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ORIGINAL ARTICLE
4 (
1
); 35-46
doi:
10.21106/ijma.54

Antenatal Care Services Utilization in Yobe State, Nigeria: Examining Predictors and Barriers

World Health Organization, Rua Major, Kanhangula, Luanda, Angola
World Health Organization, UN Building, Central Business District, Abuja, FCT Nigeria
Corresponding author email: ausadiq@yahoo.com
Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective:

In Nigeria, wide disparities exist between the different parts of the country, with the states in the North East zone having poor health resources. The objective of this study is to assess whether women's biological, sociocultural, and economic characteristics are associated with utilization of ante natal care services as measured by number of antenatal care (ANC) visits in Yobe State.

Methods:

This is a secondary data analysis of the 2008 Nigeria Demographic and Health Survey with records from 33,385 women between 15-49 years who had given birth between January 2003 and December 2008 in Yobe State. Bivariate Pearson's Chi square test and two stages of Multivariate regression analysis were conducted.

Results:

Women with at least primary level education (adjusted OR (AOR) = 2.40; CI 1.24 - 4.67), belonging to professional employment category (AOR = 12.07; CI 0.19 - 75.74) and those who had access to skilled health workers (AOR = 5.13; CI 2.50 - 10.52) are more likely to make the required number of ANC visits compared to those who are illiterates, unemployed and had no access to skilled health workers.

Conclusion and Global Health Implications:

This study demonstrated that educational level, family wealth income, and availability of skilled health worker were consistently associated with the number of ANC visits even after controlling for covariates. These three covariates are in tandem with the Millenium Development Goals (MDG) 1 - eradication of extreme poverty and hunger; MDG 2 - universal basic education; MDG 3 - gender equality; and MDG 4 - maternal mortality. There is the need for inter-sectoral holistic intervention approach.

Keywords

Antenatal Care Services
ANC Utilization
MDGs
Yobe State
Nigeria
Skilled Health Workers

Background and Objective

Nigeria has one of the highest maternal mortality ratios (MMR) in the world. Between 2010 - 2012, the World Health Organization (WHO) estimated that the country has an MMR of 630 per 100,000 live births.[1] This figure indicates that the country only surpassed war torned and or politically unstable countries like Sierra Leone (890 per 100,000), Liberia (777 per100, 000) and Chad (1,100 per 100,000) live births respectively.[1] The poor maternal outcome might not be unrelated to the low utilization rates of maternal health care services. For example, about half of the estimated eight million annual numbers of pregnancies have not had antenatal care (ANC) in 2010. Furthermore, among those that had ANC, 45% have made less than the minimum four ANC visits as recommended by the WHO.[1] This national average does not reveal the disparities that exist within and between the six geopolitical zones of the country which are fairly heterogeneous in terms of religious and cultural affiliations. Women from the North East zone of Nigeria are more likely to die due to pregnancy related complications.[2] It is important to note that disparities exist even within a given geopolitical zone. For instance, while the North East zonal average for the proportion of women who had ANC was 43%, Yobe state had the lowest with only 36% ANC utilization rate.[3] These figures might even be lower since the state is largely rural, lowest number of skilled health workers, and poor records of vital events.[4] Further, the sensitivity of the surveillance system is low based on recent reports that indicated the state has low ANC utilization and having MMR that is two fold higher than the reported national average of 630 per 100,000 live births.[5,6] Although Yobe state has 528 public and private health facilities,[3] however, these facilities lack both technical and institutional capacity,[3,4] which invariability might have contributed to the low utilization of ANC services. With an estimated annual number of pregnancies of 600,000 and only 45 public employed midwives,[7] a midwife is expected to attend to more than 50 pregnancies per day which could compromise the quality of services rendered.

