Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination
BackgroundImmunization is an efficient and cost-effective public health program. It averts millions of child deaths per year. It is taken as one of the main interventions that can be used to achieve the third Sustainable Development Goal, which is to end preventable deaths of newborns and under-five...
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1420567/full |
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| author | Ashagrie Sharew Iyassu Ashagrie Sharew Iyassu Haile Mekonnen Fenta Haile Mekonnen Fenta Zelalem G. Dessie Zelalem G. Dessie Temesgen T. Zewotir |
| author_facet | Ashagrie Sharew Iyassu Ashagrie Sharew Iyassu Haile Mekonnen Fenta Haile Mekonnen Fenta Zelalem G. Dessie Zelalem G. Dessie Temesgen T. Zewotir |
| author_sort | Ashagrie Sharew Iyassu |
| collection | DOAJ |
| description | BackgroundImmunization is an efficient and cost-effective public health program. It averts millions of child deaths per year. It is taken as one of the main interventions that can be used to achieve the third Sustainable Development Goal, which is to end preventable deaths of newborns and under-five children by 2030. The study was done with the aim of identifying appropriate confounder identification methods and examining confounders for the causal effect of a number of antenatal care visits on age-specific childhood vaccination.MethodsA family of generalized linear models with log link functions was used to model the covariate and the number of antenatal care association. A cumulative link model was used to model the number of antenatal care and covariate-age-specific childhood vaccination associations. AIC and BIC values were used to compare models. Significance testing methods and change in estimate methods were used to identify covariates that confound the effect of a number of antenatal care on age-specific childhood vaccinations.ResultA zero-inflated Poisson model was selected to model covariate–exposure association, and a proportional odds model with a log link was selected to model the outcome variable. Among significance testing methods, the common cause approach yielded smaller values of BIC and a smaller number of covariates. However, the likelihood ratio test showed no difference between the common cause and other approaches. A change in the estimate method is more conservative at a 10% cut point, which selects a smaller number of confounders. However, the significance testing method was better performed than the change in estimate method.ConclusionThe significance testing method with a p-value of less than or equal to 0.2 performed better than a change in estimate method at a 10% cut point of effect change for confounder identification. Mothers’ age at first birth, region, place of residence, education status of mothers, presence of radio and television in the household, religion, household size, wealth status, total children ever born, and birth order number are identified as confounders. |
| format | Article |
| id | doaj-art-b326421a43a54d3a87cd4cd028fb9e34 |
| institution | DOAJ |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Public Health |
| spelling | doaj-art-b326421a43a54d3a87cd4cd028fb9e342025-08-20T03:05:46ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-05-011310.3389/fpubh.2025.14205671420567Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccinationAshagrie Sharew Iyassu0Ashagrie Sharew Iyassu1Haile Mekonnen Fenta2Haile Mekonnen Fenta3Zelalem G. Dessie4Zelalem G. Dessie5Temesgen T. Zewotir6College of Science, Bahir Dar University, Bahir Dar, EthiopiaDepartment of Statistics, Debre Markos University, Debre Markos, EthiopiaCollege of Science, Bahir Dar University, Bahir Dar, EthiopiaPopulation Health, Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, FinlandCollege of Science, Bahir Dar University, Bahir Dar, EthiopiaSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South AfricaSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South AfricaBackgroundImmunization is an efficient and cost-effective public health program. It averts millions of child deaths per year. It is taken as one of the main interventions that can be used to achieve the third Sustainable Development Goal, which is to end preventable deaths of newborns and under-five children by 2030. The study was done with the aim of identifying appropriate confounder identification methods and examining confounders for the causal effect of a number of antenatal care visits on age-specific childhood vaccination.MethodsA family of generalized linear models with log link functions was used to model the covariate and the number of antenatal care association. A cumulative link model was used to model the number of antenatal care and covariate-age-specific childhood vaccination associations. AIC and BIC values were used to compare models. Significance testing methods and change in estimate methods were used to identify covariates that confound the effect of a number of antenatal care on age-specific childhood vaccinations.ResultA zero-inflated Poisson model was selected to model covariate–exposure association, and a proportional odds model with a log link was selected to model the outcome variable. Among significance testing methods, the common cause approach yielded smaller values of BIC and a smaller number of covariates. However, the likelihood ratio test showed no difference between the common cause and other approaches. A change in the estimate method is more conservative at a 10% cut point, which selects a smaller number of confounders. However, the significance testing method was better performed than the change in estimate method.ConclusionThe significance testing method with a p-value of less than or equal to 0.2 performed better than a change in estimate method at a 10% cut point of effect change for confounder identification. Mothers’ age at first birth, region, place of residence, education status of mothers, presence of radio and television in the household, religion, household size, wealth status, total children ever born, and birth order number are identified as confounders.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1420567/fullantenatal carechildhood immunizationconfounderssignificance testingchange in estimate |
| spellingShingle | Ashagrie Sharew Iyassu Ashagrie Sharew Iyassu Haile Mekonnen Fenta Haile Mekonnen Fenta Zelalem G. Dessie Zelalem G. Dessie Temesgen T. Zewotir Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination Frontiers in Public Health antenatal care childhood immunization confounders significance testing change in estimate |
| title | Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination |
| title_full | Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination |
| title_fullStr | Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination |
| title_full_unstemmed | Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination |
| title_short | Identifying confounders and estimating the causal effect of antenatal care on age-specific childhood vaccination |
| title_sort | identifying confounders and estimating the causal effect of antenatal care on age specific childhood vaccination |
| topic | antenatal care childhood immunization confounders significance testing change in estimate |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1420567/full |
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