88 J Contemp Med Sci | Vol. 4, No. 2, Spring 2018: 88–91 Neonatal mortality rate at Al-Elwaya maternity hospital in Baghdad city: Retrospective study Hawraa Hussein Ghafel Maternal and Neonate Nursing Department, College of Nursing, University of Baghdad, Baghdad, Iraq. Correspondence to Hawraa Hussein Ghafel (email: hawraa_2004@yahoo.com). (Submitted: 24 February 2018 – Revised version received: 10 March 2018 – Accepted: 22 April 2018 – Published online: 26 June 2018) Objective This study was conducted to assess the neonatal mortality rate in Baghdad city during the last 10 years (2008–2017). This study was conducted at Al-Elwaya maternity hospital in Baghdad city: The retrospective study last 10 years ago (2008– 2017) regarding neonatal mortality rate. This study was started in October 2017 to February 2018. The data regarding neonatal mortality rate was achieved from the data recorded in the Statistical Department in the hospital. Results The result shows meaningful S-shaped auto-regression model tested in two-tailed alternative statistical hypothesis for two factors, time sequence per (years) factor as (Independent), and number of dead birth factor as (Dependent). Slope value was estimated and indicated that increasing with inverse transformation of one lagged period factor (1 year), occurring with a positive increment on natural logarithm transformation of the unit of dead birth number, and that estimated by (−0.95284), and the increment was recorded as highly significant and positive effectiveness at P < 0.01, as well as strong and highly significant correlation ship at P < 0.01 between studied factors and accounted (0.69863), with meaning determination coefficient of R-square (48.808%), which explanation disturbances among the numbers of dead birth along with the studied periods. Conclusion The results of this study show that the neonatal mortality rate increased with the time sequence for the last 10 years (2008–2017) in Al-Elwaya maternity hospital in Baghdad city. Keywords retrospective study, neonatal mortality rate, prediction of Neonatal Mortality, time sequence Introduction The first 28 days of life during the neonatal period are the most vulnerable period for a newborn’s survival. Newborns face the highest risk of dying in their first month of their life, at a global rate of 19 deaths per 1000 live births. Globally, 2.6 million newborns died in the first month of their life in 2016, approx- imately 7,000 newborn deaths every day most of which hap- pened in the first week, with about 1 million dying on the first day and approximately to 1 million dying within the next 6 days.1 The large number of the neonatal deaths are occurred in the first day and week, with about 1 million dying on the first day and approximately 1 million dying within the next 6 days. More than 60 countries will miss the reducing neonatal mortality to at least as low as 12 deaths per 1000 live births by 2030. About half of them will not reach the target by 2050. These countries carry about 80% of the burden of neonatal deaths in 2016.2 Neonatal mortality accounts for a large pro- portion of child deaths in many countries, especially in low-in- come settings. Mortality during the neonatal period is considered as an indicator of both maternal and newborn health and care.3 The newborn mortality rate (NMR) is the number of deaths of newborns under 1 year old per 1000 live births.4 The NMR has often been used as an indicator of the standard of a country’s social, educational and healthcare sys- tems. Strategies, which address inequalities both within a country and between countries, are necessary if there is going to be further improvement in global perinatal health.5 In 2015, in the United Kingdom, 1360 babies who were born after 24 weeks’ gestation died in their first 28 days of life. Overall, neo- natal mortality rates are declining. This means that generally fewer babies per 1000 births are dying each year. In 2014, 31% of babies who died in their first 28 days of life died related to complications after birth; this was the largest cause of death. About 28% of babies died due to congenital anomalies, and 18% of deaths were due to babies being born extremely early, how early a baby is born has an effect on their chance of sur- vival, and a high proportion of neonatal deaths in the United Kingdom are due to complications caused by prematurity. The following survival rates have been calculated from the number of live births and deaths in 2013.6 About 0.75 million neonates die every year in India, the highest rate of any country in the world. The neonatal mortality rate (NMR) declined from 52 per 1000 live births in 1990 to 28 in 2013, but the rate of decline has been slow and lags behind that of newborn mor- tality rates. Among neonatal deaths, the rate of decline in early neonatal mortality rate (ENMR) is much lower than that of late NMR. The high level and slow decline in early NMR are also reflected in a high and stagnant perinatal mortality rate. The rate of decline in NMR, and to an extent ENMR, has accel- erated with the introduction of National Rural Health Mission in mid-2005. Almost all states have witnessed this phenom- enon, but there is still a huge disparity in NMR between and even within the states. The disparity is further compounded by rural–urban, poor–rich and gender differentials. There is an interplay of different demographic, educational, socioeco- nomic, biological and care-seeking factors, which are respon- sible