Dr. Adeniyi F. FAGBAMIGBE

Basic Information

Olopade 

Name: Dr. Adeniyi F. FAGBAMIGBE

Faculty: PUBLIC HEALTH

EmailThis email address is being protected from spambots. You need JavaScript enabled to view it.

 Department:Epidemiology and Medical Statistics

 Designation: Senior Lecturer

Brief Biography: Adeniyi is a Medical Statistician and Health Data Scientist with both practical research and teaching experience spanning Medical Statistics, Biostatistics, Behavioural Sciences, Survival Analysis, Categorical data analysis, Experimental Design, Probability and Applied Probability, Time Series, Epidemiology, Demography, Health Inequalities and Statistical Modelling and Inferences. He has applied these statistical concepts to a different area of health sciences through research into clinical and public health. He holds a PhD in Biostatistics from the University of Ibadan Nigeria. Before that, he obtained a First Class Honours degree in Statistics from the University of Ilorin, Nigeria and Masters of Science in Medical Statistics from Lancaster University, United Kingdom and Masters in Business Administration from Ekiti State University, Nigeria. He is a graduate fellow of the Consortium for Advanced Research Training in Africa (CARTA) and an Affiliate of the African Academy Of Sciences. He has attended several training in data science. His research focus is in the application of Statistical, Epidemiology and Demographic techniques with a critical interest in disease modelling and survival analysis to improve human health and the world we live in. His research interest spanned the connection between human behavior and health outcomes. He has applied Bayesian modelling with a special interest in MCMC to diverse areas of clinical and public health research. He has taught and mentored several Undergraduate and Postgraduate students and also conducted researches and surveys which centred on disease modelling and applications of Biostatistics, Epidemiology, project development, implementation, monitoring and evaluation, curriculum development as well as data analysis, interpretation and reporting. He has participated in numerous National and International health programs including cross countries analysis of DHS dataset in sub-Sahara Africa and several peer-reviewed publications. He has also attended many local and international conferences in the last five years. He has collaborated with other scientists in clinical, public health, environmental health, population, demography and pure statistical researches and scientific research through which he offered advises on methodologies and provided statistical consultancy for different organizations. His long term research goal is to be a formidable Medical Statistician and Health data Scientist within a formidable health research team.

Resume

Permanent Address: Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.; This email address is being protected from spambots. You need JavaScript enabled to view it.,   

Phone No: +2348061348165,

Google Scholar: https://tinyurl.com/yd38ohq5

Researchgate: https://www.researchgate.net/profile/Adeniyi_Fagbamigbe

Scopus: https://www.scopus.com/authid/detail.uri?authorId=50861113000

Pubmed: https://tinyurl.com/y8omwn6d

ORCID: https://orcid.org/0000-0001-9184-8258

Linkedin: https://www.linkedin.com/in/adeniyi-francis-fagbamigbe-5a830133/                                                             

University Education (With Dates):

  1. University of Ibadan, Nigeria. (Sep 2013 - Feb 2014)
  2. University of Ibadan, Nigeria. (Mar 2008 - Feb 2012)
  3. University of Lancaster, United Kingdom (Oct 2005 - Sep 2006)
  4. University of Ilorin, Nigeria. (Feb 1993  -  Jan 1998)

Academic Qualifications (With Dates and granting Bodies):

  1. Masters in Project Development and Implementation (MPDI) (2014), University of Ibadan, Nigeria
  2. Doctor of Philosophy (PhD) in Biostatistics (2012), University of Ibadan, Ibadan, Nigeria
  3. Masters of Science (M.Sc) Medical Statistics, (2006), University of Lancaster, United Kingdom
  4. Bachelor of Science (B.Sc) Statistics (First Class Honours), (1998), University of Ilorin, Nigeria
  5. Research (Both past and ongoing)

Research

(a) Completed

  1. A Comparative Analysis of Fertility Differentials in Ghana and Nigeria

This retrospective study compared the two countries’ fertility levels and their determinants as well as the differentials in the effect of these factors across the two countries. We carried out a retrospective analysis of data from the Nigeria and Ghana Demographic Health Surveys, 2008. The sample of 33,385 and 4,916 women aged 15-49 years obtained in Nigeria and Ghana respectively was stratified into low, medium and high fertility using reported children ever born. Data were summarized using appropriate descriptive statistics.

  1. Current and Predicted Fertility using Poisson Regression Model: Evidence from 2008 Nigerian Demographic Health Survey

We built a non-linear model to identify fertility determinants and predict fertility using women’s background characteristics. We used 2008 Nigeria Demography and Health Survey dataset consisting of 33,385 women with 31.4% from an urban area. Fertility was measured using children ever born (CEB) and fitted into multi-factors additive Poisson regression models.

  1. Differentials and Correlates of Infants Mortality in Nigeria: A Comparative Survival Analysis between North East and South West Nigeria

We used a nationally representative cross-sectional data from the NDHS 2008 survey. Our analysis was based on the 23,995 and 11,546 births during five years preceding data collection from women aged 15-49 years in NE and SW Nigeria respectively. We censored the children who have not had their first birthday as of the day of the interview and estimated the IMR with Life tables using West Models. Descriptive statistics, bivariate and multivariate Cox regression models were made.

  1. Modelling time to uptake of modern contraceptives among sexually active women of reproductive age in Nigeria: Survival analysis approach

Contraception is fast becoming a recurrent decimal in modern society as a way of achieving desired fertility goal. We used data from 2013 NDHS, a nationally representative survey covering the entire population residing in non-institutional dwelling units in the country. Among others, the women were asked questions about their background characteristics, reproductive history and childhood mortality, knowledge, source, and use of family planning methods. 

  1. Marital Status and HIV Prevalence among women in Nigeria: Evidence from a National Survey
  2. Economic status, a salient motivator for medicalisation of FGM in sub-Saharan Africa: Myth or reality from 13 national demographic health surveys
  3. Africa’s response to the COVID-19 pandemic: A Review of the Nature of the Virus, Impacts and Implications for Preparedness
  4. Demystifying the factors associated with rural – urban gaps in severe acute malnutrition among under five children in low
  5. and middle income countries : a decomposition analysis
  6. Severe acute malnutrition among under-five children in low- and middle-income countries: A hierarchical analysis of associated risk factors
  7. Survival Analysis and Prognostic Factors of Time to First Domestic Violence after Marriage among Married Women in Africa

(b) In Progress

1. Diarrhoea among under-five children in 56 low- and middle-income countries: Prevalence and multilevel analysis of associated risk factors

The study is therefore designed to carry out a meta-analysis of the prevalence of diarrhoea among under-five year children in 56 LMIC. The study also sought to identify the individual-specific factors, neighbourhood factors and country-level factors that affect occurrence of diarrhoea among under-five children in the 56 LMIC using hierarchical Bayesian logistic regression model.

2. Mind the Gap: What explains the poor-non-poor inequalities in having severe acute malnutrition among under-five children in low and middle-Income countries? Compositional and structural characteristics

A good understanding of the poor-non-poor gap in childhood development of severe acute malnutrition (SAM) is a must in tackling the age-long critical challenge to health outcomes of vulnerable children in low- and middle-income countries (LMIC). There is a dearth of information about the factors explaining differentials in wealth inequalities in the distribution of SAM in LMIC. This study is aimed at quantifying the contributions of demographic, socioeconomic, contextual and proximate factors in explaining the poor-non-poor gap in SAM in LMIC.

 3. Evaluation of survival analysis regression models in assessing the association between conception modes and the incidence of Type-1 diabetes among Swedish Births 1985-2015

The data on the onset of type-1 diabetes among children born in Sweden between 1985 and 2015 and conceived either spontaneously or by assisted reproductive technology (ART) showed skewed age distribution since most ART-conceived children are younger and a probable peak in the risk of type-1 diabetes at 10-14 years of age. We aimed to apply and compare the performance of different survival analysis regression models to the data to identify and quantify the risk of ART and other prognostic factors on the timing of onset of diabetes among the children. We used the information on all singleton children (n= 3,138,540) from the Swedish National Board of Health and Welfare, 1985 to 2015. The main determinate variable was the mode of conception. We applied the Cox proportional hazard, parametric and the flexible parametric survival regression (FPSR) models to the data. The loglikelihood, Akaike information criteria and Bayesian information criteria were used to select the best model. Significance was determined at 5% significance level.

4. Evaluation of the performance of different survival regression frailty models using Swedish dental implant data

The choice of appropriate methods for estimating the effects of covariates in survival data with frailty poses challenges to public health researchers. This study aimed to apply a flexible parametric survival regression (FPSR) model Cox proportional hazard with frailty and other parametric models to estimate factors associated with the timing of complications affecting implant-supported dental restorations in a Swedish cohort. The data were obtained from a randomly selected cohort (n=596) of Swedish patients provided with dental restorations supported by implants in 2003. Patients were evaluated over 9 years for complications including (i) implant loss, (ii) peri-implantitis and (iii) technical complications. We applied a flexible parametric survival regression (FPSR), Cox proportional hazard with frailty and parametric models with frailty to identify the factors associated with the timing of complications. We explored the goodness of fit of the models and used the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC).

5. Hierarchical analysis of factors associated with childhood mortality in Nigeria: Approximation of survival regression by Poisson model in Bayesian MCMC procedures

The need for more pragmatic approaches to achieve sustainable development goal on childhood mortality reduction necessitated this study. Simultaneous study of the influence of where the children live and the censoring nature of children survival data is scarce. We identified the compositional and contextual factors associated with under-five (U5M) and infant (INM) mortality in Nigeria from 5 MCMC Bayesian hierarchical Poisson regression models as approximations of survival

regression. The 2018 DHS data of 33,924 under-five children were used. The risks of INM and U5M were highest among children with none/low maternal education, multiple births, short birth interval. Compared with the null model, 81% vs 10% and 59% vs 35% of the total variation in INM and U5M were explained by the state- and neighbourhood-level factors respectively. Risk of infants and under-five mortality in Nigeria is influenced significantly by compositional and contextual factors. The Poisson regression models fitted the survival data.

