Ethnicity as a cultural factor influencing complete vaccination among children aged 12-23 months in Nigeria

Human Vaccines and Immunotherapeutics, Volume 17, No. 7, Year 2021

Interpretation

Achieving complete vaccination for children has been challenging in Nigeria. Yet, addressing Nigeria’s completeness of vaccination requires ethno-cultural diversity consideration rather than nationally population based. This study explored patterns and determinants of complete vaccination among children of Hausa/Fulani, Igbo and Yoruba, the predominant ethnicities in Nigeria. The study used a cross-sectional data involving 3980 children aged 12–23 months extracted from the 2018 Nigeria Demographic and Health Survey dataset. In this study, complete vaccination is defined as a child who received all recommended vaccinations. A generalized linear mixed model applied to clustered data was used for data analysis (α = 0.05). The prevalence of complete vaccinations was 56.3%, 40.8% and 18.2% among Igbo, Yoruba and Hausa/Fulani children, respectively. The likelihood of complete vaccination was higher among children who were of Igbo (aOR = 1.38; CI: 1.20–1.59) compared with Hausa/Fulani. Predictors of complete vaccination were maternal age-at-childbirth, education, prenatal-care attendant and place of delivery among Hausa/Fulani; place of residence and perceived access to self-medical help, among Igbo; while prenatal-care attendance, among Yoruba. The odds of complete vaccination were higher among Hausa/Fulani (aOR = 1.65; CI: 1.04–2.61), Igbo (aOR = 2.55; CI: 1.20–5.44) and Yoruba (aOR = 4.22; CI: 1.27–13.96) children from higher wealth-quintile households compared to those from poor households. There was evidence of variability in the likelihood of complete vaccination in all the ethnic groups. The Hausa/Fulani tribe had the lowest complete vaccination coverage for children aged 12–23 months. Context-specific program intervention to improve complete vaccination is needed to ensure that the SDG target for vaccination is met. The present analysis was conducted using the 2018 Nigeria Demographic Health Survey (NDHS) data. The NDHS is a population-based cross-sectional design aimed at providing maternal and child health indicators to assist policymakers and programme managers in designing and evaluating programs and strategies for improving the health of the country’s population.9 Nigeria is the most populated country in Africa with the population figure of about 200 million, of whom 17% were under-five children in 2018. Administratively, Nigeria has 36 states including a Federal Capital Territory zoned into six geopolitical groups. Of over 250 ethnic compositions, Hausa/Fulani, Igbo and Yoruba are predominant. The six regions in Nigeria are mainly defined by these three ethnic groups. While the Yoruba and Igbo women predominantly have formal education, only a few of such women are found in Hausa/Fulani ethnic groups. The Hausa/Fulani women mostly belong to Islamic religion. Contrariwise, the Igbo and Yoruba women are mainly Christians. Two-stage cluster sampling technique was employed for the survey using the sampling frame containing the enumeration areas (EAs) of the 2006 Nigeria Population and Housing Census (NPHC). At the first stage, 1400 EAs (referred to as clusters) were selected as the primary sampling units; the second stage involved the selection of 40,427 households as the secondary units for the survey. The detailed description of the sampling design and strategies has been reported in the 2018 NDHS report.9 In the present study, data of children aged 12–23 months, who had valid information on the basic recommended vaccines, belonged to eligible women of childbearing age who were residents of the selected households within the clusters, and either of the Hausa/Fulani or Igbo or Yoruba tribes. Children with missing information or ‘don’t know’ records were excluded from the analysis. A total of 3980 met all these criteria. In this study, the term ‘cluster’ was used in DHS to describe the ‘neighborhood’ where children live. The outcome of interest was the complete vaccination status of children aged 12–23 months as at a year old. Going by WHO recommendations, a child who received one dose of Bacille Calmette–Guerin (BCG), one dose of measles, three doses of polio, and three doses of diphtheria, tetanus and pertussis (DPT) vaccines by the age of 12 months has a complete vaccination.9,16 Therefore, children who have been immunized with all these basic vaccines are deemed to have complete vaccinations – this is coded “1”; and “0” if otherwise. The key independent variable was ethnicity. The analysis was restricted to the three most prominent ethnic groups: Hausa/Fulani, Igbo and Yoruba in Nigeria.24 Other independent variables were included to define child/maternal, household and health characteristics