Savedoff 2010; Gwatkin et

• al. 2005). The Economic hardship of the household along with access to health care facilities

and degrees of health awareness make a difference in rich-poor health care seeking behaviour (Gwatkin et al. 2005). On this way, private health care facilities are mostly occupied with out-

• f-pocket financing which lacks in the capacity of healthcare redistribution. Hence, the larger

15 public sector will increase the redistributive capacity of health care resources across poor and poor as well as sick and healthy people. In turn for a long run, the public health financing may have effects on the economy of a nation. Reduced investment in public health care may results into the less healthy population in turn to less economic productivity. On the other hand, less effort in preventive measures leads to health worsening and severe diseases which need more expensive care (Martin et al. 2012). Hence, less public health spending may more cost to the national economy (Amiri and Gerdtham 2013; Lawn et al. 2004). Child health particularly infectious diseases and malnutrition contribute a large share of child mortality (Lopez et al. 2006; Black et al. 2008; Gutbrod et al. 2000). Most of the infectious diseases can be prevented, and malnutrition can be minimised through universal and equitable health coverage. Studies found that the universal health coverage through public financing in developing countries prevents the diseases through vaccination and also reduced the malnutrition through nutritional food supply. Evidence from Tamil Nadu (state of India) suggests that the efficient public health spending translated into a very good performance in child immunisation and supply of nutrient food which in turn, results into better child health compared to the major states of India even which have similar economic development like Tamil Nadu (Dreze and Sen 2013). Similarly, public health financing through providing clinical facilities, counselling the parents and ensuring medicine and nutritional food with special attention to vulnerable groups efficiently improved the health outcomes, particularly childhood malnutrition and mortality in Cuba (Cooper et al. 2006; Perez 2009). On the contrary, private health providers deny the universal health care coverage because of high out-

• f-pocket payment (Khan and Mahmud 2015; Economic Research Foundation 2006).

Furthermore, health contingency can push a household with above poverty line into below the line due to high out-of-pocket spending in the private sector (Dreze and Sen 2013). The public health insurance through private health care provisions is also questionable because insurance covered patients could be identified as ‘unprofitable’ in the profit-seeking health care system (Dreze and Sen 2013). Thus, the expectation of universalism and equity in health care facilities from the private sector is a matter of concern. In this regard, the Director-General of WHO in a speech of ministerial meeting emphasised on political commitment and integrated effort at national level for universal health coverage (WHO 2013) said that

16 “Progress towards universal coverage cannot be achieved by health ministers acting alone, even in the presence of political commitment at the highest level of government. It requires a concerted national effort, with an especially close engagement of minsters of health and finance”. This study has several limitations. Firstly, the analysis was carried out on 146 developing countries at the aggregate level; thus the results show combined effect rather than regional or country specific outcome. Secondly, it is tricky to draw a conclusion about causation from a retrospective observation of data as it was used in this study. Thirdly, the changes in economic factors, particularly in health spending may have long-term effects; longitudinal study may be useful for this purpose. Fourthly, inter-year and intra-year (seasonal) variation in mortality have not been modelled the data rather for two periods has been used. Fifthly, efficiency in health care spending has not been considered in the analyses which may make a difference in health

• utcome. Nevertheless, the global data for developing countries which is used in the analysis

is taken from high quality centralised database with free of recall bias. This study used a large volume of data which allowed for robust statistical analysis. Further, the data used in the study are publicly available and can be reproducible.

Conclusion

As the findings of this study suggest, the major transformation in health care system is required to achieve universal and equitable health coverage in the developing countries. The private health care system cannot improve the poor health to the good health even after the insurance coverage but the public sector can do. That identification does not mean that the private sector has no role at all in health outcomes. However, only increase in public health financing is not enough for good health outcomes, but the efficiency and effectiveness of budgetary fund are required because the increase in health care funding not always translate into better clinical health outcome due to poor efficiency (Ssozi and Amlani 2015; Pritchard and Williams 2011). Nevertheless, the governments in developing countries have to re-examine seriously the way in which the private sector is involved in the health care financing. The public financing in health care system should be increased and the role of private sector in health care system should carefully be fixed so that universal and equitable health care utilisation across different income groups irrespective of their paying ability could be addressed which may translate into better health outcome in general and reduced child mortality in particular.

