Prevalence, predictors of low birth weight and its association with maternal iron status using serum ferritin concentration in rural Eastern Ethiopia: a prospective cohort study

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Study Justification:
– Low birth weight (LBW) is a significant predictor of perinatal survival, infant morbidity, and mortality, as well as future developmental disabilities and illnesses.
– The nutritional status of pregnant women has been identified as a research priority, but evidence on LBW and its association with prenatal iron status in rural Ethiopia is limited.
– This study aimed to assess the prevalence of LBW, predictors of LBW, and the association between LBW and maternal iron status using serum ferritin concentration in rural Eastern Ethiopia.
Study Highlights:
– The study found that 20.2% of neonates in the study area were born with LBW.
– Women who were iron deficient during pregnancy had a 5.04 times higher risk of delivering a baby with LBW compared to those who were not iron deficient.
– Neonates of iron-deficient mothers had lower birth weight compared to neonates of mothers with normal iron status.
– Other factors associated with LBW included maternal under-nutrition, maternal height, and female neonates.
– However, women who were supplemented with iron and folic acid during pregnancy had a 45% decreased chance of delivering a baby with LBW.
Recommendations for Lay Readers and Policy Makers:
– LBW is a public health concern in rural Eastern Ethiopia, and efforts should be made to address this issue.
– Strategies to improve maternal nutritional status should be implemented, including promoting the consumption of diversified and iron-rich foods.
– Universal access and compliance with iron and folic acid supplementation during pregnancy should be enhanced to improve maternal health.
– Comprehensive intervention strategies based on a life-cycle approach, targeting vulnerable periods for women during pregnancy and their neonates, are recommended.
Key Role Players Needed to Address Recommendations:
– Health extension workers: They can play a crucial role in promoting desirable food behavior and nutritional practices among pregnant women.
– Community health promoters (Women Developmental Army): They can help in disseminating information and raising awareness about the importance of maternal nutrition and iron supplementation.
– Health professionals: They can provide guidance and support in implementing interventions to improve maternal nutritional status and access to iron and folic acid supplementation.
Cost Items to Include in Planning Recommendations:
– Training and capacity building for health extension workers and community health promoters.
– Development and dissemination of educational materials on maternal nutrition and iron supplementation.
– Monitoring and evaluation activities to assess the effectiveness of interventions.
– Provision of iron and folic acid supplements to pregnant women.
– Outreach programs and community engagement activities to promote desirable food behavior and nutritional practices.
Please note that the cost items provided are general suggestions and may vary based on the specific context and resources available.

Introduction: Low birth weight (LBW) is one of the major predictors of perinatal survival, infant morbidity, and mortality, as well as the risk of developmental disabilities and illnesses in future lives. The effect of the nutritional status of pregnant women on birth outcomes is becoming a common research agenda, but evidence on the level of low birth weight (LBW) and its association with prenatal iron status in Ethiopia, particularly among rural residents, is limited. Thus, this study aimed to assess the prevalence, predictors of LBW, and its association with maternal iron status using serum ferritin concentration in Haramaya district, eastern Ethiopia, 2021. Methods: A community-based prospective cohort study design was conducted. Of a total of 427 eligible pregnant women followed until birth, 412 (96.48%) were included in the final analysis. Iron status was determined using serum ferritin (SF) concentration from venous blood collected aseptically from the ante-cubital veins analyzed on a fully automated Cobas e411 (German, Japan Cobas 4000 analyzer series) immunoassay analyzer. Iron deficiency(ID) and iron deficiency anemia (IDA) were classified as having SF less than 15 μg/L and SF less than 15 μg/L and Hb level of < 11.0 g/dl during the first or third trimester or < 10.5 g/dl during the second trimester as well, respectively. Birthweight was measured within 72 h of birth and < 2500 g was considered LBW. Birthweight was measured within 72 h of birth and < 2500 g was considered as LBW. A Poisson regression model with robust variance estimation was used to investigate the factors associated with LBW and the association between maternal iron status and LBW. An adjusted prevalence ratio with a 95% confidence interval was reported to show an association using a p-value < 0.05. Results: About 20.2% (95% CI: 16%-24%) of neonates were born with LBW. The prevalence of LBW was 5.04 (95% CI = 2.78–9.14) times higher among women who were iron deficient during pregnancy compared to those who were normal. The neonates of women who were iron deficient during pregnancy had lower birth weight (aPR=5.04; 95% CI = 2.78–9.14) than the neonates of women who were normal. Prevalence of LBW was higher among mothers who were undernourished (MUAC < 23cm) (aPR = 1.92; 95% CI= 1.33–2.27), stunted (height <145cm) (aPR=1.54; 95% CI=1.04–2.27) and among female neonates (aPR=3.70; 95% CI= 2.28–6.00). However, women who were supplemented with iron and folic acid (IFAS) during pregnancy had a 45% decreased chance of delivering low birth weight (aPR= 0.55; 95% CI=0.36–0.84). Conclusion: We found that LBW is of public health significance in this predominantly rural setting. ID during pregnancy is found to have a negative effect on birth weight. IFA supplementation, the maternal under-nutrition, height, and sex of neonates were identified as predictors of low weight at birth. To improve maternal nutritional status, health interventions must address targeted strategies promoting desirable food behavior and nutritional practices. These include; promoting the consumption of diversified and rich iron food to improve the maternal nutritional status. A continued effort is needed in enhancing universal access and compliance with IFA supplementation to improve maternal health. Intervention strategies that are complementary and comprehensive across the vulnerable periods for women during pregnancy and their neonates that are based on a life-cycle approach are suggested.