according to empirical literature.25,26 These include child sex, birth order, maternal age-at-birth, employment, education, marital status, region, place of residence, religion, household wealth status, media exposure, health insurance coverage, health decision-involvement, perceived access to self-medical help, place of delivery and prenatal-care assistance. A media exposure variable was derived and classified as exposed if a household had access to at least one of radio, television or newspaper; otherwise, not exposed. The wealth index variable was derived from the generated weighted factor score using principal component analysis as contained in the recode file. These scores were categorized into low, middle, and high wealth quintiles. Health decision-involvement’s variable is premised on women’s ability to decide on personal health care, household purchases and visitation to relatives. These related variables are coded as 2 (if she decides alone), 1 (if joint decision) and 0 (if she took no part), respectively. The aggregated scores were classified as 0 (no involvement), 1–3 (low) and 4–6 (high). Similarly, perceived access to self-medical help’s variable is derived subject to a woman opinion on the following dichotomized variables: obtaining permission to visit a health facility, getting the required treatment fee, distance to a health facility, or being accompanied to the health facility – 0 score implied no problem; otherwise, the problem. Frequencies, percentages and charts were used as descriptive measures at the univariate stage. The chi-square test was used to assess the association between the outcome variable and the individual independent variables at the bivariate stage. Asides, both simple and multiple GLMMs with a binomial random distribution and logit link function are used to explore the predictors of children’s complete vaccination. As clustering of children’s complete vaccination may ensue if characteristics within clusters are alike, failure to account for such clustered or nested nature of the data often lead to biased parameter estimates of the fixed effects. The method also supports the dependence structure of data for units within these clusters and estimates the magnitude of such correlation after taking into consideration the inclusion of explanatory variables.27 An extension of generalized linear models is the GLMM that accounts for all contextual information. The model appropriately estimates fixed- and random-effects for nested data. In brief, the model is as follows: Let Yij be the complete vaccination status of ith child in the jth cluster defined as For EY=1/Xij,φj,εj=π, the GLMM can be described as follows: where π=Pr(Y=1/Xij,φj,εj) =eβpxijp+θrφrj+εj1+eβpxijp+θrφrj+εj p-variable is the level-1 denoted by xijp (which varies within and between clusters); r-variable is the level-2 denoted by φrj (varies only between clusters); and the random intercept is εj At the bivariate level, GLMM was used to identify the respective explanatory variable’s influence on child complete vaccination. Also, it was used to identify predictors of complete vaccinations among children aged 12–23 months using a 4-stage approach at the multivariate level for the pooled data. The adopted 4-stage random intercept was premised on the classification of explanatory variables such that models 1, 2 and 3, respectively, included variables to define child/maternal, household and health characteristics, irrespective of their significance status at the bivariate level. Thereafter, significant factors from models 1–3 were included in the final model 4. Also, correlates of children’s complete vaccinations peculiar to each of the ethnic groups were identified using the significant factors (p < .05) in any of the simple models for each of the ethnicity. The odds ratios (OR) including their CIs and the intra-neighborhood correlation coefficient (ICC) which quantifies the proportion of variance explained due to hierarchical data clustering effect are reported. In each of the models, ICC was computed using the estimated random intercept variance and ICC ≥ 2% is deemed to have a significant neighborhood effect which calls for a multilevel approach.28 Akaike Information Criteria (AIC) values are also reported for model comparison; the model with the least value was adjudged as being more adequate.29 All analyses were carried out at 5% level of significance, using STATA 14 SE (StataCorp LP, College Station, USA). Ethical approval for the parent study was obtained from the Nigeria National Ethics Committee. Informed consent and all other international ethical standards of confidentiality and anonymity were certified. The details of the ethical approval have been reported earlier.9 The Demographic and Health Surveys Program approved the utilization of the dataset for the present analysis.