Considering the Yobe State Strategic Health Development Plan 2010 - 2015 is in its final year, there is the need to assess the the predictors of ANC utilization in the state in order to sustain the achievements recorded towards Millenium Development Goal number five (MDG 5) which is to reduce maternal deaths by two thirds compared to what was recorded in 1990. Unfortunately, there seems to be a dearth of local research studies on maternal mortality in Nigeria. For instance, despite Nigeria being among the areas with high MMR in the world,[8-10] reports of systematic reviews of 2,500 and 5,575 showed that only 3 (1.2%) and 5 (0.5%) articles respectively were from Nigeria and non from Yobe state.[8,11] One of the plausible reasons for such findings is that most published studies in Nigeria were hospital-based and focused more on medical causes of death such as hemorrhage, eclampsia, obstructed labor, ruptured uterus, sepsis, malaria and anemia in pregnancy, which does not provide information on antecedents before arrival to a health facility.[11,12]

This paper is an effort to bridge this gap aimed to find out whether women's individual and community level factors influence the utilization of ANC services in Yobe state as measured by number of antenatal care visits.

Methodology

This is a cross-sectional study using data from the 2008 Nigeria Demographic and Health Survey (2008 NDHS) after receiving approval from ORC Macro and ICF International based in Calverton Maryland, USA. A total of 967 women between 15-49 years who had given birth between January 2003 and December 2008 participated in the study. Details on survey instruments and methodology are available in the NDHS report.[2,25]

The data was analyzed using SPSS version 16. Bivariate Pearson's Chi square test statistic and two stages of Multivariate regression analysis were conducted in order to identify factors that predict the utilization of ANC in Yobe State. First, logistic regression of one variable at a time was conducted to get the unadjusted odds ratio and thereafter, a multivariate logistic regression was conducted to obtain adjusted odds ratios aimed at accounting for the effect of each of the study covariates.

We utilized the Anderson health behavior model as a framework for analyzing the determinants of utilization of health services.[13] The model is composed of three sets of individual and community level factors that provide constructs to assess individuals' capacity to access and use health services. The three main set of factors are a) predisposing characteristics at individual level; b) enabling characteristics which focus on community level factors such as health care financing mechanism and health resources and c) need characteristics which is the perceived state of health by individual and health workere.[14] This unique characteristic of the Anderson's Model was underscored by its application in a range of medical research such as the utilization of health care services[15-17] and other social issues.[18-24]

Results

Descriptive

Out of the 967 respondents, a total of 648 (67%) had at least one ANC visit during the last pregnancy before the 2008 NDHS survey. Among those that had ANC, only 328 had four or more recommended ANC visits constituting only 33.9% of the total study sample. Moreover, 319 (33%) and 320 (33.1%) of repondents had zero or less than four ANC visits respectively. About 26.4% of the respondents commenced their ANC visits in their third trimester (Table 1).

Table 1. Bio-socio-demographic Characteristics of Study Respondents
Independent variable Proportion of sample (%) Number of ANC visits (N=967) (%)
<4 visits ≥4 visits
Age in years
    <20 22.1 90.7 9.3
    20 - 34 44.9 74.9 25.1
    35 - 49 33.0 90.6 9.4
Parity
    1 13.0 73.3 26.7
    2 - 4 36.4 76.1 23.9
    5+ 50.6 85.0 15.0
Birth order
    First 13.0 73.3 26.7
    Second 13.5 73.4 26.6
    Third 12.8 74.8 25.2
    Fourth or higher 60.6 84.4 15.6
Birth interval between the last two deliveries
    Less 24 months 25.3 80.8 19.2
    24-48 month 55.4 79.9 20.1
    49+ months 19.3 85.9 14.1
When first ANC visit was made
    First trimester 19.4 11.4 88.6
    Second trimester 54.2 27.6 72.4
    Third trimester 26.4 48.3 51.7
Place of domicile
    Rural 72.8 90.5 9.5
    Urban 27.2 65.0 35.0
Marital status
    Never married 6.6 100.0 0.0
    Married 89.7 82.1 17.9
    Living together 0.1 100.0 0.0
    Divorced/separated 2.0 89.5 10.5
    Widowed 1.7 87.5 12.5
Ethnicity
    Hausa 21.5 81.2 18.8
    Yoruba 0.5 40.0 60.0
    Igbo 0.1 0.0 100.0
    Fulani 17.4 91.7 8.3
    Kanuri/Baribari 42.2 77.5 22.5
    Others 18.3 94.3 5.7
Religion
    Islam 98.7 83.6 16.4
    Christianity 1.0 70.0 30.0
    Tradition 0.3 100.0 0.0
Level of autonomy
    None 79.8 83.7 16.3
    Some 16.7 77.1 22.9
    Full 3.5 70.0 30.0
Family wealth index
    Poorest 53.7 95.0 5.0
    Poorer 24.6 80.3 19.7
    Middle 12.6 63.1 36.9
    Rich 7.4 52.8 47.2
    Richest 1.7 56.2 43.8
Respondent highest education level
    No formal education 82.0 88.3 11.7
    Primary 9.1 60.2 39.8
    Secondary 8.1 65.4 34.6
    Higher 0.8 50.0 50.0
Total years of schooling
    Zero 82.0 88.3 11.7
    Less than 6 years 9.1 60.2 39.8
    6-12 years 8.4 64.4 34.6
    13+ years 0.5 40.0 50.0
Respondent occupation
    Not working 50.6 86.0 14.0
    Unskilled worker 39.6 85.6 14.4
    Skilled worker non professional 9.0 67.8 32.2
    Professional 0.8 25.0 75.0
Distance
    No 82.6 77.8 22.2
    Yes 17.4 88.6 14.4
Have health insurance
    No 99.6 83.6 16.4
    Yes 0.4 75.0 25.0
Attended by skilled health worker during ANC visits
    No 91.0 80.2 19.8
    Yes 9.0 27.6 72.4
Received health talks during ANC
    No 8.8 9.1 90.9
    Yes 91.2 30.7 69.3
Access to the media
    Never/rarely 80.0 86.7 13.3
    Almost always 20.0 71.0 29.0

