Factors associated with the use of deworming drugs during pregnancy in Tanzania; an analysis from the 2015–16 Tanzanian HIV and malaria indicators survey

BMC Pregnancy and Childbirth, Volume 22, No. 1, Year 2022

Interpretation

Background: The use of deworming drugs is one of the important antenatal strategies in preventing anaemia in pregnancy. Little is known about the factors associated with the use of deworming drugs, which accounts for the aim of this study. Method: The study used data from the 2015–16 Tanzania HIV Demographic and Health Survey and Malaria Indicators Survey (2015–16 TDHS-MIS). A total of 6924 women of active reproductive age from 15 to 49 were included in the analysis. Both univariate and multiple logistic regression analyses were used. Results: The majority of interviewed women 3864(60.1%) took deworming drugs. In a weighed multiple logistic regression, women residing in urban areas reported greater use of deworming drugs than women residing in rural areas [AOR = 1.73, p = 0.01, 95% CI (1.26–2.38)]. In the four areas of residence, compared to women residing in mainland rural areas, women residing in mainland urban areas and Pemba islands reported greater use of deworming drugs [mainland urban (AOR = 2.56 p < 0.001,95% CI(1.78–3.75), and Pemba Island (AOR = 1.18, p < 0.001, 95% CI(1.17–1.20)]. However, women residing in Zanzibar Island (Unguja) were less likely to use deworming drugs compared to women in mainland rural women (AOR = 0.5, p < 0.001, 95% CI (0.45–0.55). Similarly, compared to women under 20 years of age, women between 20 to 34 years reported significantly greater use of deworming drugs [20 to 34 years (AOR = 1.30, p = 0.03, 95% CI(1.02–1.65). Likewise, greater use of deworming drugs was reported in women with a higher level of education compared to no education [higher education level (AOR = 3.25, p = 0.01,95% CI(1.94–7.92)], rich women compared to poor [rich (AOR = 1.43, p = 0.003, 95% CI (1.13–1.80)] and in women who initiated antenatal care on their first trimester of pregnancy compared to those who initiated later [AOR = 1.37, p < 0.001, 95% CI (1.17–1.61)]. Conclusion: Women who were more likely to use the deworming drugs were those residing in urban compared to rural areas, aged between 20 and 34 years, those with a higher level of formal education, wealthier, and women who book the antenatal clinic (ANC) within their first trimester of pregnancy. Considering the outcomes of anaemia in pregnancy, a well-directed effort is needed to improve the use of deworming drugs. This study was a cross-sectional analysis of a dataset from the 2015–16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) dataset (2015-16TDHS-MIS). The dependent variable was the use of deworming drugs. The independent variables were: 1) Antenatal booking (early compared to late antenatal booking): In the TDHS-MIS, early antenatal booking refers to having the first antenatal visit during the first trimester of pregnancy, while late antenatal booking refers to the first antenatal visit after the first trimester of pregnancy [14]. 2) age group of a woman during the TDHS-MIS (20–34, and more than 34, compared to age less than 20 years), 3) place of residence (urban compared to rural), 4), area of residence (mainland urban, Unguja and Pemba compared to mainland urban), 5) wealth index (middle and rich compared to poor), 6) parity (para 2–4, and para 5+ compared to para 1), and 7) level of education (primary, secondary and higher education compared to no education). The TDHS-MIS also collected information about household wealth, and categorized the participants into groups by principal component analysis [14]. Households were given scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, plus housing characteristics, such as the source of drinking water, toilet facilities, and flooring materials. National wealth quintiles were compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by their score, and then dividing the distribution into five equal categories, each with 20% of the population [14]. The details about the 2015–16 TDHS-MIS has been described in the respective DHS report [14]. Brieflly, the 2015–16 TDHS-MIS is the sixth in series of the Tanzania Demographic and Health Survey and Malaria Indicator Survey, with the primary objective of providing up-to-date estimates of basic demographic and health indicators for successful policy planning and implementation. The sampling procedure involved two stages to obtain a sample for urban and rural areas in both Tanzania mainland and Zanzibar. In the first stage, a total of 608 sample points (clusters) were identified. These clusters were the enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census [16]. The second stage involved a systematic selection of households, whereby 22 households were selected from each cluster to yield a representative probability sample of 13,376 households. A more detailed description of the sampling technique has been described in the TDHS-MIS report [14]. To enhance representativeness Tanzania was divided into nine geographic zones namely Western Northern zone, Central zone, Southern Highland zone, Southern zone, South-West Highland zone, Lake zone, Eastern zone, and Zanzibar and a representative sample obtained from each of the zones. To ensure statistical representation of the whole country, the distribution of the women in the sample was weighted (or mathematically adjusted) such that it resembles the true distribution in the country. Oversampled women from a small region contributed a small amount to the national total while undersampled women from a large region, like Dar es Salaam, contributed much more. In this way, the “weight” was calculated, which was used to adjust the number of women from each region so that each region’s contribution to the total is proportional to the actual population of the region [14]. Data collection involved four questionnaires based on the DHS program’s standard and have been described and published in the DHS report [14]. In this study, the data analysis process used data obtained from the Woman’s Questionnaire containing information from all eligible women aged 15–49 years. The information collected includes background characteristics, birth history and childhood mortality, knowledge and use of family planning methods, fertility preferences, access to antenatal services, delivery, and postnatal care, breastfeeding and infant feeding practices, vaccinations and childhood illnesses, marriage and sexual activity, women’s work and husbands’ background characteristics, adult mortality, including maternal mortality, malaria, domestic violence, and other health-related issues. The study population included all women of reproductive age (aged 15–49 years). The study used Individual file recode (TZIR7BFL). The analysis included only women who remembered the timing for antenatal booking of their youngest child and /or had an antenatal card for the most recent pregnancy for reference [14]. Those who had not been able to recall the timing (which included those who had no antenatal card for reference) or those who did not respond to the question on whether the woman took any drug for intestinal worms were removed from the analysis. Statistical Package for Social Sciences (IBM SPSS version 20) was employed for data analysis. Both weighed and unweighed data analysis were performed. A weighted data analysis was done by using weights determined by the DHS statisticians in order to increase the representativeness of the sample [14]. The variables which were presumed to influence the use of deworming drugs during pregnancy were filtered from the DHS-MIS and were first described in terms of percentage and frequencies. Then, the association between the dependent and independent variables was assessed by using the Chi-squared test. The variables that revealed a significant association were fitted in a binary weighted logistic regression model independently and the crude odds ratios (COR) established. Afterwards, all variables were entered into the model and adjusted odds ratios (AOR) were established to determine the significant independent predictors of the use of deworming drugs. Variables were considered to be significantly associated with the use of deworming drugs if p-value< 5%.