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References

Akinkugbe, O. & Mohanoe, M. (2009). Public health expenditure as a determinant of health status in Lesotho. Social Work Public Health. 24:131-147. doi: 10.1080/19371910802569716

• Amiri. A. & Gerdtham, U. G. (2013). Impact of maternal and child health on economic growth:

New evidence based on Granger causality and DEA analysis. Geneva, Switzerland: Partnership for Maternal, Newborn and Child Health; Available at: http://www.who.int/pmnch/topics/part_publications/201303_Econ_benefits_econometri c_study.pdf, accessed June 13, 2016. Amouzou, A., Habi, O. & Bensaïd, K. for Niger Countdown Case Study Working Group. (2012). Reduction in child mortality in Niger: A countdown to 2015 country case study. The Lancet, 380(9848):1169-1178, doi: http://dx.doi.org/10.1016/S0140- 6736(12)61376-2 Anyanwu, C. J., & Erhijakpor, E. O. A. (2007). Health expenditures and health outcomes in

• Africa. African Development Bank Economic Research Working Paper No 91, Available

at: http://www.afdb.org/fileadmin/uploads/afdb/Documents/Knowledge/25144332-FR- HEALTH-EXPENDITURES-AND-HEALTH-OUTCOMES-IN-AFRICA.PDF, accessed January 12, 2016. Arifeen, S. E., Black, R. E., Caulfield, L. E., Antelman, G., Baqui, A. H., Nahar, Q., Alamgir,

• S. & Mahmud, H. (2000). Infant growth patterns in the slums of Dhaka in relation to

birth weight, intrauterine growth retardation and prematurity. American Journal of Clinical Nutrition, 72:1010-1017. Baldacci, E., Clements, B., Gupta, S., & Cui, Q. (2008). Social spending, human capital, and growth in developing countries. World Development, 36(8):1317-41. doi: 10.1016/j.worlddev.2007.08.003 Barros, P. P. (1998). The black box of health care expenditure growth determinants. Health Economics, 7(6):533–44, doi: 10.1002/(SICI)1099-1050(199809)7:63.0.CO;2-B Black, R. E., Allen, L. H., Bhutta, Z. A., Caulfield, L. E., De Onis, M., Ezzati, M. et al. (2008) Maternal and child undernutrition: Global and regional exposures and health consequences. The Lancet, 371:243-260. doi: http://dx.doi.org/10.1016/S0140- 6736(07)61690-0 Blunch, N. H. (2013). Staying alive: Adult literacy programs and child mortality in rural Ghana. World Development, 42(2):114-126, doi:10.1016/j.worlddev.2012.06.021

18 Breusch, T. S. & Pagan, A. R. (1997). A simple test for heteroskedasicity and random coefficient variation. Econometrica, 45:1287-1294. doi:10.2307/1911963 Chamberlain, G. (1982). Multivariate regression models for panel data. Journal of Econometrics, 18:5-45. doi: 10.1016/0304-4076(82)90094-X Cooper, R. S., Kennelly, J. F. & Ez-Garcia, P. O. (2016). Health in Cuba. International Journal