AI Digest

Study Justification:

The study aimed to investigate the influence of ethnicity as a cultural factor on complete vaccination among children aged 12-23 months in Nigeria. This research was important because achieving complete vaccination in Nigeria has been challenging, and it was hypothesized that considering ethno-cultural diversity rather than a nationally population-based approach could lead to more effective vaccination strategies.

Highlights:

– The study used data from the 2018 Nigeria Demographic and Health Survey, involving 3980 children aged 12-23 months.
– Complete vaccination was defined as a child who received all recommended vaccinations.
– The prevalence of complete vaccinations was 56.3% among Igbo children, 40.8% among Yoruba children, and 18.2% among Hausa/Fulani children.
– Factors influencing complete vaccination varied among the ethnic groups, including maternal age-at-childbirth, education, prenatal-care attendant, place of delivery, place of residence, and perceived access to self-medical help.
– Children from higher wealth-quintile households had higher odds of complete vaccination compared to those from poor households.
– The study highlighted the need for context-specific program interventions to improve complete vaccination and meet the Sustainable Development Goal target for vaccination.

Recommendations:

– Develop targeted vaccination strategies that consider the specific cultural and ethnic characteristics of different regions in Nigeria.
– Improve access to prenatal care and healthcare facilities, particularly in areas with lower vaccination rates.
– Increase awareness and education about the importance of complete vaccination among parents and caregivers.
– Implement measures to address socioeconomic disparities that affect vaccination rates, such as providing financial support for families in lower wealth quintiles.

Key Role Players:

– Ministry of Health: Responsible for developing and implementing vaccination policies and programs.
– Healthcare Providers: Involved in delivering vaccinations and providing education to parents and caregivers.
– Community Leaders: Play a crucial role in promoting vaccination and addressing cultural beliefs and misconceptions.
– Non-Governmental Organizations (NGOs): Can support vaccination campaigns, provide resources, and conduct community outreach programs.
– Researchers and Academics: Continuously study and evaluate vaccination strategies to inform policy and program development.

Cost Items for Planning Recommendations:

– Vaccine Procurement: Budget for the purchase and distribution of vaccines.
– Healthcare Infrastructure: Allocate funds for improving healthcare facilities and ensuring access to prenatal care.
– Education and Awareness Campaigns: Invest in public health campaigns to educate parents and caregivers about the importance of complete vaccination.
– Training and Capacity Building: Provide training for healthcare providers to ensure proper administration and monitoring of vaccinations.
– Research and Evaluation: Allocate resources for ongoing research and evaluation of vaccination programs to identify areas for improvement.
Please note that the cost items provided are general categories and not actual cost estimates. The specific costs will depend on the scale and scope of the vaccination programs and interventions implemented.

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, as it presents findings from a cross-sectional study using a large dataset. However, to improve the evidence, the abstract could provide more information on the study design, sampling methods, and statistical analysis techniques used.

