Prevalence of parasitic infections and associations with pregnancy complications and outcomes in northern Tanzania: a registry-based cross-sectional study

A retrospective cross-sectional study was conducted using maternally-linked data from KCMC medical birth-registry. Birth records from all women who delivered singletons for the period from 2000–2011 were utilized.

This study was conducted at KCMC which is one of four general referral hospitals in Tanzania, situated in Moshi urban district (municipal) of Kilimanjaro region in Northern Tanzania. The hospital receives deliveries from nearby communities and referral cases from other health care facilities inside the region and the nearby regions. The hospital has an average annual delivery rate of 4000 births.

From 2000 to the end of year 2011, a total of 40,039 deliveries were recorded at the medical birth registry. We excluded multiple gestations and rural medical referral for various medical complications which were not related to parasitic infections to avoid overrepresentation of studying women with high risk pregnancies. The remaining 30,797 births which constituted our sample size were evaluated (Fig. 1).

In this study, the pregnancy complication such as maternal anemia and pregnancy outcomes (i.e. preterm delivery, low birth weight, perinatal death and birth defects) were the main outcomes.

Gestational age at birth was calculated from the first day of the woman’s last menstrual period and counted in completed weeks. Low birth weight was defined as infant born with a weight of less than 2500 grams while Preterm birth was defined as birth occurred at less than 37 weeks gestation. Perinatal mortality was defined as the number of stillbirths and deaths in the first week of life (early neonatal deaths) per 1000 live births.

Birth defects which were recorded in the birth registry included; hydrocephalus, spinal bifida, anencephaly (neural tube defect), tallipes, potters syndrome, malformation of the legs, neck malformation, congenital heart disease, congenital keloids and conjoined twins.

The exposure/predictor variables in this study include major parasitic infections as recorded in the medical birth registry i.e. malaria, helminthes (intestinal worm & schistosomiasis) and amebiasis infection. The socio demographic variables studied includes maternal age, maternal occupation, marital status, antenatal care visit (ANC) and area of residence. Mother occupation variable was categorized in two groups; employed (professional and service) and unemployed (housewife, farmer, business, student). Education variable was categorized into “lower education” (<12 years) is up to 11 years of schooling and “upper education” ( ≥12) from 12 years of schooling to higher education.

We also analyzed hygiene and sanitation variables including mothers who were drinking boiled water, water source (tap water, well, river, spring and others) and type of toilet (toilets with flush, pit latrines).

Some maternal sociodemographic factors such as maternal age, parity, education, occupation, marital status and antenatal care visits were considered as potential confounders. While maternal HIV status was considered as an effect modifier for the association between malaria and anaemia.

We used secondary medical birth registry data which was prospectively collected through interview using a standardized questionnaire to all women who delivered at KCMC for the period of 2000 to 2011. Each woman was individually consented to participate prior the interview. According to medical birth registry regulations, each woman who gives birth at KCMC is assigned with a unique identification number (ID) which is constant for all births that occur at KCMC. The mother ID is also assigned to her respective siblings; this makes it possible to create a reproductive history for each woman for subsequent births that occurred at KCMC. During the interview, each woman was asked if she had any parasitic infection during pregnancy (self-reported by the woman). Mothers were also asked to bring their antenatal care visit card to validate some information with regard to pregnancy status including infections. All the information collected was recorded and entered in the computerized database at the medical birth registry. In summary, the information collected from women includes maternal and paternal sociodemographic characteristics, the health status of the mother before pregnancy, during pregnancy (including a parasitic infection which was recorded as infections during pregnancy) and delivery and infant status after birth (see Additional file 1).

Selection bias is a common problem in hospital based studies. For example, women with pregnancy complications during prenatal care are more likely be advised by their clinician or care providers to have delivery at tertiary hospitals for delivery. This may lead to overrepresentation of high risk women who deliver at tertiary hospital which may result to overestimation of the studied adverse perinatal outcomes. On the other hand, the effect of parasitic infections on pregnancy outcomes depends on gestational age when the infections occur, Due to lack of routine screening for parasitic infection among pregnant women in the study setting, majority of women had diagnosis for parasitic infections during their second or third trimesters. This may lead to underestimation of the reported prevalence of parasitic infections.

The ethical approval was obtained from Kilimanjaro Christian Medical University College Research and Ethics Committee (KCMUCo) for the registry project. Both written and verbal consents were sought from individual mothers prior to the interview. Since there was no participant aged less than 16 years, each participant was able to provide an informed consent. Participants were also informed about the importance of the medical birth registry project, and that participation to the study was on voluntary basis. Both confidentiality and privacy were adhered to, where use of unique mother identification number was used instead of names and interviews were conducted in a privacy room.

