Science Journal of Public Health
Volume 4, Issue 1, January 2016, Pages: 43-48

Regional Differences in the Optimal Utilisation of Antenatal Care in Nigeria

Linda Ochuole Ugalahi, Oyindamola Bidemi Yusuf, Joshua Odunayo Akinyemi, Ayo Stephen Adebowale

Department of Epidemiology and Medical Statistics, Faculty of Public Health, University of Ibadan, Ibadan, Nigeria

Email address:

(L. O. Ugalahi)
(O. B. Yusuf)
(J. O. Akinyemi)
(A. S. Adebowale)

To cite this article:

Linda Ochuole Ugalahi, Oyindamola Bidemi Yusuf, Joshua Odunayo Akinyemi, Ayo Stephen Adebowale. Regional Differences in the Optimal Utilisation of Antenatal Care in Nigeria. Science Journal of Public Health. Vol. 4, No. 1, 2016, pp. 43-48. doi: 10.11648/j.sjph.20160401.16


Abstract: Many maternal deaths in Nigeria are as a result of pregnancy related complications that are preventable through utilisation of antenatal care facility. The World Health Organisation recommends at least four visits to an antenatal care facility to attain full life saving potentials for pregnant women and their unborn babies. As the deadline for the Millennium Development Goals (MDG 5), which focuses on maternal health and access to health facilities) approaches, it is important to evaluate the optimal utilisation of ANC and impact of regional differences. This study determined factors that affect optimal utilisation of ANC visits. The National Demographic and Health Survey, 2013 dataset on women aged 15-49 years who had their most recent birth in the last 5 years prior the survey was used for the analysis. Optimal utilisation of ANC was defined as four or more visits. Data were analyzed using Chi-square and binary logistic regression models (α=0.05). Mean age of women was 29±7 years and 53% achieved optimal utilisation. The identified predictors of optimal use of ANC were age, wealth index, number of children alive, and region among others. Women in the South-West were about 7 (OR=6.73, 955% CI=5.843, 7.758; p<0.001) times more likely to have had optimal utilisation of ANC than those in the North Central zone. This strength of relationship was retained after other socio-demographic factors were included in the regression model as control. Respondents aged 34-39 years were 2 times more likely to attain optimal utilisation of ANC facility compared to those aged 15-19 years (OR=1.50, 95% CI: 1.152, 1.946). Respondents who belong to the richest wealth quintile were about 3 times more likely to attain optimal utilisation of ANC visits (OR=2.86, 95% CI: 2.162, 3.775) compared to respondents in the poorest quintile. Optimal utilisation of ANC in Nigeria is still poor and differentials exist across the regions. Therefore, regional specific programmes targeting better utilisation of ANC visits among women should be provided particularly in the Northern part of Nigeria.

Keywords: Optimal Utilisation, Maternal Health, Maternal Mortality, Focused Antenatal Care (FANC), Health Regional Differences


1. Introduction

Maternal morbidity and mortality occur due to complications during pregnancy and child birth. The World Health Organization (WHO) estimates that maternal mortality is over 500 000 deaths per year worldwide and 99 percent of these occur in developing countries. Nigeria accounts for about 10 percent of the world’s overall maternal mortality [1,2]. Thus Nigeria is among countries with high burden of Maternal Mortality globally.

An estimated 800 women die every day from preventable pregnancy related causes [3]. Pregnancy related complications such as infections, eclampsia, and obstructed labour and maternal deaths may be effectively reduced through services obtainable in antenatal care services. Despite the benefits of antenatal care services, women do not utilize them optimally.

Studies have identified factors that affect the use of antenatal care facility in Nigeria. Several of these studies were done based on individual local government areas and states. [4-11]. Other studies were based on data collected at regional level, [12-14]. A few however, have utilized nationwide data, [15-17].