AI Digest

Study Justification:

The study aimed to investigate the factors associated with the use of deworming drugs during pregnancy in Tanzania. This is important because deworming drugs are a crucial strategy in preventing anemia in pregnancy. However, little is known about the factors that influence their use. Understanding these factors can help inform interventions and improve the use of deworming drugs, ultimately reducing the burden of anemia in pregnant women.

Highlights:

– The majority of interviewed women (60.1%) reported taking deworming drugs during pregnancy.
– Women residing in urban areas were more likely to use deworming drugs compared to those in rural areas.
– Women residing in mainland urban areas and Pemba islands reported greater use of deworming drugs compared to mainland rural areas.
– Women residing in Zanzibar Island (Unguja) were less likely to use deworming drugs compared to mainland rural women.
– Women between the ages of 20 and 34 were more likely to use deworming drugs compared to those under 20 years of age.
– Women with a higher level of education and higher wealth were more likely to use deworming drugs.
– Women who initiated antenatal care during their first trimester of pregnancy were more likely to use deworming drugs.

Recommendations:

Based on the study findings, the following recommendations can be made:

1. Increase awareness and education about the importance of deworming drugs during pregnancy, particularly in rural areas and Zanzibar Island (Unguja).
2. Improve access to deworming drugs in rural areas and Zanzibar Island (Unguja) to ensure equitable distribution.
3. Target interventions towards younger women, emphasizing the benefits of deworming drugs during pregnancy.
4. Strengthen antenatal care services and encourage early booking to promote the use of deworming drugs.
5. Implement strategies to address socioeconomic disparities, such as providing subsidies or free deworming drugs for women with lower education levels and lower wealth.