Data analysis was performed using SPSS Software (SPSS Inc., Chicago, IL) version 18.0 for analysis. Student t-test was used to compare the difference in means for continuous variables The Chi-squared test (χ²) was used to compare proportions of categorical variables. The odds Ratios (ORs) with 95 % confidence intervals for pregnancy complications and adverse pregnancy outcomes were estimated using multivariable logistic regression model while controlling for potential confounders. Five models were run where each adverse pregnancy outcome (i.e. preterm birth, low birth weight, perinatal death and birth defect) and complication (i.e. maternal anaemia) were treated as an outcome and assessed independently in a multivariable logistic regression model against parasitic infections (malaria, helminths and amoeba) as an independent variables (Table 3).

A variable was considered to be a confounder if its inclusion in the model changed the crude odds ratio by 10 % or more. We also tested an interaction between malaria infection and HIV on anaemia, but we found that there was no statistical intercation.

A total of 30,797 births were evaluated. There were only three infections/infestations which were evaluated including malaria, helminthiasis and amebiasis. The prevalence for malaria, amebiasis and helminthiasis was 17 %, 0.7 % , and 0.6 % respectively.

The association between sociodemographic characteristics and prevalence of parasitic infections are shown in Table 1. Malaria, helminthiasis and amebiasis were significantly associated with most of the demographic variables studied (Table 1), except for amebiasis which not dependent on maternal education level, type of toilet and area of residence. We found that number of antenatal care visits (>4 visits), being unemployed, low maternal education attainment (<12 years), residing in rural area were associated with an increased risk of helminthesis and amebiasis.

The sociodemographic characteristic associated with adverse pregnancy outcome and maternal anemia are presented in Table 2. Poor attendance to antenatal care (<4 visits) was significantly associated with preterm delivery (P < 0.001). Furthermore, extreme maternal age (<20 and ≥35 years), primiparity (i.e. para 1), being unmarried, being unemployed, having low education, positive HIV status and living in rural area were also significantly associated with delivery of low birth weight infant (P < 0.05). We also found a significant increase in perinatal mortality in relation to high maternal age (≥35 years), poor attendance to ANC, unemployed, low education and living in rural area. On the other hand, low maternal age (<20 years) and primiparity were significantly associated with maternal anaemia P < 0.05).

The results from multivariable logistic regression models for association between maternal anemia, pregnancy outcomes and parasitic infections are shown in Table 3. Since the binary logistic regression model is suitable for binary outcome and we have five outcomes; we performed five models where each adverse pregnancy outcome and complication was treated as an outcome while parasitic infections (i.e. malaria, schistosomiasis and helminths) were treated as an exposure variables for each model. Since some demographic characteristics were independently associated with outcome of interest, we adjusted for maternal age, parity, antenatal care visits, maternal education, maternal occupation, area of residence and marital status. Women recorded with malaria infection during pregnancy had 33 % (OR 1.33, 95 % CI: 1.07–1.66) increased odds of getting anemia as compared to those who were not infected. These women were also 1.13 times (95 % CI: 1.01–1.26) more likely to have preterm delivery. Malaria infection during pregnancy was also associated with increased odds of birth defect (OR 1.49, 95 % CI: 0.73–3.02), but this association was not statistically significant.

We also found that women who were recorded to have helminth infestations during pregnancy had 1.3-fold (95 % CI: 0.48–3.53) increased odds of maternal anemia as compared to their counterparts who were not infected, but this association did not reach statistical significance. Women recorded with amebiasis were more likely to deliver preterm infants as compared to women who were not infected (OR 1.79; 95 % CI: 1.12–2.9).

Since malaria and HIV both have an influence on maternal anaemia, we performed a sub-analysis to test for interaction between malaria and HIV co-infection on maternal anemia, but there was no statistically significant interaction (data not shown).

Our study used a large sample size which makes it possible to make an inference with high precision. Information was collected by well-trained nurse’s midwives through interviewing the women using a standardized questionnaire and supplemented with information obtained from medical records and antenatal care clinic cards to confirm the information from the questionnaire to ensure data completeness and accuracy for most important study variables.

Our study also had some limitations which are important to be taken into account while interpreting this result. First, this study used hospital-based data which have already been recorded for performing different research projects and not specifically meant for this study. Secondly, the assessment of parasitic infection was based on self-reported information which may lead to under or overestimation of the reported prevalence of infection. Third, this was a hospital-based study which may suffer from referral bias. However, this may have huge consequences in generalization of our findings if women who were studied had different risk characteristics compared to other women in the general population. We excluded women who were referred from rural facilities for various medical complications and those with multiple gestations to avoid overrepresentation of high risk women in our study. The effect of this exclusion on results is not known. But we believe that the exclusion of these women was not related to severe parasitic infections. Fourth, we did not assess the effect of other maternal variables which have been associated with adverse perinatal outcomes such as interpregnancy interval, preeclampsia, delivery complications as well as missing data. The effect of these factors on the studied outcomes remains unclear. Fifth, we used data that were collected for many years, therefore some diagnosis criteria for studied parasitic infections may have been changed over time; this may affect the reliability of the reported findings. Finally, Data on parasitic infections were based on self-reported information by participants; this may lead to self desirability bias and compromise validity of our findings.