Behzad Karami Matin

Khalil Moradi

Satar Rezaei

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Int J Pediatr, Vol.3, N.1-2, Serial No.14, February 2015                                                                                                    441 
Original Article (Pages: 441-447) 
 
http:// ijp.mums.ac.ir 
 
Macro Determinants of Infant Mortality in ECO 
Countries:Evidence from Panel Data Analysis 
Satar Rezaei
1
, Khalil Moradi
2
, *Behzad Karami Matin
11 
1 School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran. 
2 School of Nursing and Midwifery, Kermanshah University of Medical Sciences, Kermanshah, Iran. 
 
 
Abstract 
Introduction 
Infant Mortality Rate (IMR) is widely used to assessing the health status of population in both developing 
and developed countries. The aim of this study was to identify the main factors affect infant mortality in 
the Economic Cooperation Organization (ECO) countries for the years 2005 to 2012. 
Materials and Methods  
A panel data model from ECO countries between 2005 and 2012 was used to identify the effect of some 
of key explanatory variables [Gross Domestic Product (GDP) per capita, Female Labour Participation 
Rate, Public expenditure as percentage of Total health expenditure and Total Fertility Rate] on infant 
mortality. The data was obtained from World Bank and World Health Organization.  Also, the data 
analyzed by STATA version_12.  
Results 
This study indicated the GDP per capita and public spending had a negative and significant effect on 
infant mortality in studied countries. A higher total fertility rate is also associated with higher infant 
mortality. In addition, our analysis showed there is not association significant between female labour 
participation rate and infant mortality. 
Conclusion 
GDP per capita, public expenditure as % of total health expenditure and total fertility rate were identified 
as the main determinant of infant mortality in ECO countries between 2005 and 2012. We hope the results 
of current study provide useful information for health policy- makers to better understand the main factors 
affecting on infant mortality. 
Key Words:  Determinants, ECO countries, Infant mortality, Panel data. 
 
                                                            
*Corresponding Author:  
Behzad Karami Matin, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran. 
Email: BKM_1340@yahoo.com 
Received date: Jan 5, 2014 ; Accepted date: Jan 22, 2015 
Infant Mortality in ECO Countries 
Int J Pediatr, Vol.3, N.1-2, Serial No.14, February 2015                                                                                                     442 
Introduction 
Infant mortality generally is defined as 
deaths before the reaching the first year of 
life. Usually one of the main indicators and 
most widely used for assessing health status 
of a population is infant mortality rate per 
1000 live births. It is believed that the infant 
mortality is reflected an improper children 
care and is also closely associated with well-
being in a given regions or country (1-4). 
This is demonstrated that factors affecting 
on health status in a given country could be 
impact on infant mortality in its community. 
Most of studies both in developed and 
developing countries have been evaluated 
the main factors affecting on infant mortality 
rate (5-9). In these studies, the GDP per 
capita, health expenditures, female labour 
participation rate, fertility rate and etc. were 
identified as the main explanatory variables 
affecting on infant mortality rate.  
Rezaei et al. investigated the main 
determinant of infant mortality in Iran from 
1967 to 2012 years by time series 
approaches. They concluded the total 
fertility rate, percentage of people living in 
rural regions, number of physicians and 
mean years of schooling were the main 
factors affecting on infant mortality rate (8). 
Also, there is high level of infant mortality 
rate in regions which have suffered from 
unsuitable live conditions, inappropriate 
socioeconomic status and inequalities of 
health. According to a report by UNICEF, 
published in 2011, annually 11 million 
infant die throughout the world which about 
90 % of them occur in Low and Middle 
Countries (LMICs) (10); Or a report 
published in 2009 by United Nation 
demonstrated there is a huge gap between 
developed and developing countries in terms 
of infant mortality rate. The infant mortality 
rate per 1000 live births varied from 5 in 
developed countries to 51 for the developing 
countries.  
Understanding of main factors of infant 
mortality and its relative importance for 
health policy making and health planning is 
essential tool to implementation of effective 
programme in order to reduce infant 
mortality in each country or regions. 
Therefore this study aimed to investigate the 
effect some of main factors and its severity 
on infant mortality over an eight-year span 
from 2005 to 2012 by unbalanced panel data 
approach in Economic Cooperation 
Organization (ECO
12
) countries (Figure.1). 
We hope our study provides useful 
information and valuable for health planning 
and enable health policy-makers to better 
understand the factors affecting infant 
mortality in studied countries.  
 