Key Role Players:

1. Ministry of Health: Responsible for developing and implementing policies related to maternal health and deworming drug distribution.
2. Healthcare Providers: Involved in educating pregnant women about the importance of deworming drugs and prescribing them during antenatal care visits.
3. Community Health Workers: Engaged in community outreach and education programs to raise awareness about deworming drugs and promote their use.
4. Non-Governmental Organizations (NGOs): Collaborate with the government to implement interventions targeting specific populations and areas with low deworming drug usage.
5. Donors and Funding Agencies: Provide financial support for deworming drug programs and initiatives.

Cost Items for Planning Recommendations:

1. Education and Awareness Campaigns: Budget for developing and disseminating educational materials, organizing community events, and conducting awareness campaigns through various media channels.
2. Drug Procurement and Distribution: Allocate funds for the purchase and distribution of deworming drugs to healthcare facilities, particularly in rural areas and Zanzibar Island (Unguja).
3. Training and Capacity Building: Set aside resources for training healthcare providers and community health workers on the importance of deworming drugs and their proper administration.
4. Monitoring and Evaluation: Include funds for monitoring and evaluating the implementation and impact of deworming drug interventions.
5. Subsidies or Free Drug Programs: Consider budgeting for subsidies or free deworming drugs for women with lower education levels and lower wealth to address socioeconomic disparities.
Please note that the cost items provided are general categories and not actual cost estimates. The actual costs will depend on the specific context, scale, and implementation strategies of the interventions.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study used a large sample size and conducted multiple logistic regression analyses to identify factors associated with the use of deworming drugs during pregnancy. The results showed significant associations between various independent variables and the use of deworming drugs. However, the study design was cross-sectional, which limits the ability to establish causality. To improve the strength of the evidence, future research could consider a longitudinal design to better understand the temporal relationship between the independent variables and the use of deworming drugs. Additionally, the study could include a control group to compare the outcomes between women who used deworming drugs and those who did not. This would provide further evidence of the effectiveness of deworming drugs in preventing anaemia in pregnancy.

Abstract

This study was a cross-sectional analysis of a dataset from the 2015–16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) dataset (2015-16TDHS-MIS). The dependent variable was the use of deworming drugs. The independent variables were: 1) Antenatal booking (early compared to late antenatal booking): In the TDHS-MIS, early antenatal booking refers to having the first antenatal visit during the first trimester of pregnancy, while late antenatal booking refers to the first antenatal visit after the first trimester of pregnancy [14]. 2) age group of a woman during the TDHS-MIS (20–34, and more than 34, compared to age less than 20 years), 3) place of residence (urban compared to rural), 4), area of residence (mainland urban, Unguja and Pemba compared to mainland urban), 5) wealth index (middle and rich compared to poor), 6) parity (para 2–4, and para 5+ compared to para 1), and 7) level of education (primary, secondary and higher education compared to no education). The TDHS-MIS also collected information about household wealth, and categorized the participants into groups by principal component analysis [14]. Households were given scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, plus housing characteristics, such as the source of drinking water, toilet facilities, and flooring materials. National wealth quintiles were compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by their score, and then dividing the distribution into five equal categories, each with 20% of the population [14]. The details about the 2015–16 TDHS-MIS has been described in the respective DHS report [14]. Brieflly, the 2015–16 TDHS-MIS is the sixth in series of the Tanzania Demographic and Health Survey and Malaria Indicator Survey, with the primary objective of providing up-to-date estimates of basic demographic and health indicators for successful policy planning and implementation. The sampling procedure involved two stages to obtain a sample for urban and rural areas in both Tanzania mainland and Zanzibar. In the first stage, a total of 608 sample points (clusters) were identified. These clusters were the enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census [16]. The second stage involved a systematic selection of households, whereby 22 households were selected from each cluster to yield a representative probability sample of 13,376 households. A more detailed description of the sampling technique has been described in the TDHS-MIS report [14]. To enhance representativeness Tanzania was divided into nine geographic zones namely Western Northern zone, Central zone, Southern Highland zone, Southern zone, South-West Highland zone, Lake zone, Eastern zone, and Zanzibar and a representative sample obtained from each of the zones. To ensure statistical representation of the whole country, the distribution of the women in the sample was weighted (or mathematically adjusted) such that it resembles the true distribution in the country. Oversampled women from a small region contributed a small amount to the national total while undersampled women from a large region, like Dar es Salaam, contributed much more. In this way, the “weight” was calculated, which was used to adjust the number of women from each region so that each region’s contribution to the total is proportional to the actual population of the region [14]. Data collection involved four questionnaires based on the DHS program’s standard and have been described and published in the DHS report [14]. In this study, the data analysis process used data obtained from the Woman’s Questionnaire containing information from all eligible women aged 15–49 years. The information collected includes background characteristics, birth history and childhood mortality, knowledge and use of family planning methods, fertility preferences, access to antenatal services, delivery, and postnatal care, breastfeeding and infant feeding practices, vaccinations and childhood illnesses, marriage and sexual activity, women’s work and husbands’ background characteristics, adult mortality, including maternal mortality, malaria, domestic violence, and other health-related issues. The study population included all women of reproductive age (aged 15–49 years). The study used Individual file recode (TZIR7BFL). The analysis included only women who remembered the timing for antenatal booking of their youngest child and /or had an antenatal card for the most recent pregnancy for reference [14]. Those who had not been able to recall the timing (which included those who had no antenatal card for reference) or those who did not respond to the question on whether the woman took any drug for intestinal worms were removed from the analysis. Statistical Package for Social Sciences (IBM SPSS version 20) was employed for data analysis. Both weighed and unweighed data analysis were performed. A weighted data analysis was done by using weights determined by the DHS statisticians in order to increase the representativeness of the sample [14]. The variables which were presumed to influence the use of deworming drugs during pregnancy were filtered from the DHS-MIS and were first described in terms of percentage and frequencies. Then, the association between the dependent and independent variables was assessed by using the Chi-squared test. The variables that revealed a significant association were fitted in a binary weighted logistic regression model independently and the crude odds ratios (COR) established. Afterwards, all variables were entered into the model and adjusted odds ratios (AOR) were established to determine the significant independent predictors of the use of deworming drugs. Variables were considered to be significantly associated with the use of deworming drugs if p-value< 5%.

