Risk factors for major external structural birth defects among children in Kiambu County, Kenya: a case-control study

Background: Although major external structural birth defects continue to occur globally, the greatest burden is shouldered by resource-constrained countries with no surveillance systems. To our knowledge, many studies have been published on risk factors for major external structural birth defects, however, limited studies have been published in developing countries. The objective of this study was to identify risk factors for major external structural birth defects among children in Kiambu County, Kenya. Methods: A hospital-based case-control study was used to identify the risk factors for major external structural birth defects. A structured questionnaire was used to gather information retrospectively on maternal exposure to environmental teratogens, multifactorial inheritance, and sociodemographic-environmental factors during the study participants' last pregnancies. Descriptive analyses (means, standard deviations, medians, and ranges) were used to summarize continuous variables, whereas categorical variables were summarized as proportions and percentages in frequency tables. Afterward, logistic regression analyses were conducted to estimate the effects of the predictors on the odds of major external structural birth defects in the country. Results: Women who conceived when residing in Ruiru sub-county (adjusted odds ratio [aOR]: 5.28; 95% CI; 1.68-16.58; P<0.01), and Kiambu sub-county (aOR: 0.27; 95% CI; 0.076-0.95; P=0.04), and preceding siblings with history of birth defects (aOR: 7.65; 95% CI; 1.46-40.01; P=0.02) were identified as the significant predictors of major external structural birth defects in the county. Conclusions: These findings pointed to MESBDs of genetic, multifactorial inheritance, and sociodemographic-environmental etiology. Thus, we recommend regional defect-specific surveillance programs, public health preventive measures, and treatment strategies to understand the epidemiology and economic burden of these defects in Kenya. We specifically recommend the integration of clinical genetic services with routine reproductive health services because of potential maternal genetic predisposition in the region.


Introduction
Worldwide, an estimated 7.9 million children are born every year with a birth defect of which approximately 3.3 million die before age five and around 3.2 million could be physically disabled for life 1,2 . More than 94% of such defects occur in developing countries where about 95% of these children do not survive beyond childhood 1 . Birth defects are defined as abnormalities of body structures or functions that develop during the organogenesis period (first trimester of gestation) and detectable during pregnancy, at birth, or soon after 2,3 . These defects may be classified as major when associated with significant adverse health effects requiring medical/surgical care; otherwise, they are described as minor 1,2 . Alternatively, they can be classified as external when visible at birth or soon after; or internal when advanced medical imaging techniques are required for their detection [4][5][6] . Consequently, the phrase 'major external structural birth defects' (MESBDs) denotes congenital physical abnormalities that are clinically obvious at birth or soon after which call for medical and/or surgical interventions 1,2 . The causes of these defects can be classified into three categories: (i) identifiable environmental factors (teratogens/micronutrient deficiencies); (ii) identifiable genetic factors; and (iii) complex genetic and idiopathic environmental factors, described as multifactorial inheritance 1,4,[7][8][9][10] . One-third of these causes are attributed to identifiable environmental and genetic factors, whereas the rest are believed to be of multifactorial aetiology 1,4,[7][8][9][10] . Additionally, an environmental endowment of women of reproductive age is thought to operate through their socioeconomic and sociodemographic characteristics leading to causes of MESBDs, described as sociodemographicenvironmental factors 1,4,[8][9][10] .
Organogenesis occurs in the first eight weeks of gestation; however, approximately half of pregnancies are usually unplanned/ unintended, thus not recognized until the end of the second trimester 1,4,[11][12][13] . Completing more years of education could improve maternal health because educated women are more likely to make informed reproductive health choices than those with low levels of education to improve birth outcomes [14][15][16][17] . Some of the notable maternal decisions include planned pregnancy, preconception folic acid intake in anticipation of conception, and subsequently prompt prenatal care 14,16,18-23 . Supplemental vitamins with folic acid are dispensed during routine antenatal care (ANC) visits, as well as health education on adequate nutrition, avoidance of environmental teratogens, and maternal infections as public health preventive strategies for MESBDs 10,24 . These measures could be effective only when pregnant women promptly began antenatal care within eight weeks of gestation before the intrauterine formation of MESBDs 4 . Folic acid is essential for normal development of the brain and spinal cord during the first 4 weeks of conception, and have been found to reduce the occurrence of neural tube defects, orofacial clefts, limb reduction defects, urinary system defects, and omphalocele; some of the most prevalent defects in the county [25][26][27] . Thus, the recommended first ANC at the 12 th week of pregnancy could be a sub-optimal preventive strategy for these defects, nevertheless it improves experiences of the women during pregnancy and childbirth 28 . Maternal occupation as a predictor of MESBDs could be dependent on educational levels, nonetheless occupations such as farming could expose women of reproductive age to teratogenic pesticides 29 .
Maternal residence at conception is similarly a significant predictor of MESBDs determined by environmental etiology attributed to widespread poverty, environmental pollution, inadequate health care services, and ineffective preventive strategies; factors largely found in developing countries 1,7,30 . Parental age is a multifaceted risk factor whose mechanisms of actions in the intrauterine formation of MESBDs are underpinned by human biology and socio-economic endowment among women of reproductive age. From the biologic standpoint, the female gametogenesis begins before birth with the initial meiotic division (prophase stage) expected to complete shortly before ovulation, however, this is not the case always because the process may delay up to 45 years to conclude 24 . Thus, the oocytes take exceedingly long in the prophase stage increasing the likelihood of meiotic errors due to exposure to the environmental teratogens 24 . Advancing maternal age beyond 35 years is similarly a risk factor for MESBDs of genetic etiology due to chromosomal abnormalities 24,31,32 . Similarly, from the genetic viewpoint, genetic mutations and accumulation of chromosomal aberrations during the maturation of male germ cells have been attributed to the formation of MESBDs in utero 33,34 . The amount of deoxyribonucleic acid damage in sperm of men aged 36-57 is three times that of men <35 years, increasing the likelihood of these defects in aging couples 34,35 . From the socioeconomic perspective, parental age could be associated with MESBDs of multifactorial etiology ascribed to physiological interactions between complex genetic and idiopathic environmental attributes of women of reproductive age 1,7,30,36,37 .
To our knowledge, many studies on the risk factors have been published in developed countries, however, such publications are scanty in developing countries owing to the rarity of the defects, unplanned/unintended pregnancies, and difficulties in

