Skip to main content

Determinants of neural tube defects among women who gave birth in hospitals in Eastern Ethiopia: evidence from a matched case control study

Abstract

Introduction

Neural tube defects (NTDs) are severe birth defects caused by nutritional, genetic or environmental factors. Because NTDs continue to have a significant health and economic impact on children and community at large, it is crucial to investigate potential risk factors in order to develop novel approaches to NTDs prevention. Determinants for the development of NTDs differ by country, region as well as within the country. The objective of this study was to identify the determinants of NTDs among newborns delivered in three hospitals found in eastern Ethiopia.

Methods

A hospital-based matched case-control study was conducted among 138 cases and 138 control women who delivered in three teaching hospitals in Eastern Ethiopia in 2021. Data were collected using a structured and pre-tested interviewer-administered questionnaire. Cases were mothers who delivered a neonate with any type of NTDs regardless of gestational age or fetal viability, whereas controls were mothers who delivered an apparently healthy newborn. Chi-square was used to assess the significant difference between the two groups. Conditional logistic regression model was used to generate adjusted odds ratio with its corresponding 95% confidence intervals and compare the two groups.

Results

Anencephaly (51.4%) and spinal bifida (34.1%) were the most frequently observed NTDs. None of study participants took preconception folic acid supplementation. Being a non-formal mothers (AOR = 0.34, 95% CI: 0.12–0.92, P = 0.034), rural residence, (AOR = 3.4, 95% CI: 1.18–9.78, P = 0.023), history of spontaneous abortion (AOR = 2.95, 95% CI: 1.15–7.55, P = 0.023), having severe anemia (AOR = 3.4, 95% CI: 1.17–9.87, P = 0.024), history of fever or cold (AOR = 2.75; 95% CI: 1.05–7.15, P = 0.038), and an exposure to various agro-chemicals (AOR = 3.39, 95% CI: 1.11–10.3, P = 0.032) were independent determinants of NTDs.

Conclusion and Recommendation

In this study, NTDs were associated to several determinant factors in the area, including residential area, history of spontaneous abortion, severe anemia, fever/cold, antibiotic use before or during early pregnancy, and exposure to agrochemicals. Addressing the identified determinants is critical in averting the incidence of NTDs in the study area. Moreover, more research is needed to investigate women’s dietary practices as well as the practice of preconception folic acid supplementation for pregnant women in Ethiopia’s current health care system.

Peer Review reports

Introduction

Neural tube defects (NTDs) are congenital malformations that occur in the development of the central nervous system during embryonic period [1]. Neural tube formation is central issue to developmental biology with the closure being dependent on the methionine cycle and folate cycle [2]. NTDs can occur in the cranial region (anencephaly, encephalocele), spinal region (spina bifida), or in combination (craniorachisis or complex phenotypes) [3, 4]. NTDs are among the second and most serious congenital anomalies that occur because of incomplete closure of the brain or spinal cord between 12 and 28 days of pregnancy. They are associated with a high rate of neonatal death, morbidity, psychological, emotional, economical problem as well as lifelong disability in survivors and their families [5, 6].

A recent meta-analysis estimated that 260,100 NTDs affected birth outcomes worldwide [7]. Each year, it is estimated that nearly 200,000 neonates are born with NTDs in low and middle-income countries (LMICs) [8]. Another recent meta-analysis research found that, the pooled birth prevalence of NTDs in eastern Africa was 33 per 10,000 births, with Ethiopia having the highest (60 per 10,000 births) and Malawi having the lowest (5 per 10,000 births) [9]. In Ethiopia, the Tigray region had the highest incidence rate of NTDs, accounting for 131 per 10,000 [10] and the eastern part of Ethiopia has the second highest incidence rate (107.5 per 10,000), with the trend increasing alarmingly in recent years [11]. Any woman of childbearing age is at risk of having an NTD-affected pregnancy and it is impossible to determine which women will have NTD-affected pregnancy [12]. Even though the etiology of most NTDs remains undetermined, land mark large -scale randomized randomized clinical trials proofed that genetic, environmental and nutritional risk factors are considered to contribute to their development [13, 14], and among these dietary risk factors play a major role [15]. Mishra, P.R. et al., (2020) reported that 70–95% NTDs are linked to genetics and maternal vitamin intake (MVI) [14]. Over the past 35 years researchers have identified that deficiency of folates at the cellular level may be responsible for NTDs due to disturbed bioavailability of folates, and other nutritional factors, such as trace elements [16]. An increasing body of evidences showed that women who had a previous history of abortions are more likely to develop NTDs [17,18,19,20,21], maternal diabetes [22], and maternal “flu” in the first trimester [23, 24], certain parental occupations [25, 26], are also risk factors of developing NTDs. Omer et al., 2016, observed that the intake of folic acid by the mothers usually starts after conception due to a lack of awareness of its importance is a risk factors for the development of NTDs [27]. Another risk factors for neural tube defects are maternal exposure to valproic acid [28,29,30]. Maternal hyperthermia in early pregnancy following episodes of maternal fever or heat exposure is also a risk factor for NTDs [31,32,33,34,35,36]. Different experimental studies showed that hyperglycemia lies within the pathogenic pathway of NTDs, and increasing dietary quality reduced risks of NTDs [37,38,39,40,41,42,43]. Exposures to organic solvents; agricultural chemicals, including pesticides; water nitrates; heavy metals such as mercury; ionizing radiation; and water disinfection by-products [44,45,46,47,48,49,50,51] are independent factors for incidence of NTDs. Recently, there is an increase in understanding of risk factors for development of NTDs, and preventative and treatment approaches have witnessed great advances throughout the years. Even though, these risk factors have been identified in Ethiopia, there are not well established the risk factors of NTDs in the real context of the whole country including eastern Ethiopia, which has the second highest burden with an increasing trend in a recent year. Thus, the current study aimed to identify the determinants of NTDs among women who delivered in three hospitals in eastern Ethiopia.