• f Epidemiology, 35:817-824. doi:10.1093/ije/dyl175

Cutler, D., Deaton, A., & Lleras-Muney, A. (2006). The determinants of mortality. Journal of Economic Perspectives, 20:97-120. doi:10.1257/jep.20.3.97 Darmstadt, G. L., Bhutta, Z. A., Cousens, S., Adam, T., Walker, N. & De-Bernis, L. for Lancet Neonatal Survival Steering Team. (2005). Evidence-based, cost-effective interventions: How many newborn babies can we save? The Lancet, 365(9463):977-988. doi: 10.1016/S0140-6736(05)71088-6 Das, J. & Hammer, J. (2004). Strained mercy: Quality of medical care in Delhi. Economic and Political Weekly, 39(9):951-961. Das, J., Holla, A., Das, V., Mohanan, M., Tabak, D. & Chan, B. (2012). In urban and rural India, a standardised patient study showed low levels of provider training and huge quality gaps. Health Affairs, 31(12):2774-84. doi: 10.1377/hlthaff.2011.1356 Devarajan, S., Swaroop, V., & Zou, H. (1996). The composition of public expenditures and economic growth. Journal of Monetary Economics, 37:313-44. doi: 10.1016/S0304- 3932(96)90039-2 Dreze, A. & Sen, A. (2013). An uncertain glory: India and its contradictions. Penguin Allen Lane, Penguin Books, New Delhi Economic Research Foundation (2006). Government health expenditure in India: A benchmark

• study. Available at: http://www.macroscan.org/anl/oct06/pdf/Health_ Expenditure.pdf,

Accessed January 25, 2015. Ensor, T., Cooper, S., Davidson, L., Fitzmaurice, A., Graham, W. J. (2010). The impact of economic recession on maternal and infant mortality: Lessons from history. BMC Public Health, 10:727. doi: 10.1186/1471-2458-10-727 Farag, M., NandaKumar, A. K., Wallack, S., Hodgkin, D., Gaumer, G. & Erbil, C. (2012). The income elasticity of health care spending in developing and developed countries. International Journal of Health Care Finance Economics, 12(2):145-162. doi: 10.1007/s10754-012-9108-z

19 Filmer, D. & Pritchett, L. (1999). The impact of public spending on health: Does money matter? Social Science and Medicine, 49:1309-1323. doi:10.1016/S0277- 9536(99)00150-1 Garenne, M. & Gakusi, A. (2006). Vulnerability and resilience: Determinants of under-five mortality changes in Zambia. World Devlopment, 34(10):1765-1787. doi: 10.1016/j.worlddev.2006.02.005 Gerdtham, U., Sogaard, J., Andersson, F. & Jonsson, B. (1992). An econometric analysis of health care expenditure: A cross-section study of the OECD countries. Journal of Health

• Economics. 11(1):63-84. doi: 10.1016/0167-6296(92)90025-V

Geweke, J., Gautam, G., Town, J. R. (2003). Bayesian inference for hospital quality in a selection model. Econometrica, 71:1215-1238. Glied, S. & Lleras-Muney, A. (2008). Technological innovation and inequality in health. Demography, 45:741-761. doi: 10.1353/dem.0.0017

• Goli. S., Rahaman, A. & Singh, D. (2015). The effect of early child marriages and early

childbearing on women’s nutritional status in India. Maternal and Child Health Journal 19:1864-80. doi: 10.1007/s10995-015-1700-7 Granados, C. & Sánchez, F. (2014). Water reforms, decentralization and child mortality in Colombia, 1990–2005. World Development, 53(1):68-79, doi: 10.1016/j.worlddev.2013.01.007 Gupta, S., Verhoeven, M., & Tiongson, E. R. (2002). The effectiveness of government spending on education and health care in developing and transition economies. European Journal of Political Economy, 18(4):717-37. doi: 10.1016/S0176-2680(02)00116-7

• Gupta. S., Verhoeven, M., & Tiongson, E. (2003). Public spending on health care and the poor.

Health Economics, 12(8):685-96. doi: 10.1002/hec.759 Gutbrod, T.,Wolke, D., Soehne, B., Ohrt, B. & Riegel, K. (2000). Effects of gestation and birth weight on the growth and development of very low birth weight small for gestational age infants: A matched group comparison. Archives of Disease in Childhood. Fetal and Neonatal Edition, 82:F208-14. doi: 10.1136/fn.82.3.F208 Gwatkin, D., Wagstaff, A. & Yazbeck, A. (2005). Reaching the poor with health, nutrition, and population services: What works, what doesn’t, and why. Washington, DC: The World Bank. Available at: https://openknowledge.worldbank.org/handle/10986/7393, accessed June 13, 2016. Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46:1251-71. doi: 10.2307/1913827