Abstract

The present analysis was conducted using the 2018 Nigeria Demographic Health Survey (NDHS) data. The NDHS is a population-based cross-sectional design aimed at providing maternal and child health indicators to assist policymakers and programme managers in designing and evaluating programs and strategies for improving the health of the country’s population.9 Nigeria is the most populated country in Africa with the population figure of about 200 million, of whom 17% were under-five children in 2018. Administratively, Nigeria has 36 states including a Federal Capital Territory zoned into six geopolitical groups. Of over 250 ethnic compositions, Hausa/Fulani, Igbo and Yoruba are predominant. The six regions in Nigeria are mainly defined by these three ethnic groups. While the Yoruba and Igbo women predominantly have formal education, only a few of such women are found in Hausa/Fulani ethnic groups. The Hausa/Fulani women mostly belong to Islamic religion. Contrariwise, the Igbo and Yoruba women are mainly Christians. Two-stage cluster sampling technique was employed for the survey using the sampling frame containing the enumeration areas (EAs) of the 2006 Nigeria Population and Housing Census (NPHC). At the first stage, 1400 EAs (referred to as clusters) were selected as the primary sampling units; the second stage involved the selection of 40,427 households as the secondary units for the survey. The detailed description of the sampling design and strategies has been reported in the 2018 NDHS report.9 In the present study, data of children aged 12–23 months, who had valid information on the basic recommended vaccines, belonged to eligible women of childbearing age who were residents of the selected households within the clusters, and either of the Hausa/Fulani or Igbo or Yoruba tribes. Children with missing information or ‘don’t know’ records were excluded from the analysis. A total of 3980 met all these criteria. In this study, the term ‘cluster’ was used in DHS to describe the ‘neighborhood’ where children live. The outcome of interest was the complete vaccination status of children aged 12–23 months as at a year old. Going by WHO recommendations, a child who received one dose of Bacille Calmette–Guerin (BCG), one dose of measles, three doses of polio, and three doses of diphtheria, tetanus and pertussis (DPT) vaccines by the age of 12 months has a complete vaccination.9,16 Therefore, children who have been immunized with all these basic vaccines are deemed to have complete vaccinations – this is coded “1”; and “0” if otherwise. The key independent variable was ethnicity. The analysis was restricted to the three most prominent ethnic groups: Hausa/Fulani, Igbo and Yoruba in Nigeria.24 Other independent variables were included to define child/maternal, household and health characteristics according to empirical literature.25,26 These include child sex, birth order, maternal age-at-birth, employment, education, marital status, region, place of residence, religion, household wealth status, media exposure, health insurance coverage, health decision-involvement, perceived access to self-medical help, place of delivery and prenatal-care assistance. A media exposure variable was derived and classified as exposed if a household had access to at least one of radio, television or newspaper; otherwise, not exposed. The wealth index variable was derived from the generated weighted factor score using principal component analysis as contained in the recode file. These scores were categorized into low, middle, and high wealth quintiles. Health decision-involvement’s variable is premised on women’s ability to decide on personal health care, household purchases and visitation to relatives. These related variables are coded as 2 (if she decides alone), 1 (if joint decision) and 0 (if she took no part), respectively. The aggregated scores were classified as 0 (no involvement), 1–3 (low) and 4–6 (high). Similarly, perceived access to self-medical help’s variable is derived subject to a woman opinion on the following dichotomized variables: obtaining permission to visit a health facility, getting the required treatment fee, distance to a health facility, or being accompanied to the health facility – 0 score implied no problem; otherwise, the problem. Frequencies, percentages and charts were used as descriptive measures at the univariate stage. The chi-square test was used to assess the association between the outcome variable and the individual independent variables at the bivariate stage. Asides, both simple and multiple GLMMs with a binomial random distribution and logit link function are used to explore the predictors of children’s complete vaccination. As clustering of children’s complete vaccination may ensue if characteristics within clusters are alike, failure to account for such clustered or nested nature of the data often lead to biased parameter estimates of the fixed effects. The method also supports the dependence structure of data for units within these clusters and estimates the magnitude of such correlation after taking into consideration the inclusion of explanatory variables.27 An extension of generalized linear models is the GLMM that accounts for all contextual information. The model appropriately estimates fixed- and random-effects for nested data. In brief, the model is as follows: Let Yij be the complete vaccination status of ith child in the jth cluster defined as For EY=1/Xij,φj,εj=π, the GLMM can be described as follows: where π=Pr(Y=1/Xij,φj,εj) =eβpxijp+θrφrj+εj1+eβpxijp+θrφrj+εj p-variable is the level-1 denoted by xijp (which varies within and between clusters); r-variable is the level-2 denoted by φrj (varies only between clusters); and the random intercept is εj At the bivariate level, GLMM was used to identify the respective explanatory variable’s influence on child complete vaccination. Also, it was used to identify predictors of complete vaccinations among children aged 12–23 months using a 4-stage approach at the multivariate level for the pooled data. The adopted 4-stage random intercept was premised on the classification of explanatory variables such that models 1, 2 and 3, respectively, included variables to define child/maternal, household and health characteristics, irrespective of their significance status at the bivariate level. Thereafter, significant factors from models 1–3 were included in the final model 4. Also, correlates of children’s complete vaccinations peculiar to each of the ethnic groups were identified using the significant factors (p < .05) in any of the simple models for each of the ethnicity. The odds ratios (OR) including their CIs and the intra-neighborhood correlation coefficient (ICC) which quantifies the proportion of variance explained due to hierarchical data clustering effect are reported. In each of the models, ICC was computed using the estimated random intercept variance and ICC ≥ 2% is deemed to have a significant neighborhood effect which calls for a multilevel approach.28 Akaike Information Criteria (AIC) values are also reported for model comparison; the model with the least value was adjudged as being more adequate.29 All analyses were carried out at 5% level of significance, using STATA 14 SE (StataCorp LP, College Station, USA). Ethical approval for the parent study was obtained from the Nigeria National Ethics Committee. Informed consent and all other international ethical standards of confidentiality and anonymity were certified. The details of the ethical approval have been reported earlier.9 The Demographic and Health Surveys Program approved the utilization of the dataset for the present analysis.