Materials and methods

Study setting

The study was conducted in Dilchora Referral Hospital, Hiwot Fana Specialized Teaching Hospital, and Adama Hospital Medical College, found in the eastern part of Ethiopia. Dilchora Referral Hospital is found in Dire Dawa city administration, which is 515 km away from Addis Ababa, the capital of Ethiopia, and serves approximately five million populations from neighboring regions, including Oromia and Somali regions. Hiwot Fana Specialized Teaching Hospital is found in the Harari Region, which is 526 km away from Addis Ababa, and delivers services to the entire community of eastern Ethiopia. In addition, the hospitals also serve as teaching centers for health and medical science students. Adama Hospital Medical College is found in the Oromia Region. It serves as a referral center for more than 6 million people from different regions neighboring zones and regions, including Afar, Amhara, and Somali.

Study design

A matched case-control design was used to address the objective of this study. Cases and controls were enrolled in the obstetrics/gynecology ward and Neonate Infant and Child Unit (NICU) from March to October 2021.

Study participants

All newborns in the selected hospitals who fulfilled the case, and control criteria were included. Newborns whose mothers were very sick, emotionally upset during data collection, or died after delivery were excluded from this study.

Sample size determination and procedure

The sample size was calculated assuming an equal number of cases and controls (1:1), odds ratio of 3.0, power of 80%, 95% confidence level of and non-response rate of 5%. The final sample size was 276 (138 cases and 138 controls). Cases were ascertained prospectively until the calculated sample size was reached. Control neonates were randomly selected from the same hospital. Cases and apparently healthy control neonates (1:1) were matched for a neonate’s sex, and maternal age.

Operational definition

Neural tube defects (NTDs)

is defined as any newborn baby or terminated with anencephaly or spinal bifida, or encephalocele, or meningocele or mylemeningocele.

Cases

Mothers, who gave birth to a neonate with any type of NTDs, irrespective of gestational age and fetal survivorship at birth.

Control

Mothers who gave birth to a neonate without NTDs who are apparently healthy.

Data collection procedure and tool

The data from the cases were collected after the mothers delivered a neonate or had terminated her pregnancy due to NTDs in the labor, gynecology ward, and NICU. Control mothers were interviewed randomly within 48 hrs of birth without discrimination regarding their ethnicity, religion, or marital status. A pretested structured questionnaire prepared in the local language and translated to English by an independent translator to check its consistency. Eight trained midwives who worked in the gynecology, obstetrics ward and neonate,infant, and child care unit (NICU) were asked participated mothers about their socio-demographic and medical history data, including, reproductive history, ANC follow-up, obstruction, maternal illness, drug history, preconceptional folic acid, environmental factors, and neonatal status.

Data quality control

The questionnaire was pre-tested before the actual data were collected and the necessary adjustments were made based on the results of the preliminary tests. Before starting the actual data collection, two days extensive training was given for data collectors and supervisors. Data were collected using the KoBo Tool application via mobile device. The data were checked before leaving the data collection site for immediate action.

Data processing and analyses

Data were cleaned and analyzed using SPSS for Windows 25. Descriptive analysis was presented using means, frequencies and percentages. To assess the significant difference between the two groups, Pearson and Fisher exact chi-square test was used for comparing catagorical variables. For continous variables, either a paired t test or Wilcoxon Signed rank test was used. All assumptions were checked. A multivariable conditional logistic regression model was used to identify the independent determinants of NTDs. The measure of association of each variable was determined using a parameter of adjusted odds ratio with 95% confidence intervals. Statistical significance declared at P-value < 0.05. A standard error of > 2.0 was used to test for multicollinearity. Model’s fitness was assessed using the Hosmer and Lemeshow tests with P > 0.05 used as fit.

Results

Of 138 cases, 30(21.7%), 22(15.9%), and 86(62.3%) were from Dil Chora teaching hospital, Hiwot Fana specialization teaching hospital, and Adama medical college hospital, respectively. The overall Mean ± (S.D.) age of mothers was 26.2 ± 5.9 years. Rural resident women were found to be more prevalent than urban resident women (53.6% vs. 46.4%) (P = 0.023). Besides, maternal age 18–24 years was lower among cases (26.8%) as compared to controls (41.3%) (P = 0.036). Regarding the family size, most of the mothers who were part of households with 1–5 people were higher among cases (79.7%) as compared to controls (64.5%) (P = 0.005) (Table 1).

Table 1 Demographic data of the cases and controls in Eastern Ethiopia

Among cases, 97 (70.3%) of mothers were hade 1–3 years gap between the previous pregnancy. The proportion of primigravida women in the cases was higher than in the control group (18.1% vs. 8%) and the difference was statistically significant (p = 0.012) (Table 2).

Table 2 Obstetric and health characteristics of case and controls in Eastern Ethiopia

Type of NTDs

Of the total NTDs, 51.4% and 34.1% were anencephaly and spinal Bifida, respectively (Fig. 1).