Biological characteristics of respondents

The age group 20 - 34 years old constituted the majority (44.9%) of the respondents with a mean age of 27.2 + 3.2 years. The age group 15 - 19 years old constituted 22.1% of the sample. The extreme of ages (<20 years and ≥35 years) had the lowest proportion of women who had four or more ANC visits. Majority of the women (87%) had at least two children (Table 1).

Cultural characteristics of respondents

Majority of the women were married (89.7%), belonging to Kanuri/Baribari ethnic group (42.2%), Muslims (98.7%), lack any form of autonomy (79.8%) and lived in rural areas (72.8%). Living in urban areas (27.2%), Yoruba ethnicity (60%), Christians (30%) and having full autonomy (30%) had higher proportion of women that had four or more ANC visits (Table 1).

Economic characteristics of respondents

Majority of the respondents were illiterate (82%), unemployed (50%) and belonged to the poorest/ poor wealth quintile (78.3%), and only 11.7%, 14% and 24,7%, respectively of these categories of women had met the recommended minimum of four ANC by the WHO (Table 1).

Respondents’ health system characteristics

Distance to the nearest health facility and lacking health insurance policy (99.6%) showed lower proportion of women that had appropriate number of ANC visits. Majority of the respondents (91%) were not attended by skilled health care workers and fewer still (19.8%) had achieved the WHO recommendation of at least four ANC visits (Table 1).

Results of bivariate and logistic regression analysis

Age is significantly associated with the number of ANC visits (χ2 = 43.11; df = 2; P < 0.00). The age group 15 - 19 years were less likely to make four or more ANC visits compared to women who were aged 20 - 34 years even after controlling for the covariates (AOR = 1.72; CI 0.75 - 3.91) (Table 2).