Fig. 1: Map of ECO Member States 
                                                            
1 Azerbaijan, Iran,  Kazakhstan, Pakistan, 
Turkmenistan, Tajikistan, Turkey, Uzbekistan, 
Afghanistan , Kyrgyz Republic.  
  
Rezaei et al. 
Int J Pediatr, Vol.3, N.1-2, Serial No.14, February 2015                                                                                                    443 
Materials and Methods 
This was a cross sectional descriptive 
study. We used unbalanced panel data of 
ECO countries (10 countries) between 2005 
and 2012. The reason why we used ECO 
countries is that these countries are similar 
regarding to the some of the socioeconomic 
and social indicators. The data on infant 
mortality rate per 1000 live births, total 
fertility rate per women, GDP per capita 
(current US$), public health expenditure as 
% of total health expenditure and female 
labor force participation rate (% of female 
population ages 15 and above) were 
obtained from World Bank and World 
Health Organization data bank.  
The primary model was used as: 
IMR= F (gdp, tfr, pexp, flp) 
These variables were extracted through 
literature review and their availability. 
Finally, we used log-log model (Cobb 
Douglas) to determine the main factors 
affecting on infant mortality in ECO 
countries. In this model, the coefficient 
shows how percentages the infant mortality 
rate is changed by per 1 % changes in 
explanatory variables. So, the β1 to β4 
indicate the elasticity of infant mortality rate 
with regard to the explanatory variables.  
Limr= β0 + β1Ltfrit + β2Lgdpit + β3Lpexpit + 
β4Lflpit + ɛit 
Where: 
i indicates countries and t indicates time 
period; Limr: the logarithm of infant 
mortality rate per 1000 live births;  
Ltfr: the logarithm of total fertility rate per 
women;  
Lgdp: the logarithm of GDP per capita 
based on current $US; 
 Lpexp: the logarithm of public health 
expenditure as % of total health expenditure;  
Llfp: the logarithm of the logarithm of 
female labor force Participation rate.  
 In addition, we used the F- Limer test (for 
choosing panel or pool data). If the null 
hypothesis is rejected, the panel data is 
preferred. In the panel data, we used 
Hausman test to determine whether to 
choose random effects or fixed effects 
models for analysis. In the Hausman test: 
H0: random effects would be consistent and 
efficient; 
 H1: random effects would be inconsistent. If 
the null hypothesis is rejected, the fixed 
effect estimator is consistence. Also, the 
Modified Wald test for heteroscedasticity in 
panel data is performed. The data analysis 
was done by Stata version_12.    
Results 
During the study period, Iran (18) and 
Afghanistan (77.8) countries had a highest 
and lowest average of infant mortality rate, 
respectively. The average of IMR per 1000 
live births was 42.3 (range: from 84 to 15) in 
ECO countries. The descriptive statistics of 
variables used in the study are presented in 
(Table.1). 
 The average of highest and lowest total 
fertility rate was related to the Afghanistan 
(6.05) and Iran (1.9) countries, respectively.  
 
 
Infant Mortality in ECO Countries 
Int J Pediatr, Vol.3, N.1-2, Serial No.14, February 2015                                                                                                     444 
    Table 1: Descriptive statistics of variables used in the study in ECO countries, 2005-2012 
Variables Mean SD Min Max Observations 
 
imr 
overall  
42.37 
20.8 15 84 N= 80 
between 21.5 18 77.8 n=10 
within 3.5 36 49.7 T=10 
 
tfr 
overall  
      2.96 
1.2 1.8 6.9 N= 80 
between 1.24 1.9 6.05 n=10 
within 0.21 2.05 3.8 T=10 
 
flp 
overall  
41.6 
18.7 14 68 N= 80 
between 19.6 14.8 66.4 n=10 
within 1.16 38 44.6 T=10 
 
gdp 
overall  
 4369.6 
3657 252 12120 N= 80 
between 3540 449 9323 n=10 
within 1396 132 8481 T=10 
 
pexp 
overall  
42.37 
18.9 9.2 75 N= 80 
between 19.2 16.7 71.8 n=10 
within 4.2 30.3 51.2 T=10 
The trend of infant mortality rate between 
2006 and 2011 in ECO countries is shown in 
(Figure.2). As can be seen, the IMR 
decreased in all countries during the study 
period. For example, the IMR per 1000 live 
births in Iran was decreased from 22 in 2007 
to 15 in 2012; or the IMR per 1000 live 
births in Pakistan decreased from 80 in 2007 
to 71 in 2012. Overall the average of IMR 
per 1000 live births in ECO countries 
decreased from 47.8 at the beginning of the 
study to 37.3 at the end of the study. 
        