20 Horton, R. (2009). The global financial crisis: An acute threat to health. The Lancet, 373(9661):355-56, doi: http://dx.doi.org/10.1016/S0140-6736(09)60116-1 James, C. & Savedoff, W. (2010). Risk pooling and redistribution in health care: An empirical analysis of attitudes toward solidarity, Health Systems Financing – The path to universal

• coverage. Background Paper 5, World Health Report, Geneva: World Health

Organization; 2010, Available at: http://www.who.int/healthsystems/topics/financing/healthreport/, accessed June 13, 2016. Khan, J. A. M. & Mahumud, R. A. (2015). Is healthcare a ‘Necessity’ or ‘Luxury’? an empirical evidence from public and private sector analyses of South-East Asian countries? Health Economics Review, 5(3):1-9, doi: 10.1186/s13561-014-0038-y Kirk, D. (1996). Demographic transition theory. Population Studies 50:361-387. doi: 10.1080/0032472031000149536 Lawn, J. E., Cousens, S., Darmstadt, G. L., Paul, V., Martines, J. (2004). Why are 4 million newborn babies dying every year? The Lancet, 364(9450):2020. doi: 10.1016/S0140- 6736(04)17511-9 Lopez, A. D., Mathers, C. D., Ezzati, M., Jamison, D. T. & Murray, C. J. L. (2006). Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data. The Lancet, 367:1747-57. doi: http://dx.doi.org/10.1016/S0140- 6736(06)68770-9 Maddala, G. S. (1971). The use of variance component models in pooling cross section and time series data. Econometrica, 39:341-58. Martin, A., Lassman, D., Whittle, L. & Catlin, A. for National Health Expenditure Accounts

• Team. (2011). Recession contributes to slowest annual rate of increase in health spending

in five decades. Health Affairs, (Millwood) 30(1):11-22. doi: 10.1377/hlthaff.2010.1032 Martin, G., Grant, A., D’Agostino, M. (2012). Global health funding and economic

• development. Global Health, 8:8. doi: 10.1186/1744-8603-8-8

Maruthappu, M. Bonnie Ng, K. Y., Williams, C., Atun, R. & Zeltner, T. (2015). Government halth care spending and child mortality. Pediatrics, 135(4):1-8, doi: 10.1542/peds.2014- 1600 Mason, K. O. (1997). Explaining fertility transition. Demography, 34:443-54. doi: 10.2307/3038299 Novignon, J., Olakojo, S. A. & Nonvignon, J. (2012). The effects of public and private health care expenditure on health status in sub-Saharan Africa: New evidence from panel data

21 analysis. Health Economics Review, 2:22. doi: http://www.healtheconomicsreview.com/content/2/1/22

• Parkin. D., McGuire, A. & Yule, B. (1987). Aggregate health care expenditures and national

income: Is health care a luxury good. Journal of Health Economics, 6(2):109-27. doi: 10.1016/0167-6296(87)90002-6 Perez, R. (2009). The Public Health Sector and Nutrition in Cuba, MEDICC Review, 11(4):6- 8. Preston, S. H. (1975). The changing relation between mortality and level of economic

• development. Population Studies, 29:231-48. doi: 10.1080/00324728.1975.10410201

Pritchard, C. & Williams, R. (2011). Poverty and child (0-14 years) mortality in the USA and

• ther Western countries as an indicator of “how well a country meets the needs of its

children” (UNICEF). International Journal of Adolescent Medicine and Health, 23(3): 251-55. doi: 10.1515/ijamh.2011.052 Rah, J. H., Christian, P., Shamim, A. A., Arju, U. T., Labrique, A. B. & Rashid, M. (2008). Pregnancy and lactation hinder growth and nutritional status of adolescent girls in rural

• Bangladesh. Journal of Nutrition, 132:1505-11.