Materials

N/A

Innovations

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

1. Mobile health (mHealth) interventions: Develop mobile applications or text messaging services to provide pregnant women with information about the importance of deworming drugs, reminders to take the medication, and access to healthcare providers for any questions or concerns.

2. Community health worker training: Train community health workers to educate pregnant women about the benefits of deworming drugs and provide them with the medication directly in their communities. This can help overcome barriers such as distance to healthcare facilities and lack of transportation.

3. Public awareness campaigns: Launch campaigns to raise awareness about the importance of deworming drugs during pregnancy. This can be done through various channels such as radio, television, social media, and community gatherings.

4. Integration of antenatal care services: Ensure that deworming drugs are included as a routine part of antenatal care services. This can be done by updating guidelines and protocols for healthcare providers and ensuring that the medication is readily available in healthcare facilities.

5. Targeted interventions for vulnerable populations: Identify and target specific populations, such as women in rural areas or those with lower levels of education, who may have lower access to deworming drugs. Implement tailored interventions to address their specific needs and barriers.

6. Collaboration with schools and educational institutions: Partner with schools and educational institutions to educate young girls and women about the importance of deworming drugs during pregnancy. This can help raise awareness and promote early adoption of healthy behaviors.

7. Strengthening supply chains: Improve the availability and accessibility of deworming drugs by strengthening supply chains and ensuring consistent availability in healthcare facilities, especially in rural areas.

8. Financial incentives: Explore the possibility of providing financial incentives, such as subsidies or vouchers, to pregnant women to encourage them to access and use deworming drugs. This can help overcome financial barriers and increase uptake.

9. Research and data collection: Conduct further research to better understand the factors influencing the use of deworming drugs during pregnancy. This can help inform the development of targeted interventions and policies to improve access and utilization.

10. Policy advocacy: Advocate for policies and guidelines that prioritize the use of deworming drugs during pregnancy and ensure their inclusion in national maternal health programs. This can help create a supportive environment for improving access and utilization.