 
             Fig.2: Infant mortality rate per 1000 live births in ECO countries, 2005-2012
Rezaei et al. 
Int J Pediatr, Vol.3, N.1-2, Serial No.14, February 2015                                                                                                    445 
The results of F-Limer, Hausman and 
modified Wald tests are depicted in (Table. 
2). The results indicated that the panel data 
in against pool data is appropriated. Also, 
the results of Hausman and modified Wald 
revealed that the random effect is preferred 
and there are heteroscedasticity among the 
residuals of the model. Because of having a 
heteroskedasticiy, estimating the model with 
ordinary least square estimator will results in 
wrong t statistics, so we employed the 
Generalized least squares (GLS) random 
effects model which deletes the effects of 
heteroskedasticiy.   
 
       Table 2: Results of F limer, Hausman and modified Wald tests 
Tests Statistics P-value 
F Limer                    F(9,66)= 381 <0.001 
Hausman test                    Chi2 = 0.86 0.93 
Modified Wald                    Chi2 = 93 <0.001 
 
The estimate of GLS random effect model is 
presented in (Table.3). The results showed 
that Total Fertility Rate (TFR) had a positive 
and significant impact on infant mortality 
rate in Eco countries during the study 
period. The coefficient of TFR was 3.12 that 
this indicates a 10 % increases in TFR will 
leads to approximately 3 % increase in 
infant mortality rate. 
 
The current study indicated there are 
significant and negative associations 
between GDP per capita and public health 
expenditure as % of total health expenditure 
with infant mortality. Also, there is not 
significant relationship between female 
labour participation rate and infant mortality 
rate.  
 
Table 3: Econometric results of determinants of infant mortality rate in ECO countries (2005-2012) 
by GLS-random effect model    
     Variables Coefficients SD p>|z| 95% Conf. Interval 
Lower limit Upper limit 
Ltfr 3.12 0.88 <0.001 1.39 4.85 
Llfp -0.15 0.16 0.35 -0.47 0.16 
Lgdp -0.001 0.00014 <0.001 -0.0021 -0.0015 
Lpexp -0.29 0.05 <0.001 -0.39 -0.19 
c 59 8.7 <0.001 42 77 
                                                            Within = 0.80   
          R-square                                                  Between = 0.63 
                                                                             Overall = 0.63 
 
 
 
