Micronutrient status among pregnant women in zinder, niger and risk factors associated with deficiency

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Study Justification:
– Anemia and micronutrient deficiencies in pregnant women are associated with adverse pregnancy outcomes.
– In Niger, 58.6% of pregnant women are anemic, but the micronutrient statuses are unknown.
– This study aimed to estimate the prevalence of micronutrient deficiencies among pregnant women in Zinder, Niger and explore associated risk factors.
Study Highlights:
– The study was conducted in rural communities in the Zinder Region of Niger as part of the baseline assessment for the Niger Maternal Nutrition (NiMaNu) Project.
– A total of 770 blood samples from pregnant women in 88 randomly selected rural villages were analyzed for various micronutrients.
– The prevalence of micronutrient deficiencies among pregnant women was high, indicating a severe public health problem.
– Iron deficiency was found in 20.7% of women based on ferritin levels and 35.7% based on soluble transferrin receptor levels.
– Other deficiencies included low zinc (40.7%), marginal vitamin A (79.7%), low folate (44.3%), and low vitamin B12 (34.8%).
– Common risk factors associated with micronutrient deficiencies included gravidity, mid-upper-arm circumference, geophagy, malaria, and the result of the woman’s last pregnancy.
– Interventions to strengthen antenatal care and improve access and adherence to nutrition and health interventions are critical for pregnant women in this population.
Recommendations:
– Promote the strengthening of antenatal care services for pregnant women in rural communities in Zinder, Niger.
– Improve access to and adherence to nutrition and health interventions for pregnant women.
– Address common risk factors associated with micronutrient deficiencies, such as gravidity, mid-upper-arm circumference, geophagy, malaria, and previous pregnancy outcomes.
Key Role Players:
– Local governmental health officials
– Researchers and scientists
– Health practitioners and caregivers
– Community leaders and volunteers
– Non-governmental organizations (NGOs) and international agencies
Cost Items for Planning Recommendations:
– Training and capacity building for health practitioners and caregivers
– Development and implementation of antenatal care programs
– Provision of nutrition and health interventions, including supplements and fortified foods
– Monitoring and evaluation of interventions
– Community outreach and education programs
– Research and data collection activities
– Logistics and transportation for supplies and equipment
– Administrative and management costs

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a community-based cross-sectional survey with a large sample size (n = 770) of pregnant women in rural communities in Niger. The study objectives were clearly stated, and the prevalence of micronutrient deficiencies among pregnant women in Zinder, Niger was estimated. The study also explored associated risk factors. The study was conducted as part of a larger programmatic intervention to improve antenatal care services, which adds to the strength of the evidence. However, to improve the evidence, it would be beneficial to include information on the methodology used for data collection and analysis, as well as the limitations of the study.