Fig. 1
figure 1

Type of NTDs among deliveries in hospital in Eastern Ethiopia

Determinants of NTDs

After controlling for confounding variables, multivariate conditional logistic regression analysis identified that mothers who lived in rural areas, had formal education, had a history of elective or terminated abortions, suffered from severe anemia and fever or cold in pre or early pregnancy, and were exposed to various agro-chemicals were significantly associated with the development of NTDs (Table 3).

Table 3 Multivariable analysis for the determinants of NTDs among women who gave birth in hospitals in Eastern Ethiopia

Mothers living in rural areas were 3.4 times higher odds of developing NTDs compared to mothers living in urban areas (AOR = 3.4, 95% CI: 1.18–9.78, P = 0.023). Mothers who had history of elective termination were nearly three times more likely to develop NTDs (AOR = 2.95, 95% CI: 1.15–7.55, P = 0.023) than those who had no history of elective termination.

The risk of having neonates with NTDs was 3.4 higher (AOR = 3.4, 95% CI: 1.17–9.87, P = 0.024) in mothers who suffered from severe anemia in pre or early pregnancy compared with their counterparts. Mothers who had a history of fever in pre or early pregnancy were 2.75 times more likely to have a neonate with NTDs (AOR = 2.75; 95% CI: 1.05–7.15, P = 0.038) than mothers who had no history of fever in pre or early pregnancy.

The risk of having neonates with NTDs was nearly 3.4-fold higher (AOR = 3.39, 95% CI: 1.11–10.3, P = 0.032) in mothers exposed to various agrochemicals compared with their counterparts. The odds of having NTD was 66% lower among mothers who had attended education from grade 1–12 (AOR = 0.34, 95% CI: 0.12–0.92, P = 0.034) compared to illiterate ones.

Discussion

The objective of this case-control study was to identify the determinants of NTDs. In this study, women who resided in rural areas had higher odds of newborns with NTDs compared to their urban counterparts. This finding is supported by a study conducted in Tigray and Amhara Regional State of Ethiopia [20, 49]. This disparity in residence area could be attributed to differences in education level, health awareness, workload, and stress, as well as economic and cultural factors.

We also found that women with non-formal education had greater odds of newborns with NTDs compared to counterparts. This finding is in line with a study conducted in other studies [20, 52]. Lunau et al., (2015) also reported that there was a significant relationship between women who had lower education and exposed to higher levels of work stress [53]. Experiencing stress before or after early pregnancy could be a predictor for development of NTDs. It was hypothesized that maternal stress could increase the circulating adrenocorticotropin and cortisol levels and affects the fetus’s neural development [54]. This hypothesis was also supported by a systematic review and meta-analysis conducted by Jia et al. (2019) and Suarez and Lucina et al. (2003) [55, 56].

Another potential mechanism associated with the damaging effects of stress may be altered micronutrient concentrations via its influence on nutrient stores in the body [57], including folic acid and other nutrients that are responsible for development of NTDs.

Maternal history of elective or termination or spontaneous abortion was significantly associated with having NTDs affected pregnancy. Our study agreed with other studies [17, 18, 58]. The epidemiologic study showed that a low serum or plasma folate level was associated with an increased risk of early spontaneous abortion [59,60,61], which could be a level of maternal serum folic acid responsible for spontaneous abortions and development of NTDs. Moreover, maternal serum and erythrocyte folate concentration decreases from the twenty weeks of pregnancy onwards and remain low for a long time after delivery [62,63,64], which could the reason for developing NTDs in the next pregnancy particularly for women with short inter-pregnancy intervals. Hence, periconceptional folic acid supplements can effectively prevent not only the occurrence of NTDs and but also spontaneous abortion during early pregnancy.

However, Golalipour et al. (2014), De marco et al. (2014) and Todoroff et al., (2000) reported that there was no association between prior spontaneous abortion and development of NTDs [65,66,67]. This discordant finding between studies could be attributed to the methodological approaches: used.

Mothers with suffered from chronic anemia was also significantly associated with NTDs in this study. The possible mechanism by which chronic anemia before or during early pregnancy could increase NTDs risk in neonate may be through elevated maternal serum homocysteine and the disturbance of methylation process. Disturbance of maternal fetal serum homocysteine and methylation may be responsible for the development of NTDs in the fetus. Various dietary factors, such as folic acid and vitamin B12 influence serum homocysteine levels and play a role in the methylation pathway [68,69,70,71,72,73]. Ferritin can also modulate folate availability via the cellular one-carbon pathway, implying that low iron status can alter folate utilization even when adequate folate intake and extracellular folate concentrations are present [74, 75]. Serum homocysteine levels and methylation seem to be positively correlated with folate deficiency [76]. Iron deficiency is the most common cause of anemia [77,78,79], which could possibly play a role in development of NTDs in humans. However, the need for more evidence to substantiate this pathway was suggested [80] and showed no significant difference in maternal ferritin or hemoglobin concentrations between NTD-affected and non-affected pregnancies [81]. To know more, further investigation of the mechanism that connects anemia and NTDs will be needed.

We also observed a significant association between fever/cold before or early pregnancy and developing NTDs, which is consistent with the report of studies conducted in various settings around the world [82,83,84]. A possible physiological mechanism for the association between fever/hyperthermia and the development of NTDs may be that fever is a marker of another underlying process. Specific infections or immune disturbances contribute to increased risk for NTDs. Fever is also associated with increased levels of pro-inflammatory cytokines and other molecules [85] that cross the placenta to affect fetal brain development via mechanisms other than hyperthermia.

