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Chibuogwu Izugbara

Chibuogwu Izugbaraab

aDepartment of Sociology, University of Pretoria, South Africa bHuman Economy Programme, University of Pretoria, South Africa Background: Nigeria remains the largest contributor to neonatal mortality in Africa. Nigeria’s neonatal mortality rate is 48/1000 live births. Existing research on the causes of neonatal mortality in Nigeria has placed great emphasis on  factors such as diarrhea, malaria, measles and acute respiratory infections, whooping cough, tuberculosis, bronchopneumonia, dirty feeding bottles and utensils, inadequate disposal of household refuse, poor storage of drinking water and household wealth index[1-4]. However, insufficient attention has been given to parental age-related factors. Understanding the implications of parental age differences for child health can add to our knowledge of the correlates of neonatal mortality and furnish insights to support the design and delivery of interventions to address the problem. Objective: To examine the implications of spousal age-related factors for child health outcomes. Methods: Data for this study were drawn from the 2008 Nigeria Demographic and Health Survey. Univariate and multivariate statistical analyses were used to assess the relationship between neonatal mortality and parental age-related contextual factors focusing on maternal and paternal ages, spousal age, sex of child, household wealth index and place of residence. Results: The multivariate logistic regression analyses yielded significantly increased risk of neonatal mortality among neonates of parents with age differences of 15 years or more. Conclusion: Neonates of couples with age differences of less than 15 years die less compared to neonate of spouses with age difference of 15 years and above.


Of the 130 million babies born globally every year, about 4 million die in the first 4 weeks of life, during the neonatal period [5].  Neonatal mortality rate is defined as the number of infants dying before reaching 28 days of life, per 1,000 live births [6]. Most neonatal deaths (99%) occur in low and middle-income countries, mostly in sub-Saharan Africa, including Nigeria [7, 8]. Globally, Nigeria ranks second to India with the highest number of neonatal deaths [9]. Currently in Africa, Nigeria’s neonatal mortality rate is the highest of the region at 48/1000 live births with 241,000 neonatal deaths annually[10]. Neonatal mortality remains disturbingly high in Nigeria, despite the significant decline in most parts of the developing world, including some sub-Sahara African countries, such as Ghana and Uganda [9]. These deaths in the first month of life primarily reflect both factors associated with maternal health before and during pregnancy, and with the health problems of the newborn[11]. Deaths in this age range result chiefly from inadequate growth (prematurity, intrauterine growth retardation) and congenital anomalies[11]. As a result, neonatal mortality rates provide an indicator of the factors affecting pregnancy, delivery, the neonate and the adequacy of services in the prenatal, intrapartum, and neonatal periods[12]. Research into the causes of high neonatal mortality in Nigeria has focused on such factors as preterm birth, infections, asphyxia and low birth weight[1]. Maternal complications in labor, breastfeeding practices, dirty feeding bottles and utensils, inadequate disposal of household refuse, poor storage of drinking water, household wealth index and maternal characteristics are also correlated with neonatal mortality[2-4]. Few studies have examined the implications of spousal age-related factors for child health outcomes. The few available studies were conducted in developed countries. These studies show that spousal demographic factors, especially age, have huge implications for early child health outcomes. For instance, European studies published between 2002 and 2008 associated advanced paternal age with fetal death, which includes both miscarriage and stillbirth[13, 14]. Additionally, a 2002 study in Jerusalem linked paternal age with pre-eclampsia[15]. Pre-eclampsia is a complication of pregnancy associated with the development of high blood pressure, and protein in the urine[16]. Significant associations have surfaced between advanced paternal age and childhood conditions such as cleft lip and palate, childhood cancers, congenital heart defects and childhood neuropsychiatric conditions such as autism, schizophrenia, epilepsy, and bipolar disorder[17-19]. Paternal age has also been implicated in the etiology of Trisomy 21, Down Syndrome[20]. Other studies found advanced paternal age to be associated with an increased risk of single gene disorders [21]. Furthermore, the literature show that the rate of transmitted de novo single nucleotide mutations increases with paternal age[22]. For instance, achondroplasia, the most common form of dwarfism, is a disease in which the probability of having an affected offspring increases exponentially as a function of the father’s age[22]. The interaction between parental age difference and offspring count in humans has also been examined[23]. In such studies, the offspring count for men reached a maximum when the female partner was approximately 6 years younger than the male[21, 23].The implications of spousal age-related factors for child health outcomes remain an understudied issue in neonatal mortality in Nigeria and the rest of the developing nations. According to a 2012 UNICEF report, early childhood health determines the quality of health, well-being, learning and behavior across a person’s life span; it is a period of great development and with this development comes great vulnerability[10]. Against this backdrop, this paper examines whether age differences between spouses is associated with neonatal mortality in Nigeria. The similarities or dissimilarities in mortality rates of neonates with regard to differences in their parents’ ages are conceptualized and divided into taxonomically and analytically useful categories. Knowledge about these similarities and dissimilarities is linked to the general literature on infant and childhood mortality in Nigeria and the rest of the developing nations.