6. Hierarchical analysis of risk factors of diarrhoea among under-five children in low- and middle-income countries: disentangling context from composition

Several studies have documented the burden and risk factors associated with diarrhoea in low and middle-income countries (LMIC). To the best of our knowledge, the contextual and compositional factors associated with diarrhoea were poorly operationalized, explored and understood in these studies. We investigated multilevel risk factors associated with diarrhoea among under-five children in LMIC. We analysed diarrhoea-related information of 796,150 under-five children (Level 1) nested within 63,378 neighbourhoods (Level 2) from 57 LMIC (Level 3) from cross-sectional and nationally representative Demographic Health Survey. We used multivariable hierarchical Bayesian logistic regression models. The overall prevalence of diarrhoea was 14.2% ranging from 3.8% in Armenia to 31.4% in Yemen.

7. Decomposition analysis of the compositional and contextual factors associated with poor-non-poor inequality in diarrhoea among under-five children in low- and middle-income countries

To assess the magnitude of wealth inequalities in the development of diarrhoea among U5C in the LMIC, identified and quantified contextual and compositional factors’ contribution to the inequalities. We used cross-sectional data from 57 Demographic and Health Surveys conducted between 2010 and 2018 in LMIC. Descriptive statistics were used to understand the gap in having diarrhoea between the children from poor and non-poor households and across the selected covariates using Fairlie decomposition techniques with multivariable binary logistic regressions at p=0.05.

Publications (All)

Book Chapters

  1. Fagbamigbe, A.F., (2019) Selected Topics in Medical Statistics (1st Edition) ISBN: 978-978-546-330-E, Edited by Adebowale A. S. & Akinyemi J.O.; Chapter 8: Principles and Methods of Data Simulation in Health Research in Page 107-19 Andkolads Publishers, Ile Ife, Nigeria
  2. Fagbamigbe, A. F., Adeoye, I. A., & Musa I. (2019) Selected Topics in Medical Statistics (1st Edition) ISBN: 978-978-546-330-E, Edited by Adebowale A. S. & Akinyemi J.O. Chapter 14: Survival Analysis: Concepts and Techniques, Page 268-91, Andkolads Publishers, Ile Ife, Nigeria

 

Publications in Learned Peer-reviewed Journals

2010

  1. Yusuf, O. B., Adebowale, A. S., Fagbamigbe, A.F., Bamgboye, E.A. and Oyediran, A.B.O.O. (2010) Profile of academic and senior non-teaching staff in a Nigerian university. Journal of Educational Administration and Policy Studies 2(7), pp. 92 - 98. https://academicjournals.org/journal/IJEAPS/article-abstract/9C38273984
  2. Fagbamigbe, A.F. and Adebowale, A. S. (2010), A model for measuring association between bivariate censored outcomes. Journal of Modern Mathematics and Statistics. 4(4): pp 127 -136, https://doi.org/10.10.3923/jmmstat.2010.127.136
  3. Adebowale, S.A., Fagbamigbe, A.F.. and Bamgboye, E.A. (2010); Rural-Urban Differential in Maternal Mortality in Nigeria, sub-Saharan Africa; Journal of Biomedical Sciences, Vol 2, pp 74-91, cenresinpub.org/mortality.pdf

2011

  1. Adebowale, A.S., Adepoju, O.T. and Fagbamigbe, A.F. (2010); Child Spacing and Parity Progression; Implication for Maternal Nutritional Status among Women in Ekiti Communities; Pakistan Journal of Nutrition 10 (5): 485-491; http://docsdrive.com/pdfs/ansinet/pjn/2011/485-491.pdf
  2. Adebowale, A.S., Adepoju, O.T., Okareh, O. T. and F. Fagbamigbe (2011), Social epidemiology of Adverse Nutritional Status Outcomes among Women in Nigeria: NDHS, 2008, Pakistan Journal of Nutrition 10 (9): 888-898, ISSN 1680-5194 http://docsdrive.com/pdfs/ansinet/pjn/2011/888-898.pdf
  3. Apau, G.S, Fagbamigbe, A.F, Adebowale, A.S. and Bamgboye, E.A. (2011); Modelling Morbidity Related Absenteeism among Workers in University of Ibadan Community, Nigeria: Poisson Regression, International Journal of the Physical Sciences Vol. 6(18), pp. 4458-4465, https://academicjournals.org/journal/IJPS/edition/9_September
  4. Fagbamigbe A.F., Akinyemi, J.O., Adedokun, B.O. and Bamgboye, E.A.; (2011) Gender variation in the self-reported likelihood of HIV infection in comparison with HIV test results in rural and urban Nigeria. AIDS Research and Therapy, 8:44 https://doi.org/10.1186/1742-6405-8-44
  5. Adebowale, A.S., Fagbamigbe, A.F. and Bamgboye, E.A. (2011) Contraceptive Use: Implication for Completed Fertility, Parity Progression and Maternal Nutritional Status in Nigeria, sub-Saharan Africa.” Afr Journal Reproductive Health Vol. 15 No. 4 pp 69-78; https://www.ajol.info/index.php/ajrh/article/view/74794
  6. Fagbamigbe, A.F. ., Adebowale, A.S., and Olaniyan, F.A, (2011) A comparative analysis of Condom use among unmarried youths in rural community in Nigeria; Public Health Research. 2011; 1(1): 8-16 https://doi.org/10.5923/j.phr.20110101.02

2012

  1. Adebowale, A.S., Fagbamigbe, A.F. and Bello, S. (2012); Refined age Distribution and Demographic parameters Estimation in Nigeria: An Indirect approach, Journal of Statistics and Management Sciences, Vol. 15(1), pp. 29-48; https://doi.org/10.1080/09720510.2012.10701611;
  2. Muruka, C, Fagbamigbe A.F., Muruka, A., Njuguna, J., Otieno, D.J., Onyando, J., Wanjiku, Z.S. and Onyango, Z. (2012), The Relationship between Bacteriological Quality of Dug-Wells & Pit Latrine Siting in an Unplanned Peri-Urban Settlement: A Case Study of Langas – Eldoret Municipality, Western Kenya. Public Health Research 2. No. 2, 32-36 https://doi.org/10.5923/j.phr.20120202.06
  3. Abiona, T.O., Adebowale, A.S. and Fagbamigbe, A.F. (2012), Time series analysis of admission in the Accident and Emergency unit of University College Hospital, Ibadan Nigeria; American Journal of Computational and Applied Mathematics, 2(1): 1-9 https://doi.org/10.5923/j.ajcam.20120201.01
  4. Adebowale, A.S., Yusuf, O.B, and Fagbamigbe, A.F. (2012): Survival Probability and Predictors for Woman Experience Childhood Death in Nigeria: “Analysis of North-South Differentials”. BMC Public Health 12. No. 1, 430-442. https://doi.org/10.1186/1471-2458-12-430
  5. Adebowale, A.S., Fagbamigbe, A.F. Okareh, O.T., Lawal, G.O. (2012): Survival Analysis of Timing of First Marriage among Women of Reproductive age in Nigeria: Regional Differences. African Journal of Reproductive Health 16. No. 4, 95-107. https://www.ajol.info/index.php/ajrh/article/view/83687

2013

  1. Adebowale, A.S., Titiloye, M.A, Fagbamigbe, A.F., Akinyemi, J.O. (2013): Statistical modeling of social risk factors for sexually transmitted diseases among female youths in Nigeria. Journal Infections in Developing Countries 7. No. 1, 17-27. http://doi.org/10.3855/jidc.2272
  2. Akanbiemu, A.F., Olumide A, Fagbamigbe A.F. and Adebowale, A.S. (2013), Effect of Perception and Free Maternal Health Services on Antenatal Care Facilities Utilization in Selected Rural and Semi-Urban Communities of Ondo State, Nigeria. British Journal of Medicine & Medical Research 3(3): 681-697, http://doi.org/10.9734/BJMMR/2013/2621
  3. Fagbamigbe, A.F., Akanbiemu, A.F., Adebowale, A.S., Ma-nuwa Olumide, A. and Korter, G.O. (2013), Practice, Knowledge and Perceptions of Antenatal Care Services among Pregnant Women and Nursing Mothers in Southwest Nigeria Intl Journal of Maternal and Child Health 2013, 1(1):7-16 ; doi.org/ 10.12966/ijmch.05.02.2013
  4. Oyedeji, K.S., Fagbamigbe, A.F., Ogboi, J.S., Bashorun, A.T., Issa, K.B., Amida, P, Ogundiran, A. and Ezire, O. (2013), Does Pre-Survey Training Impact Knowledge of Survey Administrators and Survey Outcomes in Developing Countries? Evaluation Findings of a Training of Trainers Workshop for National AIDS and Reproductive Health Survey-Plus in Nigeria International Journal of MCH and AIDS 2(1) 1, 129-138 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4948138/
  5. Fatiregun, A.A., Adebowale, A.S., Ayoka, R.O. and Fagbamigbe, A.F. (2013) Assessing full immunisation coverage using lot quality assurance sampling in urban and rural districts of southwest Nigeria. Trans R Soc Trop Med Hyg 107 (11): 731-74, https://www.ncbi.nlm.nih.gov/pubmed/24062523 ; https://doi.org/10.1093/trstmh/trt079
  6. Fatiregun, A.A., Adebowale, A.S. and Fagbamigbe, A.F. (2014): Epidemiology of measles in Southwest Nigeria: an analysis of measles case-based surveillance data from 2007 to 2012. Transactions of the Royal Society of Tropical Medicine and Hygiene 108(3), 133-140 ; https://doi.org/10.1093/trstmh/tru004