Amendments from Version 1
To address the reviewers' comments, we have clarified that; the hypothesized odds ratio used in sample size calculation was set at 2.0 (universally accepted), different types of birth defects were collectively used in sample size calculation rather individual defects due to the rarity of the defects coupled with the unavailability of surveillance systems for birth defects in the country, and that data collection period spanned three months from May 31st 2019 to July 31st 2019. Additionally, some of these defects are potentially fatal and could possibly introduce survivor bias in the study, thus we clarified being cognizant of this epidemiological phenomenon, however we could not minimize it considering that pathological examinations to determine the causes of death in stillbirths and miscarriages is not a routine practice in the country. Maternal residence, at conception and paternal age were controlled for in the multivariable analyses, however maternal cigarette smoking was not controlled for due to negligible responses received from the study participants. We have also redesigned our conceptual framework, defined maternal exposure to pesticides and chronic illnesses in the context of this study. We also improved the texts in the introduction, discussion, and conclusion sections of the manuscript, including changes to Figure 1 and all Tables.
Any further responses from the reviewers can be found at the end of the article REVISED identifying these women until the end of the second trimester when the defects have already formed 4 . To address this gap, this study investigated maternal periconceptional exposure to environmental teratogens, sociodemographic-environmental, and multifactorial risk factors for MESBDs in Kiambu County, Kenya. The study assessed: maternal periconceptional exposure to farm-sprayed pesticides, and teratogenic therapeutic medicines proxied by maternal chronic illnesses (epilepsy and depression); multifactorial inheritance proxied by the history of siblings with birth defects, sex of the "last born" current child, nature of pregnancy, and parity; and sociodemographicenvironmental factors consisting of maternal age, paternal age, residence, level of education, occupation, and adequate prenatal care proxied by gestational age at first ANC, and preconception folic acid intake. The findings of this study could provide great public health opportunities for the formulation of specific treatment strategies, preventive measures, risk-based surveillance systems, and clinical genetic services for the most prevalent MESBDs, regionally and nationally. Consequently, the objective of this study was to identify the risk factors for MESBDs among children in Kiambu County, Kenya.