Study Design


The data used in this study are from 2008 Nigeria Demographic and Health Survey (NDHS), the most comprehensive of all the demographic and health surveys conducted in the country. The study was conducted by the National Population Commission (NPC) from June to October 2008, with financial support from the United States Agency for International Development (USAID) and United Nations Fund for Population Activities (UNFPA). ICF Macro International provided technical assistance. Questionnaires were administered on a nationally representative sample of 36,800 households drawn from all 36 states and the Federal Capital Territory[24]. The 2008 NDHS elicited information on demographic and health indicators both at the national and state levels. Data for this study were collected from 33,385 women of reproductive age (15-49 years) who have had at least one live birth in the five years preceding the survey (2003-2008), with a total of 104,808 births. Of these, 5,665 neonates died.

Statistical Analysis

The outcome variable for this study is neonatal mortality and was measured as the duration of survival since birth in days. The children’s survival status and age at death in days (if the child had died), or the last 28 (0-27) days they were known to be alive (if child was still living at the time of the survey), were combined to generate the outcome variable. Neonates known to have died (i.e. non-censored observation) were regarded as the cases, whereas neonates who were still alive at the time of the survey were treated as right-censored. Right censoring occurs when a subject leaves the study before an event occurs, or the study ends before the event has occurred [25]. The key explanatory variable in this study is spousal age difference categorized as (1) 1-14 years old (2) 15 years old and above. Bivariate associations were used to examine the association between the independent socioeconomic and demographic variables and the dependent variable, spousal age difference. In order to examine such an association, Pearson Chi-squared test assisted in identifying factors that are significantly associated with spousal age difference. The final stage of the analysis was multivariate analysis, which yielded the odds ratios. The binary logistic regression model was used in this study because the outcome variable is dichotomous or binary: neonatal mortality was coded as 0 (Dead) and 1 (Alive), respectively. Descriptive statistics calculated in this study included maternal and paternal ages, child’s sex, household wealth index and place of residency. For the purpose of this study, maternal age was divided into three age categories: 15-24 (reference group), 25-34, and 35-49 years, while paternal age was divided into four age categories: 15-24 (reference age group), 25-34, 35-44, and 45-64 years. Different age groups where used for males and females because the mean and median ages of menopause for Nigerian women are 49±3 and 49.0 years [26]. A new variable, spousal age, was generated by adding up the three maternal age groups with the four paternal age groups. The matching up of these age groups made it possible to study spousal age differences. Rates of neonatal mortality were calculated for each maternal and paternal age group. The adjusted odds ratio along with their 95% confidence intervals associated with maternal and paternal age groups, with reference to the 15–24 age groups, were derived through unconditional multivariate logistic regression analysis. Odds ratio (OR) is defined in this study as the measure of association between an exposure and an outcome. It represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure[27].  Paternal Age is defined as the age of the father in completed years at the time of delivery[28]. Maternal age is defined as the age of the mother in completed years at the time of delivery[28]. Spousal Age Difference is defined in this study as the difference between the ages of spouses. Ages of parents were categorized in order to probe the interaction between different age groups of spouses on child health outcomes. Age gaps of spouses coded “1-14” and “15 and above” years was used to simplify the analysis and interpretation of results and also because the author was interested in two possible outcomes (i.e. neonates surviving or dying). However, also, age gaps of 1-14 was used because, the mean age difference between spouses in Nigeria is 12.0 years if the wife marries before age 15, compared to 8.5 years if the wife marries at or after age 20[24]. Spousal age differences in Nigeria are even greater when the girl is a second or third wife. In polygynous marriages, the mean age difference between spouses is 15.3 years, compared to 8.8 years in monogamous marriages[24]. Nigeria Demographic and Health Survey is abbreviated as NDHS [24]