Materials

N/A

Innovations

Based on the information provided, here are some potential innovations that could improve access to maternal health:

1. Ethnicity-specific interventions: Develop targeted interventions that take into account the cultural and ethnic diversity of Nigeria, focusing on the specific needs and challenges faced by different ethnic groups, such as the Hausa/Fulani, Igbo, and Yoruba.

2. Community-based vaccination programs: Implement community-based vaccination programs that bring vaccination services closer to the communities, making it more convenient for mothers to access and complete their child’s vaccinations.

3. Health education and awareness campaigns: Conduct health education and awareness campaigns that specifically address the importance of complete vaccination and its benefits, targeting different ethnic groups and addressing any cultural beliefs or misconceptions that may hinder vaccination uptake.

4. Improving access to prenatal care: Enhance access to prenatal care services, particularly among the Hausa/Fulani ethnic group, by providing culturally sensitive and appropriate prenatal care options, including the availability of female healthcare providers and religious accommodations.

5. Strengthening healthcare infrastructure: Invest in improving healthcare infrastructure, particularly in rural areas, to ensure that healthcare facilities are equipped to provide comprehensive maternal and child health services, including vaccination services.

6. Empowering women through education: Promote education among women, particularly in the Hausa/Fulani ethnic group, to empower them with knowledge and decision-making abilities regarding their own health and the health of their children.

7. Addressing socioeconomic disparities: Implement strategies to address socioeconomic disparities, such as providing financial support or incentives for families from lower wealth quintiles to access and complete vaccinations for their children.

These innovations aim to address the specific challenges identified in the study and improve access to maternal health, particularly in relation to complete vaccination coverage among children in Nigeria.

AI Innovations Description

Based on the description provided, the recommendation to improve access to maternal health in Nigeria is to implement context-specific program interventions that address the factors influencing complete vaccination among children aged 12-23 months, particularly considering the ethnic diversity in the country.

The study found that there were variations in complete vaccination rates among different ethnic groups in Nigeria, with the Hausa/Fulani children having the lowest coverage. Therefore, it is important to develop targeted interventions that take into account the specific needs and cultural factors of each ethnic group.

Some key recommendations based on the study findings include:

1. Ethnicity-specific interventions: Develop and implement vaccination programs that are tailored to the cultural beliefs, practices, and preferences of each ethnic group. This may involve engaging community leaders, religious leaders, and traditional healers to increase awareness and acceptance of vaccinations.

2. Maternal education and empowerment: Improve access to education and empower women, especially in Hausa/Fulani communities where formal education for women is limited. Educated mothers are more likely to seek and utilize maternal health services, including vaccinations, for their children.

3. Prenatal care attendance: Promote and facilitate regular prenatal care attendance among all ethnic groups. Prenatal care provides an opportunity to educate mothers about the importance of vaccinations and ensure that they receive the necessary information and resources to complete the vaccination schedule for their children.

4. Health facility accessibility: Improve access to health facilities, particularly in rural areas where access may be limited. This can be achieved by increasing the number of health facilities, improving transportation infrastructure, and providing incentives for healthcare providers to work in underserved areas.