This study also found that the use of antibiotics before or early pregnancy was associated with NTDs. The possible reason is that antibiotic medications may have antifolate effects [86]. Some specific forms of antibiotics such as sulfonamides are risk for fetus developing NTDs [87, 88]. However, our finding was not in agreement with a study conducted by Wang M et al., (2014) [89]. Nevertheless, there is no clear mechanism that antibiotics are risk factors for the development of NTDs.

It was also observed that maternal exposure to agrochemicals before or during the early pregnancy period was associated with increased the odds of NTDs in the offspring, which is supported by other studies [17, 50, 90]. The possible explanation could be that agricultural chemicals are lipophilic and alter cell proliferation and differentiation during neurulation [91], averted neurological development and impairment. Agricultural pesticides enter the food chain through animal food sources and crops, including run-off in water bodies [92]. Agricultural chemicals are used more frequently as part of livelihood activities in the study area, implying the need for more research before dismissing this potentially massive exposure. In contrast, a study conducted from a similar case control study in Tigray, Ethiopia, found no significant association between agro-chemicals and NTDs [49]. The strength of this investigation was that both cases and controls were drawn from similar settings in a 1:1 ratio to avoid selection bias. Furthermore, a strong case ascertainment was used to identify NTD cases. An effort was also made to investigate several factors that could be potential determinants, which would contribute to a clear understanding of the risk factors for development of NTDs.

Despite all its significant findings this study has some limitations. The first limitation was the exposure status of study participants was determined, retrospectively, which could be influenced by recall bias. The second limitation of this study is also that biomarkers and genetic polymorphism were not addressed. Moreover, due to the nature of facility-based research, generalization to the general population is difficult. The third limitation was that there was insufficient evidence to support our claim that fever/cold, anemia, and elective termination were associated with the development of NTDs. Moreover, due to the presence of very small numbers in some categories of predictive variables, the model estimates may be unstable which should be interpreted carefully.

Conclusion

The study found that anencephaly and spinal Bifida are the two most common types of NTDs in the region. The results indicated that the development of NTDs was associated with residence area, history of abortion, history of severe anemia, history of fever, any antibiotics used before or during early pregnancy, and exposure to agrochemicals. Though we did find that dietary factors were a leading causes for developing a NTDs in the study area. As a result, our findings suggest that mulitisectoral efforts should be made to intervene the dietary factors and to control environmental factors such as agrochemicals that contaminate food and water sources. These should be considered as a foundation for public health promotion in the prevention of NTDs. In addition, behavior change interventions based on various strategies, on preconception folic acid or iron-folic acid supplementation should be implemented at the community, school, and health facility levels should be implemented to curb the emerging burden of NTDs in Ethiopia. In general, nutrition intervention including, mandatory iron and folic acid fortification using common vehicles like flour, salt and oil or practicing good dietary iron and folate food sources or preconception iron-folic acid supplementation is required. Furthermore, engage a global network of partners who are experts in conducting NTD prevention programs to track, monitor blood folate concentrations, and develop intervention programs to increase the amount of iron and folic acid consumed by women of reproductive age. Moreover, a multi-sectoral effort aimed at reducing the risk of NTDs is needed in the study area is needed. Dietary practice among cohort women who gave birth with and with out NTDs should be studied in the study area and at the national level.

Data Availability

All data generated or analyzed during this study are included in this published article.

Abbreviations

AOR:

Adjusted matched odds ratio

ANC:

Antenatal Care

CA:

Congenital Anomalies

CI:

Confidence Interval

FSI:

Folate Supplementation Intake

IFA:

Iron- Folic Acid

MVI:

Maternal Vitamin Intake

NICU:

Neonate and Infant care Unit

NTDs:

Neural Tube Defects

OR:

Odds ratios

SDG:

Sustainable Development Goal

References

  1. Yacob A, Carr CJ, Foote J, Scullen T, Werner C, Mathkour M, et al. The global burden of neural tube defects and disparities in neurosurgical care. World Neurosurg. 2021;149:e803–e20.

    Article  PubMed  Google Scholar 

  2. Leung K-Y, Pai YJ, Chen Q, Santos C, Calvani E, Sudiwala S, et al. Partitioning of one-carbon units in folate and methionine metabolism is essential for neural tube closure. Cell Rep. 2017;21(7):1795–808.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Copp AJ, Bernfield M. Etiology and pathogenesis of human neural tube defects: insights from mouse models. Curr Opin Pediatr. 1994;6(6):624–31.

    Article  CAS  PubMed  Google Scholar 

  4. Wallingford JB, Niswander LA, Shaw GM, Finnell RH. The continuing challenge of understanding, preventing, and treating neural tube defects. Science. 2013;339(6123):1222002.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Avagliano L, Massa V, George TM, Qureshy S, Bulfamante GP, Finnell RH. Overview on neural tube defects: from development to physical characteristics. Birth Defects Research. 2019;111(19):1455–67.

    Article  CAS  PubMed  Google Scholar 

  6. ICBDSR W. Birth defects surveillance a manual for programme managers. Geneva: World Health Organization; 2014.

    Google Scholar 

  7. Blencowe H, Kancherla V, Moorthie S, Darlison MW, Modell B. Estimates of global and regional prevalence of neural tube defects for 2015: a systematic analysis. Ann N Y Acad Sci. 2018;1414(1):31–46.

    Article  PubMed  Google Scholar 

  8. Lo A, Polšek D, Sidhu S. Estimating the burden of neural tube defects in low–and middle–income countries. J Global Health. 2014;4(1).

  9. Ssentongo P, Heilbrunn ES, Ssentongo AE, Ssenyonga LV, Lekoubou A. Birth prevalence of neural tube defects in eastern Africa: a systematic review and meta-analysis. BMC Neurol. 2022;22(1):1–11.