for the differentials and the high burden of neonatal mortality. Addressing inequity in India is an important cross-cutting action that will reduce newborn mortality.7 Methodology This study conducted at Al-Elwaya Maternity Hospital in Baghdad City: Retrospective study for the last 10 years (2008– 2017) regarding the neonatal mortality rate. This study was started in October 2017 to February 2018. The data regarding neonatal mortality rate was achieved from the data recorded ISSN 2413-0516 Research Methods Hawraa Hussein Ghafel et al. 89J Contemp Med Sci | Vol. 4, No. 2, Spring 2018: 88–91 Neonatal mortality rate in Baghdad: Retrospective study Research in the Statistical Department in the hospital. The following sta- tistical data analysis approaches were used to analyze and assess the results of the study under application of the statis- tical package (SPSS) version 18.0: Fitted of long-term trends for simple auto-linear and auto-nonlinear regression equa- tions, such that [inverse, (polynomial autoregression quad- ratic, cubic), power, compound, S-shaped, logistic, compound, growth and exponential] predicated equations are applicable for newborn death rate, incidence rates of congenital delivery, and neonatal mortality rates, as dependent variables affected by lagged sequence of times as an independent variable (per year). For the abbreviations of the comparisons significant (CS), used the followings: NS, non-significant at P > 0.05, S, significant at P < 0.05, HS, highly significant at P < 0.01. The neonatal mortality rate calculated with the number of deaths during the first 28 days* of life per 1000 live births in a given year.9–13 Results Table 1 shows that the neonatal mortality rate in general increases with the sequences of the years for the last 10 years from 2008–2017, according to the data recorded in the Statis- tical Department in Al-Elwaya maternity hospital except in 2015, due to the loss of data related to migration. Table 2 shows meaningful S-shaped auto-regression model tested in two-tailed alternative statistical hypothesis for two factors, time sequence per (year) factor as (independent), and number of dead birth factor as (dependent). Slope value was estimated and indicating that increasing with inverse transformation of one lagged period factor (1 year), occurring with a positive increment on natural logarithm transformation of the unit of dead birth number, and that estimated by (−0.95284), and the increment was recorded as highly signifi- cant and positive effectiveness at P < 0.01, as well as strong and highly significant correlation ship at P < 0.01 between studied factors, and accounted (0.69863), with meaning determina- tion coefficient of R-square (48.808%), which explanation dis- turbances among the numbers of dead birth along with the studied periods. Figure 1 shows the long-term trend of time sequence (years) factor on the number of neonatal mortality rate factor. Table 3 shows meaningful power-shaped auto-regression model tested in two-tailed alternative statistical hypothesis for two factors, time sequence per (year) factor as (independent), and NMR factor as (dependent). Slope value was estimated and indicating that increasing with natural logarithm trans- formation one lagged of period factor (1 year), occurring with a positive increment on natural logarithm transformation unit of (NMR), and that estimated by (0.491195), and the incre- ment was recorded as highly significant and positive effective- ness at P < 0.01, as well as strong and highly significant correlation ship at P < 0.01 between studied factors, and accounted (0.74364), with meaning determination coefficient of R-square (55.301%), which explanation disturbances among the numbers of dead birth along with the studied periods. Figure 2 shows the long-term trend of time sequence (years) factor on the (NMR) factor. Table 1. Distribution of the neonatal mortality rate (2008–2017) Years The total number of deliveries The total number of a life deliveries A life males A life females The total number of neonatal death Neonatal mortality rate 2008 16,912 16,653 8564 8589 0.259 15.55 2009 18,369 18,107 8972 9135 0.262 14.46 2010 20,232 20,129 10,072 10,057 0.303 15.05 2011 18,596 18,297 8192 10,105 0.299 16.34 2012 16,315 15,791 8504 7287 0.278 17.60 2013 17,579 17,279 8656 8673 0.300 17.36 2014 22,648 22,275 12,136 10,139 0.390 17.50 2015 22,001 21,675 8872 12,803 0.326 15.04 2016 19,752 19,499 9653 9846 0.353 18.10 2017 19,342 19,192 9657 9535 0.356 18.54 Table 2. Correlation of time sequence (per year) on the neonatal mortality rate Dependent variable method ... S-shaped model no of dead birth Simple correlation coefficient 0.69863 Meaningful linear regression tested in two-tailed alternative statistical hypothesisR-square 0.48808 F (Statistic) 8.58095 Sig. level 0.0168 (S)* Variables in the equation Variable B SE.B Beta t-Test Sig. of (t) Sequence per year −0.95284 0.325278 −0.69863 −2.929 0.0168 (Constant) 5.769005 0.122418 – 47.125 0.0000 Predicted equation is Y = e^(b0 + (b1/t)) or Ln(Y) = b0 + (b1/t) *S: significance at P < 0.05, t: time sequence (per year). 