Anemia and micronutrient (MN) deficiencies in pregnant women are associated with adverse pregnancy outcomes. In Niger, 58.6% of pregnant women are anemic, however, MN statuses are unknown. The study objectives were to estimate the prevalence of MN deficiencies among pregnant women in Zinder, Niger and explore associated risk factors. Pregnant women living in randomly selected rural villages (n = 88) were included. Capillary and venous blood samples (n = 770) were analyzed for hemoglobin (Hb) and plasma ferritin, soluble transferrin receptor (sTfR), zinc (pZn), retinol binding protein (RBP), folate and vitamin B12. C-reactive protein and alpha-1-acid glycoprotein were measured to adjust for inflammation. The prevalence of MN deficiencies in pregnant woman was high, indicative of a severe public health problem. Prevalence of iron deficiency was 20.7% and 35.7%, by ferritin (8.3 mg/L), respectively. In total, 40.7% of women had low pZn (<50 μg/dL), 79.7% had marginal RBP (<1.32 μmol/L), 44.3% of women had low folate (<10 nmol/L) and 34.8% had low B12 concentrations (10 km from the CSI were randomly selected and randomized to order of participation. Women from the first 4 villages in each CSI catchment area (CSI-village, CS-village, and 2 additional villages) were enrolled with a target of approximately 16–20 women enrolled per village. If the sample size of approximately 77 women per CSI catchment area was not met by the first 4 randomized villages of each CSI, then additional villages on the randomization list of each CSI catchment area were included until the sample size was reached. A total of 88 communities were included in the present survey. Pregnant women were identified using the random walk method [16], with the starting point randomly selected for each village (market, primary school or mosque). Pregnant women at any week of gestation were eligible to participate in the survey if they provided written informed consent, had resided in the village for the previous six months and had no plans to move out of the study area within the coming two months. Women were ineligible if they had an illness warranting immediate hospital referral or were unable to provide consent due to mental disability. The NiMaNu Project was approved by the National Ethical Committee in Niamey (Niger: 005/2013/CCNE) and the Institutional Review Board of the University of California, Davis (USA) (IRB, University of CA, Davis: 447971). Consent materials were presented in both written and oral format, in the presence of a neutral witness. Informed consent was documented with a written signature or a fingerprint prior to enrollment in the study. The study was registered at www.clinicaltrials.gov as {“type”:”clinical-trial”,”attrs”:{“text”:”NCT01832688″,”term_id”:”NCT01832688″}}NCT01832688. As part of the baseline survey, each enrolled woman participated in two study visits, spaced approximately one month apart. The first visit occurred in the home, and the follow-up visit (i.e., visit 2) was conducted in a central village location. Information on socio-economic status (SES) and demographic characteristics of the woman and her household, pregnancy and health status, dietary practices, food security, and knowledge, attitudes and practices (KAP) pertaining to ANC and nutrition were collected via structured interviews by trained female fieldworkers at both study visits. Woman’s weight, height, mid-upper arm circumference (MUAC) and symphysis-fundal height (SFH) were measured in duplicate at both visits, to 50 g and 0.1 cm precision, respectively [17,18]. If the 2 measurements were >0.2 kg (weight) or >0.5 cm apart (height, MUAC, and SFH), a third measurement was taken; results represent the mean of the two closest measurements. Low MUAC was defined as <23 cm [19]. Dietary MN adequacy was assessed using the Minimum Dietary Diversity for Women (MDD-W) as a proxy indicator; the population of women who reported consuming at least five of ten defined food groups in the previous 24 h (using a list-based food frequency questionnaire) was considered to have a higher likelihood of MN adequacy [20]. Household SES was estimated using three proxy indices (housing quality, household assets, and household livestock), as previously described in detail elsewhere [21]. Household food insecurity, defined as the limited or uncertain access to adequate food of sufficient quality, was assessed using the Household Food Insecurity Access Scale (HFIAS) of the Food and Nutrition Technical Assistance/USAID [22]. IFA coverage was defined as the individual having received IFA supplements at any point during her current pregnancy. IFA adherence was defined as the individual having consumed IFA daily in the previous week. Gestational age was estimated as a weighted average of the following obtained information: reported last menstrual period (LMP; by estimated number of months, lunar cycles and/or proximity to a religious or cultural event), time elapsed since quickening, and two fundal height measurements taken approximately one month apart [23,24]. Trimester of pregnancy was defined as follows: 1st trimester, <13 weeks; 2nd trimester: ≥13 weeks to <27 weeks; and 3rd trimester, ≥27 weeks. Capillary blood samples were collected at visit 2 for the measurement of Hb in all women. In a sub-set of women, 7.5 mL venous blood samples were collected at the same time point for measurement of plasma ferritin, soluble transferrin receptor (sTfR), zinc (pZn), retinol binding protein (RBP), α-1-acid glycoprotein (AGP), C-reactive protein (CRP), vitamin B12, folate and histidine-rich protein II (HRP2) concentrations. According to procedures recommended by the International Zinc Nutrition Consultative Group (IZiNCG) [25,26], blood was drawn from the antecubital vein and collected in an evacuated, trace element free polyethylene