Women educational status, household wealth and distance of antenatal have been identified as factors associated with the use of antenatal care [15,18]. Poor communication, poverty, cultural norms, personal cost and poor power supply were identified as factors that affect the quality of care obtainable in an antenatal care facility. These reasons invariably affect the utilisation of these facilities [19]. Physical accessibility of health facilities was identified as a factor that affects utilisation of ANC services [20]. Despite several studies done on factors that affect ANC utilization, few studies have been done to identify factors that affect optimal utilization of ANC using a national representative data. As the year 2015 marks the deadline for the Millennium Development Goals (MDG 5), which focuses on improving maternal health, it is important to evaluate the utilisation of ANC and the impact of regional differences on optimal utilisation. The objectives of this study were to determine the factors associated with optimal utilisation of antenatal care and to determine the regional influence on the optimal utilisation of ANC amidst other socio-demographic factors.

2. Methodology

Nigeria is one of the sub-Saharan African countries located in the West African region. It covers a total area of 923,768 kilometer square. Nigeria comprises of 36 states and a Federal Capital Territory (FCT). These states are grouped into six geopolitical zones; North Central, North East, North West, South East, South-South and South West.

Data for this study was obtained from the National Demographic and Health Survey [21]. The survey made use of a population based cross-sectional study design.

The 36 states were regrouped by geopolitical location into six zones and using the 2006 Population census implementation, each locality was subdivided into Enumeration Areas (EAs). A complete list of the EAs served as the sample frame of the survey. The sampling technique for the 2013 NDHS was a stratified sample, selected at random in three stages from the sampling frame. At the first stage; each state was stratified into urban and rural areas; this resulted in a list of localities. At the second stage one enumeration area was randomly selected from a selected locality with equal probability selection, the resulting list of households served as sampling frame for the selection of households in the third stage. At the third stage 45 households were selected in every urban and rural cluster through equal probability systematic sampling using the household listing. More details can be obtained from the NDHS report [21].

For the purpose of this study a sample of 9909 women within reproductive age 15-49yrs, who gave birth within the last five years and had the history of index birth, was used.

Extraction of relevant data from the NDHS dataset was performed, weighting of the data was done and simple summary statistics (percentage for categorical variables or mean for continuous variables) for all independent variables was also performed. Socio economic factors that affect utilisation of ANC were identified across the two regions of the country i. e. northern and southern regions. Chi-square test was used to investigate associations between optimal utilisation and categorical variables such as age, geopolitical zones, wealth index etc. Variables that were significant in the chi square analysis were then entered into a binary logistic regression model to further investigate the strength of these associations at 5% level of significance. Model fit was assessed using the Hosmer Lemeshow goodness of fit test.

Number of visits to antenatal care facility was the outcome variable in this analysis, it was categorized into two; optimum use and no optimum use. Optimum use was defined as four or more visits and no optimum use defined as less than four visits [22].

(1)

The key explanatory variable was region of residence (North Central, North West, North East, South East, South West and South South). Others include; age, region, place of residence, educational level, religion, wealth index, occupation, place of antenatal, ethnicity, number of children, husband’s/partner’s educational level and occupation. SPSS version 20 was used for analysis.

3. Results

The mean age of the women was 29 years (SD=7.5). Women within the age group 30-34 years had the highest proportion of optimal utilisation of ANC (82.8%), while those aged 15-19 had the least proportion (67.6%) (p<0.001). Optimal utilisation increased with increase in educational level; respondents with higher educational level had the highest proportion compared to respondents with no education (95.1% vs. 66.9%, p<0.001). The same pattern was observed in the wealth index of respondents, the richest had the highest proportion while the poorest had the least proportion (93.5% vs. 61.2%, p<0.001). Respondents who were employed had highest proportion of optimal utilisation of ANC while those unemployed had the lowest (80.9% vs. 73.6%, p<0.001). (Table 1)

Table 1. Socio demographic factors associated with optimal utilisation.