The study was embedded into the Haramaya Health Demographic Surveillance and Health Research Centre (HDS-HRC), which was established in 2018. The HDS-HRC covers 12 rural kebeles (the lowest administrative unit in Ethiopia) out of 33 kebeles found in the district located approximately 500 KM away from the capital city, Addis Ababa. From 5252 pregnant women in the district during the study period, 2306 were under follow-up of the HDS-HRC [27, 28]. A community-based prospective cohort study was conducted. All pregnant women whose serum ferritin and hemoglobin concentrations were determined at their second or third trimester and who later gave singleton live births were eligible for the study. Neonates reached later on 72 h of birth were excluded. We also excluded pregnant women whose exposure was determined in the first trimester, as the fetal weight gain in the first trimester is known to be minimal. This study is a longitudinal study that obtained birth outcome information of pregnant women, the exposure of LBW was determined from Charan and Biswas's study [29], with the input of 95% confidence level, 5% marginal error, 80% power, and 1:1 ratio between exposed and non-exposed subjects. The expected prevalence of LBW in exposed and non-exposed subjects was taken from prior studies [30]. As a result, 432 sample sizes were computed. Nevertheless, by adding a 10% non-response rate 475 participants were included. After constructing a sampling frame from the HDS-HRC database, simple random sampling was applied to the eight randomly selected kebeles and then the eligible women were selected using the computer-generated lottery method. Nevertheless, for this specific paper, 427 pregnant women who were in their second or third trimester during the baseline survey were considered. Figure 1 displays a detailed description a flow diagram for study into two phases. Study flow shows date and duration, study design, and data collected As described in the previous papers [31, 32], from 475 calculated sample sizes, 448 pregnant women were included in the baseline survey. For this specific paper, 427 whose serum ferritin and hemoglobin concentrations were determined at their second or third trimester during the baseline survey were considered. Of 427 followed pregnant women, birth weight was taken from 412 neonates, as lost to follow-up [2], multiple births [3] and early neonatal death [2], birth weight measurement taken after 72 h of birth [3], and fetal loss [5] were excluded. We recruited participants selected from the HDS-HRC database voluntarily from the community during home-to-home visits. We obtained days in which antenatal care services were not held for pregnant women in the nearby health facilities. On these dates, researchers visited the randomly selected kebeles and eligible pregnant women required for recruitment. Although special attention was given to involving all eligible pregnant women for participation, some of them did not volunteer to participate in the cohort. We made announcements using health extension workers to invite pregnant women to select kebeles in the district. Upon recruitment and signing of informed consent, we assessed socio-economic characteristics, dietary practices, anthropometric measurements, and collected blood samples for hematology and biochemical analysis. We carried out the face-to-face interviews to collect knowledge, attitudes, and obstetric and other pregnancy-related data on house-to-house visits. The two-day training was given by research experts to train data collectors, laboratory professionals, and supervisors before the pre-test on each data collection tool. A day field pre-testing session followed the training in a nearby rural district. These trained data collectors carried out all data collection for this study at the randomly selected kebeles in the HDS-HRC. After the baseline study, participants' telephone numbers and addresses were collected and entered into a book, and we entered the expected date of delivery for each participant. The occurrence of births in the cohort was promptly found and informed by pre-established local community health promoters which the country labeled as ''Women Developmental Army (WDA)" and health extension workers (HEW). We used a structured questionnaire to gather data on the birth experiences