tube containing lithium heparin (Sarstedt AG & Co., Numbrecht, Germany). In the field, samples were stored immediately between 4 and 8 °C until separation. Plasma was separated from heparinized blood at the Regional Hospital of Zinder ≤8 h from collection, by centrifuging at 3000 rpm for 10 min. Plasma was aliquoted in clear or amber (B12 and folate) microcentrifuge tubes and stored at −20 °C until shipment to the United States and Germany on high-salinity ice packs for laboratory analyses. Hb concentration was measured immediately after capillary blood collection with a HemoCue 201+ photometer (Hemocue AB, Angelholm, Sweden). Plasma ferritin, sTfR, RBP, CRP, and AGP concentrations were measured using a combined sandwich ELISA technique and pZn was measured colormetrically (WAKO Chemicals GmbH, Neuss, Germany) at the VitMin Lab (Willstaett, Germany) [27]. All samples were measured in duplicate and the inter-assay CV for the control sample ranged from 3.0 to 9.2%. Plasma B12 and folate concentrations were measured by enzyme-based immunoanalysis using a Cobas(R) e41 analyzer (Roche Diagnostics, Switzerland) and the reagents vitamin B12 (theoretical normality values 95% CI: 191–663 pg/mL) and folate III (4.6–18.7 ng/mL). Plasma HRP2 concentrations (indicative of current or recent malaria parasitemia) were measured using a commercially available CELISA kit (Cellabs Pty Ltd., Brookvale, Australia), following the manufacturer’s instructions. Plasma samples were measured in singlicate on plates with positive and negative controls provided by the manufacturer; samples with an absorbance value greater than the OD of the negative control +0.1 unit were considered positive for malaria antigen. Assuming a 50% prevalence of deficiency, the total sample size required to estimate the prevalence of each MN deficiency ±3.5% (95% CI) was n = 784. Venous blood for assessment of MN concentrations was collected from all eligible pregnant women participating in visit 2 of the NiMaNu Project until the required sample size was obtained. The study had a power of 80% to detect regression coefficients between continuous variables when the absolute value of the standardized coefficient was ≥0.122, assuming an intra-cluster correlation coefficient of 0.01. Descriptive statistics were calculated for all variables. Variables not normally distributed (ferritin, sTfR, folate, B12) were log transformed, and characterized by parametric distribution, prior to subsequent analysis. Biomarkers considered to be acute phase proteins or reactants (ferritin, pZn, RBP) were adjusted for elevated CRP and AGP to remove the confounding effect of sub-clinical infection and inflammation on the assessment of nutritional status and deficiency. A continuous regression method was used to adjust MN biomarker concentrations to the 10th percentile of CRP and AGP concentrations for the study-specific population (CRP = 0.38 mg/L; AGP = 0.23 g/L) [28,29]. MN deficiency cut-offs in pregnant women are not well established, especially in a setting with a high prevalence of sub-clinical infection and inflammation. Therefore, the following cut-offs were used for descriptive purposes only; all analyses were conducted using continuous MN concentrations to retain the maximum information available. Anemia was defined as Hb < 11.0 g/dL in the first and third trimesters and Hb < 10.5 g/dL in the second trimester [13]. Iron deficiency was variously defined as plasma ferritin 8.3 mg/L [27,30]. Zinc deficiency was defined as pZn < 50 µg/dL [26]. Marginal vitamin A status was defined as RBP < 1.32 µmol/L [31]. Low and marginal B12 concentrations were defined as plasma B12 < 148 pmol/L and 148–221 pmol/L, respectively. Low folate was defined as plasma folate concentration 5 mg/L and >1 g/L, respectively. Associations between independent risk factors and outcome variables (Hb, plasma ferritin, sTfR, pZn, RBP, B12, and folate) were evaluated using bivariate generalized linear mixed models (SAS PROC GLIMMIX). The association between independent risk factors and MMN deficiency was evaluated using mixed-model logistic regression (SAS PROC GLIMMIX). Hierarchical clustering models used a random effect of village nested within CSI (i.e., cluster) and a fixed effect of region. Potential predictors included SES and demographic factors, obstetric history, KAP concerning pregnancy, and current nutritional and health status. All bivariate models were reconsidered including trimester of pregnancy as an additional independent variable to assess whether any of the significant associations in the bivariate models were attributable to variation in gestational age. Although all pregnant women in the survey catchment area were eligible for participation, only one participant was in her first trimester at visit 2; therefore models controlling for trimester of pregnancy are restricted to women in their second and third trimesters. Hypothesis driven multivariable generalized linear mixed models were constructed to explore relationships between malaria antigenemia, adolescence or primigravidae, and biomarkers of anemia and iron status. All statistical analyses were completed with SAS System software for Windows release 9.4 (SAS Institute, Cary, North Carolina, United States). Data are presented as mean (95% CI), geometric mean (95% CI), or β (95% CI) unless otherwise noted. β-coefficients from analyses using log transformed outcome variables are exponentiated regression coefficients and interpreted as percent increase/decrease (multiplicative); β coefficients from analyses using non-transformed outcome variables are interpreted as unit increase/decrease (additive). A p value < 0.05 was considered statistically significant. All models were evaluated for model assumptions, including normality of residuals, linearity and observations with undue leverage.