Table 2. Factors Associated with the Number of Antenatal Care Visits Attended.
Independent variable Bivariate analysis Multivariate logistic regression analysis
n Chi-Square (χ2) test Unadjusted OR 95% Cl for unadjusted OR P-value (unadjusted OR) Adjusted OR 95% Cl for adjusted OR P-value for adjusted OR
<4 visits ≥4 visits Lower Upper Lower Upper
Age in years
<20 194 20 χ2 (2, N=967)=43.11, p=0.00 1.00 1.00
20-34 325 109 3.25 1.96 5.41 0.00 1.72 0.75 3.91 0.20
35-49 289 30 1.01 0.56 1.82 0.98 0.87 0.30 2.48 0.79
Parity
1 77 28 χ2 (2, N=967)= 12.16, p=0.00 1.00 1.00
2-4 223 70 0.86 0.52 1.44 0.57 0.47 0.20 1.11 0.09
5+ 346 61 0.44 0.29 0.81 0.01 0.46 0.18 1.2 0.11
Birth order
First 77 28 χ2 (3, N=967)= 13.73, p=0.00 1.00 1.00
Second 80 29 1.00 0.54 1.83 0.99 8.93 0.38 208.05 0.17
Third 77 26 0.93 0.50 1.73 0.82 0.12 0.01 3.09 0.20
Fourth or higher 412 76 0.51 0.31 0.83 0.01
Birth interval between the last two deliveries
Less 24 months 143 34 χ2 (2, N=967)=2.43, p=0.30 1.00 1.00
24-48 months 310 78 1.06 0.68 1.66 0.81 1.19 0.17 8.49 0.86
49+ months 1 16 19 0.69 0.37 1.27 0.23 195.78 2.35 16.28 0.02
Place of domicile
Rural 637 67 χ2 (1, N=967)=90.36, p=0.00 1.000 1.00
Urban 171 92 5.12 3.58 7.31 0.00 2.14 1.23 3.73 0.01
Ethnicity
Hausa 169 39 χ2 (5, N=967) =46.94, p=0.00 1.00 1.00
Yoruba 2 3 6.50 1.05 40.23 0.04 44.78 0.00 1.00
Igbo 0 1 7.00 0.00 1.00 94.28 0.00 1.00
Fulani 154 14 0.39 0.21 0.75 0.01 0.054 0.00 0.65 0.02
Kanuri/Baribari 316 92 0.26 0.13 0.54 0.00
Others 167 10 0.00 0.00 1.00
Religion
Islam 797 157 χ2 (2, N=967)= 1.93, p=0.38 1.00 1.00
Christianity 7 3 2.12 0.56 8.55 0.26 0.99 0.17 2.31 0.99
Tradition 3 0 0.00 0.00 1.00
Level of autonomy
None 577 112 χ2 (2, N =967)=6.74, p=0.03 1.00 1.00
Some 111 33 1.53 0.99 2.37 0.06 8.74 0.62 12.45 0.11
Full 21 9 2.21 0.99 4.95 0.05 33.35 7.13 41.33 1.00
Family wealth index
Poorest 493 26 χ2 (4, N=967)= 139.35, p=0.00 1.00 1.00
Poorer 191 47 4.67 2.81 7.75 0.00 3.24 1.83 5.74 0.00
Middle 77 45 11.08 6.46 19.00 0.00 6.00 2.94 12.25 0.00
Rich 38 34 16.97 9.24 31.16 0.00 6.16 2.38 15.94 0.00
Richest 9 7 14.75 5.09 42.72 0.00 4.44 0.64 30.64 0.13
Respondent highest educ level
No formal education 700 93 χ2 (3, N=967)=73.03, p=0.00 1.00 1.00
Primary 53 35 4.97 3.08 8.02 0.00 2.40 1.24 4.67 0.01
Secondary 51 27 3.99 2.38 6.66 0.00 5.08 2.08 12.39 0.00
Higher 4 4 7.53 1.85 30.61 0.00 10.21 3.15 14.77. 1.00
Respondent occupation
Not working 419 68 χ2 (3, N=967)=39.21, p=0.00 1.00
Unskilled worker 326 55 1.04 0.71 1.53 0.84 1.00
Skilled worker non-professional 59 28 2.92 1.74 4.91 0.00 1.23 0.10 15.31 0.87
Professional 2 6 18.49 3.66 93.47 0.00 12.07 0.19 75.74 0.24
Distance
No 389 111 χ2 (1, N=967)= 179.79, p=0.00 1.00 1.00
Yes 93 12 0.45 0.24 0.86 0.02 0.99 0.22 4.50 0.99
Has health insurance policy
No 805 158 χ2 (1, N=967)=0.21, p=0.66 1.00
Yes 3 1 1.70 0.18 16.41 0.65 1.12 0.99 1.71 0.15
Attended by skilled health worker*
No 473 117 χ2 (1, N=967)=78.86, p=0.00 1.00 1.00
Yes 16 42 10.61 5.76 19.54 0.00 5.13 2.50 10.52 0.00
Access to the media as source of health information
Never/rarely 670 103 χ2 (1, N=967)=27.65, p=0.00 1.00 1.00
Almost always 137 56 2.66 1.83 3.86 0.00 0.99 0.37 2.71 0.99