Study design and settings
A hospital-based case-control study was conducted to identify the risk factors for MESBDs. The study participants were recruited as they presented to the child welfare clinics, neonatal/pediatric units, and occupational clinics for care during the data collection period from May 31 st 2019 to July 31 st 2019. A case-control design was the optimal design for this study considering its suitability for the investigation of rare outcomes, as is the case with MESBDs. Even though a population-based design would have been preferable, the ease of recruiting case and control subjects within the hospital settings disproportionately favored the hospital-based design. This was an observational study, therefore was reported as per the STROBE guidelines 38 .
The study was conducted in 13 hospitals comprising threecounty referral hospitals (Kiambu, Gatundu, and Thika), eight sub-county hospitals (Karuri, Kihara, Wangige, Nyathuna, Lari, Tigoni, Lussigetti, and Kigumo), and two faith-based hospitals (Presbyterian Church of East Africa Kikuyu Orthopedic and African Inland Church Cure International) situated within Kiambu County, Kenya. Notably, neither population-based nor hospital-based surveillance systems for MESBDs existed in the county nor the study hospitals. Nonetheless, cases detected by primary health providers during childbirth and neonatal care were recorded for the compilation of monthly hospital reports and subsequent entry into the District Health Information System (DHIS). The cases were drawn from Kiambu, Thika, Gatundu, Tigoni, Kikuyu, and Cure hospitals, which provided occupational and rehabilitative health services to children with MESBDs. The controls, on the other hand, were drawn from Kiambu, Gatundu, Thika, Karuri, Kihara, Wangige, Nyathuna, Lari-Rukuma, Tigoni, Lussigetti, and Kigumo hospitals which provided child welfare services to the under-fives. Kiambu is the second-most densely inhabited county with an estimated population of 2.4 million people out of an estimated national population of 47.5 million 39 . Its economic mainstay is largely agriculture, comprising tea, coffee, and dairy farming 39 . Of the county's total estimated population, approximately 2.2% aged ≥5 years are living with lifelong disabilities 39 . A study carried out in the county between 2014 and 2018 observed defects of the musculoskeletal system as the most prevalent single system defects followed by central nervous, orofacial clefts genital, ocular, and anal organ defects 25 .

Study population and eligibility of participants
The study population consisted of children aged ≤5 years old seeking health services at the study hospitals during the study period spanning from May to July 2019. All children whose mothers consented to participate in the study were recruited.

Case definition and recruitment
Cases were defined as children aged ≤5 years born with at least one MESBD to resident women of Kiambu County and seeking health care services at the neonatal units, pediatric wards, child welfare clinics, and/or occupational therapist clinics of the study hospitals during the three-month study period. The Research Assistants (RAs) liaised with team leads of the departments listed above to identify cases of MESBDs. The team leads had been working in these departments, thus were conversant with the cases seeking services. The team leads invited the mothers of the children who met the case definition to comfortable private rooms within the departments where informed consent was sought and interviews conducted by the RAs. All cases that met this definition and whose caregivers consented to participate were prospectively recruited into the study until the required sample was attained (see Sample size determination).

Control definition and recruitment
Controls were defined as children aged ≤5 years born without any forms of birth defects to resident women of Kiambu County and attending routine child welfare clinics at the study hospitals during the same three-month study period. The Research Assistants liaised with team leads of the child welfare clinics to identify the children without any form of birth defects and were seeking routine immunization, and growth monitoring services. The team leads had been working in these clinics, hence were familiar with most of the under-fives seeking the services. These services are provided between 8.00 am and 5.00 pm from Monday to Friday; the team leads introduced the RAs who then briefed the potential participants on the study objectives. Because of the relatively large number of controls available, they were selected by simple randomization using sealed envelopes upon definition of the sample population and frequencymatched to the cases by the day of presentation. Informed consent was sought from the study participants who met the study eligibility criteria; those who consented to participate in the study were prospectively recruited and invited to secluded comfortable rooms within the clinics where face-to-face interviewer questionnaires were administered till the desired sample size was achieved (see sample size determination).