    Article  Google Scholar 

  10. Berihu BA, Welderufael AL, Berhe Y, Magana T, Mulugeta A, Asfaw S, et al. High burden of neural tube defects in Tigray, Northern Ethiopia: hospital-based study. PLoS ONE. 2018;13(11):e0206212.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Berhane A, Belachew T. Trend and burden of neural tube defects among cohort of pregnant women in Ethiopia: where are we in the prevention and what is the way forward? PLoS ONE. 2022;17(2):e0264005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Wolff T, Witkop C, Miller T, Syed S. Preventive Services Task Force. Folic acid supplementation for the prevention of neural tube defects: an update of the evidence for the US Preventive Services Task Force. Ann Intern Med. 2009;150:632–9.

    Article  PubMed  Google Scholar 

  13. Wilde JJ, Petersen JR, Niswander L. Genetic, epigenetic, and environmental contributions to neural tube closure. Annu Rev Genet. 2014;48:583.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Mishra PR, Barik M, Mahapatra A. Molecular genetics involved in neural tube defects: recent advances and future prospective for molecular medicine. Neurol India. 2020;68(5):1144.

    PubMed  Google Scholar 

  15. Berhane A, Fikadu T, Belachew T. Dietary practice among cohort pregnant women who gave birth to neonates with and without neural tube defect: a comparative cross-sectional study. J Nutritional Sci. 2022;11:e24.

    Article  Google Scholar 

  16. Copp AJ, Stanier P, Greene ND. Neural tube defects: recent advances, unsolved questions, and controversies. Lancet Neurol. 2013;12(8):799–810.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Gashaw A, Shine S, Yimer O, Wodaje M. Risk factors associated to neural tube defects among mothers who gave birth in North Shoa Zone Hospitals, Amhara Region, Ethiopia 2020: case control study. PLoS ONE. 2021;16(4):e0250719.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Pei L, Wu J, Li J, Mi X, Zhang X, Li Z, et al. Effect of periconceptional folic acid supplementation on the risk of neural tube defects associated with a previous spontaneous abortion or maternal first-trimester Fever. Hum Reprod. 2019;34(8):1587–94.

    Article  CAS  PubMed  Google Scholar 

  19. Tesfay FA, Aga FB, Teshome GS. Determinants of neural tube defect among children at Zewditu memorial hospital, addis ababa, Ethiopia a case control study. Int J Afr Nurs Sci. 2021;15:100318.

    Google Scholar 

  20. Tadesse AW, Kassa AM, Aychiluhm SB. Determinants of neural tube Defects among newborns in AMHARA Region, ETHIOPIA: A case-control study. International Journal of Pediatrics. 2020;2020.

  21. Gedefaw A, Teklu S, Tadesse BT. Magnitude of neural tube defects and associated risk factors at three teaching hospitals in Addis Ababa, Ethiopia. BioMed Research International. 2018;2018.

  22. Kappen C, Kruger C, MacGowan J, Salbaum JM. Maternal diet modulates the risk for neural tube defects in a mouse model of diabetic pregnancy. Reprod Toxicol. 2011;31(1):41–9.

    Article  CAS  PubMed  Google Scholar 

  23. Luteijn J, Brown M, Dolk H. Influenza and congenital anomalies: a systematic review and meta-analysis. Hum Reprod. 2013;29(4):809–23.

    Article  PubMed  Google Scholar 

  24. Oster ME, Riehle-Colarusso T, Alverson CJ, Correa A. Associations between maternal Fever and Influenza and congenital heart defects. J Pediatr. 2011;158(6):990–5.

    Article  PubMed  Google Scholar 

  25. Podgórski R, Stompor M, Kubrak T, Podgórska D. Neural tube defects: risk factors and prevention. 2017.

  26. Fathe KR. Dietary and genetic influences on neural tube defects 2014.

  27. Omer IM, Abdullah OM, Mohammed IN, Abbasher LA. Prevalence of neural tube defects Khartoum, Sudan August 2014–July 2015. BMC Res Notes. 2016;9(1):495.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Agopian A, Tinker SC, Lupo PJ, Canfield MA, Mitchell LE, Study NBDP. Proportion of neural tube defects attributable to known risk factors. Birth Defects Research Part A: Clinical and Molecular Teratology. 2013;97(1):42–6.

    Article  CAS  PubMed  Google Scholar 

  29. Tung EW, Winn LM. Valproic acid increases formation of reactive oxygen species and induces apoptosis in postimplantation embryos: a role for oxidative stress in valproic acid-induced neural tube defects. Mol Pharmacol. 2011;80(6):979–87.

    Article  CAS  PubMed  Google Scholar 

  30. Yerby MS. Management issues for women with Epilepsy: neural tube defects and folic acid supplementation. Neurology. 2003;61(6 suppl 2):23–S6.

    Google Scholar 

  31. Kerr SM, Parker SE, Mitchell AA, Tinker SC, Werler MM. Periconceptional maternal Fever, folic acid intake, and the risk for neural tube defects. Ann Epidemiol. 2017;27(12):777–82. e1.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Pei L, Zhu H, Ye R, Wu J, Liu J, Ren A, et al. Interaction between the SLC19A1 gene and maternal first trimester Fever on offspring neural tube defects. Birth Defects Research Part A: Clinical and Molecular Teratology. 2015;103(1):3–11.