2014

  1. Fagbamigbe, A.F. and Adebowale, A.S. (2014) Current and Predicted Fertility using Poisson Regression Model: Evidence from 2008 Nigerian Demographic Health Survey Modelling and predicting fertility outcomes among Nigeria women. Afr J Reprod Health 2014; 18(1): 71-83 https://www.ajol.info/index.php/ajrh/article/view/102464
  2. Ogboi, J.S., Agu, P.U.,Fagbamigbe, A.F., Audu O., Akubue, A., Obianwu, I. (2014),  Misdiagnosis  of  malaria  using  wrong  buffer  substitutes  for  rapid  diagnostic  tests in  poor  resource  setting  in  Enugu,  Southeast  Nigeria Malaria World Journal, 5(6), 1-6 https://malariaworld.org/mwj/2014/research-misdiagnosis-malaria-using-wrong-buffer-substitutes-rapid-diagnostic-tests-poor
  3. Fagbamigbe, A.F. and Alabi, O. (2014) Differentials and Correlates of Infants Mortality in Nigeria: A Comparative Survival Analysis between North East and South West Nigeria. International Journal of Tropical Disease & Health, 4(8) pp: 869-886, https://doi.org/10.9734/IJTDH/2014/9597
  4. Adebowale, A.S., Fagbamigbe, A.F. and Bamgboye, E.A. Re-analysis of Nigerian 2006 Census Age Distribution using Growth Rate and Mortality Level. Southern African Journal of Demography 15(1), Pp 82-99. https://www.jstor.org/stable/soutafrijourdemo.15.1.81?seq=1#page_scan_tab_contents
  5. Olatoregun, O., Fagbamigbe, A.F., Akinyemi, O.J., Yusuf, O.B. and Bamgboye, E.A. ( 2014) A Comparative Analysis of Fertility Differentials in Ghana and Nigeria Afr J Reprod Health 2014; 18(3): 36-47. https://www.ajol.info/index.php/ajrh/article/view/109197
  6. Ogboi, S.J., Agu, P.U., Akpoigbe, J.K., Fagbamigbe, A.F., Audu, O., Obianwu, I.M. and Akabueze, J. (2014) Prevalence and Risk Factors of Malaria in HIV-Infected Pregnant Women on Anti-Retroviral Therapy in Enugu, South East Nigeria; Journal of AIDS and Clinical Research, 5:7 https://doi.org/10.4172/2155-6113.1000321
  7. Fatiregun, A.A., Fagbamigbe, A.F., Adebowale, A.S. (2014) Epidemiology of rubella disease in south-west Nigeria: Trends and projection from measles case-based surveillance data South Afr J Infect Dis 2014;29(2):60-64 http://www.tandfonline.com/doi/abs/10.1080/23120053.2014.11441571

2015

  1. Fagbamigbe, A.F., Bamgboye, E. A., Yusuf, O.B., Akinyemi, O. J., Issa, B. K., Ngige, E., Amida, P., Bashorun, A., Abatta, E. (2015) The Nigeria wealth distribution and health seeking behaviour: evidence from the 2012 national HIV/AIDS and reproductive health survey. Health Economics Review 5:5, 1-10 PMID: 25853003 [PubMedhttps://doi.org/ 10.1186/s13561-015-0043-9
  2. Fagbamigbe, A.F. and Idemudia, E.S. (2015) Barriers to antenatal care use in Nigeria: evidences from Non-users and implications for maternal health programming BMC Pregnancy and Childbirth, 15:95 1-10  https://doi.org/10.1186/s12884-015-0527-y PubMed: 25885481
  3. Fagbamigbe, A.F. and Idemudia, E.S. (2015) Assessment of quality of antenatal care services in Nigeria: evidence from a population-based survey Reproductive Health (2015) 12:88, 1-9; https://doi.org/10.1186/s12978-015-0081-0 PMCID:PMC4574449
  4. Fagbamigbe, A.F., Adebowale, A.S., and Morhason-Bello, I.O. (2015). Survival analysis of time to uptake of modern contraceptives among sexually active women of reproductive age in Nigeria BMJ Open 2015(5):1-10,e008371.https://doi.org/10.1136/bmjopen-2015-008371
  5. Fagbamigbe, A.F. and Idemudia, E.S. (2015). Does Gender and Age at Sexual Initiation affect Modern Contraceptive Use among Teenagers and Young adults in Nigeria? Gender and Behaviour 13(2) 6710-6719. https://www.questia.com/library/journal/1P3-3906144301/does-gender-and-age-at-sexual-initiation-affect-modern
  6. Ezire, O., Okekearu, I., Fagbamigbe, A.F., & Faweya, O. (2015). Analysis of Health Facility Based Barriers and Facilitators to use of Sexual and Reproductive Health Care Services among Most at Risk Populations (MARPS): Evidence from a Mystery Client Survey in Nigeria. Journal of Tropical Diseases and Public Health, 3(4), 1–5. https://doi.org/10.4172/2329891X.1000171

2016

  1. Morhason-Bello I.O., Fagbamigbe, A.F., Mumuni, T.O., Adesina, O.A., Abdus-Salam, A.R., Ifemeje, A., Ojengbede, O.A. (2016). Evaluation of correct knowledge of key danger signs in pregnancy among antenatal clinic attendees at a tertiary health facility in Nigeria. Niger J Clin Pract;19(2):227–32. https://doi.org/ 10.4103/1119-3077.164347
  2. Fagbamigbe, A.F. and Idemudia, E.S. (2016) Survival analysis and prognostic factors of timing of first childbirth among women in Nigeria. BMC Pregnancy Childbirth:16:102, pp1–12. Https://doi.org/ 10.1186/s12884-016-0895-y. https://doi.org/10.1186/s12884-016-0895-y
  3. Fagbamigbe, A.F. and Idemudia, E.S. (2016). Survival analysis and determinants of timing of first birth after marriage in Nigeria. Afr Popul Stud, 30(2), 2444–57. https://doi.org/10.11564/30-2,-856
  4. Yusuf, O. B., Akinyemi, J.O., Fagbamigbe, A.F. , Ajayi, I.O., Bamgboye, E.A., Ngige, E., Issa, K., Abatta, E., Ezire, O., Amida, P., Bashorun, A. (2016) Controlling malaria in pregnancy: how far from the Abuja targets? Malaria World Journal, 7(7), 3–10. https://malariaworld.org/sites/default/files/mwjournal/article/MWJ2016_7_7.pdf
  5. Fagbamigbe, A.F., Adebayo, S.B., and Idemudia, E.S. (2016). Marital status and HIV prevalence among women in Nigeria: Ingredients for evidence-based programming. International Journal of Infectious Diseases, 48(1), 57–63. https://doi.org/10.1016/j.ijid.2016.05.002
  6. Fagbamigbe, A.F. and Akinyemi, O.J. (2016). Modelling the survivorship of Nigeria children in their first 10 years of life. The Nigerian Health Journal, 16(1), 1–19. http://www.tnhjph.com/index.php/tnhj/article/view/194/pdf_1
  7. Fagbamigbe, A.F. and Idemudia, E.S. (2016). Wealth and antenatal care utilization in Nigeria: Policy implications. Health Care for Women International, 38(1): 17-37. https://doi.org/10.1080/07399332.2016.1225743
  8. Adebowale, A.S., Fagbamigbe, A.F. and Adebayo, A.M. (2016). Regional Differences in Adolescent Childbearing in Nigeria. Journal of Population and Social Studies, 24(2), 101–116. https://doi.org/10.14456/jpss.2016.8
  9. Eze, P.N., Mosokomani, V.S., Udeigwe, T.K., Oyedele, O.F., & Fagbamigbe, A.F. (2016). Data in Brief Geostatistical analysis of trace elements PXRF dataset of near-surface semi-arid soils from Central Botswana. Data in Brief, Elsevier 9, 764–770. https://doi.org/10.1016/j.dib.2016.10.010

2017

  1. Fagbamigbe, A.F., Adebowale, A.S. and Bamgboye, E.A. (2017) A Survival Analysis Model for Measuring Association between Bivariate Censored Outcomes : Validation Using Mathematical Simulation. Am J Math Stat, 7(1):7–14. https://doi.org/10.5923/j.ajms.20170701.02
  2. Shodimu, M.A., Yusuf, O.B., Akinyemi, J.O., Fagbamigbe, A.F. , Bamgboye, E.A., Ngige, E., Issa, K., Abatta, E., Ezire, O., Amida, P., Bashorun, A. (2017). Determinants of perceived stigmatizing and discriminating attitudes towards people living with HIV / AIDS among women of reproductive age in Nigeria. Journal of AIDS and HIV Research, 9(6), 139–151. https://doi.org/10.5897/JAHR2016.0391
  3. Fagbamigbe, A.F. and Ojebuyi, B.R. (2017) Influence of Spousal Communication about Family Planning and HIV/AIDS-related Issues on Modern Contraceptive Use in Nigeria. Journal of Health Management, 19(2) 1-14; https://doi.org/10.1177/0972063417699693
  4. Fagbamigbe, A.F. and Idemudia, E.S, (2017) Diversities in timing of sexual debut among Nigerian youths aged 15-24 years: parametric and non-parametric survival analysis approach. Afri Health Sci. 2017; 17(1): 39-51. https://dx.doi.org/10.4314/ahs.v17i1.7
  5. Obiyan, M.O., Fagbamigbe, A.F., Adetutu, O.M., and Oyinlola, F.F. (2017), Fertility, labour force participation and poverty among married women in Nigeria African Popul Stud, 31(1):3408–3420. https://dx.doi.org/10.11564/31-1-999
  6. Okwor, V.C., Fagbamigbe, A.F. and Fawole, O.I. Survivorship of patients with head and neck cancer receiving care in a tertiary health facility in Nigeria. Cancer Manag Res. 2017;9:331-338. https://doi.org/10.2147/CMAR.S133108.
  7. Fagbamigbe, A.F. and Makanjuola, V.A. Modeling association between times to recurrence of the different polarities in bipolar disorder among service seekers in urban Nigeria: a survival analysis approach. Neuropsychiatr Dis Treat. 2017;13:1967-1974. https://doi.org/10.2147/NDT.S133167.
  8. Alo, O.D., Akinyemi, J.O., Akpa, M.O., Yusuf, O.B., Fagbamigbe, A.F. , Bamgboye, E.A., Adebayo, S.B., Issa, K., Agbi, P. and Ezire, O. (2017). Level and determinants of pharmacovigilance programme awareness in Nigeria : A multilevel analysis. Afr J of Pharm and Pharm, 11(29), 342–348. https://doi.org/10.5897/AJPP2017.4571
  9. Morakinyo, O.M. and Fagbamigbe, A.F. (2017). Neonatal, infant and under-five mortalities in Nigeria : An examination of trends and drivers (2003-2013 ). PLoS ONE, 12(8), e0182990. https://doi.org/10.1371/journal.pone.0182990
  10. Fagbamigbe, A.F., Morakinyo, O.M., and Abatta, E. (2017). Analysis of Regional Variations in Influence of Household and Environmental Characteristics on Prevalence of Diarrhoea among Under-Five Children in Nigeria. . Ann Med Health Sci Res., 7(3), 119–130. http://www.amhsr.org/archive/amhsr-volume-7-issue-3-may-2017.html
  11. Akinyemi, J. O., Yusuf, B. O., Fagbamigbe, A. F., Bamgboye, E. A., Issa, B. K., Ngige, E., … Bashorun, A. (2017). Derivation and appraisal of maternal mortality estimates in Nigeria from the 2012 National HIV/AIDS and Reproductive Health Survey. Afr Journal of Medicine and Medical Sciences, 46(1), 159–166.
  12. Fagbamigbe, A. F., Lawal, A. M., & Idemudia, E. S. (2017). Modelling self-assessed vulnerability to HIV and its associated factors in a HIV-burdened SAHARA-J: Journal of Social Aspects of HIV/AIDS, 14(1), 140–152. https://doi.org/10.1080/17290376.2017.1387598
  13. Fagbamigbe, A. F., Mashabe, B., Lepetu, L., & Abel, C. (2017). Are the timings and risk factors changing ? Survival analysis of timing of first antenatal care visit among pregnant women in Nigeria (2003 – 2013). International Journal of Womens Health, 9(1), 807–819. https://doi.org/10.2147/IJWH.S138329
  14. Fagbamigbe, A. F., Hurricane-Ike, E., Yusuf, O.B, & Idemudia, E.S. (2017). Trends and drivers of skilled birth attendant use in Nigeria (1990–2013): policy implications for child and maternal health. International Journal of Women’s Health, Volume 9(1), 843–853. https://doi.org/10.2147/IJWH.S137848