Sample size determination
The sample size was estimated as per the Kelsey JL et al. 40 formula specified for case-control studies as follows: - Where: n 1 is the number of cases and n 2 is the number of controls; p 1 is the proportion of cases whose caregivers did not begin prenatal care in the first trimester (primary exposure), p 2 is the proportion of controls whose caregivers did not begin prenatal care in the first-trimester set at 57% 11,12 . Remarkably, Z α/2 (1.96) and Z β (-0.84) are the values specifying the desired two-tailed confidence level (95%) and statistical power (80%), respectively. The odds ratio (OR) for the effect of the primary exposure (cases whose caregivers did not begin prenatal care in the first trimester) was hypothesized to be 2.0 (universally accepted). The ratio (r) of unexposed to exposed individuals was set at 3.0, and given the estimates, a total sample size of 408 participants was derived (102 cases, and 306 controls).

Data collection process and study variables
Before data collection, four nursing graduate interns were recruited and trained as RAs on sound interviewing techniques, and information derivation/validation from antenatal care (ANC) booklets. This was to ensure the data collection process spanning three months (May 31 st 2019 to July 31 st , 2019) was conducted in a standardized manner. The ANC booklet contains maternal profile, medical/surgical history, previous pregnancy history, clinical notes, and physical examination findings on ANC visits, among others. The maternal profile includes name, age, parity gravidity, height, weight, last menstrual period (LMP), expected date of delivery (EDD), and date of first ANC. Face-to-face structured questionnaires (see Extended data) were administered to the mothers of the study participants by RAs in comfortable secluded rooms within neonatal units and occupational therapy clinics for cases and child welfare clinics for the controls. Data were gathered retrospectively on exposures to environment-teratogens (farm-sprayed pesticides, and teratogenic medicines proxied by chronic illnesses), multifactorial inheritance (parity, nature of pregnancy, history of siblings with birth defects and sex of the "lastborn" (current) child), and sociodemographic-environmental factors (maternal age, paternal age, residence, education level, occupation, and adequate prenatal care proxied by gestational age at first ANC and preconception folic acid intake). The predictors were assessed as shown in Table 1. Table 1. Study variables and their assessments.

Variable (type) Method of assessment
Exposure to farm-sprayed pesticides (nominal) Captured as "yes" for those who sprayed farms with pesticides and "no" for those who did not spray farms with pesticides Teratogenic therapeutic medicines for chronic illnesses (nominal) Captured as a nominal variable, categorized, and labelled; 1= "medicines for hypertension", 2= "no medicines for chronic illnesses" and 3= "medicines for other chronic illnesses" ANC began 8 weeks post-conception began (nominal)

Captured as yes/no
Gestational age (weeks) at first ANC (continuous) Captured in weeks, categorized, and labelled; 1<9 weeks, and 2≥ 9 weeks at first ANC visit.

Residence (nominal)
Captured as a nominal variable, and categorized into five groups: 1=Thika, 2=Gatundu, 3=Kiambu, 4=Ruiru, and 5=other sub-counties The conceptual framework was organized based on the three causal categories of MESBDs (multifactorial inheritance, environmental teratogens, and sociodemographic-environmental factors). Nonetheless, because disentangling genetic etiology (identifiable, and complex) was a scientific limitation of observational studies as is the case in our study, analysis of such factors sufficed as a multifactorial inheritance in this conceptual framework to measure maternal genetic predispositions. A conceptual framework depicting the predictor-outcome relationship is displayed in Figure 1. The flow chart of the simple-random systematic sampling strategy is shown in Figure 2.