AI Innovations Description

Based on the study titled “Factors associated with the use of deworming drugs during pregnancy in Tanzania; an analysis from the 2015–16 Tanzanian HIV and malaria indicators survey,” the following recommendation can be developed into an innovation to improve access to maternal health:

1. Strengthening Antenatal Care (ANC) Services: Implement strategies to encourage early antenatal booking, such as community awareness campaigns and incentives for women to seek ANC services during their first trimester of pregnancy. This can be done through partnerships with local healthcare providers, community leaders, and women’s groups.

2. Targeted Education and Awareness: Develop targeted educational programs to increase awareness about the importance of deworming drugs during pregnancy. These programs should focus on reaching women in rural areas, younger women, and those with lower levels of education. Utilize various communication channels, such as radio, television, and community health workers, to disseminate information about the benefits and availability of deworming drugs.

3. Improving Access to Deworming Drugs: Ensure the availability and accessibility of deworming drugs in both urban and rural areas. This can be achieved by strengthening the supply chain management system, training healthcare providers on the administration of deworming drugs, and establishing partnerships with pharmaceutical companies to ensure a steady supply of quality drugs.

4. Addressing Socioeconomic Factors: Implement interventions to address socioeconomic factors that influence the use of deworming drugs, such as wealth disparities and educational attainment. This can include providing subsidies or financial assistance for deworming drugs to women from low-income backgrounds and promoting educational opportunities for women to empower them to make informed decisions about their health.

5. Monitoring and Evaluation: Establish a robust monitoring and evaluation system to track the implementation and impact of the recommended interventions. Regularly assess the coverage and utilization of deworming drugs during pregnancy, as well as the associated factors, to identify areas for improvement and inform future interventions.

By implementing these recommendations, it is expected that access to maternal health, specifically the use of deworming drugs during pregnancy, can be improved, leading to better health outcomes for pregnant women and their babies.

AI Innovations Methodology

Based on the provided description, here are some potential recommendations to improve access to maternal health:

1. Increase awareness and education: Implement comprehensive education programs to raise awareness about the importance of deworming drugs during pregnancy. This can be done through community health workers, antenatal care clinics, and mass media campaigns.

2. Strengthen antenatal care services: Improve access to antenatal care services by ensuring that pregnant women have timely and regular visits to healthcare facilities. This can be achieved by increasing the number of healthcare providers, improving infrastructure, and reducing barriers to accessing care.

3. Address regional disparities: Develop targeted interventions to address regional disparities in the use of deworming drugs. This can involve increasing resources and support for rural areas and areas with lower utilization rates.

4. Improve affordability and availability: Ensure that deworming drugs are affordable and readily available to pregnant women. This can be achieved through government subsidies, partnerships with pharmaceutical companies, and strengthening supply chains.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Define the indicators: Identify specific indicators that measure access to maternal health, such as the percentage of pregnant women receiving deworming drugs during antenatal care visits.

2. Collect baseline data: Gather data on the current utilization rates of deworming drugs during pregnancy, as well as other relevant factors such as demographic characteristics and socioeconomic status.

3. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and their potential impact on access to maternal health. This model should consider factors such as population size, geographical distribution, and resource allocation.

4. Input data and run simulations: Input the baseline data into the simulation model and run multiple simulations to assess the potential impact of the recommendations. This can involve adjusting variables such as the coverage of education programs, the number of healthcare providers, and the availability of deworming drugs.

5. Analyze results: Analyze the results of the simulations to determine the potential impact of the recommendations on improving access to maternal health. This can involve comparing the baseline data with the simulated outcomes to identify trends and patterns.

6. Refine and validate the model: Refine the simulation model based on the analysis of the results and validate it using additional data sources or expert input. This will help ensure the accuracy and reliability of the simulation.

7. Communicate findings and make recommendations: Present the findings of the simulation analysis, including the potential impact of the recommendations, to relevant stakeholders and decision-makers. Use this information to make informed recommendations for improving access to maternal health.

It is important to note that the methodology described above is a general framework and may need to be adapted based on the specific context and data availability.

Author

Dima Health

Statistics:

Citations: 4

Identifiers:

DOI: 10.1186/s12884-021-04291-6

Research Areas:

Environmental, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Violence and Injury

Study Countries:

Tanzania

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Quantitative

Participants Gender:

Female