 
Infant Mortality in ECO Countries 
Int J Pediatr, Vol.3, N.1-2, Serial No.14, February 2015                                                                                                     446 
Discussion  
Infant mortality rate is one of the main 
indicators used to measuring health status of 
population in a given country thought out 
the world. In this paper we attempted to 
identify effect some of key variables such as 
total fertility rate, GDP per capita, public 
spending as % of total health expenditure 
and female labour participation rate on 
infant mortality using GLS random effect 
for the eight-year span 2005 to 2012 in ECO 
countries. The results of current study are 
useful for health policy- makers that how the 
infant mortality can be prevented in studied 
countries.   
The descriptive analysis in our study showed 
Afghanistan had the highest average of 
infant mortality rate (78.7 per 1000 live 
births) and total fertility rate (6.05 per 
women) in the study period. In addition, the 
lowest average of infant mortality rate (78.7 
per 1000 live births) and total fertility rate 
(1.9 per women) was belonged to the Iran. 
Our empirical analysis indicated the total 
fertility rate had an effect positive and 
significantly on infant mortality rate. This 
finding is consistence with studies 
conducted in Iran using time series analysis 
by Rezaei et al. (8), cross sectional data for 
117 countries by Zakir et al. (5), an 
ecological study using data from 192 
countries by Sartorius et al (11). In these 
studies similar to current study, TFR is 
identified as one of the main factors impact 
on infant mortality rate. Zakir et al. (5) 
found 10 % increases in total fertility rate 
will leads to increase in infant mortality rate 
by 8.2 % which the coefficient of this 
covariate in the current study was 3.21.  
Our study also showed higher level of GDP 
per capita is associated with lower infant 
mortality rate. On the other hands, the GDP 
per capita had a negative and significant 
effect on infant mortality in studied 
countries. Jiménez -Rubio in his study using 
a panel data of 20 Organization for 
Economic Co-operation and Development 
(OECD) countries from 1970 to 2001 
showed that there were negative and 
significant association between GDP per 
capita and infant mortality rate. In his study 
the coefficient of GDP per capita was -0.1 
which this finding implies that if GDP per 
capita 10 % increases, the infant mortality 
rate will decrease by 1 % (12). It should be 
noted that in some of studies (7, 8) there 
were not association between income and 
infant mortality.  
One of the other variables which in present 
study are considered was public spending as 
% of total health expenditure. Our results 
indicated that public spending as % of total 
health expenditure had an effect negative 
and significant relationship with infant 
mortality rate which in consistence with 
other studies (6, 9). The coefficient of this 
covariate was -0.29 which indicating if the 
GDP per capita 10 % increases, the infant 
mortality will decrease by 2.9 %. Shetty et 
al. investigated the correlation between 
health expenditures and infant mortality rate 
in 34 Asia countries. They concluded that 
the health expenditures is one of the most of 
determinant of infant mortality rate in Asia 
countries (13). Female labour participation 
rate was also considered in our study. 
Results revealed there was not a significant 
association between female labour 
participation rate and infant mortality rate 
Rezaei et al. 
Int J Pediatr, Vol.3, N.1-2, Serial No.14, February 2015                                                                                                    447 
which in consistence with Rezaei et al. study 
in Iran (8).     
Conclusion 
In this study we attempted to identify the 
main factors affecting infant mortality rate 
in ECO countries for the eight-year span 
from 2005 to 2012. Our finding indicated 
the GDP per capita, total fertility rate and 
public health expenditure as % of health 
expenditures were the main determinant on 
infant mortality rate in studied countries. We 
hope the results of this study enable health 
policy makers to better understand about 
main factors impact on infant mortality and 
help to designing and implementing of 
effectiveness programme in order to reduce 
infant mortality rate.     
Conflict of interests: None. 
References 
1. Reidpath DD, Allotey P. Infant mortality rate 
as an indicator of population health. Journal 
of Epidemiology and Community Health 
2003;57(5):344-6. 
2. Rosicova K GA, van Dijk JP, Kollarova J, 
Rosic M, Groothoff JW. Regional 
socioeconomic indicators and ethnicity as 
predictors of regional infant mortality rate in 
Slovakia. International journal of public 
health 2011;56(5):523-31. 
3. Fantini MP SE, Dallolio L, Loghi M, Savoia 
E. Persistent geographical disparities in 
infant mortality rates in Italy (1999–2001): 
comparison with France, England, Germany, 
and Portugal. The European Journal of Public 
Health 2006;16(4):429-32. 
4. Ijaz Z. Impact of Female Literacy Rate and Health 
Facilities on Infant Mortality Rate in Pakistan. 
International Journal of Humanities and Social 
Science 2012; 2(3): 135-40.       
5. Zakir M, Wunnava PV. Factors affecting 
infant mortality rates: evidence from cross–
sectional data. Applied Economics Letters 
1999;6(5):271-3. 
6. Mustafa HE, Odimegwu C. Socioeconomic 
determinants of infant mortality in Kenya: 
analysis of Kenya DHS 2003. J Humanit Soc 
Sci 2008;2:1934-722. 
7. Dallolio L, Gregori V, Lenzi J, Franchino G, 
Calugi S, Domenighetti G. Socio-economic 
factors associated with infant mortality in 
Italy: an ecological study. Int J Equity Health 
2012;11(1):45. 
8. Rezaei S, Karami Matin B, Homaie Rad E. 
Socioeconomic Determinants of Infant 
Mortality in Iranian Children: A Longitudinal 
Econometrics Analysis. International Journal 
of Pediatrics 2015;3(1.1):375-80. 
9. Muldoon KA, Galway LP, Nakajima M, 
Kanters S, Hogg RS, Bendavid E, et al. 
Health system determinants of infant, child 
and maternal mortality: A cross-sectional 
study of UN member countries. Global 
Health 2011;7:42. 
10. UNICEF 2011.  Millennium  Development  
Goals.  available  at: 
http://www.unicef.org/mdg/childmortality.ht
ml laoJ, 2014. 
11. Sartorius B , Sartorius K: Global infant 
mortality trends and attributable determinants 
– an ecological study using data from 192 
countries for the period 1990–2011. 
Population Health Metrics 2014 12:29.   
12. Jiménez-Rubio D. The impact of fiscal 
decentralization on infant mortality rates: 
Evidence from OECD countries. Social 
Science & Medicine 2011;73(9):1401-7. 
13. Anil Shetty, Shetty S. The correlation of 
health spending and infant mortality rate in 
Asian countries Int J Contemp Pediatr 
2014;1(2):100-5. 
 


Macro Determinants of Infant Mortality in ECO Countries:Evidence from Panel Data Analysis

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Macro Determinants of Infant Mortality in ECO Countries:Evidence from Panel Data Analysis

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