Notes: OR=Odds ratio; CI=Confidence intervals; *Attended at least one ANC visit=648

Parity of ≥2 (AOR = 0.47; CI 0.20 - 1.11), religion (AOR = 0.99; CI 0.17 - 2.31), distance to the nearest health facility (AOR = 0.99; CI 0.22 - 4.50), availability of health insurance policy (AOR = 1.12; CI 0.99 - 1.71) and access to the media as a source of information on MHS (AOR = 0.99; CI 0.37 - 2.71) have no impact on the use of ANC services after controlling for education, family wealth index, and availably of skilled health workers (Table 2).

Place of domicile (χ2 = 90.36; df = I; P < 0.00), ethnicity (χ2 = 46.94; df = 5; P < 0.00), level of education (χ2 = 73.03; df = 3; P < 0.00), occupation (χ2 = 39.21; df = 3; P < 0.00), family wealth index (χ2 = 139.35; df = 4; P < 0.00) and availability of skilled health workers (χ2 = 78.86; df = I; P < 0.00) are associated with the number of ANC visits (Table 2).

After adjusting for covariates, women of Yoruba and Igbo ethnic groups were 44 and 94 times respectively more likely to achieve the recommended four or more ANC visits compared to women belonging to Hausa ethnic group (Table 2). Women living in urban areas (AOR = 2.14; CI 1.23 - 3.73), having some form of autonomy (AOR = 8.74; CI 0.62 - 12.45) and those in the highest wealth quintile (AOR = 4.44; CI 0.64 - 30.64) had four or more number of ANC visits compared to their rural colleagues, those without any form of autonomy and belonging the poorest wealth quintile respectively (Table 2).

Similarly, women with at least primary level education (AOR = 2.40; CI 1.24 - 4.67), belonging to professional employment category such as lawyers, health workers, teachers etc (AOR = 12.07; CI 0.19 - 75.74) and those who have access to skilled health workers (AOR = 5.13; CI 2.50 - 10.52) are more likely to make the required number of ANC visits compared to those who are illiterates, unemployed and had no access to skilled health workers respectively (Table 2).

Predictive model on the utilization of ANC services

The model contained six predictive variables (age, family wealth quintile, religious affiliation, highest educational attainment, parity, and distance to health facilityr). These variables were selected based on the result of the bivariate Pearson Chi square test, binary logistic regression and or known theoretical facts. These variables were found to be statistically significant χ2 (28, N=967) 53.10; P< 0.00, indicating that, the model was able to distinguish between participants who have had less than four ANC visits and those who had four or more ANC visits. The variables accounted for 39.1% (Cox & Snell R Square) and 54.4% (Nagelkerke R Square) of variability among participants, correctly classified 80.4% of cases and together with Hosmer and Lemeshow goodness of fit test indicated the model being useful (p = 0.77) since the p-value is larger than the alpha level[26] (table not shown).

Discussions

Maternal and Child Health Services (MCHS) is among the top priority of Yobe State government as enshrined in the state health strategic plan for 2010 - 2015. Despite significant progress in MCHS, the state has not met the MDG five.[3] In 2008, the MMR in the state was reported to be 1,549 per 100, 000 live births which is about three times higher than the national average of 545 per 100,000 live births.[2,3] Furthermore, the ANC utilization rate was 36% and of these only 9.8% had access to appropriate skilled health workers.[2,3] In general, wide disparities exist between the different parts of the country with the states in the North East zone which includes Yobe State having the worst maternal health indicators. In order to identify the root issues for the abysmal performance of the state, this study disaggregated data in line with the social determinants of health as advanced by the WHO.[27]