    Article  CAS  PubMed  Google Scholar 

  33. Suarez L, Felkner M, Hendricks K. The effect of Fever, febrile illnesses, and heat exposures on the risk of neural tube defects in a Texas-Mexico border population. Birth Defects Research Part A: Clinical and Molecular Teratology. 2004;70(10):815–9.

    Article  CAS  PubMed  Google Scholar 

  34. Graham JM Jr, Ferm VH. Heat-and alcohol-induced neural tube defects: interactions with folate in a golden hamster model. Pediatr Res. 1985;19(2):247.

    Article  CAS  PubMed  Google Scholar 

  35. Lundberg YW, Wing MJ, Xiong W, Zhao J, Finnell RH. Genetic dissection of hyperthermia-induced neural tube defects in mice. Birth Defects Research Part A: Clinical and Molecular Teratology. 2003;67(6):409–13.

    Article  CAS  PubMed  Google Scholar 

  36. Li Z, Ren A, Liu J, Pei L, Zhang L, Guo Z, et al. Maternal Flu or Fever, medication use, and neural tube defects: a population-based case‐control study in Northern China. Birth Defects Research Part A: Clinical and Molecular Teratology. 2007;79(4):295–300.

    Article  CAS  PubMed  Google Scholar 

  37. Scott JA, Braskie MN, Tosun D, Thompson PM, Weiner M, DeCarli C, et al. Cerebral amyloid and Hypertension are independently associated with white matter lesions in elderly. Front Aging Neurosci. 2015;7:221.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Yazdy MM, Liu S, Mitchell AA, Werler MM. Maternal dietary glycemic intake and the risk of neural tube defects. Am J Epidemiol. 2009;171(4):407–14.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Loeken MR, editor. Current perspectives on the causes of neural tube defects resulting from diabetic pregnancy. American Journal of Medical Genetics Part C: Seminars in Medical Genetics; 2005: Wiley Online Library.

  40. Vena F, D’Ambrosio V, Paladini V, Saluzzi E, Di Mascio D, Boccherini C et al. Risk of neural tube defects according to maternal body mass index: a systematic review and meta-analysis. J Maternal-Fetal Neonatal Med. 2021:1–10.

  41. Bitew ZW, Worku T, Alebel A, Alemu A. Magnitude and associated factors of neural tube defects in Ethiopia: a systematic review and meta-analysis. Global Pediatr Health. 2020;7:2333794X20939423.

    Article  Google Scholar 

  42. Wahbeh F, Manyama M. The role of vitamin B12 and genetic risk factors in the etiology of neural tube defects: a systematic review. Int J Dev Neurosci. 2021;81(5):386–406.

    Article  CAS  PubMed  Google Scholar 

  43. Rosenbluh O, Walfisch A. Birth defects associated with obesity. Clin Exp Obstet Gynecol. 2021;48(3):472–7.

    Article  Google Scholar 

  44. Yang W, Carmichael SL, Roberts EM, Kegley SE, Padula AM, English PB, et al. Residential agricultural pesticide exposures and risk of neural tube defects and orofacial clefts among offspring in the San Joaquin Valley of California. Am J Epidemiol. 2014;179(6):740–8.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Rana M, Bisht SS, Rana AJ, Upadhyay J. Neural tube defects, its etiology: environmental exposures and genes, possible risk factors. J Pharm Sci Res. 2017;9(2):131.

    CAS  Google Scholar 

  46. Kalra S, Dewan P, Batra P, Sharma T, Tyagi V, Banerjee BD. Organochlorine pesticide exposure in mothers and neural tube defects in offsprings. Reprod Toxicol. 2016;66:56–60.

    Article  CAS  PubMed  Google Scholar 

  47. Suarez L, Felkner M, Brender JD, Canfield M, Zhu H, Hendricks KA. Neural tube defects on the Texas-Mexico border: what we’ve learned in the 20 years since the Brownsville cluster. Birth Defects Research Part A: Clinical and Molecular Teratology. 2012;94(11):882–92.

    Article  CAS  PubMed  Google Scholar 

  48. Blatter BM, van der Star M, Roeleveld N. Review of neural tube defects: risk factors in parental occupation and the environment. Environ Health Perspect. 1994;102(2):140–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Berihu BA, Welderufael AL, Berhe Y, Magana T, Mulugeta A, Asfaw S, et al. Maternal risk factors associated with neural tube defects in Tigray regional state of Ethiopia. Brain Develop. 2019;41(1):11–8.

    Article  Google Scholar 

  50. Rull RP, Ritz B, Shaw GM. Neural tube defects and maternal residential proximity to agricultural pesticide applications. Am J Epidemiol. 2006;163(8):743–53.

    Article  PubMed  Google Scholar 

  51. Finnell RH, Simoes Caiaffa F, Carvalho CD, Kim S, Lei Y, Steele J, Cao X, et al. Gene environment interactions in the etiology of neural tube defects. Front Genet. 2021;12:608.

    Article  Google Scholar 

  52. Li Z, Ren A, Zhang L, Guo Z, Li Z. A population-based case–control study of risk factors for neural tube defects in four high‐prevalence areas of Shanxi Province, China. Paediatr Perinat Epidemiol. 2006;20(1):43–53.

    Article  PubMed  Google Scholar 

  53. Lunau T, Siegrist J, Dragano N, Wahrendorf M. The association between education and work stress: does the policy context matter? PLoS ONE. 2015;10(3):e0121573.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Gitau R, Cameron A, Fisk NM, Glover V. Fetal exposure to maternal cortisol. The Lancet. 1998;352(9129):707–8.