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

1. Mobile Health (mHealth) Applications: Develop mobile applications that provide pregnant women with access to information and resources related to maternal health. These apps could include features such as appointment reminders, educational content, and nutrition tracking.

2. Telemedicine: Implement telemedicine programs that allow pregnant women in rural areas to consult with healthcare professionals remotely. This would improve access to prenatal care and allow for early detection and management of complications.

3. Community Health Workers: Train and deploy community health workers in rural areas to provide basic prenatal care, education, and support to pregnant women. These workers could also help identify high-risk pregnancies and refer women to appropriate healthcare facilities.

4. Mobile Clinics: Establish mobile clinics that travel to remote areas to provide prenatal care and essential maternal health services. This would bring healthcare closer to pregnant women who may have limited access to healthcare facilities.

5. Supply Chain Management: Improve the supply chain management of maternal health products, such as iron supplements and prenatal vitamins, to ensure that they are readily available in rural areas. This would help address deficiencies in essential micronutrients among pregnant women.

6. Health Education Programs: Develop and implement health education programs that focus on improving maternal nutrition and promoting healthy behaviors during pregnancy. These programs could be delivered through community workshops, radio broadcasts, or mobile applications.

7. Public-Private Partnerships: Foster collaborations between government agencies, non-profit organizations, and private companies to improve access to maternal health services. This could involve leveraging private sector resources and expertise to expand healthcare infrastructure in underserved areas.

8. Transportation Solutions: Address transportation barriers by providing transportation vouchers or arranging transportation services for pregnant women to access healthcare facilities. This would help overcome geographical barriers and ensure timely access to prenatal care.

9. Maternal Health Financing: Explore innovative financing mechanisms, such as microinsurance or community-based health financing, to make maternal health services more affordable and accessible to women in low-income communities.

10. Data Collection and Monitoring: Implement robust data collection and monitoring systems to track maternal health indicators and identify areas for improvement. This would help inform evidence-based decision-making and ensure accountability in the delivery of maternal health services.
AI Innovations Description
Based on the description provided, the recommendation to improve access to maternal health and address the high prevalence of micronutrient deficiencies among pregnant women in Zinder, Niger is to implement targeted interventions. These interventions should focus on strengthening antenatal care services and improving access and adherence to nutrition and health interventions for pregnant women in the population.

Specifically, the following actions can be taken:

1. Strengthen Antenatal Care (ANC) Services: Enhance the quality and availability of ANC services in the rural communities of Zinder, Niger. This can be achieved by training healthcare providers on best practices for maternal health, including screening and management of micronutrient deficiencies. ANC visits should be encouraged and promoted to ensure regular monitoring and support for pregnant women.