In the bivariate analysis of neonatal mortality and demographic variables at the individual level, neonates of women aged 35-49 or even older were 95% more likely to die compared to those of women aged 15-24 (Table 1). With regard to paternal age, 37.98% of neonatal deaths were correlated with men who were between 35-44 years old (Table 1). Mortality among neonates was more prevalent among spouses with age differences of 15 years and above (Table 1). Male neonates had a higher rate of mortality at 57.37% compared to 42.63% among female neonates. The odds ratio for death among girls was 0.79 (95% CI .73140 – .81501) (Table 1). Spouses living in rural areas were 1.3 times more likely to experience neonatal mortality compared with their urban counterparts (OR, 1.3, CI: .19079-.32175). With regard to household wealth index, neonatal mortality was highest among parents of moderate households (Table 1). Logistic regression analysis showed that maternal and paternal ages, spousal age difference, and sex of child were significantly associated with neonatal mortality. Female children were less likely to die as neonates compared to male children (Table 2). Spouses with age difference above 15 years were more likely to experience neonatal mortality compared to those of the reference group category (OR. 1.4, 95% CI .538616-.6190392). Older women (35-45) were more likely to experience mortality among neonates compared to younger mothers (OR. 0.95, 95% CI .4285714- .8472978 (Table 2)


The findings of the study showed a clear effect of maternal and paternal ages on the risk of neonates. This finding suggest that older women may be at increased risk of neonatal mortality due to common disease associated with older age, such as diabetes and hypertension and complications of pregnancy, such as abruption, which are also associated with increasing maternal age. This finding supports the research findings of [29], who found that the risk of infant mortality was high in older women (35 years and above). With regard to neonates born to spouses living in rural areas, these parents were more likely to have their children die as neonates compared to their urban counterparts (OR, 1.3, CI: 19079-.31275). This supports [2] argument that cities and towns tend to have lower mortality rates than rural areas, possibly because people residing in rural areas are less educated than their urban counterparts and the distribution of amenities favors the urban areas. Access to drinkable water in the rural areas and easy access to health-care services by members of the community could also reduce risks of neonatal mortality. Availability and access to drinkable water within the community could prevent children from contracting avoidable infections and water-borne diseases, such as diarrheal disease and other forms of infections. This study points to the importance of good infrastructure for child survival. This result has established an elevated risk of neonatal mortality for communities in poor socio-economic contexts. This result finding also establishes one of the reasons rural areas tend to have poorer child health outcomes than their urban counterparts. Wealth index covariate is another important determinant of infant and child mortality that was established in this study. Spouses of the moderate wealth quintile reported the highest rate of neonatal mortality (Table 2). This corroborates previous findings by[30], which established that socio-economic factors such as education, occupation and wealth index are more important in infancy than childhood. [31] study of maternal and neonatal mortality in rural Ethiopia also found similar evidence. They found that the greatest risk of both neonatal mortality and stillbirth was to the rich households, not to the poorest. On the other hand [32] additionally, found higher incidence of malnutrition and thus of morbidity and mortality among children of a low wealth quintile than among children of the wealthiest quintile. This inequity is a composite of many factors, including economic access to antibiotics and other drugs from private venders, where a wealthy family often has a better access in addition to better nutrition and improved housing since access to antibiotics plays an important role in newborn survival. However, this finding needs further investigation with a focus on how the true wealth status can be determined in Nigeria. My opinion is that the asset variables selected to indicate wealth status may not have correctly reflected the actual wealth status of all households. This study also established that child’s sex is an important predictor of neonatal mortality. Male neonates had higher rates of mortality compared with female neonates (Male, 57.37%, Female, 42.63%, Table 2). This finding also supports research findings of [33]. However, the survival advantage of girls over boys may be attributed to high vulnerability to infectious disease [34] Another possible reason for the low rate of neonatal deaths among girls may be because of the development of early fetal lung maturity in the first week of life [35], resulting in a lower incidence of respiratory diseases in female neonates compared with male neonates. Globally, it is estimated that approximately 23% of newborn deaths are attributed to respiratory problems[36]. There was a significant increase in the risk of neonatal mortality if the couple’s age difference was above 15 years (Table 2).