    Article  CAS  Google Scholar 

  55. Suarez L, Cardarelli K, Hendricks K. Maternal stress, social support, and risk of neural tube defects among Mexican americans. Epidemiology. 2003;14(5):612–6.

    Article  PubMed  Google Scholar 

  56. Jia S, Wei X, Ma L, Wang Y, Gu H, Liu D, et al. Maternal, paternal, and neonatal risk factors for neural tube defects: a systematic review and meta-analysis. Int J Dev Neurosci. 2019;78:227–35.

    Article  PubMed  Google Scholar 

  57. Lopresti AL. The effects of psychological and environmental stress on micronutrient concentrations in the body: a review of the evidence. Adv Nutr. 2020;11(1):103–12.

    Article  PubMed  Google Scholar 

  58. Blanco-Muñoz J, Lacasaña M, Borja‐Aburto VH. Maternal miscarriage history and risk of anencephaly. Paediatr Perinat Epidemiol. 2006;20(3):210–8.

    Article  PubMed  Google Scholar 

  59. Nelen WL, Blom HJ, Steegers EA, den Heijer M, Thomas CM, Eskes TK. Homocysteine and folate levels as risk factors for recurrent early pregnancy loss. Obstet Gynecol. 2000;95(4):519–24.

    CAS  PubMed  Google Scholar 

  60. Navarrete-Muñoz EM, Valera-Gran D, de la Hera MG, Gimenez-Monzo D, Morales E, Julvez J, et al. Use of high doses of folic acid supplements in pregnant women in Spain: an INMA cohort study. BMJ open. 2015;5(11):e009202.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Gaskins AJ, Rich-Edwards JW, Hauser R, Williams PL, Gillman MW, Ginsburg ES, et al. Maternal prepregnancy folate intake and risk of spontaneous abortion and stillbirth. Obstet Gynecol. 2014;124(1):23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Zheng D, Li C, Wu T, Tang K. Factors associated with spontaneous abortion: a cross-sectional study of Chinese populations. Reproductive Health. 2017;14(1):1–9.

    Article  CAS  Google Scholar 

  63. Homeister B. Lathers. Management of spontaneous abortion(3).pdf>. 1962.

  64. Zetterberg H. Methylenetetrahydrofolate reductase and transcobalamin genetic polymorphisms in human spontaneous abortion: biological and clinical implications. Reproductive Biology and Endocrinology. 2004;2(1):1–8.

    Article  Google Scholar 

  65. De Marco P, Merello E, Calevo MG, Mascelli S, Pastorino D, Crocetti L, et al. Maternal periconceptional factors affect the risk of spina bifida-affected pregnancies: an Italian case–control study. Child’s Nerv Syst. 2011;27(7):1073–81.

    Article  Google Scholar 

  66. Todoroff K, Shaw GM. Prior spontaneous abortion, prior elective termination, interpregnancy interval, and risk of neural tube defects. Am J Epidemiol. 2000;151(5):505–11.

    Article  CAS  PubMed  Google Scholar 

  67. Golalipour MJ, Qorbani M, Mirfazeli A, Mobasheri E. Risk factors of neural tube defects in northern Iran. Iran Red Crescent Med J. 2014;16(6).

  68. Morris MS, Jacques PF, Rosenberg IH, Selhub J. Circulating unmetabolized folic acid and 5-methyltetrahydrofolate in relation to anemia, macrocytosis, and cognitive test performance in American seniors. Am J Clin Nutr. 2010;91(6):1733–44.

    Article  CAS  PubMed  Google Scholar 

  69. Selhub J, Morris MS, Jacques PF, Rosenberg IH. Folate-vitamin B-12 interaction in relation to cognitive impairment, anemia, and biochemical indicators of vitamin B-12 deficiency. Am J Clin Nutr. 2009;89(2):702S–6S.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Lanska DJ. Historical aspects of the major neurological vitamin deficiency disorders: the water-soluble B vitamins. Handb Clin Neurol. 2010;95:445–76.

    Article  PubMed  Google Scholar 

  71. Mobasheri E, Keshtkar A, Golalipour M-J. Maternal folate and vitamin B12 status and neural tube defects in Northern Iran: a case control study. Iran J Pediatr. 2010;20(2):167.

    PubMed  PubMed Central  Google Scholar 

  72. Mahmood L. The metabolic processes of folic acid and vitamin B12 deficiency. J Health Res Reviews. 2014;1(1):5.

    Article  Google Scholar 

  73. Smits LJ, Essed GG. Short interpregnancy intervals and unfavourable pregnancy outcome: role of folate depletion. The Lancet. 2001;358(9298):2074–7.

    Article  CAS  Google Scholar 

  74. Oppenheim EW, Adelman C, Liu X, Stover PJ. Heavy chain ferritin enhances serine hydroxymethyltransferase expression and de novo thymidine biosynthesis. J Biol Chem. 2001;276(23):19855–61.

    Article  CAS  PubMed  Google Scholar 

  75. Valberg L. Plasma ferritin concentrations: their clinical significance and relevance to patient care. Can Med Assoc J. 1980;122(11):1240.

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Felkner M, Suarez L, Canfield MA, Brender JD, Sun Q. Maternal serum homocysteine and risk for neural tube defects in a Texas-Mexico border population. Birth Defects Research Part A: Clinical and Molecular Teratology. 2009;85(6):574–81.

    Article  CAS  PubMed  Google Scholar 

  77. Haider BA, Olofin I, Wang M, Spiegelman D, Ezzati M, Fawzi WW. Anaemia, prenatal iron use, and risk of adverse pregnancy outcomes: systematic review and meta-analysis. BMJ. 2013;346.