5. Socioeconomic factors: Address socioeconomic disparities by implementing strategies to reduce poverty and improve household wealth status. Children from higher wealth-quintile households were found to have higher vaccination rates, indicating the need to address financial barriers to accessing healthcare services.

6. Media exposure and health education: Utilize media channels, such as radio, television, and newspapers, to disseminate information about the importance of vaccinations and address misconceptions or concerns. Health education campaigns can help increase awareness and knowledge among parents, leading to improved vaccination rates.

By implementing these recommendations, it is possible to improve access to maternal health and increase vaccination rates among children in Nigeria, ultimately contributing to the achievement of the Sustainable Development Goals (SDGs) target for vaccination.

AI Innovations Methodology

The study described in the provided text focuses on the influence of ethnicity on complete vaccination among children aged 12-23 months in Nigeria. The study used data from the 2018 Nigeria Demographic and Health Survey (NDHS) and employed a cross-sectional design. The methodology involved analyzing the data using a generalized linear mixed model (GLMM) to account for the clustered nature of the data.

Here is a brief description of the methodology used to simulate the impact of recommendations on improving access to maternal health:

1. Data Collection: The study utilized data from the 2018 NDHS, which is a population-based survey designed to provide health indicators for policymakers and program managers. The survey employed a two-stage cluster sampling technique to select households and clusters representing different ethnic groups in Nigeria.

2. Sample Selection: The analysis focused on children aged 12-23 months from the three predominant ethnic groups in Nigeria: Hausa/Fulani, Igbo, and Yoruba. Children with missing or incomplete information were excluded from the analysis, resulting in a final sample of 3980 children.

3. Outcome Variable: The outcome of interest was the complete vaccination status of children aged 12-23 months. Complete vaccination was defined as receiving all recommended vaccinations, including BCG, measles, polio, and DPT vaccines.

4. Independent Variables: The key independent variable was ethnicity, specifically the three ethnic groups mentioned above. Other independent variables included child/maternal, household, and health characteristics such as child sex, birth order, maternal age-at-birth, education, marital status, region, place of residence, religion, household wealth status, media exposure, health insurance coverage, health decision-involvement, perceived access to self-medical help, place of delivery, and prenatal-care assistance.

5. Descriptive Analysis: Descriptive measures such as frequencies, percentages, and charts were used to summarize the data at the univariate stage. The chi-square test was used to assess the association between the outcome variable (complete vaccination) and the independent variables.

6. GLMM Analysis: GLMMs were used to explore the predictors of complete vaccination among children aged 12-23 months. GLMMs are an extension of generalized linear models that account for the clustered or nested nature of the data. The models estimated fixed and random effects for nested data, considering the inclusion of explanatory variables.

7. Model Building: A 4-stage approach was used to build the multivariate models. Models 1, 2, and 3 included variables related to child/maternal, household, and health characteristics, respectively, irrespective of their significance at the bivariate level. Significant factors from these models were included in the final model (Model 4).

8. Analysis and Reporting: Odds ratios (OR) and their confidence intervals (CI) were reported to quantify the associations between the independent variables and complete vaccination. The intra-neighborhood correlation coefficient (ICC) was calculated to assess the proportion of variance explained by the clustering effect. Akaike Information Criteria (AIC) values were used for model comparison.

9. Statistical Software: The analysis was conducted using STATA 14 SE, a statistical software package.

It is important to note that the methodology described above is specific to the study on complete vaccination among children in Nigeria. To simulate the impact of recommendations on improving access to maternal health, a different methodology would be required, focusing on maternal health indicators and relevant factors.

Authors & Co-Authors

Statistics:

Citations: 2

Authors: 6

Identifiers:

DOI: 10.1080/21645515.2020.1870394

ISSN: 21645515

Research Areas:

Community Interventions, Disparities, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care

Study Countries:

Nigeria

Study Design:

Cross Sectional Study, randomised-control-trial

Study Approach:

Quantitative

Participants Gender:

Female