2018

  1. Akinyemi, A. I., Fagbamigbe, A. F., Omoluabi, E., Agunbiade, O. M., & Adebayo, S. O. (2018). Diarrhoea Management Practices and Child Health Outcomes in Nigeria: Sub-National Analysis. Advances in Integrative Medicine, 5; 15-22. https://doi.org/10.1016/j.aimed.2017.10.002
  2. Fagbamigbe, A. F., Afolabi, R. F., & Idemudia, E. S. (2018). Demand and Unmet Needs of Contraception among Sexually Active In-Union Women in Nigeria: Distribution, Associated Characteristics, Barriers, and Program Implications. SAGE Open, 8(1), 215824401775402. https://doi.org/10.1177/2158244017754023
  3. Fagbamigbe, A. F. & Bakre, B. B. (2018). Evaluating Likelihood Estimation Methods in Multilevel Analysis of Clustered Survey Data. African J Appl Stat.;5(1):351–76. http://dx.doi.org/10.16929/ajas/351.220
  4. Gil-Alana, L.A., Yaya, O.S. & Fagbamigbe, A. F. (2018) Time series analysis of quarterly rainfall and temperature (1900–2012) in sub-Saharan African countries. Theor Appl Climatol. Springer Vienna; 2018;1–16. https://doi.org/10.1007/s00704-018-2583-5
  5. Morakinyo O.M., Balogun, F.M. & Fagbamigbe, A. F. (2018) Housing type and risk of malaria among under ‑ five children in Nigeria : evidence from the malaria indicator survey. Malar J. BioMed Central; 17(311):1–11. https://doi.org/10.1186/s12936-018-2463-6;
  6. Fagbamigbe, A. F., Awoyelu, I. E., Akinwale, O. L., Akinwande, T. Y., Enitilo, B. K., & Bankole, O. (2018). Factors contributing to the duration of postpartum abstinence among Nigerian women : semi-parametric survival analysis. Heliyon, 4(12), e01032. https://doi.org/10.1016/j.heliyon.2018.e01032
  7. Fagbamigbe, A. F., Obiyan, M. O., & Fawole, O. I. (2018). Parametric survival analysis of menarche onset timing among Nigerian girls. Heliyon, 4(12), e01105. https://doi.org/10.1016/j.heliyon.2018.e01105
  8. Gbadebo, B. M., Fagbamigbe, A.F., & Adebowale, S. A. (2018) Environmental Factors as Predictors of Childhood Mortality Experience in Nigeria. Afr J Env Heal Sc.; 5(11):23–34.

2019

  1. Fagbamigbe, A. F., Abel, C., Mashabe, B. & Adebowale, A. S. (2019) Survival analysis and prognostic factors of the timing of first antenatal care visit in Nigeria, Advances in Integrative Medicine 6(1), 1-10. https://doi.org/10.1016/j.aimed.2018.12.002
  2. Fagbamigbe, A. F. (2019). On the discriminatory and predictive accuracy of the RDT against the microscopy in the diagnosis of malaria among under-five children in Nigeria. Malaria Journal, 18(46), 1-12. https://doi.org/10.1186/s12936-019-2678-1
  3. Ojebuyi, B. R., Fagbamigbe, A. F., & Akinola, O. O. (2019). Prevalence of and Factors Influencing Parent–Child Communication about HIV/AIDS, and Sexual and Reproductive Health Issues in Nigeria. SAGE Open, 9(1), 1-12. https://doi.org/10.1177/2158244019833880
  4. Adebayo, S., Gayawan, E., Fagbamigbe, A. F., & Bello, F. (2019). Bayesian geo-additive spatial modelling of HIV prevalence using data from population-based surveys. HIV & AIDS Review. 18(1), 1-14, https://doi.org/10.5114/hivar.2019.83852
  5. Adeoye, I. A., & Fagbamigbe, A. F. (2019). What is the Link between Malaria Prevention in Pregnancy and Neonatal Survival in Nigeria ? Afr J Rep Health., 23(1), 139–149. https://doi.org/10.29063/ajrh2019/v23i1.14
  6. Fagbamigbe, A. F., Afolabi, R. F., Alade, K. Y., Adebowale, A. S., & Yusuf, B. O. (2019). Unobserved Heterogeneity in the Determinants of Under-five Mortality in Nigeria: Frailty Modeling in Survival Analysis. African Journal of Applied Statistics, 6(1), 565–583. https://doi.org/10.16929/ajas/565.231
  7. Fagbamigbe, A. F., Basele, G. K., Makubate, B., & Oluyede, B. O. (2019). Application of the Exponentiated Log-Logistic Weibull Distribution to Censored Data. Nig. Soc. Phys. Sci, 1(1), 12–19. https://jnsps.org/jnsps_articles/2019/6faf3561354149eaa9d1f53cdc351b2f.php
  8. Fagbamigbe, A. F., Abi, B., Akinwumi, T., Ogunsuji, O, Odigwe, A. and Olowolafe, T. (2019). Survival Analysis and Prognostic Factors Associated with the Timing of First Forced Sexual Act among Women in Kenya, Zimbabwe and Cote d‘Ivoire.” Scientific African 4:e00092. https://doi.org/10.1016/j.sciaf.2019.e000922
  9. Fagbamigbe, A. F., Afolabi, R. F. and Yusuf, O. B. (2019). “Trend Analysis of Teenage Pregnancy in Nigeria (1961-2013): How Effective Is the Contraceptive Use Campaign?” International Journal of Public Health Science (IJPHS) 8(2):21–31. https://doi.org/10.11591/ijphs.v8i2.16429
  10. Fagbamigbe, A. F., Adebowale, A. S., & Ajayi, I. (2019). An assessment of the nutritional status of ART receiving HIV-orphaned and vulnerable children in South-West Nigeria. Heliyon, 5(May), e02925. https://doi.org/10.1016/j.heliyon.2019.e02925
  11. Adebowale, A. S., Fagbamigbe, A. F., Morakinyo, O., Obembe, T., Afolabi, R. F., & Palamuleni, M. E. (2019). Parental Educational Homogamy and Under-Five Mortality in Sub-Saharan Africa: Clarifying the Association’s Intricacy. Scientific African, e00255. https://doi.org/10.1016/j.sciaf.2019.e00255

2020

  1. Morhason-Bello, I. O., & Fagbamigbe, A. F. (2020). Association between Knowledge of Sexually Transmitted Infections and Sources of the Previous Point of Care among Nigerians : Findings from Three National HIV and AIDS Reproductive Health Surveys. Intl J. of Reproductive Medicine, 2020, 1–11. https://doi.org/10.1155/2020/6481479
  2. Fagbamigbe, A. F., Akintayo, A. O., Oshodi, O., Makinde, F. T., Babalola, M., Damilola, E. A., Enabor, O. C. & Dairo, M. D. (2020). Survival Analysis and Prognostic Factors of Time to First Domestic Violence after Marriage among Married Women in Africa. Public Health, 181(2020), 1–13. https://doi.org/https://doi.org/10.1101/524637
  3. Fagbamigbe, A. F., Kandala, N. B., & Uthman, O. (2020). Severe acute malnutrition among under-five children in low- and middle-income countries: A hierarchical analysis of associated risk factors. Nutrition, 110768. https://doi.org/10.1016/j.nut.2020.110768
  4. Fagbamigbe, A. F., Kandala, N. B., & Uthman, O. A. (2020). Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in low- and middle-income countries. BMC Public Health, 20(555), 1–14. https://doi.org/10.1186/s12889-020-08635-3
  5. Morhason-Bello, I. O., Fagbamigbe, A. F., Yusuf, O. K., and Ojengbede, O. A. (2020). “Economic Status, a Salient Motivator for Medicalisation of FGM in Sub-Saharan Africa: Myth or Reality from 13 National Demographic Health Surveys.” SSM - Population Health 11: 100602. https://doi.org/10.1016/j.ssmph.2020.100602.
  6. Fagbamigbe, A. F., Kandala, N. B., & Uthman, O. A. (2020). Demystifying the factors associated with rural – urban gaps in severe acute malnutrition among under ‑ five children in low ‑ and middle ‑ income countries : a decomposition analysis. Scientific Reports. Nature Publishing Group UK; 2020;10:1–15. https://doi.org/10.1038/s41598-020-67570-w.
  7. Adebowale, A. S., Fagbamigbe, A. F., Akinyemi, J. O., Olowolafe, T., Onwusaka, O., Adewole, D. Saidu, S, Palamuleni, M. (2020) Dynamics of Poverty-Related Dissimilarities in Fertility in Nigeria: 2003-2018. African, Elsevier; 2020;e00468. https://doi.org/10.1016/j.sciaf.2020.e00468
  8. Oyedele, O. K., Fagbamigbe, A. F. & Ayeni, O. (2020) Modelling time-to-discontinuation of exclusive breastfeeding: analysis of infants and under-2 survival in Nigeria. Afr Popul Stud 34(1), 1–13.
  9. Fagbamigbe, A. F., Ojo, A. E., Onyeike, N. O., Okafor, I. P., Atilola, S. O., Olabuyi, R. A, Afolabi, R. F., (2020). Survival analysis of time interval between first and second childbirth among women in Nigeria. J. Med. Med. Sc 49,.
  10. Kodaolu, M. Y., Fagbamigbe, A. F., & Ajayi, I. O. (2020). Stocking pattern for anti ‑ malarial medications among proprietary patent medicine vendors in Akinyele Local Government Area , Ibadan , Nigeria. Malaria Journal, 19(279), 1–15. https://doi.org/10.1186/s12936-020-03350-1
  11. Oluyede, B. O., Mashabe, B., Fagbamigbe, A. F., Makubate, B., & Wanduku, D. (2020). Heliyon The exponentiated generalized power series Family of distributions : theory , properties and applications. Heliyon, 6(August), e04653. https://doi.org/10.1016/j.heliyon.2020.e04653