The low ANC utilization rates in the North Eastern states of Nigeria which include Yobe State is consistent with areas with the high levels of poverty, low female literacy and empowerment.[4,28] This is a reflection of the socioeconomic development, access and utilization MCHS rendered in the state. While it might have cultural connotations, however, MCHS will only be used when geographical and economic access is guaranteed. For instance, the Yobe State health strategic plan for 2010 - 2015 clearly indicated the lack of technical and institutional capacity which could have contributed to the low utilization of ANC services.[3] The worsening of the current Boko Haram Islamist extremist insurgency particularly from 2011 to date, could have further decimated the availability of skilled health workers based on recent report that the doctor population ratio is 1 for every 54,000 people.[7] Similarly, the estimated workload for a midwife is 257 pregnant women per week. Furthermore, a study on the state of health system following the Boko Haram insurgency has indicated that health workers have been abducted and/or killed and many health facilities were closed.[28]

The findings of this study showed that few respondent have access to skilled health workers (9%), very high proportion of illiterates (82%), families living in poverty (78.3%), high risk pregnancies among teenagers (22.1%) and women more than 34 years (33%) and lack of female autonomy (79.8%) in terms of decision making, economic independence and freedom of going out of their matrimonial home on health grounds. These findings suggest that these women are likely to have high proportion of complicated pregnancies, poor access and utilization of MCHS, which might have contributed to the high MMR as was similarly observed in other studies.[29-33] Furthermore, these high risk pregnancies coupled with short interval between births (25.3%) and grand multipara (50.6%) as observed in this study, could be the underlying root causes for most of the high proportion of preventable maternal deaths.[9,10] ANC is an objective strategy to effectively identify high risk pregnancies. However, the low proportion of women who had four or more number of ANC visits means that, many high risk pregnant women may not be detected and may result in life threatening condition and in extreme cases could lead to the death of a woman and or her baby. The lack of autonomy further compound the scenario, since it may lead to delays to decide to seek modern medical care when early signs of danger are noticed.

Although, the low ANC utilization rate could be influenced by place of domicile, ethnicity, religion and female autonomy, however, these factors were not found to be consistently statistically significant after controlling for covariates such as education and income levels. The low utilization of ANC services as observed in this study is not in keeping with the findings of another study in Nigeria that reported Muslim women are less likely to have four or more number of ANC visits compared to their Christian counterparts.[29] This assertion is not consistent when confounders such as tribe, income and level of education were controlled as was the case in this study. Moreover, after controlling for age, wealth index, education and distance, parity and religion have no significant impact on the number of ANC visits and its main effect associations shifted from been statistically significant to not significant (Table 2). Hence, the role of ethnicity and religion needs to be studied as both shape the attitude and behaviors of the populace. The reason been that, each of the major ethnic group particularly Hausa, Igbo, Fulani and Kanuris are predorminantly (>90%) adherents of either Christianity or Islam and each has different ethnically driven norms on pregnancy and childbirth.

It is important to underscore that the study being cross sectional design has only demonstrated the strength of associations rather than causal factors. Moreover, DHS data is individual based and therefore might not fully represent community level factors and hence the need for studies with robust designs.

Conclusions and Global Health Implications

This study demonstrated that, educational level, family wealth income, and availability of skilled health worker are consistently associated with the number of ANC even after controlling for covariates. These three predicor variables are in tandem with MDG 1 (eradication of extreme poverty and hunger), MDG 2 (universal basic education), MDG 3 (gender equality) and MDG 4 (maternal mortality). These three variables have significant impact on population health outcome and need for intersectoral collaboration with ministries of education, agricultural and other social services using primary health care as the springboard. A sustainable approach is to provide compulsory free universal basic education for girls (MDG 2) to emhance uptake and retention of girl's up to secondary level of education. This will have a multiplier effect towards reduction in poverty (MDG 1), improve female autonomy and equality (MDG 3) and improve health cultural capital that will ultimately reduce maternal deaths (MDG 5). Hence, the provision of health care services should be driven by results based management approach in order to enhance realistic multipronged planning, ownership, commitment, accountability and transparency among various stakeholders. There is therefore, the need for an independent periodic program reviews to guide timely and appropriate interventions.

Ethical Approval:

The 2008 Nigeria Demographic and Health Survey (2008 NDHS) was approved by ORC Macro and ICF International, Calverton, Maryland, USA.

