MULTILEVEL COUNT REGRESSION ANALYSIS OF FACTORS AFFECTINGANTENATAL CARE VISITS IN NIGERIA

Authors

  • Musa Ganaka Kubi
    Abubakar Tafawa Balewa University, Bauchi, Nigeria
  • Tobias Chukwudi Ossai
    Nasarawa State University, Keffi , Nigeria
  • E. O Ben
    Abubakar Tafawa Balewa University, Bauchi, Nigeria
  • Rilwan Bala Muhammad
    Federal U niversity of Health Science Azare, Nigeria
  • Y. B. Usman
    Federal Polytechnic Idah, Nigeria

Keywords:

Antenatal care visit , Zero-inflated negative binomial , Multilevel count data modeling

Abstract

Adequate antenatal care (ANC) is essential for maternal and neonatal health, yet utilization in Nigeria remains suboptimal. This study aimed to determine the factors influencing number of ANC visits using multilevel count data regression model. Data from 12,719 women in the 2024 Nigerian Demographic and Health Survey data were analyzed. A multilevel Zero Inflated Negative Binomial (ZINB) model was selected over competing count models based on its superior ability to handle the data's over dispersion, substantial zero inflation (28 %) and clustered structure. Both count (frequency) and zero-inflation (non-visit) components were estimated.In the count component, higher maternal age (25–39: AIRR =1.053; 40-49: AIRR =1.073), maternal secondary (AIRR =1.069) and higher education (AIRR =1.113), husband’s secondary (AIRR =1.077) and higher education (AIRR =1.113), wealthier households (middle: AIRR =1.054; rich: AIRR =1.116), media exposure (AIRR =1.054), employment (AIRR = 1.035), insurance (AIRR =1.080), shorter distance to health facilities (AIRR =1.040), and prior pregnancy termination (AIRR =1.036) were associated with increased ANC visits. In the zero-inflation component, maternal and husband education (AORs =0.530–0.205), wealth (AOR middle =0.731; rich =0.355), employment (AOR =0.641) and shorter facility distance (AOR =0.763) reduced the likelihood of non-attendance, whereas higher parity (2-4: AOR =1.408; ≥5: AOR =1.614) and husband-dominated decision-making (AOR =1.297) increased it. ANC utilization is shaped by demographic, socioeconomic, educational, and access-related factors, with pronounced regional and parity disparities. Targeted interventions are needed to improve equitable ANC coverage.

Author Biographies

Musa Ganaka Kubi

Department of Public Health

Tobias Chukwudi Ossai

Department of Statistics and Data Analytics

E. O Ben

Department of Statistics

Rilwan Bala Muhammad

Department of Epidemiology and Biostatistics

Y. B. Usman

Department of Mathematics and Statistics

Dimensions

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Published

03-07-2026

How to Cite

MULTILEVEL COUNT REGRESSION ANALYSIS OF FACTORS AFFECTINGANTENATAL CARE VISITS IN NIGERIA. (2026). FULafia Journal of Science and Technology , 10(2), 174-183. https://doi.org/10.62050/fjst2026.v10n2.731

Issue

Vol. 10 No. 2 (2026): Fulafia Journal of Science and Technology (FJST)

Section

Physical Sciences
Copyright & Licensing

How to Cite

MULTILEVEL COUNT REGRESSION ANALYSIS OF FACTORS AFFECTINGANTENATAL CARE VISITS IN NIGERIA. (2026). FULafia Journal of Science and Technology , 10(2), 174-183. https://doi.org/10.62050/fjst2026.v10n2.731

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