Preprint

  1. Badu, K., Thorn, J. P.R., Goonoo, N., Dukhi, N., Fagbamigbe, A. F.,, Kulohoma, B. W., Oyebola, K., et al. “Africa’s Response to the COVID-19 Pandemic: A Review of the Nature of the Virus, Impacts and Implications for Preparedness.” AAS Open Research 3:19, 1-21. https://doi.org/10.12688/aasopenres.13060.1.
  2. Aloui-Zarrouk, Z., El Youssfi, L., Badu, K., Fagbamigbe, A. F., Matoke-Muhia, D., Ngugi, C., Dukhi, N., Mwaura, G. (2020). The wearing of face masks in African countries under the COVID-19 crisis: luxury or necessity? [version 1; peer review: awaiting peer reviewhttps://doi.org/10.12688/aasopenres.13079.1">https://doi.org/10.12688/aasopenres.13079.1

Researches

(a) Completed

  1. A Comparative Analysis of Fertility Differentials in Ghana and Nigeria

This retrospective study compared the two countries’ fertility levels and their determinants as well as the differentials in the effect of these factors across the two countries. We carried out a retrospective analysis of data from the Nigeria and Ghana Demographic Health Surveys, 2008. The sample of 33,385 and 4,916 women aged 15-49 years obtained in Nigeria and Ghana respectively was stratified into low, medium and high fertility using reported children ever born. Data were summarized using appropriate descriptive statistics.

  1. Current and Predicted Fertility using Poisson Regression Model: Evidence from 2008 Nigerian Demographic Health Survey

We built a non-linear model to identify fertility determinants and predict fertility using women’s background characteristics. We used 2008 Nigeria Demography and Health Survey dataset consisting of 33,385 women with 31.4% from an urban area. Fertility was measured using children ever born (CEB) and fitted into multi-factors additive Poisson regression models.

  1. Differentials and Correlates of Infants Mortality in Nigeria: A Comparative Survival Analysis between North East and South West Nigeria

We used a nationally representative cross-sectional data from the NDHS 2008 survey. Our analysis was based on the 23,995 and 11,546 births during five years preceding data collection from women aged 15-49 years in NE and SW Nigeria respectively. We censored the children who have not had their first birthday as of the day of the interview and estimated the IMR with Life tables using West Models. Descriptive statistics, bivariate and multivariate Cox regression models were made.

  1. Modelling time to uptake of modern contraceptives among sexually active women of reproductive age in Nigeria: Survival analysis approach

Contraception is fast becoming a recurrent decimal in modern society as a way of achieving desired fertility goal. We used data from 2013 NDHS, a nationally representative survey covering the entire population residing in non-institutional dwelling units in the country. Among others, the women were asked questions about their background characteristics, reproductive history and childhood mortality, knowledge, source, and use of family planning methods. 

  1. Marital Status and HIV Prevalence among women in Nigeria: Evidence from a National Survey
  2. Economic status, a salient motivator for medicalisation of FGM in sub-Saharan Africa: Myth or reality from 13 national demographic health surveys
  3. Africa’s response to the COVID-19 pandemic: A Review of the Nature of the Virus, Impacts and Implications for Preparedness
  4. Demystifying the factors associated with rural – urban gaps in severe acute malnutrition among under five children in low
  5. and middle income countries : a decomposition analysis
  6. Severe acute malnutrition among under-five children in low- and middle-income countries: A hierarchical analysis of associated risk factors
  7. Survival Analysis and Prognostic Factors of Time to First Domestic Violence after Marriage among Married Women in Africa

(b) In Progress

1. Diarrhoea among under-five children in 56 low- and middle-income countries: Prevalence and multilevel analysis of associated risk factors

The study is therefore designed to carry out a meta-analysis of the prevalence of diarrhoea among under-five year children in 56 LMIC. The study also sought to identify the individual-specific factors, neighbourhood factors and country-level factors that affect occurrence of diarrhoea among under-five children in the 56 LMIC using hierarchical Bayesian logistic regression model.

2. Mind the Gap: What explains the poor-non-poor inequalities in having severe acute malnutrition among under-five children in low and middle-Income countries? Compositional and structural characteristics

A good understanding of the poor-non-poor gap in childhood development of severe acute malnutrition (SAM) is a must in tackling the age-long critical challenge to health outcomes of vulnerable children in low- and middle-income countries (LMIC). There is a dearth of information about the factors explaining differentials in wealth inequalities in the distribution of SAM in LMIC. This study is aimed at quantifying the contributions of demographic, socioeconomic, contextual and proximate factors in explaining the poor-non-poor gap in SAM in LMIC.

 3. Evaluation of survival analysis regression models in assessing the association between conception modes and the incidence of Type-1 diabetes among Swedish Births 1985-2015

The data on the onset of type-1 diabetes among children born in Sweden between 1985 and 2015 and conceived either spontaneously or by assisted reproductive technology (ART) showed skewed age distribution since most ART-conceived children are younger and a probable peak in the risk of type-1 diabetes at 10-14 years of age. We aimed to apply and compare the performance of different survival analysis regression models to the data to identify and quantify the risk of ART and other prognostic factors on the timing of onset of diabetes among the children. We used the information on all singleton children (n= 3,138,540) from the Swedish National Board of Health and Welfare, 1985 to 2015. The main determinate variable was the mode of conception. We applied the Cox proportional hazard, parametric and the flexible parametric survival regression (FPSR) models to the data. The loglikelihood, Akaike information criteria and Bayesian information criteria were used to select the best model. Significance was determined at 5% significance level.

4. Evaluation of the performance of different survival regression frailty models using Swedish dental implant data

The choice of appropriate methods for estimating the effects of covariates in survival data with frailty poses challenges to public health researchers. This study aimed to apply a flexible parametric survival regression (FPSR) model Cox proportional hazard with frailty and other parametric models to estimate factors associated with the timing of complications affecting implant-supported dental restorations in a Swedish cohort. The data were obtained from a randomly selected cohort (n=596) of Swedish patients provided with dental restorations supported by implants in 2003. Patients were evaluated over 9 years for complications including (i) implant loss, (ii) peri-implantitis and (iii) technical complications. We applied a flexible parametric survival regression (FPSR), Cox proportional hazard with frailty and parametric models with frailty to identify the factors associated with the timing of complications. We explored the goodness of fit of the models and used the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC).

5. Hierarchical analysis of factors associated with childhood mortality in Nigeria: Approximation of survival regression by Poisson model in Bayesian MCMC procedures

The need for more pragmatic approaches to achieve sustainable development goal on childhood mortality reduction necessitated this study. Simultaneous study of the influence of where the children live and the censoring nature of children survival data is scarce. We identified the compositional and contextual factors associated with under-five (U5M) and infant (INM) mortality in Nigeria from 5 MCMC Bayesian hierarchical Poisson regression models as approximations of survival

regression. The 2018 DHS data of 33,924 under-five children were used. The risks of INM and U5M were highest among children with none/low maternal education, multiple births, short birth interval. Compared with the null model, 81% vs 10% and 59% vs 35% of the total variation in INM and U5M were explained by the state- and neighbourhood-level factors respectively. Risk of infants and under-five mortality in Nigeria is influenced significantly by compositional and contextual factors. The Poisson regression models fitted the survival data.

6. Hierarchical analysis of risk factors of diarrhoea among under-five children in low- and middle-income countries: disentangling context from composition

Several studies have documented the burden and risk factors associated with diarrhoea in low and middle-income countries (LMIC). To the best of our knowledge, the contextual and compositional factors associated with diarrhoea were poorly operationalized, explored and understood in these studies. We investigated multilevel risk factors associated with diarrhoea among under-five children in LMIC. We analysed diarrhoea-related information of 796,150 under-five children (Level 1) nested within 63,378 neighbourhoods (Level 2) from 57 LMIC (Level 3) from cross-sectional and nationally representative Demographic Health Survey. We used multivariable hierarchical Bayesian logistic regression models. The overall prevalence of diarrhoea was 14.2% ranging from 3.8% in Armenia to 31.4% in Yemen.

7. Decomposition analysis of the compositional and contextual factors associated with poor-non-poor inequality in diarrhoea among under-five children in low- and middle-income countries

To assess the magnitude of wealth inequalities in the development of diarrhoea among U5C in the LMIC, identified and quantified contextual and compositional factors’ contribution to the inequalities. We used cross-sectional data from 57 Demographic and Health Surveys conducted between 2010 and 2018 in LMIC. Descriptive statistics were used to understand the gap in having diarrhoea between the children from poor and non-poor households and across the selected covariates using Fairlie decomposition techniques with multivariable binary logistic regressions at p=0.05.