Minimizing bias
Considering potential biases inherent in case-control studies that were likely to invalidate the study results, deliberate attempts were made to minimize their occurrence. First and foremost, the research assistants were trained on sound interviewing techniques and information derivation/validation from ANC booklets to minimize interviewer and minimize information biases, respectively. In a bid to minimize recall bias, gestational age at the first ANC was estimated from the dates of the last menstrual period and dates of the first ANC obtained from the ANC booklets.
Data processing and statistical analysis Following data collection, filled questionnaires were manually checked daily for accuracy and completeness and subsequently entered into a Microsoft Excel spreadsheet (Microsoft Office Professional Plus 2019) by two independent data managers to reduce potential errors. The excel dataset was validated and exported to Stata software version 14.0 (Stata Corporation, Texas, USA) for further cleaning, coding, and analyses. Descriptive analyses (means, medians, standard deviations, and ranges) were used to summarize continuous variables, whereas proportions and percentages for categorical variables were generated and presented in frequency tables. Afterward, the effect of each predictor on the odds of MESBDs was assessed using univariable logistic regression models at a liberal P-value (P≤0.20) 41 . Gestational age at first ANC as a continuous variable was categorized into groups (<9 weeks and ≥9 weeks) for  evaluation in the univariable analyses 1,4,11-13 . Additionally, parity as a continuous variable was grouped into two groups: =1=primiparous or >1=multiparous categories for assessment in the univariable analyses 42,43 . However, maternal age as a continuous variable was insignificant in the univariable analyses, thus, recategorized into two groups; <35 years, and ≥35 and reassessed for statistical significance; women aged at least 35 years have previously been reported to have an increased likelihood of giving birth to children with MESBDs 44 . Paternal age as a continuous variable was similarly insignificant in the univariable analyses, thus recategorized into seven groups and reassessed for statistical significance which was still insignificant. Nevertheless, paternal age was further recategorized into two groups (<35 years, and ≥35) and reassessed for statistical significance yet still insignificant; males aged at least 35 years have previously been associated with increased likelihood of defect-affected births in their female counterparts 34 . Variables found statistically significant in the univariable analyses were fitted to a multivariable model where a backward stepwise approach was used to eliminate variables from the model at P-value >0.05. Nature of pregnancy was however collinear in the multivariable analyses thus dropped in the final multivariable analysis.
To minimize the confounding effects, elimination of nonsignificant predictors was only considered when their exclusion from the model did not yield more than a 30% change in the effects of the remaining variable 41 . Two-way interactions were fitted between the remaining variables of the final model and assessed for significance. A Hosmer-Lemeshow test was used to assess the goodness of fit of the logistic model, with a P-value of >0.05 being suggestive of a good fit.

Results
A total of 408 study respondents (102 cases and 306 controls) were enrolled in this study.  (Table 2).
Environmental-teratogens: Of the 408 study respondents, 15 (3.68%) were exposed to farm-sprayed pesticides, of which four (3.92%) were in the case group and 11 (3.59%) were in the control group (Table 2).
Multifactorial inheritance: Of the 408 study respondents, 404 (98.77%) had single gestations for the current child, of which 99 (97.06%) and 304 (99.35%) were in the case and control groups, respectively (Table 2). Of the study participants,   (Table 2). Of the 15 study participants, 12 stated the name or described the nature of the defects in their previous pregnancies/births, however, 3 participants were unable to do so. Of the 12 study respondents, 7 of the case subjects with congenital talipes equinovarus reported a history of birth defects in their previous births of which 4 subjects reported a recurrence of congenital talipes equinovarus, whereas 3 reported foot aversion, internally rotated shorthand (phocomelia), and congenital scoliosis. On the other hand, 5 control subjects reported a history of siblings with birth defects in their preceding births comprising 3 cases of congenital talipes equinovarus, 1 case of autism, and 1 case of deafness (Table 3).

Logistic regression analyses
Notably, the factors assessed for statistical significance in the univariable analyses and found associated with MESBDs at P≤0.20 included maternal age, residence, education, occupation, ANC visits beginning eight weeks post-conception, gestational (age) at first ANC visits, nature of pregnancy, and history of siblings with birth defects (Table 4). Subsequently, these variables were fitted to the multivariable model for the final analysis, except education being distal relative to occupation, gestational age at first ANC visits, and ANC beginning eight weeks post-conception. (Figure 1). .
In the multivariable analysis, only maternal residence at conception, and history of siblings with birth defects were shown as the significant predictors MESBDs at a 5% significance level (  (Table 5).