Variables Optimal use% Total women p-value
Age (years)      
15-19 67.6 516 <0.001
20-24 76.0 4907
25-29 78.4 2606
30-34 82.8 2124
35-39 82.4 1604
40-44 81.8 836
45-49 75.2 314
Region     <0.001
North Central 74.3 1445
North East 65.7 1514
North West 68.4 2637
South East 90.7 1272
South South 87.8 1002
South West 94.9 2037
Residence     <0.001
Urban 86.1 4428
Rural 73.5 5479
Educational level     <0.001
No education 66.9 3504
Primary 80.8 2606
Secondary 88.8 3470
Higher 95.1 327
Religion     <0.001
Christianity 87.1 4569
Islam 72.2 5255
Traditional 79.5 83
Wealth index     <0.001
Poorest 61.2 1251
Poorer 69.2 2047
Middle 79.1 2273
Richer 85.3 2388
Richest 93.5 1949
Employment status     <0.001
Unemployed 73.6 2346
Employed 80.9 7562
Ethnicity     <0.001
Hausa 66.8 2656
Igbo 91.5 1592
Yoruba 95.2 1714
Others 75.5 3945
Number of children alive     <0.001
1-4 80.0 7112
5-9 77.2 2720
10 and Above 61.3 75
Place of ANC     <0.001
At a home 84.9 304
Government health facility 76.0 7480
Private health facility 89.2 2123
Husband’s/partners educational status     <0.001
No education 64.9 2693
Educated 84.5 7215
Husband’s/partners employment status     0.032
unemployed 91.7 48
employed 79.1 9860

3.1. Differences in Optimal Utilization of ANC in the Geo-political Zones

There was a difference in the proportion of respondents who attained optimal utilisation of ANC in the different zones. Age was found to be significantly associated with optimal utilisation in the northern zones. Respondents aged 35-39 years had the highest proportion of optimal utilisation in the North Central zone (82.2%), while those aged 15-19 had the least 61.0%. Respondents in urban residence had higher proportions of optimal utilisation of ANC in the North Central (88.8%), and North West (71.8%); however this proportion increased in South West zone (95.7%).

Wealth index was significantly associated with optimal utilisation across all zones, proportion of respondents increased with increase in wealth index i. e. from the poorest quintile to the richest quintile (North Central: 43.6% vs. 93.3%; North East: 65.1% vs. 80.8%; South East: 73.4% vs. 97.4%). Educational status of the respondents husband/partner was associated with optimal utilisation. In the North East, 60.3% of those whose husbands had no education attained optimal utilisation compared to 71.5% of the respondents with educated husbands/partners. This pattern was similar in the South West zone however with slightly higher proportion of 87.5% vs. 95.6% for not educated and educated respectively. (Table 2)

Table 2. Factors associated with optimal utilisation in the geo-political zones.