Rajkumar, A. S., & Swaroop, V. (2008). Public spending and outcomes: Does governance matter? Journal

• f

Development Economics, 86(1):96-111. doi: 10.1016/j.jdeveco.2007.08.003 Semba, R. D., De-Pee, S., Sun, K., Sari, M., Akhter, N. & Bloem, M. W. (2008). Effect

• f parental formal education on risk of child stunting in Indonesia and Bangladesh:

A cross-sectional

• study. The

Lancet, 371:322-28. doi: http://dx.doi.org/10.1016/S0140-6736(08)60169-5 Sreevidya, S. & Sathyasekaran, B. W. C. (2003). High caesarean rates in Madras (India): A population based cross-sectional study. BJOG: An International Journal of Obstetrics and Gynecology, 110(2):106-11. doi: 10.1046/j.1471-0528.2003.02006.x Ssewanyana, S. & Younger, S. (2008). Infant mortality in Uganda: Determinants, trends and the Millennium Development Goals. Journal of African Economics, 17(1):34-61. doi: 10.1093/jae/ejm004 Ssozi, J. & Amlani, S. (2015). The Effectiveness of Health Expenditure on the Proximate and Ultimate Goals of Healthcare in Sub-Saharan Africa. World Development, 76(12):165-

• 79. doi: http://dx.doi.org/10.1016/j.worlddev.2015.07.010
• StataCorp. (2013). Stata: Release 13. Statistical Software. College Station, TX: StataCorp LP.

22 Turner, R. (1991). Better access to health services in Nicaragua lowered infant mortality. International Family Planning Perspectives, 17:77-78. doi: 10.2307/2133563

• UNESCO. (2010). Education Counts: Towards the Millennium Development Goals. Paris:

UNESCO. Available at: http://unesdoc.unesco.org/images/0019/001902/190214e.pdf, accessed February 23, 2016.

• UNICEF. (2015). How WASH relates to health, education and development. UNICEF: Water,

Sanitation and Hygeine. Avialable at: http://www.unicef.org/wash/index_healthandeducation.html, accessed January 05, 2016. Victora, C. G., Adair, L., Fall, C., Hallal, P. C., Martorell, R., Richter, L. et al. (2008). Maternal and child undernutrition: Consequences for adult health and human capital. The Lancet 371:340-57. doi: http://dx.doi.org/10.1016/S0140-6736(07)61692-4 Wagstaff, A. & Cleason, M. (2004). The millennium development goals for health: Rising to the challenge. Washington DC: The World Bank. Available at: http://web.worldbank.org/archive/website01063/WEB/IMAGES/296730PA.PDF, accessed December 11, 2015. Williams, C. & Maruthappu, M. (2013). Health economic crises: Public health and neoliberal economic crises. American Journal

• f

Public Health, 103(1):7-9. doi: 10.2105/AJPH.2012.300956 Winkvist, A., Rasmussen, K. M. & Habicht, J. P. (1992). A new definition of maternal depletion syndrome. American Journal of Public Health, 82(5):691-94. World Bank (2015). The World Development Indicators. Available at: http://data.worldbank.org/data-catalog/world-development-indicators, accessed January 27, 2015. World Health Organisation [WHO] (2013). Ministerial meeting on universal health coverage. Available at: http://www.who.int/dg/speeches/2013/universal_health_coverage/en/, accessed June 13, 2016. World Health Organisation [WHO]. (2014). Children: Reducing mortality. Media Centre: World Health Organisation. Available at: http://www.who.int/mediacentre/factsheets/fs178/en/, accessed December 11, 2015. World Health Organization [WHO]. (2015). Child mortality and causes of death. Geneva, Switzerland: WHO. Available at: http://www.who.int/gho/child_health/mortality/causes/en/. Accessed June 13, 2015.

23 Yaqub Ojapinwa & Yussuff (2012). Public Health Expenditure and health outcome in Nigeria: the impact of governance. European Scientific Journal, 8(13):189-201. You, D., Hug, L., Ejdemyr. S. & Beise, J. for United Nations Inter-agency Group for Estimation

• f Child Mortality. (2015). Levels and trends in child mortality. UNICEF, WHO and The

World Bank: UN-DESA Population Division. Available at: http://www.unicef.org/media/files/Levels_and_Trends_in_Child_Mortality_2014.pdf, accessed February 25, 2015. ****************************