of each participant. Birth outcomes such as gestational age at birth, birth weight, birth delivery method, neonatal mortality, stillbirth, abortions, and postpartum morbidity of mothers were obtained. Among all the birth outcomes data, birth weight was used as the outcome variable in this study. Birth weight was gauged within 72 h of birth by trained and well-experienced data collectors who were employed by HDS-HRC. Among all the birth outcomes data, birth weight was used as the outcome variable in this study. As described in the previous papers [31, 32], in the baseline survey, data were collected through face-to-face interviews by trained research assistants using a standard pretested questionnaire (food frequency questionnaire) translated to the local language. The questionnaire contains data on socio-economic, obstetric, maternal perception, food consumption, dietary diversity, knowledge, attitude, and practices of pregnant women. Dietary diversity was assessed using the validated Food Frequency Questionnaire (FFQ), containing 27 commonly the list of food items consumed [33–37]. In addition, Mid-Upper Arm Circumference (MUAC) and maternal height measurements were taken. The questionnaire was initially prepared in English language and translated to the local language (Afan Oromo) by individuals with good command of both languages. It was also pre-tested on 10% of the sample in Kersa District before actual implementation. A 5 ml venous blood was aseptically drawn from the antecubital veins and aliquoted into plain test tubes without anticoagulants. The blood samples were centrifuged, followed by separation of serum, stored frozen at -80 °C, and analyzed at the national chemistry laboratory in Ethiopian Public Health Institute (EPHI). We measured SF and serum high-sensitive C-reactive protein (hsCRP). SF was analyzed on a fully automated Cobas e411 (German, Japan Cobas 4000 analyzer series) immunoassay analyzer by the electro-chemiluminescence (ECL) method using commercial kits supplied by Roche Company, Germany at National Clinical Chemistry Reference Laboratory, EPHI. Whereas, highly sensitive C-protein reactive (hsCRP) was analyzed by Roche/Hitachi Cobas 6000 (c501): (German, Japan Cobas 6000 series of Roche) fully automated clinical chemistry analyzer [38]. The tests were performed by trained and experienced medical laboratory technologists. Two levels of quality control (QC) samples were performed at least once every 24 h when the test is in use, once per reagent kit, and following each calibration to evaluate the functionality of the instrument and reagent, and the results of QC were evaluated using the Levey–Jennings chart (Wesgard rules). The calibration method has been standardized against the WHO International Standard NIBSC code: 03/178, 1st International Standard (IS) NIBSC (National Institute for Biological Standards and Control) "Reagent for Ferritin (human liver)" 80/602, and Reference preparation of the IRMM (Institute for Reference Materials and Measurements) BCR470/CRM470 (RPPHS-Reference Preparation for Proteins in Human Serum) for serum ferritin and serum hsCRP respectively. Calibration was performed as per the standard operating procedures (SOPs).The high ferritin cut-off point (SF  30 μg/L [39]. Serum CRP levels higher than 5 mg/L were termed as high CRP [33]. Anemia was defined as a Hb level of < 11.0 g/dl during the first or third trimester or < 10.5 g/dl during the second trimester [39]. Hemoglobin concentration was measured at each study site by well-trained medical technologists from capillary blood using a portable HemoCue Hb 301®, which is a gold standard for fieldwork. Hemoglobin values were adjusted for altitude as per the Center for Disease Prevention and Control (CDC) recommendation [40]. The significance of babies was computed to the nearest 100 g using calibrated Docbel BRAUNH scale). A LBW was defined as a live birth baby born with a birth weight of < 2500 g, and control was defined as a live birth baby born with a birth weight of ≥ 2500 g [41]. To estimate the economic level of families, a wealth index was employed. The wealth dispersion was generated by applying principal component analysis (PCA). The index was calculated based on the ownership of latrine, agricultural land and size, selected household asset, a quantity of