Publications

Book Chapters

  1. Fagbamigbe, A.F., (2019) Selected Topics in Medical Statistics (1st Edition) ISBN: 978-978-546-330-E, Edited by Adebowale A. S. & Akinyemi J.O.; Chapter 8: Principles and Methods of Data Simulation in Health Research in Page 107-19 Andkolads Publishers, Ile Ife, Nigeria
  2. Fagbamigbe, A. F., Adeoye, I. A., & Musa I. (2019) Selected Topics in Medical Statistics (1st Edition) ISBN: 978-978-546-330-E, Edited by Adebowale A. S. & Akinyemi J.O. Chapter 14: Survival Analysis: Concepts and Techniques, Page 268-91, Andkolads Publishers, Ile Ife, Nigeria

Publications in Learned Peer-reviewed Journals

2010

  1. Yusuf, O. B., Adebowale, A. S., Fagbamigbe, A.F., Bamgboye, E.A. and Oyediran, A.B.O.O. (2010) Profile of academic and senior non-teaching staff in a Nigerian university. Journal of Educational Administration and Policy Studies 2(7), pp. 92 - 98. https://academicjournals.org/journal/IJEAPS/article-abstract/9C38273984
  2. Fagbamigbe, A.F. and Adebowale, A. S. (2010), A model for measuring association between bivariate censored outcomes. Journal of Modern Mathematics and Statistics. 4(4): pp 127 -136, https://doi.org/10.10.3923/jmmstat.2010.127.136
  3. Adebowale, S.A., Fagbamigbe, A.F.. and Bamgboye, E.A. (2010); Rural-Urban Differential in Maternal Mortality in Nigeria, sub-Saharan Africa; Journal of Biomedical Sciences, Vol 2, pp 74-91, cenresinpub.org/mortality.pdf

2011

  1. Adebowale, A.S., Adepoju, O.T. and Fagbamigbe, A.F. (2010); Child Spacing and Parity Progression; Implication for Maternal Nutritional Status among Women in Ekiti Communities; Pakistan Journal of Nutrition 10 (5): 485-491; http://docsdrive.com/pdfs/ansinet/pjn/2011/485-491.pdf
  2. Adebowale, A.S., Adepoju, O.T., Okareh, O. T. and F. Fagbamigbe (2011), Social epidemiology of Adverse Nutritional Status Outcomes among Women in Nigeria: NDHS, 2008, Pakistan Journal of Nutrition 10 (9): 888-898, ISSN 1680-5194 http://docsdrive.com/pdfs/ansinet/pjn/2011/888-898.pdf
  3. Apau, G.S, Fagbamigbe, A.F, Adebowale, A.S. and Bamgboye, E.A. (2011); Modelling Morbidity Related Absenteeism among Workers in University of Ibadan Community, Nigeria: Poisson Regression, International Journal of the Physical Sciences Vol. 6(18), pp. 4458-4465, https://academicjournals.org/journal/IJPS/edition/9_September
  4. Fagbamigbe A.F., Akinyemi, J.O., Adedokun, B.O. and Bamgboye, E.A.; (2011) Gender variation in the self-reported likelihood of HIV infection in comparison with HIV test results in rural and urban Nigeria. AIDS Research and Therapy, 8:44 https://doi.org/10.1186/1742-6405-8-44
  5. Adebowale, A.S., Fagbamigbe, A.F. and Bamgboye, E.A. (2011) Contraceptive Use: Implication for Completed Fertility, Parity Progression and Maternal Nutritional Status in Nigeria, sub-Saharan Africa.” Afr Journal Reproductive Health Vol. 15 No. 4 pp 69-78; https://www.ajol.info/index.php/ajrh/article/view/74794
  6. Fagbamigbe, A.F. ., Adebowale, A.S., and Olaniyan, F.A, (2011) A comparative analysis of Condom use among unmarried youths in rural community in Nigeria; Public Health Research. 2011; 1(1): 8-16 https://doi.org/10.5923/j.phr.20110101.02

2012

  1. Adebowale, A.S., Fagbamigbe, A.F. and Bello, S. (2012); Refined age Distribution and Demographic parameters Estimation in Nigeria: An Indirect approach, Journal of Statistics and Management Sciences, Vol. 15(1), pp. 29-48; https://doi.org/10.1080/09720510.2012.10701611;
  2. Muruka, C, Fagbamigbe A.F., Muruka, A., Njuguna, J., Otieno, D.J., Onyando, J., Wanjiku, Z.S. and Onyango, Z. (2012), The Relationship between Bacteriological Quality of Dug-Wells & Pit Latrine Siting in an Unplanned Peri-Urban Settlement: A Case Study of Langas – Eldoret Municipality, Western Kenya. Public Health Research 2. No. 2, 32-36 https://doi.org/10.5923/j.phr.20120202.06
  3. Abiona, T.O., Adebowale, A.S. and Fagbamigbe, A.F. (2012), Time series analysis of admission in the Accident and Emergency unit of University College Hospital, Ibadan Nigeria; American Journal of Computational and Applied Mathematics, 2(1): 1-9 https://doi.org/10.5923/j.ajcam.20120201.01
  4. Adebowale, A.S., Yusuf, O.B, and Fagbamigbe, A.F. (2012): Survival Probability and Predictors for Woman Experience Childhood Death in Nigeria: “Analysis of North-South Differentials”. BMC Public Health 12. No. 1, 430-442. https://doi.org/10.1186/1471-2458-12-430
  5. Adebowale, A.S., Fagbamigbe, A.F. Okareh, O.T., Lawal, G.O. (2012): Survival Analysis of Timing of First Marriage among Women of Reproductive age in Nigeria: Regional Differences. African Journal of Reproductive Health 16. No. 4, 95-107. https://www.ajol.info/index.php/ajrh/article/view/83687

2013

  1. Adebowale, A.S., Titiloye, M.A, Fagbamigbe, A.F., Akinyemi, J.O. (2013): Statistical modeling of social risk factors for sexually transmitted diseases among female youths in Nigeria. Journal Infections in Developing Countries 7. No. 1, 17-27. http://doi.org/10.3855/jidc.2272
  2. Akanbiemu, A.F., Olumide A, Fagbamigbe A.F. and Adebowale, A.S. (2013), Effect of Perception and Free Maternal Health Services on Antenatal Care Facilities Utilization in Selected Rural and Semi-Urban Communities of Ondo State, Nigeria. British Journal of Medicine & Medical Research 3(3): 681-697, http://doi.org/10.9734/BJMMR/2013/2621
  3. Fagbamigbe, A.F., Akanbiemu, A.F., Adebowale, A.S., Ma-nuwa Olumide, A. and Korter, G.O. (2013), Practice, Knowledge and Perceptions of Antenatal Care Services among Pregnant Women and Nursing Mothers in Southwest Nigeria Intl Journal of Maternal and Child Health 2013, 1(1):7-16 ; doi.org/ 10.12966/ijmch.05.02.2013
  4. Oyedeji, K.S., Fagbamigbe, A.F., Ogboi, J.S., Bashorun, A.T., Issa, K.B., Amida, P, Ogundiran, A. and Ezire, O. (2013), Does Pre-Survey Training Impact Knowledge of Survey Administrators and Survey Outcomes in Developing Countries? Evaluation Findings of a Training of Trainers Workshop for National AIDS and Reproductive Health Survey-Plus in Nigeria International Journal of MCH and AIDS 2(1) 1, 129-138 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4948138/
  5. Fatiregun, A.A., Adebowale, A.S., Ayoka, R.O. and Fagbamigbe, A.F. (2013) Assessing full immunisation coverage using lot quality assurance sampling in urban and rural districts of southwest Nigeria. Trans R Soc Trop Med Hyg 107 (11): 731-74, https://www.ncbi.nlm.nih.gov/pubmed/24062523 ; https://doi.org/10.1093/trstmh/trt079
  6. Fatiregun, A.A., Adebowale, A.S. and Fagbamigbe, A.F. (2014): Epidemiology of measles in Southwest Nigeria: an analysis of measles case-based surveillance data from 2007 to 2012. Transactions of the Royal Society of Tropical Medicine and Hygiene 108(3), 133-140 ; https://doi.org/10.1093/trstmh/tru004

2014

  1. Fagbamigbe, A.F. and Adebowale, A.S. (2014) Current and Predicted Fertility using Poisson Regression Model: Evidence from 2008 Nigerian Demographic Health Survey Modelling and predicting fertility outcomes among Nigeria women. Afr J Reprod Health 2014; 18(1): 71-83 https://www.ajol.info/index.php/ajrh/article/view/102464
  2. Ogboi, J.S., Agu, P.U.,Fagbamigbe, A.F., Audu O., Akubue, A., Obianwu, I. (2014),  Misdiagnosis  of  malaria  using  wrong  buffer  substitutes  for  rapid  diagnostic  tests in  poor  resource  setting  in  Enugu,  Southeast  Nigeria Malaria World Journal, 5(6), 1-6 https://malariaworld.org/mwj/2014/research-misdiagnosis-malaria-using-wrong-buffer-substitutes-rapid-diagnostic-tests-poor
  3. Fagbamigbe, A.F. and Alabi, O. (2014) Differentials and Correlates of Infants Mortality in Nigeria: A Comparative Survival Analysis between North East and South West Nigeria. International Journal of Tropical Disease & Health, 4(8) pp: 869-886, https://doi.org/10.9734/IJTDH/2014/9597
  4. Adebowale, A.S., Fagbamigbe, A.F. and Bamgboye, E.A. Re-analysis of Nigerian 2006 Census Age Distribution using Growth Rate and Mortality Level. Southern African Journal of Demography 15(1), Pp 82-99. https://www.jstor.org/stable/soutafrijourdemo.15.1.81?seq=1#page_scan_tab_contents
  5. Olatoregun, O., Fagbamigbe, A.F., Akinyemi, O.J., Yusuf, O.B. and Bamgboye, E.A. ( 2014) A Comparative Analysis of Fertility Differentials in Ghana and Nigeria Afr J Reprod Health 2014; 18(3): 36-47. https://www.ajol.info/index.php/ajrh/article/view/109197
  6. Ogboi, S.J., Agu, P.U., Akpoigbe, J.K., Fagbamigbe, A.F., Audu, O., Obianwu, I.M. and Akabueze, J. (2014) Prevalence and Risk Factors of Malaria in HIV-Infected Pregnant Women on Anti-Retroviral Therapy in Enugu, South East Nigeria; Journal of AIDS and Clinical Research, 5:7 https://doi.org/10.4172/2155-6113.1000321
  7. Fatiregun, A.A., Fagbamigbe, A.F., Adebowale, A.S. (2014) Epidemiology of rubella disease in south-west Nigeria: Trends and projection from measles case-based surveillance data South Afr J Infect Dis 2014;29(2):60-64 http://www.tandfonline.com/doi/abs/10.1080/23120053.2014.11441571