2. Nutrition Education and Counseling: Provide comprehensive nutrition education and counseling to pregnant women, focusing on the importance of a balanced diet and the consumption of nutrient-rich foods. This can be done through group sessions, individual counseling, and the distribution of educational materials. Emphasize the significance of consuming foods rich in iron, zinc, vitamin A, vitamin B12, and folate to address the specific deficiencies identified in the study.

3. Iron and Folic Acid Supplementation: Ensure the availability and accessibility of iron and folic acid supplements to pregnant women. Promote the importance of regular and consistent intake of these supplements to prevent and treat iron deficiency anemia and folate deficiency.

4. Community Engagement and Mobilization: Engage the community, including community leaders, women’s groups, and local healthcare providers, to raise awareness about the importance of maternal health and the prevention of micronutrient deficiencies. Encourage community support and involvement in promoting healthy behaviors and seeking ANC services.

5. Integration of Services: Integrate nutrition and health interventions within existing healthcare systems to improve efficiency and effectiveness. This can involve collaboration between ANC services, nutrition programs, and other relevant stakeholders to ensure a comprehensive approach to maternal health.

6. Monitoring and Evaluation: Establish a robust monitoring and evaluation system to track the implementation and impact of the interventions. Regular assessments should be conducted to measure changes in the prevalence of micronutrient deficiencies and pregnancy outcomes among the target population.

By implementing these recommendations, it is expected that access to maternal health will be improved, and the prevalence of micronutrient deficiencies among pregnant women in Zinder, Niger will be reduced, leading to better pregnancy outcomes and improved overall maternal health.
AI Innovations Methodology
Based on the provided information, here are some potential recommendations to improve access to maternal health:

1. Strengthen Antenatal Care (ANC) Services: Enhance the quality and availability of ANC services in rural communities in the Zinder Region of Niger. This can include training healthcare providers, improving infrastructure and equipment, and ensuring the availability of essential supplies and medications.

2. Increase Access to Nutrition Interventions: Implement programs that promote adequate nutrition during pregnancy, including the provision of fortified foods, nutritional supplements, and education on healthy eating practices. This can help address the high prevalence of micronutrient deficiencies among pregnant women.

3. Improve Health Intervention Adherence: Develop strategies to improve adherence to recommended health interventions during pregnancy, such as regular ANC visits, taking iron and folic acid supplements, and following dietary guidelines. This can be achieved through community engagement, health education campaigns, and targeted counseling.

4. Address Common Risk Factors: Target interventions towards addressing common risk factors associated with micronutrient deficiencies, such as gravidity, mid-upper-arm circumference, geophagy, malaria, and the outcome of the woman’s last pregnancy. This can involve implementing targeted interventions and providing tailored support to women at higher risk.

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

1. Define the Outcome Measures: Determine the specific indicators that will be used to measure the impact of the recommendations, such as the prevalence of anemia, micronutrient deficiencies, and utilization of ANC services.

2. Collect Baseline Data: Gather data on the current status of maternal health in the target population, including the prevalence of anemia and micronutrient deficiencies, ANC utilization rates, and other relevant indicators.

3. Develop a Simulation Model: Create a mathematical or statistical model that incorporates the baseline data and simulates the potential impact of the recommendations on the outcome measures. This model should consider factors such as population size, intervention coverage, and the expected effectiveness of the interventions.

4. Run Simulations: Use the simulation model to run multiple scenarios that represent different levels of implementation and coverage of the recommendations. This will allow for the estimation of the potential impact on the outcome measures under different conditions.

5. Analyze Results: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. This can include comparing the outcomes between different scenarios and identifying the most effective strategies.

6. Refine and Validate the Model: Continuously refine and validate the simulation model based on new data and feedback from stakeholders. This will ensure that the model accurately represents the real-world context and can be used to inform decision-making.

By following this methodology, policymakers and healthcare providers can gain insights into the potential impact of different interventions and make informed decisions on how to improve access to maternal health in the Zinder Region of Niger.

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