  78. Iannotti LLOBK, Chang SC, Mancini J, Schulman-Nathanson M, Liu S, Zena L, Harris, Frank R, Witter. Iron Deficiency anemia and depleted body iron reserves are prevalent among pregnant African-American adolescents. 2005.

  79. Pathak P, Kapil U, Yajnik C, Kapoor S, Dwivedi S, Singh R. Iron, folate, and vitamin B12 stores among pregnant women in a rural area of Haryana State, India. FoodNutr Bull. 2007;28(4):435–8.

    Google Scholar 

  80. Zeng L, Dibley MJ, Cheng Y, Dang S, Chang S, Kong L, et al. Impact of micronutrient supplementation during pregnancy on birth weight, duration of gestation, and perinatal mortality in rural western China: double blind cluster randomised controlled trial. BMJ. 2008;337:a2001.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Molloy AM, Einri CN, Jain D, Laird E, Fan R, Wang Y, et al. Is low iron status a risk factor for neural tube defects? Birth Defects Research Part A: Clinical and Molecular Teratology. 2014;100(2):100–6.

    Article  CAS  PubMed  Google Scholar 

  82. Shaw GM, Todoroff K, Velie EM, Lammer EJ. Maternal Illness, including Fever, and medication use as risk factors for neural tube defects. Teratology. 1998;57(1):1–7.

    Article  CAS  PubMed  Google Scholar 

  83. Botto LD, Moore CA, Khoury MJ, Erickson JD. Neural-tube defects. N Engl J Med. 1999;341(20):1509–19.

    Article  CAS  PubMed  Google Scholar 

  84. Dreier JW, Andersen A-MN, Berg-Beckhoff G. Systematic review and meta-analyses: Fever in pregnancy and health impacts in the offspring. Pediatrics. 2014;133(3):e674–e88.

    Article  PubMed  Google Scholar 

  85. Romanovsky AA, Almeida MC, Aronoff DM, Ivanov AI, Konsman JP, Steiner AA, et al. Fever and Hypothermia in systemic inflammation: recent discoveries and revisions. Front Biosci. 2005;10(1–3):2193–216.

    Article  CAS  PubMed  Google Scholar 

  86. de Lourdes Samaniego-Vaesken M, Alonso-Aperte E, Varela-Moreiras G. Contribution of folic acid-fortified foods to fertile women’s folate recommended nutrient intake through breakfast simulation models. Public Health Nutr. 2015;18(11):1960–8.

    Article  Google Scholar 

  87. Li P, Qin X, Tao F, Huang K. Maternal exposure to sulfonamides and adverse pregnancy outcomes: a systematic review and meta-analysis. PLoS ONE. 2020;15(12):e0242523.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Lassi ZS, Imam AM, Dean SV, Bhutta ZA. Preconception care: caffeine, Smoking, alcohol, Drugs and other environmental chemical/radiation exposure. Reproductive Health. 2014;11(3):1–12.

    Article  Google Scholar 

  89. Wang M, Wang Z-P, Gong R, Zhao Z-T. Maternal Flu or Fever, medications use in the first trimester and the risk for neural tube defects: a hospital-based case–control study in China. Child’s Nerv Syst. 2014;30(4):665–71.

    Article  CAS  Google Scholar 

  90. Rappazzo KM, Warren JL, Meyer RE, Herring AH, Sanders AP, Brownstein NC, et al. Maternal residential exposure to agricultural pesticides and birth defects in a 2003 to 2005 North Carolina birth cohort. Birth Defects Research Part A: Clinical and Molecular Teratology. 2016;106(4):240–9.

    Article  CAS  PubMed  Google Scholar 

  91. Slotkin TA. Cholinergic systems in brain development and disruption by neurotoxicants: nicotine, environmental Tobacco smoke, organophosphates. Toxicol Appl Pharmcol. 2004;198(2):132–51.

    Article  CAS  Google Scholar 

  92. Ben Y, Fu C, Hu M, Liu L, Wong MH, Zheng C. Human health risk assessment of antibiotic resistance associated with antibiotic residues in the environment: a review. Environ Res. 2019;169:483–93.

    Article  CAS  PubMed  Google Scholar 

  93. Association WM. World Medical Association Declaration of Helsinki. Ethical principles for medical research involving human subjects. Bull World Health Organ. 2001;79(4):373.

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank all the study participants, data collectors, and supervisors who participated in the study, as well as the kind cooperation of staff in the health facilities of Eastern Ethiopia.

Funding

For this work no granted is obtained.

Author information

Authors and Affiliations

Authors

Contributions

A.B. wrote the main manuscript and prepared figure All authors are reviewed the manuscript.

Corresponding author

Correspondence to Anteneh Berhane.

Ethics declarations

Ethical approval and consent to participate

Ethical approval was obtained from Jimma University, Institutional Review Board (IRB) with the reference number IHR PGY/738/21. Written informed consent was obtained from mothers or care givers of newborns, and legally authorized representatives “of illiterate mothers or care givers”. The study participants’ privacy and confidentiality were maintained and used for the proposed study only. The study was conducted in accordance with the principles of Helsinki Declaration and the requirements for good clinical practice [93].

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Berhane, A., Belachew, T. Determinants of neural tube defects among women who gave birth in hospitals in Eastern Ethiopia: evidence from a matched case control study. BMC Women's Health 23, 662 (2023). https://doi.org/10.1186/s12905-023-02796-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12905-023-02796-0

Keywords