Variables North Central North East North West South East South South South West
  Optimal use (%) Total optimal use (%) Total Optimal use (%) Total Optimal use (%) Total optimal use(%) Total optimal use (%) Total
Age
15-19 61.0* 77 50.7* 134 69.2* 214 92.6 27 92.9 28 97.3 37
20-24 74.8 306 66.5 367 66.3 600 89.6 183 84.1 164 96.5 286
25-29 73.9 410 67.1 362 63.5 650 90.9 353 87.2 273 93.9 558
30-34 71.5 284 69.9 266 74.1 505 90.3 289 91.1 235 95.2 545
35-39 82.2 202 63.9 230 73.5 373 91.0 244 85.8 169 95.1 386
40-44 76.5 119 69.6 112 68.6 188 91.8 134 89.2 102 95.0 181
45-49 72.3 47 68.3 41 63.0 108 90.7 43 90.3 31 88.6 44
Residence
Urban 88.8* 340 68.7 428 71.8* 937 90.2 880 85.4* 371 95.7* 1472
Rural 69.7 1104 64.5 1086 66.5 1702 91.8 392 87.8 632 93.3 563
Educational level
No education 70.6* 606 61.3* 936 64.9* 1649 77.4* 62 88.5* 61 88.9* 190
Primary 72.8 416 67.7 322 70.1 522 86.8 386 88.2 304 93.7 655
Secondary 80.1 397 78.5 237 77.8 446 92.9 737 87.2 571 96.8 1083
Higher 96.0 25 94.1 17 100 21 98.9 88 89.6 67 94.5 109
Religion
Christianity 69.3* 677 70.4 226 88.2* 288 90.9 1238 87.4 968 96.1* 1172
Islam 79.3 750 64.9 1280 66.0 2343 80.0 10 100 27 93.3 845
Traditional 50.0 18 62.5 8 50.0 6 88.0 25 100 8 100 19
Wealth index
Poorest 43.6* 110 58.2* 455 65.1* 591 73.4* 79 50.0* 2 64.3* 14
Poorer 58.5 316 65.8 1445 66.1 812 82.9 181 88.8 89 91.8 146
Middle 78.0 549 70.3 503 67.0 528 90.6 339 85.3 279 92.0 299
Richer 85.4 335 68.3 279 71.7 474 92.9 365 86.9 358 95.5 649
Richest 93.3 135 88.2 208 80.8 234 97.4 308 87.7 275 96.4 928
Employment status(respondent)
Unemployed 69.7* 284 74.2 621 68.4 811 93.3 253 87.5 184 95.8 192
Employed 75.3 1160 63.3 893 68.4 1827 90.1 1019 87.9 819 94.9 1845
Ethnicity
Hausa 58.8* 51 70.2* 389 65.9 2175 86.7 15 100* 2 95.7 23
Igbo 85.7 28 83.3 6 93.0 43 90.8 1239 91.7 121 96.8 155
Yoruba 93.0 128 100 5 76.7 30 85.7 7 100 24 95.6 1521
Others 72.6 1239 63.8 1114 78.7 390 90.9 11 86.9 855 91.1 337
Number of children alive
0-4 74.9 1059 65.4 1003 68.7 1765 91.1* 887 87.8 735 95.0* 1662
5-9 72.8 378 66.0 497 68.4 833 90.5 379 88.2 263 95.4 370
10 and Above 55.6 9 76.9 13 56.4 39 50.0 6 75.0 4 50.5 4
Place(facility) of ANC
At a home 81.8 11 42.9 7 53.8 26 82.8* 58 88.7 71 92.4 131
Government 74.6 1123 65.7 1444 68.6 2566 89.9 574 87.5 763 94.8 1011
Private 72.3 311 69.8 63 66.7 45 92.3 640 88.7 168 95.5 895
Husband’s/partner’s educational level
No education 62.1* 380 60.3* 773 63.9* 1252 82.9* 76 77.8 36 87.5* 176
Educated 78.6 1065 71.5 740 72.5 1387 91.2 1196 88.2 967 95.6 1861
Husband’s/partner’s employment status
unemployed 100 10 75.0 4 77.8 9 100 3 100 15 100 6
employed 74.1 10 65.7 1510 68.4 2629 90.7 1269 87.7 988 94.9 2030

*Statistically significant at 0.05.

3.2. Logistic Regression Results

Respondents from the North East geopolitical zone were less likely than respondents from the North Central zone to have optimal utilisation of ANC (OR=0.50, 95% CI: 0.455, 0.557). Similarly North West respondents were less likely to attain optimal utilisation of ANC (OR=0.34, 95% CI: 0.309, 0.370), (Table 3).

Table 3. Region as a Predictor of ANC Optimal Utilisation.

Variable OR p-value 95% CI
      Lower bound Upper bound
North Centrala        
North East 0.50 <0.001 0.455 0.557
North West 0.34 <0.001 0.309 0.370
South East 4.85 <0.001 4.137 5.687
South South 1.62 0.001 1.435 1.836
South West 6.73 <0.001 5.843 7.758

(a: reference category).