Results from the logistic regression model showed that spousal age gaps, sex of child, maternal and paternal ages were statistically associated with neonatal mortality in Nigeria. The findings of this study have expanded on earlier research that implicated malnutrition, infection, dehydration and diarrhoea in neonatal in Nigeria. As rate of neonatal mortality remains high in Nigeria, this may not be resolved until spousal age-related measures as well as household-focused interventions are implemented. Spouses with age gaps of 15 years and above should be encouraged to seek medical attention whenever the need arises in their neonates. Preventing marriages of spouses with age gaps of 15 years and above through effective family planning programs need to be considered among neonatal survival interventions.  This is because neonate’s survival is related to their parent’s ages through both genetics and behaviour. Parents pass on genetic material that either improve or worsen their infant’s survival. Finally, the finding of this study may be unique to Nigeria and may not necessarily be generalizable to other countries or populations. There is need for further studies especially in newer datasets and across countries to confirm the findings of this research.

Study Limitations

Generally, mortality studies are faced with data limitations. The study draws on a cross-sectional secondary dataset; as a result, there is a tendency for child deaths to be underreported.  Mothers may be reluctant to talk about their dead children either because it brings back sad memories or because their culture discourages mention of the dead[2]. However, recall errors arising from dates of birth and death given by women interviewed in the survey were minimized by restricting the analyses to births within the 5-year period preceding the survey. Finally, the proportion of missing data was relatively small, such that it may not have influenced findings of this study.


Table 1: Bivariate analyses of neonatal mortality and maternal and paternal socio-demographic characteristics

Characteristics                    Outcomes at end of neonatal period (n=104,808) Deaths (%) (n=5,665)     Odds ratio             95% CI Maternal age at birth of child * 15-24                                       9.54                                 1 25-34                                       30.81                              0.84                 .7632516    .9310423 35-49                                       59.65                                0.95                  .8675274    1.046113 Paternal Age at Birth of child* 15-24                                         9.54                                1 25-34                                         30.81                            0.84                   7632515    .9310425 35-44                                         37.98                            0.91                  .8264131     1.00369 45-64                                         21.67                             1.1                     .9335352    1.150172 Child’s Sex* Male                                          57.37                             1 Female                                       42.63                            0.79                   .7314063    .8150122 Parental Age Difference*    1-14                                            13.99                           1 15-Above                       17.33                           2.3                      .0966805     .410784 Household wealth Index* Poor                                            30.16                          1 Moderate                                    47.87                         0.90                      9055806    1.025992 Rich                                            21.97                         0.70               .       6449142    .7492019 Region of Residence Urban                                          4.48                               1 Rural                                           5.72                              1.3                     .1907969    .3217599

Source: Calculated from the 2008 Nigeria Demographic and Health Survey Table 2: Adjusted odds ratios from logistic regression of neonatal mortality and spousal demographic factors.

Characteristics                                         Neonatal Births (104,808) Odds ratio            95% CI Maternal age at birth*** 15-24                                          1 25-34                                      0.84                     .2701677   .0714504 35-49                                        0.95                  .4285714    .8472978 Paternal Age at Birth*** 15-24                                         1 25-34                                        0.75                 2701677      .0714504 35-44                                        0.89                  2012994   .0568129 45-64                                        0.96                 0687766    .1399118 Child’s Sex*** Male                                            1 Female                                        90                   .8784612    .9367374 Spousal Age Difference***    1-14                                          1 15-Above                     1.4                   .5384616    .6190392

Source: Calculated from the 2008 Nigeria Demographic and Health Survey


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