2015

  1. Fagbamigbe, A.F., Bamgboye, E. A., Yusuf, O.B., Akinyemi, O. J., Issa, B. K., Ngige, E., Amida, P., Bashorun, A., Abatta, E. (2015) The Nigeria wealth distribution and health seeking behaviour: evidence from the 2012 national HIV/AIDS and reproductive health survey. Health Economics Review 5:5, 1-10 PMID: 25853003 [PubMedhttps://doi.org/ 10.1186/s13561-015-0043-9
  2. Fagbamigbe, A.F. and Idemudia, E.S. (2015) Barriers to antenatal care use in Nigeria: evidences from Non-users and implications for maternal health programming BMC Pregnancy and Childbirth, 15:95 1-10  https://doi.org/10.1186/s12884-015-0527-y PubMed: 25885481
  3. Fagbamigbe, A.F. and Idemudia, E.S. (2015) Assessment of quality of antenatal care services in Nigeria: evidence from a population-based survey Reproductive Health (2015) 12:88, 1-9; https://doi.org/10.1186/s12978-015-0081-0 PMCID:PMC4574449
  4. Fagbamigbe, A.F., Adebowale, A.S., and Morhason-Bello, I.O. (2015). Survival analysis of time to uptake of modern contraceptives among sexually active women of reproductive age in Nigeria BMJ Open 2015(5):1-10,e008371.https://doi.org/10.1136/bmjopen-2015-008371
  5. Fagbamigbe, A.F. and Idemudia, E.S. (2015). Does Gender and Age at Sexual Initiation affect Modern Contraceptive Use among Teenagers and Young adults in Nigeria? Gender and Behaviour 13(2) 6710-6719. https://www.questia.com/library/journal/1P3-3906144301/does-gender-and-age-at-sexual-initiation-affect-modern
  6. Ezire, O., Okekearu, I., Fagbamigbe, A.F., & Faweya, O. (2015). Analysis of Health Facility Based Barriers and Facilitators to use of Sexual and Reproductive Health Care Services among Most at Risk Populations (MARPS): Evidence from a Mystery Client Survey in Nigeria. Journal of Tropical Diseases and Public Health, 3(4), 1–5. https://doi.org/10.4172/2329891X.1000171

2016

  1. Morhason-Bello I.O., Fagbamigbe, A.F., Mumuni, T.O., Adesina, O.A., Abdus-Salam, A.R., Ifemeje, A., Ojengbede, O.A. (2016). Evaluation of correct knowledge of key danger signs in pregnancy among antenatal clinic attendees at a tertiary health facility in Nigeria. Niger J Clin Pract;19(2):227–32. https://doi.org/ 10.4103/1119-3077.164347
  2. Fagbamigbe, A.F. and Idemudia, E.S. (2016) Survival analysis and prognostic factors of timing of first childbirth among women in Nigeria. BMC Pregnancy Childbirth:16:102, pp1–12. Https://doi.org/ 10.1186/s12884-016-0895-y. https://doi.org/10.1186/s12884-016-0895-y
  3. Fagbamigbe, A.F. and Idemudia, E.S. (2016). Survival analysis and determinants of timing of first birth after marriage in Nigeria. Afr Popul Stud, 30(2), 2444–57. https://doi.org/10.11564/30-2,-856
  4. Yusuf, O. B., Akinyemi, J.O., Fagbamigbe, A.F. , Ajayi, I.O., Bamgboye, E.A., Ngige, E., Issa, K., Abatta, E., Ezire, O., Amida, P., Bashorun, A. (2016) Controlling malaria in pregnancy: how far from the Abuja targets? Malaria World Journal, 7(7), 3–10. https://malariaworld.org/sites/default/files/mwjournal/article/MWJ2016_7_7.pdf
  5. Fagbamigbe, A.F., Adebayo, S.B., and Idemudia, E.S. (2016). Marital status and HIV prevalence among women in Nigeria: Ingredients for evidence-based programming. International Journal of Infectious Diseases, 48(1), 57–63. https://doi.org/10.1016/j.ijid.2016.05.002
  6. Fagbamigbe, A.F. and Akinyemi, O.J. (2016). Modelling the survivorship of Nigeria children in their first 10 years of life. The Nigerian Health Journal, 16(1), 1–19. http://www.tnhjph.com/index.php/tnhj/article/view/194/pdf_1
  7. Fagbamigbe, A.F. and Idemudia, E.S. (2016). Wealth and antenatal care utilization in Nigeria: Policy implications. Health Care for Women International, 38(1): 17-37. https://doi.org/10.1080/07399332.2016.1225743
  8. Adebowale, A.S., Fagbamigbe, A.F. and Adebayo, A.M. (2016). Regional Differences in Adolescent Childbearing in Nigeria. Journal of Population and Social Studies, 24(2), 101–116. https://doi.org/10.14456/jpss.2016.8
  9. Eze, P.N., Mosokomani, V.S., Udeigwe, T.K., Oyedele, O.F., & Fagbamigbe, A.F. (2016). Data in Brief Geostatistical analysis of trace elements PXRF dataset of near-surface semi-arid soils from Central Botswana. Data in Brief, Elsevier 9, 764–770. https://doi.org/10.1016/j.dib.2016.10.010

2017

  1. Fagbamigbe, A.F., Adebowale, A.S. and Bamgboye, E.A. (2017) A Survival Analysis Model for Measuring Association between Bivariate Censored Outcomes : Validation Using Mathematical Simulation. Am J Math Stat, 7(1):7–14. https://doi.org/10.5923/j.ajms.20170701.02
  2. Shodimu, M.A., Yusuf, O.B., Akinyemi, J.O., Fagbamigbe, A.F. , Bamgboye, E.A., Ngige, E., Issa, K., Abatta, E., Ezire, O., Amida, P., Bashorun, A. (2017). Determinants of perceived stigmatizing and discriminating attitudes towards people living with HIV / AIDS among women of reproductive age in Nigeria. Journal of AIDS and HIV Research, 9(6), 139–151. https://doi.org/10.5897/JAHR2016.0391
  3. Fagbamigbe, A.F. and Ojebuyi, B.R. (2017) Influence of Spousal Communication about Family Planning and HIV/AIDS-related Issues on Modern Contraceptive Use in Nigeria. Journal of Health Management, 19(2) 1-14; https://doi.org/10.1177/0972063417699693
  4. Fagbamigbe, A.F. and Idemudia, E.S, (2017) Diversities in timing of sexual debut among Nigerian youths aged 15-24 years: parametric and non-parametric survival analysis approach. Afri Health Sci. 2017; 17(1): 39-51. https://dx.doi.org/10.4314/ahs.v17i1.7
  5. Obiyan, M.O., Fagbamigbe, A.F., Adetutu, O.M., and Oyinlola, F.F. (2017), Fertility, labour force participation and poverty among married women in Nigeria African Popul Stud, 31(1):3408–3420. https://dx.doi.org/10.11564/31-1-999
  6. Okwor, V.C., Fagbamigbe, A.F. and Fawole, O.I. Survivorship of patients with head and neck cancer receiving care in a tertiary health facility in Nigeria. Cancer Manag Res. 2017;9:331-338. https://doi.org/10.2147/CMAR.S133108.
  7. Fagbamigbe, A.F. and Makanjuola, V.A. Modeling association between times to recurrence of the different polarities in bipolar disorder among service seekers in urban Nigeria: a survival analysis approach. Neuropsychiatr Dis Treat. 2017;13:1967-1974. https://doi.org/10.2147/NDT.S133167.
  8. Alo, O.D., Akinyemi, J.O., Akpa, M.O., Yusuf, O.B., Fagbamigbe, A.F. , Bamgboye, E.A., Adebayo, S.B., Issa, K., Agbi, P. and Ezire, O. (2017). Level and determinants of pharmacovigilance programme awareness in Nigeria : A multilevel analysis. Afr J of Pharm and Pharm, 11(29), 342–348. https://doi.org/10.5897/AJPP2017.4571
  9. Morakinyo, O.M. and Fagbamigbe, A.F. (2017). Neonatal, infant and under-five mortalities in Nigeria : An examination of trends and drivers (2003-2013 ). PLoS ONE, 12(8), e0182990. https://doi.org/10.1371/journal.pone.0182990
  10. Fagbamigbe, A.F., Morakinyo, O.M., and Abatta, E. (2017). Analysis of Regional Variations in Influence of Household and Environmental Characteristics on Prevalence of Diarrhoea among Under-Five Children in Nigeria. . Ann Med Health Sci Res., 7(3), 119–130. http://www.amhsr.org/archive/amhsr-volume-7-issue-3-may-2017.html
  11. Akinyemi, J. O., Yusuf, B. O., Fagbamigbe, A. F., Bamgboye, E. A., Issa, B. K., Ngige, E., … Bashorun, A. (2017). Derivation and appraisal of maternal mortality estimates in Nigeria from the 2012 National HIV/AIDS and Reproductive Health Survey. Afr Journal of Medicine and Medical Sciences, 46(1), 159–166.
  12. Fagbamigbe, A. F., Lawal, A. M., & Idemudia, E. S. (2017). Modelling self-assessed vulnerability to HIV and its associated factors in a HIV-burdened SAHARA-J: Journal of Social Aspects of HIV/AIDS, 14(1), 140–152. https://doi.org/10.1080/17290376.2017.1387598
  13. Fagbamigbe, A. F., Mashabe, B., Lepetu, L., & Abel, C. (2017). Are the timings and risk factors changing ? Survival analysis of timing of first antenatal care visit among pregnant women in Nigeria (2003 – 2013). International Journal of Womens Health, 9(1), 807–819. https://doi.org/10.2147/IJWH.S138329
  14. Fagbamigbe, A. F., Hurricane-Ike, E., Yusuf, O.B, & Idemudia, E.S. (2017). Trends and drivers of skilled birth attendant use in Nigeria (1990–2013): policy implications for child and maternal health. International Journal of Women’s Health, Volume 9(1), 843–853. https://doi.org/10.2147/IJWH.S137848