Respondents aged 35-39 years were more likely to attain optimal utilisation of ANC compared to those aged 15-19 years (OR=1.50, 95% CI: 1.152, 1.946). Optimal utilisation of ANC differed with respect to geo political zones. Respondents in South East, South South and South West zones were 2, 2 and 3 times (OR=1.77, 95% CI: 1.123, 2.808; OR=1.73, 95% CI: 1.351, 2.207; OR=3.20, 95% CI: 2.353, 4.309) respectively more likely to attain optimal utilisation of ANC than North Central zone. Respondents with secondary and higher educational levels were 1 and 2 times (OR=1.28, 95% CI: 1.071, 1.532; OR=1.96, 95% CI: 1.140, 3.353) more likely than those with no education to attain optimal utilisation of ANC respectively. Respondents who belong to the richest wealth quintile were about 3 times more likely to attain optimal utilisation (OR=2.86, 95% CI: 2.162, 3.775) compared to respondents in the poorest quintile, (Table 4).

Table 4. Socio Demographic Characteristics as Predictors of ANC Optimal Utilisation.

Variables OR p-value 95% CI
      Lower bound Upper bound
Age        
15-19a        
20-24 1.11 0.352 0.890 1.388
25-29 1.06 0.570 0.856 1.327
30-34 1.41 0.005 1.107 1.787
35-39 1.50 0.003 1.152 1.946
40-44 1.62 0.001 1.203 2.180
45-49 1.46 0.044 1.010 2.094
Region        
North Centrala        
North East 0.92 0.391 0.771 1.107
North West 1.00 0.997 0.815 1.227
South East 1.77 0.014 1.123 2.808
South South 1.73 <0.001 1.351 2.207
South West 3.20 <0.001 2.353 4.309
Residence        
Urbana        
Rural 1.14 0.065 0.992 1.320
Educational level        
No educationa        
Primary 1.02 0.818 0.879 1.178
Secondary 1.28 0.007 1.071 1.532
Higher 1.96 0.015 1.140 3.353
Religion        
Christianitya        
Islam 1.05 0.603 0.879 1.250
Traditional 1.02 0.953 0.572 1.811
Wealth index        
Pooresta        
Poorer 1.17 0.041 1.006 1.368
Middle 1.53 <0.001 1.288 1.819
Richer 1.83 <0.001 1.489 2.248
Richest 2.86 <0.001 2.162 3.775
Employment status        
Unemployeda        
Employed 1.02 0.706 0.907 1.154
Ethnicity        
Hausaa        
Igbo 1.83 0.007 1.179 2.849
Yoruba 1.89 <0.001 1.329 2.683
Others 1.06 0.501 0.891 1.265
Number of children alive        
1-4a        
5-9 0.89 0.114 0.764 1.029
10 and Above 0.49 0.006 0.290 0.813
Place of ANC        
At a homea        
Government health facility 1.27 0.175 0.898 1.807
Private health facility 1.17 0.412 0.806 1.691
Husband’s/partner’s educational level        
No educationa        
Educated 1.38 <0.001 1.209 1.567
Husband’s/partner’s employment status        
Unemployeda        
employed 0.37 0.076 0.125 1.108

(a: reference category).

4. Discussion

Optimal utilisation of ANC is very important as a woman will attain maximum care from at least four visits; this is referred to as the Focused Antenatal Care (FANC).

In our study we found different predictors of optimal utilisation of ANC in the different zones. The southern geopolitical zones had higher optimal utilization of ANC compared to the northern zones. The seeming higher socio economic characteristics such as wealth status and educational status of women residing in the southern zones compared to those in the northern zones were found to affect the optimal utilisation of ANC; this is similar to results obtained from [16], which found geopolitical zones to be a factor that affects maternal healthcare service utilisation. Religious and cultural practices are vastly different and these have been found to affect utilisation of healthcare facilities, ANC visits inclusive.

There was a noticeable difference in optimal utilisation between the different age groups with older respondents attending ANC visits more than younger respondents. This finding agrees with the reports of a similar study in South Western, Nigeria [12]. Similarly [10], found women aged greater than twenty-five years utilized ANC more than those less than twenty-five years old and this is similar to results found in our study where older women attained optimal utilization of ANC more than younger women. This may be due to more knowledge about the advantages of ANC by the older women compared to their younger counter parts as they may have had previous births.