livestock, and source of water for drinking containing 41 household variables. As described in the previous paper [31] nutritional knowledge and attitude towards consumption of an iron-rich diet were evaluated with questions using the Likert scale using PCA and the factor scores were totaled and classified into terciles. Women's autonomy was evaluated by seven validated questions which were adopted from the Ethiopian demographic health survey [12]. For each question, the response was coded as "one" when the decision is made by the woman alone or jointly with her husband, or "zero" otherwise. The detailed methods of data quality assurances used are described in previous papers (3,321), in the baseline survey. Quality assurance during laboratory analysis was monitored in the National Reference Laboratory for Clinical Chemistry at the Ethiopian Public Health Institute (EPHI). The EPHI laboratory is accredited by the Ethiopian National Accreditation Office (ENAO) to conduct tests under ISO 15189:2012, Quality and Competence Medical Laboratory Requirements (accreditation no. M 0025) by well-trained and experienced laboratory professionals and standard operating procedures were strictly followed for respective parameters. Data were double entered using EPiData version 3.1 software. Data were cleaned, coded, and checked for missing and outliers, for further analysis and exported to STATA version 14 (College Station, Texas 77,845 USA) statistical software. The outcome variable was dichotomized as LBW (= 1) if newborns were born with a birth weight of < 2500 g or normal (= 0), otherwise. Thus, the Poisson regression analysis model with a robust variance estimate was fitted to identify predictors of LBW. Bivariate analysis and multivariable analyses were done to identify the association between independent variables and LBW. The backward regression was fitted with selected socio-economic and fertility-related variables. The goodness of fit was checked by Hosmer–Lemeshow statistic and omnibus tests. Possible interactions between covariates were tested. Akaike's information criterion (AIC) and Bayesian information criterion (BIC) were used to test for model fitness. All variables with p < 0.25 in the binary analyses were included in the multivariable analysis after checking for multi-collinearity using variance inflation factors. Adjustments were done for independent variables (age, Mid-Upper Arm Circumference, maternal height, sex of neonates, hemoglobin level, C-reactive protein) for assessing iron status and birth weight. The direction and strength of statistical association were measured using adjusted prevalence ratio (aPR) along with their corresponding 95% confidence interval (CI). An adjusted prevalence ratio (aRR with a 95% confidence interval was reported to show an association at a p-value < 0.05. To estimate the economic level of families, a wealth index was employed. The wealth dispersion was generated by applying principal component analysis (PCA). The index was calculated based on the ownership of the latrine, agricultural land and size, selected household assets, the quantity of livestock, and source of water for drinking containing 41 household variables. As described in the previous paper [31], nutritional knowledge and attitude towards consumption of an iron-rich diet were evaluated with questions using the Likert scale using PCA, and the factor scores were totaled and classified into tertiles. Women's autonomy was evaluated by seven validated questions which were adopted from the Ethiopian demographic health survey [37]. For each question, the response was coded as "one" when a decision is made by the woman alone or jointly with her husband or "zero" otherwise. All methods of this study were carried out under the Declaration of Helsinki's ethical principle for medical research involving human subjects [12]. Ethical approval was obtained from the Institutional Health Research Ethics Review Committee (ref no: IHRERC/266/2020) College of Health and Medical Sciences, Haramaya University before the commencement of the study. Written informed consent was obtained from each participant or legally authorized representatives for those below 16 years of age. The interview was conducted in private and confidentiality of the participants' information was maintained.