Acknowledgments:

We would like to acknowledge ORC Macro and ICF International Calverton Maryland, USA for granting us the permission to use the 2008 NDHS dataset. We are also grateful to Professor Daniel Okenu for the guidance and support.

Conflict of Interest:

The authors declare that they have no competing interests.

Funding:

The authors have no support or funding to report.

References

  1. . World Health Statistics 2013. WHO, Geneva, Switzerland 2013a Retrieved on10th April 2015 from http://apps.who.int/iris/bitstream/10665/81965/1/9789241564588_eng.pdf?ua=1/en
    [Google Scholar]
  2. . Nigeria Demographic and Health Survey 2008. Abuja, Nigeria/Calverton, MD USA: National Population Commission and ICF Macro. 2009 Retrieved on10th March 2015 from http://pdf.usaid.gov/pdf_docs/PNADQ923.pdf
    [Google Scholar]
  3. . Government. Strategic Health Development Plan 2010 - 2015. Yobe State Ministry of Health. 2010 Retrieved on 5th March 2015 from http://www.mamaye.org/sites/default/files/evidence/Yobe%20Naration2.pdf
    [Google Scholar]
  4. . Primary Health Care in Nigeria: 30 years after Alma-Ata. The Nigerian Health Review 2007 Health Reform Foundation of Nigeria, 2007, Mmm-nat Educational Window Consultant Ltd., Abuja, Nigeria
    [Google Scholar]
  5. . Organization. Maternal death surveillance and response: technical guidance. Information for action to prevent maternal death. WHO, Geneva, Switzerland. 2013b Retrieved on16th March 2015 from http://www.who.int/maternal_child_adolescent/documents/maternal_ death_sur veillance/en
    [Google Scholar]
  6. , , , . Estimating maternal mortality level in rural northern Nigeria by the sisterhood method. International Journal of Population Research. 2012;5
    [CrossRef] [Google Scholar]
  7. , , , , . Child and maternal health care using telemedicine: a case study of Yobe State, Nigeria. International Journal of Computer Engineering and Applications. 2014;7:1.
    [Google Scholar]
  8. , , , , . Knowledge gaps in scientific literature on maternal mortality: a systematic review. Bulletin of the World Health Organization. 2006;84(11):903-909.
    [Google Scholar]
  9. . State of the world's children 2012. . Retrieved on10th April 2015 http://www.unicef.org/sowc2012/pdfs/SOWC-2012-Main-Report_EN_21Dec2011.pdf
    [Google Scholar]
  10. . Trends in Maternal Mortality: 1990 to 2008 - Estimates developed by WHO, UNICEF, UNFPA, and th. World Bank' 2010 Retrieved on 16th September 2014 from http://whqlibdoc.who.int/publications/2010/9789241500265_eng.pdf
    [Google Scholar]
  11. , , . A systematic review of inequalities in the use of maternal health care in developing countries: examining the scale of the problem and the importance of context. Bulletin of the World Health Organization. 2007;85:812-819.
    [CrossRef] [PubMed] [Google Scholar]
  12. , , , , , , , , . PFA. WHO analysis of causes of maternal deaths: A systematic review. Lancet. 2006;367:1066-1070.
    [CrossRef] [PubMed] [Google Scholar]
  13. . Revisiting the behavioral model and access to medical care: does it matter? Journal of Health Social Behavior. 1995;36:1-10.
    [CrossRef] [PubMed] [Google Scholar]
  14. , , . Societal and individual determinants of medical care utilization in the United States. The MilBank Quarterly. 2005;83(4):1-28.
    [CrossRef] [Google Scholar]
  15. , , . Determinants of dental care utilization for diverse ethnic and age groups. Advances in Dental Research. 1997;11(2):254-262.
    [CrossRef] [PubMed] [Google Scholar]
  16. , , . The use of health services by older adults. Journals of Gerontology Series B-Psychological Sciences and Social Sciences. 1991;46(6):S345-S357.
    [CrossRef] [PubMed] [Google Scholar]
  17. , , , , , , . Understanding the context of healthcare utilization: Assessing environmental and provider-related variables in the behavioral model of utilization. Health Services Research. 1998;33(3):571-596.