Education is a key factor in the utilisation of healthcare in general [9,6,15]. Educating the girl child in the northern zones is not considered essential as a result of socio cultural practices and religious beliefs. Similarly, a previous report from North Central Nigeria [4] showed maternal education to be a predictor of ANC service utilisation in North Central Nigeria. Our study found higher level of education improved optimal utilization of ANC. Educated women are more likely to be aware of the benefits of optimal utilization and are likely to be empowered to make decisions about their health.

Social structure affects ANC utilisation; through communication at social gathering, women talk to their peers and discuss about different features of life including health related issues [23]. With increase in wealth, there was increase in the proportion of women who utilized ANC visits. Several studies [24,25] have linked wealth of women to utilisation; possibly because higher socio economic status is associated with higher education and employment. This enables hospital bills to be paid as more often than not bills are paid out of pockets due to poor state of health insurance in the country.

5. Conclusion

In conclusion, several factors were found to affect the optimal utilization of ANC in Nigeria and regional differences occur as well with women in South East, South West and South South utilizing ANC more than those in North East, North West and North Central. The most affected zones are the North East and North West. Measures to improve utilisation of ANC should address the following issues: education of females and regional specific programmes targeting better utilisation of ANC among women should be improved particularly in the Northern part of Nigeria.


References

  1. National Population Commission Nigeria and ICF Macro, Nigeria Demographic and Health Survey 2008, Abuja, Nigeria. National Populaton Commission and ICF Macro, 2009. Available at:http://nigeria.unfpa.org/pdf/nigeriadhs2008.pdf.
  2. World Health Organisation, World Health Report - Make every Mother and Child count, 2005. Available at: http://www.who.int/whr/2005/en/.
  3. World Health Organisation, "Maternal Mortality ratio (per 100 000 live births)". Health Statistics and Health Information Systems, 2013 pp.1. Available at: http://www.who.int/healthinfo/statistics/indmaternalmortality.
  4. K.R. Adewoye, I.O. Musah, O.A. Atoyebi and O.A. Babatunde, "Knowledge and utilisation of antenatal care services by women of child bearing age in Ilorin-East local government area, North Central Nigeria," International Journal of Science and Technology 2013 vol.3pp. 188–193.
  5. O. A.Onasoga, J. A. Afolayan and B. D.Oladimeji, "Factors influencing utilisation of antenatal care services among pregnant women in Ife Central Lga,Osun State and National Hospital Abuja, Nigeria," Advances in Applied Science Research, 2012 vol. 3 pp. 1309–1315.
  6. O.A.Onasoga, T.A. Osaji, O.A. Alade and M.C.Egbuniwe, "Awaresness and Barriers to Utilisation of Maternal Healthcare Services among Reproductive Women in Amassoma Community, Bayelsa State," Inernational Journal of Nursing and Midwifery, 2014 vol. 6 pp. 10-15.
  7. R. Onoh, O. Umerora, U. Agwu, H. Ezegwui, P. Ezeonu and A.K. Onyebuchi, "Pattern and determinants of antenatal booking at Abakaliki southeast Nigeria". Annals of Medical and Health Sciences Research, 2012 vol. 2, pp.169–75.
  8. O.U.J. Umeora, B.N. Ejikeme, S. I. Adeoye and R.N.Ogu, "Implementing the new WHO antenatal care model: voices from end users in a rural Nigerian community," Nigerian Journal of Clinical Practice 2008 vol. 3 pp.260.