90 J Contemp Med Sci | Vol. 4, No. 2, Spring 2018: 88–91 Neonatal mortality rate in Baghdad: Retrospective study Research Hawraa Hussein Ghafel et al. Discussion of the results In this study, the results show that the neonatal mortality rate increased with the time sequence for the last 10 years (2008– 2017) in Al-Elwaya maternity hospital in Baghdad city. The majority of the neonatal deaths are concentrated in the first day and within a week, Neonatal mortality accounts for a large proportion of child deaths in many countries, especially in low-income settings like Iraq. Mortality during neonatal period is considered as an indicator of both maternal and newborn health and care. Most of the pregnant woman does not receive the primary health care during pregnancy related to several causes, such as the emigration, country’s social, edu- cational and healthcare systems and strategies. Other factors such as duration of hospitalization, birth weight, and gesta- tional age have effect on newborns mortality and gestational blood pressure has direct effect on newborns mortality. Overall neonatal mortality rates have declined over the past several decades in the under developing countries; the Southeastern states have remained the leading states in high infant death in the United States. In the previous study, the researcher studied the differences in infant mortality in the United States from 2005 to 2009 according to mother’s char- acteristics (age of mother, marital status, maternal race, maternal education), birth characteristics (month when Fig. 1 Long-term trend scatter diagram correlation of time sequence factor on neonatal mortality rate factor. Table 3. Correlation of time sequence (per year) on the NMR Dependent variable method ... power – S-shaped model no of dead birth Simple correlation coefficient 0.74364 Meaningful linear regression tested in two-tailed alternative statistical hypothesisR-square 0.55301 F (Statistic) 11.13457 Sig. level 0.0087 (HS)* Variables in the equation Variable B SE.B Beta t-Test Sig. of (t) Sequence per year 0.491195 0.147203 0.743645 3.337 0.0087 (Constant) 6.502163 1.667833 – 3.899 0.0036 Predicted equation is Y = b0 × (t^b1) or Ln(Y) = Ln(b0) + (b1 × Ln(t)) *HS, highly significance at P < 0.01, t: time sequence (per year). Fig. 2 Long-term trend scatter diagram correlation of time sequence factor on the NMR. maternal prenatal care began, birth weight), and infant’s characteristics (age of infant at death). In the previous study, data suggested that mothers with no prenatal care had a very high overall neonatal death rate. It is suggested that better education and living quality should be available and improved for the mothers.8 In Uganda, NMR remains high at 27 deaths per 1000 live births. There is paucity of data on factors associated with NMR in rural communities in Uganda. The objective of this study was to determine NMR as well as factors associated with neonatal mortality in the rural communities of three districts from eastern Uganda. The neonatal mortality was found to be 34 per 1000 live births. Neonatal mortality in rural communities is higher than the national average. The use of CHW’s to mobilize and sensitize households on appropriate maternal and newborn care practices could play a key role in reducing neonatal mortality.14 Variables such as duration of hospitalization, birth weight, gestational age have negative effect on infant mortality, and gestational blood pressure has positive direct effect on infant mortality that at whole represented 66.5% of infant mortality.15 Results of another study suggest that the current community based newborn survival intervention should provide an even greater focus to essential newborn care practices, low birth weight newborns, and female education.16–18 Hawraa Hussein Ghafel et al. 91J Contemp Med Sci | Vol. 4, No. 2, Spring 2018: 88–91 Research Neonatal mortality rate in Baghdad: Retrospective study Conclusion The results of this study show that the neonatal mortality rate increased with the time sequence for the last 10 years (2008– 2017) in Al-Elwaya maternity hospital in Baghdad city. Recommendations 1. Decrease incidence of infection and injuries during delivery. 2. Enhance the services that are provided in Neonatal Inten- sive Care Unit. 3. Enhance the primary health care services. 4. Increase the awareness of pregnant women about the important of prenatal care. 5. Further studies about the causes of neonatal death in all governorate in Iraq. n References 1. UNICEF Data: Monitoring the Situation of Children and Women, The neonatal period is the most vulnerable time for a child, 2017 available at https://data.unicef.org/topic/child-survival/neonatal-mortality/ 2. WHO: Global Health Observatory (GHO) data, 2016. available at http://www. who.int/gho/child_health/mortality/neonatal_text/en/ 3. Chartbin: Current Worldwide Neonatal Mortality Rate (per 1000 live births), 2011. Available at http://chartsbin.com/view/1451 4. WHO: List of countries by infant mortality rate, 2017. available at http:// www.who.int/gho/child_health/mortality/mortality_under_five_text/en/ 5. Yu VY. 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WHO: Neonatal mortality, risk factors and causes: a prospective population- based cohort study in urban Pakistan (submitted: 09 January 2008 – Revised version received: 21 June 2008 – Accepted: 25 June 2008 – Published online: 06 January 2009) 18. Bulletin of the World Health Organization. 2009;87:130–138. doi: 10.2471/ BLT.08.050963. http://www.who.int/bulletin/volumes/87/2/08-050963/en/. This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License which allows users to read, copy, distribute and make derivative works for non-commercial purposes from the material, as long as the author of the original work is cited properly. dx.doi.org/10.22317/jcms. 06201807