Discussion
To our knowledge, this was the first case-control study conducted to identify the risk factors for MESBDs in the entire county. Our study results mimicked other findings across the world that maternal residence at conception and history of siblings with birth defects are strongly associated with the intrauterine formation of MESBDs 1,30,46 . Our study observed orofacial clefts comprising 1 (0.98%) cleft lip with the palate, and 3 (9.94%) cleft palates; limb reduction defects comprising 1 (0.98%) clubbed hand, and 4 (3.92%) limb defects; defects of the musculoskeletal system consisting of 91 (89.22%) clubfeet; and neural tube defects comprising 1 (0.98%) hydrocephalus and 1 (0.98%) Table 3. History of siblings with birth defects among case and control subjects.

Deafness 1 1
Foot aversion 1 1 Internally rotated shorthand 1 1 Congenital scoliosis 1 1  Positive siblings and familial history of specific types of MESBDs have been associated with increased risks of recurrence in subsequent pregnancies 24,46,47 . Worldwide, the recurrence rate of NTD and Down syndrome have been approximated at 2-5% and 1%, respectively 24,46,47 . Thus, accurate knowledge of birth defects by families when given to the clinicians is similarly of public health significance to improve risk assessments and reproductive health planning for couples susceptible to birth defects of genetic, and multifactorial origin 46 . Even though our study did not show a significant statistical association between MESBDs with parental age, advanced age has been strongly associated with defects of chromosomal etiology (Down syndrome), and non-syndromic etiology (neural tube defects and orofacial clefts) 1,30,34,48, . Nonetheless, our study alluded to an increased risk of chromosomal abnormalities thus suggestive of the prevalence of MESBDs of genetic origin in the county. High prevalence of Down syndrome has been observed in developing countries attributed to many older women becoming pregnant, limited family planning services, unavailability of prenatal genetic screening, diagnosis, and related services 1,30 . MESBDs are considered defects of public health importance, however the presence of certain defects; rare or common, minor or major, internal or external, functional or structural sometimes act as pointers to latent defects of similar significance because of the multiple genetic epidemiology, thus diagnosable later using advanced medical imaging techniques 3,6,46 .

Total 7 5 12
Our study similarly observed maternal residence at conception as a predictor of the intrauterine formation of MESBDs. The study showed that women who got pregnant when residing in Ruiru sub-county were 5.28 times likely to give birth to children with MESBDs compared to those who got pregnant residing in other sub-counties within Kiambu County. Conversely, the study showed that women who got pregnant when residing in Kiambu sub-county were 27% less likely to give birth to children with MESBDs compared to those who got pregnant residing in other sub-counties within the county. The study showed that Kiambu sub-county was protective implying it was relatively safe for women of reproductive age to become pregnant while residing in the sub-county. Maternal residence at the time of conception as a risk factor for MESBDs could be ascribed to variations in maternal genetic, multifactorial, sociodemographic-environmental attributes. From the genetic perspective, increased frequency of single-gene defects in developing countries has been associated with increased frequency of common recessive disorders such as hemoglobin disorders, sickle cell anemia, thalassemia, oculocutaneous albinism, and cystic fibrosis because of the discerning advantage for carriers to the mortal effects of malaria, as well as recessive conditions associated with high rates of consanguineous (cousin) marriages 1,30 . Additionally, high prevalence of defects of chromosomal etiology in developing countries have been ascribed to women delaying childbearing beyond 35 years, limited maternal access to family planning services, and absence of clinical genetic services 1,24,30,48 . Sociodemographic-environmental characteristics, and physiological interactions between complex genetic disorders, and idiopathic environmental factors could also lead to the occurrence of MESBDs associated with ethnic and geographic differences 1,30 . Thus, the epidemiology of MESBDs in the county underscore an underlying genetic, multifactorial, sociodemographic-environmental etiology contributing to the global debate on the burden of a "silent" public health problem in developing countries 1,30 .
Although our study did not show an association between MESBDs with known environmental factors (teratogens and micronutrient deficiencies), pregnancies in developing countries are at increased risk of potential teratogens because of high prevalence of intrauterine infections, maternal malnutrition, low socioeconomic levels, low levels of education, deficient environmental protection policies, and insufficiently regulated access to medicines 1,30 . This could imply the county is performing relatively well in controlling potential environmental causes of MESBDs. The teratogens consist of; (i) congenital infections; (ii) maternal and altered metabolism; and (iii) recreational and therapeutic drugs 1,30 . Congenital infections comprise toxoplasmosis, other infections (syphilis, varicella-zoster, human parvovirus B19), rubella, cytomegalovirus, and herpes, denoted by an acronym "TORCH" 1,30 . Epilepsy and insulin-dependent diabetes are the examples of maternal illnesses and altered metabolism, whereas statins and alcohol are the examples of therapeutic and recreational drugs, respectively 1,30 . Our study also did not show significant associations between MESBDs with maternal occupation, gestational age at first ANC, and ANC beginning 8 weeks post-conception; factors thought to influence maternal iron-folic acid supplementation 14,16,21 . Folic acid is crucial for the biosynthesis, and methylation of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) which are important for cell division, differentiation, and regulation of gene expression, during rapid cell division such as embryogenesis, thus is necessary for the growth and smooth functions of human cells 24,49 .
Nevertheless, some limitations were inherent in this study; there was a likelihood of differential recall bias among the study respondents; cases were more likely to remember their preconception period owing to the experience of MESBDs in the last birth than the controls, thus recall bias could affect estimates of the odds ratios. The study participants with a history of siblings with birth defects either stated or described the nature of the defects however the researchers could not ascertain accuracy of the diagnoses/descriptions, while others did not know the names of the defects. Survivor bias was also an inherent limitation in this study because some defects such as neural tube defects are potentially fatal, however the study could not establish the causes of deaths among stillbirths, and miscarriages in the study hospitals because it was not a pathological standard operating procedure in the entire Kenya. Additionally, due to the extreme rarity and stochasticity of MESBDs because of the absence of public health surveillance systems, the researchers lumped all types of MESBDs in calculating the sample size, yet births defects are largely heterogenous in their etiology, thus could also lead to underestimation of the effects of the predictors on the odds of MESBDs.