The study titled “Prevalence, predictors of low birth weight and its association with maternal iron status using serum ferritin concentration in rural Eastern Ethiopia: a prospective cohort study” provides valuable insights into the factors influencing low birth weight (LBW) and the association with maternal iron status in a rural setting. The study highlights the importance of addressing maternal nutritional status and implementing interventions to improve access to maternal health.

Based on the findings of the study, the following recommendations can be developed into an innovation to improve access to maternal health:

1. Promoting diversified and iron-rich food consumption: Develop educational programs or mobile applications that provide information on the importance of a balanced diet during pregnancy and offer guidance on selecting and preparing iron-rich foods.

2. Enhancing universal access to iron and folic acid supplementation (IFAS): Implement mobile health (mHealth) interventions, such as text message reminders or mobile applications, to ensure pregnant women receive timely reminders and information about the importance of IFAS.

3. Targeted strategies for undernourished women: Implement community-based interventions that specifically target undernourished women, providing them with nutritional support, counseling, and access to nutritious food sources.

4. Comprehensive interventions based on a life-cycle approach: Develop integrated maternal and child health programs that provide continuous care and support throughout the pregnancy and postpartum periods, including antenatal care, nutrition counseling, breastfeeding support, and postnatal care services.

5. Strengthening health systems in rural areas: Focus on improving infrastructure, training healthcare providers, and ensuring the availability of essential maternal health services, including antenatal care, skilled birth attendance, and emergency obstetric care.

Implementing these recommendations as innovative interventions can contribute to improving access to maternal health and reducing the prevalence of low birth weight in rural areas. Collaboration with local communities, healthcare providers, and policymakers is crucial for successful implementation and sustainability.
AI Innovations Description
The study titled “Prevalence, predictors of low birth weight and its association with maternal iron status using serum ferritin concentration in rural Eastern Ethiopia: a prospective cohort study” provides valuable insights into the factors influencing low birth weight (LBW) and the association with maternal iron status in a rural setting. The study highlights the importance of addressing maternal nutritional status and implementing interventions to improve access to maternal health.

Based on the findings of the study, the following recommendations can be developed into an innovation to improve access to maternal health:

1. Promoting diversified and iron-rich food consumption: The study suggests that promoting the consumption of diversified and iron-rich foods can improve maternal nutritional status. An innovation could involve developing educational programs or mobile applications that provide information on the importance of a balanced diet during pregnancy and offer guidance on selecting and preparing iron-rich foods.

2. Enhancing universal access to iron and folic acid supplementation (IFAS): The study found that women who were supplemented with iron and folic acid during pregnancy had a decreased chance of delivering low birth weight babies. To improve access to IFAS, an innovation could involve implementing mobile health (mHealth) interventions, such as text message reminders or mobile applications, to ensure pregnant women receive timely reminders and information about the importance of IFAS.

3. Targeted strategies for undernourished women: The study identified maternal undernutrition as a predictor of low birth weight. Innovations could include community-based interventions that specifically target undernourished women, providing them with nutritional support, counseling, and access to nutritious food sources. This could be achieved through partnerships with local community health workers and organizations.

4. Comprehensive interventions based on a life-cycle approach: The study suggests that intervention strategies should be comprehensive and address vulnerable periods for women during pregnancy and their neonates. An innovation could involve developing integrated maternal and child health programs that provide continuous care and support throughout the pregnancy and postpartum periods. This could include antenatal care, nutrition counseling, breastfeeding support, and postnatal care services.

5. Strengthening health systems in rural areas: The study was conducted in a predominantly rural setting, highlighting the need to strengthen health systems in these areas. Innovations could focus on improving infrastructure, training healthcare providers, and ensuring the availability of essential maternal health services, including antenatal care, skilled birth attendance, and emergency obstetric care.

Implementing these recommendations as innovative interventions can contribute to improving access to maternal health and reducing the prevalence of low birth weight in rural areas. It is important to collaborate with local communities, healthcare providers, and policymakers to ensure the successful implementation and sustainability of these interventions.
AI Innovations Methodology
The methodology used in the study titled “Prevalence, predictors of low birth weight and its association with maternal iron status using serum ferritin concentration in rural Eastern Ethiopia: a prospective cohort study” involved a community-based prospective cohort study design. The study was conducted in the Haramaya district, eastern Ethiopia, and included a total of 427 eligible pregnant women who were followed until birth, with 412 women included in the final analysis.

Iron status was determined using serum ferritin (SF) concentration from venous blood collected from the pregnant women during their second or third trimester. Iron deficiency (ID) and iron deficiency anemia (IDA) were classified based on SF levels. Birth weight was measured within 72 hours of birth, and a birth weight of less than 2500g was considered low birth weight (LBW).

The study used a Poisson regression model with robust variance estimation to investigate the factors associated with LBW and the association between maternal iron status and LBW. Adjusted prevalence ratios with 95% confidence intervals were reported to show the associations.

Data collection involved face-to-face interviews, anthropometric measurements, and collection of blood samples for hematology and biochemical analysis. Dietary practices, nutritional knowledge, and attitudes were assessed using validated questionnaires. The study also collected data on socio-economic characteristics, obstetric history, and other pregnancy-related factors.

Quality assurance measures were implemented during laboratory analysis, and data were double-entered and cleaned before analysis. Statistical analysis was conducted using STATA software, and adjustments were made for relevant confounding variables.

The study obtained ethical approval from the Institutional Health Research Ethics Review Committee, and written informed consent was obtained from each participant.

The findings of the study were published in BMC Nutrition, Volume 8, No. 1, in 2022.

Please note that the above description is a summary of the methodology used in the study. For a more detailed understanding, it is recommended to refer to the original publication.

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