    [Google Scholar]
  18. , , , , , , , , , , . Intended use of informal long-term care: The role of race and ethnicity. Ethnicity & Health. 2004;9(1):37-54.
    [CrossRef] [PubMed] [Google Scholar]
  19. , , , , , , , . Socio- economic status differences in older people's use of informal and formal help: A comparison of four European countries. Ageing and Society. 2000;26(5):745-766.
    [CrossRef] [Google Scholar]
  20. , , . Informal help in the assisted living setting: A 1-year analysis. Family Relations. 2001;50(4):335-347.
    [CrossRef] [Google Scholar]
  21. , , , , , , , , , , , , . Influence of Race, Ethnicity, and Culture on Childhood Obesity: Implications for Prevention and Treatment a consensus statement of Shaping America's Health. The Obesity Society Diabetes Care. 2008;31(11):2211-2221.
    [CrossRef] [PubMed] [Google Scholar]
  22. , , . Prevalence of obesity among children and adolescents: United States, Trends 1963-1965 Through 2007-2008. NCHS Health E-Stat 2010 June 2010. Retrieved on 5th May 2013 from http://www.cdc.gov/nchs/data/hestat/obesity_child_07_08/obesity_child_07_08.pdf
    [CrossRef] [Google Scholar]
  23. , , , , , , , , . Prevalence of high body mass index in U.S. In: children and adolescents, 2007-2008. NCHS Health E-Stat. June 2010. Vol 303. JAMA; . p. :242-249.
    [CrossRef] [PubMed] [Google Scholar]
  24. , , , , , , , , , , , , , , . Birth weight of offspring, maternal Pre-pregnancy characteristics and mortality of mothers: the Jerusalem Perinatal study cohort. Annals of Epidemiology. 2009;19(2):112-7.
    [CrossRef] [PubMed] [Google Scholar]
  25. . Guide to DHS Statistics: Demographic and Health Survey Methodology. Calverton, Maryland USA: USAID and ICF Macro 2006 Retrieved on 10th April 2015 from http://dhsprogram.com/pubs/pdf/DHSGI/Guide_to_DHS_Statistics_29Oct2012_DHSIpdf
    [Google Scholar]
  26. . Discovering statistics using SPSS. In: Chapter, 8, “Logistics regression” (2nd). Thousand Oaks, California: Sage Publications Ltd; . p. :264-268.
    [Google Scholar]
  27. . Inequities are killing people on a “grand scale”: The Reports WHOs commission on health inequalities. News Release WHO/29, August 28, 2008, WHO, Geneva, Switzerland Retrieved on10th April 2015 from http://www.who.int/mediacentre/news/releases/2008/pr29/en/index.html
    [Google Scholar]
  28. , , , , , , , , , , , , , . Health Systems Resilience: A Systems Analysis -A Case Study of Health Service Provision in Yobe State, Nigeria in the Context of the Boko Haram Insurgency. Final Report, October 2014. Rebuild Consortium and Mailman School of Public Health, Columbia University, USA Retrieved on 5th March 2015 from http://www.rebuildconsortium.com/news/documents/HealthSystemsResilience_YobeCaseStudy_FinalizedReport.pdf
    [Google Scholar]
  29. , , . Determinants of use of maternal health services in Nigeria - looking beyond individual and household factors. BMC Pregnancy and Childbirth. 2009;9:43.
    [CrossRef] [PubMed] [Google Scholar]
  30. , , , , , , , , . Northern Nigeria, Maternal, Newborn, and Child Health Program: Selected analysis from population based baseline study. The Open Demographic Journal. 2011;4:11-21.
    [CrossRef] [Google Scholar]
  31. , , . Factors influencing the selection of delivery with no one present in Northern Nigeria: implications for policy and programs. International Journal of Womens Health. 2014;6:171-183.
    [CrossRef] [PubMed] [Google Scholar]
  32. , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , . Predictors of maternal mortality in institutional deliveries in Nigeria. African Health Science. 2012;12(1):32-40.
    [Google Scholar]
  33. , , , , , , , , . Determinants of utilization of maternity services in Gidan Igwe, Sokoto, Nigeria. Sahel Medical Journal. 2010;13(3):128-134.
    [CrossRef] [Google Scholar]
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