Conclusions
These findings were indeed suggestive of genetic, multifactorial, and sociodemographic-environmental etiology of MESBDs in Kiambu County, Kenya. Thus, these findings could provide the greatest public health opportunities for health planners in the region to establish defect-specific surveillance programs, implement proven public health preventive strategies, and provide appropriate treatment interventions for the most prevalent MESBDs. Therefore, we would like to provide the following priority public health policy recommendations; establishment hospital-based surveillance systems for the most common MESBDs, and integration of clinical genetic services with routine reproductive health services, nationally. The genetic services should consist of counseling, screening, diagnosis, and associated treatments including elective termination of pregnancies for anomalies in jurisdictions with favorable legislative frameworks. Additionally, we would recommend further epidemiological, and economic evaluation studies to understand the epidemiology and economic burden of these defects in Kenya. This is a good and important research area for newborn health particularly now when a lot has been done on infectious unlike non infectious diseases. We have observed a great decrease of infant mortality given the available maternal and newborn interventions on infectious diseases. A higher contribution of non infectious disease particularly birth defects may be observed on neonatal and infant mortality with time. Below are my inputs and comments regarding this study;

Data availability
The title, abstract and introduction are well written.
○ Current citations were used.

○
The study design is appropriate however selection of cases was not appropriate given the study title and objectives. It can be admitted as one of study limitation. Cases were sampled from child welfare clinics, neonatal/pediatric units, occupational and rehabilitation clinics. All these data sources represent survivors of MESBDs and most probably non fatal MESBDs. It is difficult to get fatal MESBDs like neural tube defects (NTDs) cases from this subpopulation as majority will not survive to meet them in rehabilitation clinics.

○
The ascertainment period from the case definition is too high (5years and below). This may lead to potential recall bias as it will be very difficult for a mother to remember what happened in her pregnancy in the 3-4 years ago. Again may lead to recruitment of survivors and non fatal MESBDs cases. This could be mitigated for at least to consider/restrict enrolment into the study for children below 1 or 2 years only.
○ I understand well that the data sources were the above mentioned clinics which are complimented by the ANC booklets. However the methodology section again mentioned about DHIS and I was wondering whether it was also another data source which was used. It needs clarity for the reader to well understand sources of data for this study.

○
The methodology section need more clarity on maternal age. Is it the age of the mother during conception of the referred case? or the age of the mother during the data collection? It is also very important to define "residence" as it has implication on maternal exposures. The residence is important during conception and antenatal period. This is the period when environmental exposures can have impact on the unborn child. There is no any significance of considering residence post delivery.