2018

  1. Akinyemi, A. I., Fagbamigbe, A. F., Omoluabi, E., Agunbiade, O. M., & Adebayo, S. O. (2018). Diarrhoea Management Practices and Child Health Outcomes in Nigeria: Sub-National Analysis. Advances in Integrative Medicine, 5; 15-22. https://doi.org/10.1016/j.aimed.2017.10.002
  2. Fagbamigbe, A. F., Afolabi, R. F., & Idemudia, E. S. (2018). Demand and Unmet Needs of Contraception among Sexually Active In-Union Women in Nigeria: Distribution, Associated Characteristics, Barriers, and Program Implications. SAGE Open, 8(1), 215824401775402. https://doi.org/10.1177/2158244017754023
  3. Fagbamigbe, A. F. & Bakre, B. B. (2018). Evaluating Likelihood Estimation Methods in Multilevel Analysis of Clustered Survey Data. African J Appl Stat.;5(1):351–76. http://dx.doi.org/10.16929/ajas/351.220
  4. Gil-Alana, L.A., Yaya, O.S. & Fagbamigbe, A. F. (2018) Time series analysis of quarterly rainfall and temperature (1900–2012) in sub-Saharan African countries. Theor Appl Climatol. Springer Vienna; 2018;1–16. https://doi.org/10.1007/s00704-018-2583-5
  5. Morakinyo O.M., Balogun, F.M. & Fagbamigbe, A. F. (2018) Housing type and risk of malaria among under ‑ five children in Nigeria : evidence from the malaria indicator survey. Malar J. BioMed Central; 17(311):1–11. https://doi.org/10.1186/s12936-018-2463-6;
  6. Fagbamigbe, A. F., Awoyelu, I. E., Akinwale, O. L., Akinwande, T. Y., Enitilo, B. K., & Bankole, O. (2018). Factors contributing to the duration of postpartum abstinence among Nigerian women : semi-parametric survival analysis. Heliyon, 4(12), e01032. https://doi.org/10.1016/j.heliyon.2018.e01032
  7. Fagbamigbe, A. F., Obiyan, M. O., & Fawole, O. I. (2018). Parametric survival analysis of menarche onset timing among Nigerian girls. Heliyon, 4(12), e01105. https://doi.org/10.1016/j.heliyon.2018.e01105
  8. Gbadebo, B. M., Fagbamigbe, A.F., & Adebowale, S. A. (2018) Environmental Factors as Predictors of Childhood Mortality Experience in Nigeria. Afr J Env Heal Sc.; 5(11):23–34.

2019

  1. Fagbamigbe, A. F., Abel, C., Mashabe, B. & Adebowale, A. S. (2019) Survival analysis and prognostic factors of the timing of first antenatal care visit in Nigeria, Advances in Integrative Medicine 6(1), 1-10. https://doi.org/10.1016/j.aimed.2018.12.002
  2. Fagbamigbe, A. F. (2019). On the discriminatory and predictive accuracy of the RDT against the microscopy in the diagnosis of malaria among under-five children in Nigeria. Malaria Journal, 18(46), 1-12. https://doi.org/10.1186/s12936-019-2678-1
  3. Ojebuyi, B. R., Fagbamigbe, A. F., & Akinola, O. O. (2019). Prevalence of and Factors Influencing Parent–Child Communication about HIV/AIDS, and Sexual and Reproductive Health Issues in Nigeria. SAGE Open, 9(1), 1-12. https://doi.org/10.1177/2158244019833880
  4. Adebayo, S., Gayawan, E., Fagbamigbe, A. F., & Bello, F. (2019). Bayesian geo-additive spatial modelling of HIV prevalence using data from population-based surveys. HIV & AIDS Review. 18(1), 1-14, https://doi.org/10.5114/hivar.2019.83852
  5. Adeoye, I. A., & Fagbamigbe, A. F. (2019). What is the Link between Malaria Prevention in Pregnancy and Neonatal Survival in Nigeria ? Afr J Rep Health., 23(1), 139–149. https://doi.org/10.29063/ajrh2019/v23i1.14
  6. Fagbamigbe, A. F., Afolabi, R. F., Alade, K. Y., Adebowale, A. S., & Yusuf, B. O. (2019). Unobserved Heterogeneity in the Determinants of Under-five Mortality in Nigeria: Frailty Modeling in Survival Analysis. African Journal of Applied Statistics, 6(1), 565–583. https://doi.org/10.16929/ajas/565.231
  7. Fagbamigbe, A. F., Basele, G. K., Makubate, B., & Oluyede, B. O. (2019). Application of the Exponentiated Log-Logistic Weibull Distribution to Censored Data. Nig. Soc. Phys. Sci, 1(1), 12–19. https://jnsps.org/jnsps_articles/2019/6faf3561354149eaa9d1f53cdc351b2f.php
  8. Fagbamigbe, A. F., Abi, B., Akinwumi, T., Ogunsuji, O, Odigwe, A. and Olowolafe, T. (2019). Survival Analysis and Prognostic Factors Associated with the Timing of First Forced Sexual Act among Women in Kenya, Zimbabwe and Cote d‘Ivoire.” Scientific African 4:e00092. https://doi.org/10.1016/j.sciaf.2019.e000922
  9. Fagbamigbe, A. F., Afolabi, R. F. and Yusuf, O. B. (2019). “Trend Analysis of Teenage Pregnancy in Nigeria (1961-2013): How Effective Is the Contraceptive Use Campaign?” International Journal of Public Health Science (IJPHS) 8(2):21–31. https://doi.org/10.11591/ijphs.v8i2.16429
  10. Fagbamigbe, A. F., Adebowale, A. S., & Ajayi, I. (2019). An assessment of the nutritional status of ART receiving HIV-orphaned and vulnerable children in South-West Nigeria. Heliyon, 5(May), e02925. https://doi.org/10.1016/j.heliyon.2019.e02925
  11. Adebowale, A. S., Fagbamigbe, A. F., Morakinyo, O., Obembe, T., Afolabi, R. F., & Palamuleni, M. E. (2019). Parental Educational Homogamy and Under-Five Mortality in Sub-Saharan Africa: Clarifying the Association’s Intricacy. Scientific African, e00255. https://doi.org/10.1016/j.sciaf.2019.e00255

2020

  1. Morhason-Bello, I. O., & Fagbamigbe, A. F. (2020). Association between Knowledge of Sexually Transmitted Infections and Sources of the Previous Point of Care among Nigerians : Findings from Three National HIV and AIDS Reproductive Health Surveys. Intl J. of Reproductive Medicine, 2020, 1–11. https://doi.org/10.1155/2020/6481479
  2. Fagbamigbe, A. F., Akintayo, A. O., Oshodi, O., Makinde, F. T., Babalola, M., Damilola, E. A., Enabor, O. C. & Dairo, M. D. (2020). Survival Analysis and Prognostic Factors of Time to First Domestic Violence after Marriage among Married Women in Africa. Public Health, 181(2020), 1–13. https://doi.org/https://doi.org/10.1101/524637
  3. Fagbamigbe, A. F., Kandala, N. B., & Uthman, O. (2020). Severe acute malnutrition among under-five children in low- and middle-income countries: A hierarchical analysis of associated risk factors. Nutrition, 110768. https://doi.org/10.1016/j.nut.2020.110768
  4. Fagbamigbe, A. F., Kandala, N. B., & Uthman, O. A. (2020). Decomposing the educational inequalities in the factors associated with severe acute malnutrition among under-five children in low- and middle-income countries. BMC Public Health, 20(555), 1–14. https://doi.org/10.1186/s12889-020-08635-3
  5. Morhason-Bello, I. O., Fagbamigbe, A. F., Yusuf, O. K., and Ojengbede, O. A. (2020). “Economic Status, a Salient Motivator for Medicalisation of FGM in Sub-Saharan Africa: Myth or Reality from 13 National Demographic Health Surveys.” SSM - Population Health 11: 100602. https://doi.org/10.1016/j.ssmph.2020.100602.
  6. Fagbamigbe, A. F., Kandala, N. B., & Uthman, O. A. (2020). Demystifying the factors associated with rural – urban gaps in severe acute malnutrition among under ‑ five children in low ‑ and middle ‑ income countries : a decomposition analysis. Scientific Reports. Nature Publishing Group UK; 2020;10:1–15. https://doi.org/10.1038/s41598-020-67570-w.
  7. Adebowale, A. S., Fagbamigbe, A. F., Akinyemi, J. O., Olowolafe, T., Onwusaka, O., Adewole, D. Saidu, S, Palamuleni, M. (2020) Dynamics of Poverty-Related Dissimilarities in Fertility in Nigeria: 2003-2018. African, Elsevier; 2020;e00468. https://doi.org/10.1016/j.sciaf.2020.e00468
  8. Oyedele, O. K., Fagbamigbe, A. F. & Ayeni, O. (2020) Modelling time-to-discontinuation of exclusive breastfeeding: analysis of infants and under-2 survival in Nigeria. Afr Popul Stud 34(1), 1–13.
  9. Fagbamigbe, A. F., Ojo, A. E., Onyeike, N. O., Okafor, I. P., Atilola, S. O., Olabuyi, R. A, Afolabi, R. F., (2020). Survival analysis of time interval between first and second childbirth among women in Nigeria. J. Med. Med. Sc 49,.
  10. Kodaolu, M. Y., Fagbamigbe, A. F., & Ajayi, I. O. (2020). Stocking pattern for anti ‑ malarial medications among proprietary patent medicine vendors in Akinyele Local Government Area , Ibadan , Nigeria. Malaria Journal, 19(279), 1–15. https://doi.org/10.1186/s12936-020-03350-1
  11. Oluyede, B. O., Mashabe, B., Fagbamigbe, A. F., Makubate, B., & Wanduku, D. (2020). Heliyon The exponentiated generalized power series Family of distributions : theory , properties and applications. Heliyon, 6(August), e04653. https://doi.org/10.1016/j.heliyon.2020.e04653

Preprint

  1. Badu, K., Thorn, J. P.R., Goonoo, N., Dukhi, N., Fagbamigbe, A. F.,, Kulohoma, B. W., Oyebola, K., et al. “Africa’s Response to the COVID-19 Pandemic: A Review of the Nature of the Virus, Impacts and Implications for Preparedness.” AAS Open Research 3:19, 1-21. https://doi.org/10.12688/aasopenres.13060.1.
  2. Aloui-Zarrouk, Z., El Youssfi, L., Badu, K., Fagbamigbe, A. F., Matoke-Muhia, D., Ngugi, C., Dukhi, N., Mwaura, G. (2020). The wearing of face masks in African countries under the COVID-19 crisis: luxury or necessity? [version 1; peer review: awaiting peer reviewhttps://doi.org/10.12688/aasopenres.13079.1">https://doi.org/10.12688/aasopenres.13079.1

Contact Information

 Phone: 08061348165

 Address: Department of Epidemiology and Medical Statistics, Faculty of Public Health, College of Medicine, University of Ibadan, Ibadan, Nigeria

 EmailThis email address is being protected from spambots. You need JavaScript enabled to view it.

 FacebookProfile Link

 LinkedInProfile Link

 TwitterProfile Link

 InstagramProfile Link

 YouTubeProfile Link

PinterestProfile Link


Social Links

Get In Touch