  9. U.W.Ibor, O.A.Anjorin, A. E.Ita, M. A. Out and T.I. Bassey, "Utilisation of antenatal care in Ibadan North Local Government Area, Oyo state, Nigeria," Trends in Medical Research 2011 vol. 6 pp. 273-280.
  10. M.D. Dairo and K.E. Owoyokun, "Factors affecting the utilisation of antenatal care services in Ibadan, Nigeria," Benin Journal of Postgraduate Medicine, 2010 vol.12 pp. 3–13.
  11. V.Awusi, E. Anyanwu and V. Okeleke, "Determinants of Antenatal Care Services UtilisationInEmevor Village, Nigeria," Benin Journal of Postgraduate Medicine, 2009 vol. 11.
  12. D.A. Adekanle and A.I Isawumi, "Late Antenatal Care Booking and Its Predictors among Pregnant Women in South Western Nigeria," Online Journal of Health and Allied Sciences, 2008 vol. 7 pp.1–6.
  13. A.M. Amosu, A.M. Degun, A.M. Thomas, M.F. Olanrewaju, A.O. Babalola, P.E. Omeonu, et al. "A Study on the Acceptance and Practice of Focused Antenatal Care by Healthcare Providers in the South-West Zone of Nigeria," Archieves of Applied Science research, 2011 vol. 3 pp.484–491.
  14. M.N Sambo, G.A Abdulrazaq, A. F. Shamang and A.A.Ibrahim, "Household cost of antenatal care and delivery services in a rural community of Kaduna state, Northwestern Nigeria," Nigerian Medical Journal : Journal of the Nigeria Medical Association, 2013 vol. 54 pp.87–91.
  15. E.O. Nwosu, N.E Urama and C. Uruakpa, "Determinants of Antenatal Care Services Utilisation in Nigeria," IISTE - Journal of Developing Country Studies, 2012 vol. 2 pp.41–52.
  16. S.H. Adamu, Utilisation of Maternal Health Care Services in Nigeria : An Analysis of Regional Differences in the Patterns and Determinants of Maternal Health Care Use, 2011. Available at: http://mph/MPH_Quantitative_Dissertation_.
  17. D.N. Ononokpono and C.O. Odimegwu, "Determinants of Maternal Health Care Utilisation in Nigeria: a multilevel approach," Pan African Medical Journal, 2013 vol.17.
  18. C.A. Brown, B. S.Sohani, K. Khan, R. Lilford and W. Mukhwana.,"Antenatal Care and Perinatal Outcomes in Kwale District, Kenya," BMC pregnancy and childbirth, 2008 vol. 8 pp. 2.
  19. J. Ekabua, K. Ekabua and C. Njoku, "Proposed Framework for Making Focused Antenatal Care Services Accessible: A Review of the Nigerian Setting," Obstetrics and Gynecology, 2011 pp.1–5.
  20. L. Melhado, "The Physical Accessibility of Health Facilities Strongly Affects Haitian Women’s Use of Prenatal, Delivery Care," International Family Planning Perspectives, 2007 vol. 33 pp.38-43.
  21. Federal Ministry of Health Nigeria Technical Report - 2012 National HIV/AIDS and Reproductive Health Survey, 2013. Available at: http://www.nigeria-aids.org.
  22. World Health Organisation. Antenatal Care Randomized Trial: Manual for the Implementation of the New Model, Geneva: WHO 2002. Available at:http://whqlibdoc.who.int/hq/2001/WHO_RHR_01.30.pdf.
  23. M.S. Kulkarni and M.R. Nimbalkar. "Influence of Socio-Demographic Factors on the Use of Antenatal Care," Indian Journal of Preventive Social Medicine, 2008 vol. 39 pp.2–6.
  24. N. Nisar and F. White. "Factors affecting utilisation of antenatal care among reproductive age group women (15-49 years) in an urban squatter settlement of Karachi". The Journal of the Pakistan Medical Association, 2003 vol. 53 pp.47–53.
  25. G. Shrestha, "Factors related to utilisation of antenatal care in Nepal: A generalized linear approach," Journal of Kathmandu College, 2013 vol. 2 pp.69–74.

Article Tools
  Abstract
  PDF(252K)
Follow on us
ADDRESS
Science Publishing Group
548 FASHION AVENUE
NEW YORK, NY 10018
U.S.A.
Tel: (001)347-688-8931