○
Sample size calculation is Ok. However you can not estimate proportion of controls (p 2 ) using a study with a different objectives from your intended study.

○
The hypothesized odds ratio for the effect of the primary exposure is too high. This is the risk which you allow to be detected in your study. At least you can allow a minimal risk of odds ratio between 1.5 and 2.
○ Results were well written however there is a need to your interpretation and conclusion to reflect your exact results. If the maternal age ≤34 years was found to be protective does not mean the maternal age ≥35 years is a risk. Remember this age category was your reference. If you want to refer the age category ≥35 years then make the other category " ≤34 years" a reference in your logistic regression analysis. Otherwise I advise to interpret and make conclusion exactly as what you found in your result section.

Is the work clearly and accurately presented and does it cite the current literature? Partly
Is the study design appropriate and is the work technically sound? Partly

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Partly

Conclusions:
The conclusions have been aligned to the study findings and interpretations.

Is the study design appropriate and is the work technically sound? Yes
Are sufficient details of methods and analysis provided to allow replication by others? Yes

If applicable, is the statistical analysis and its interpretation appropriate? Partly
Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly 3. Sample size calculation: Birth defects are largely heterogeneous in their etiology, however the defects were lumped together for sample size calculation because of the extreme rarity of these defects coupled with unavailability of hospital-based/population-based surveillance programs in the county. Nevertheless, this has been cited as a limitation of the study. Results 1. Table 3: P-values for binomial variables were deleted, whereas likelihood ratio test (LRT) was performed for nominal variables/variables with more than two categories to estimate the associated P-values for each variable.
2. Maternal age: The reference category for maternal age was changed to <35 years, but showed no association in the univariable analysis. Nonetheless, the study results were suggestive of chromosomal etiology because some cases were reported to occur with down syndrome, whereas autism was also reported by control subjects as a defect in the previous births.
3. Siblings with same types of birth defects: Yes this was observed in the study. A recurrence of clubfoot was reported by some case subjects, whereas other types of birth defects were reported by case subjects to have occurred with clubfoot Discussion: Small sample sample based on combined several different types of birth defects has been cited as a limitation of this study. number.
In the univariable analyses, why p-values for the reference categories are included?
The discussion is a bit shallow. Comparison with more literatures, more in-depth look in to the implications and significances of the findings, and addressing also key relevant factors without significant association in the current study can improve the Discussion part. The paternal age was also mentioned as key factor in previous studies but not assessed in the current study. Why? There are also other possible limitations not mentioned. E.g. survivor bias and not controlling for some relevant variables in the multivariable analysis like the paternal age.
The conclusion is a bit beyond the scope of the study. E.g. awareness level of couples or the community is not assessed. Detailed and in-depth discussion by citing other relevant literatures can help readers to better understand the situation and to deduce more appropriate conclusions.

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Gestational age: Gestational age has also been presented as <9 weeks, and >=9 weeks. Pesticides exposure: Exposure redefined as maternal exposure to farm-sprayed pesticides before conception. Chronic illnesses: Chronic illnesses were used as a proxy for measuring maternal use of teratogenic therapeutic agents for chronic conditions such as epilepsy, depression, hypertension and diabetes mellitus. In this respect, it was not used as a measure for particular chronic illnesses. Conceptual framework: Redesigned to reflect the three classes of major external structural birth defects described in the study introduction. Univariable analyses: P-values for binomial variables were deleted, whereas likelihood ratio test (LRT) was performed for nominal variables/variables with more than two categories to estimate the associated P-values for each variable. Discussion: Discussion of the significant variables was improved to include their implications, and significance. Variables that showed no associations were also explained with reference to other studies. Paternal age: Paternal age was introduced in the model, however it showed no association with the defects in the univariable analyses. Nevertheless, it was controlled for in the multivariable, but still showed no association. Further, because of potential collinearity with materteral age, paternal age was controlled for without maternal age in the multivariable analyses, however, still showed no association with birth defects. Limitations of the study: Survivor bias was included as a limitation of this study because some of these defects for example neural tube defects are potentially fatal.

Conclusions:
Conclusions were aligned to the study findings and interpretations.