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Background: Low birthweight (LBW) is an important predictor of neonatal and post neonatal child morality. Though its risk factors have been extensively studied in the developed world; limited epidemiological evidence is available in developing countries including Ethiopia. The purpose of the study is to determine the risk factors of LBW in North Shewa zone, Central Ethiopia. Methods: Unmatched case-control study involving 94 cases and 376 controls was conducted from Jan to Mar 2017 in three public hospitals in the zone. A case was defined as a singleton live birth with birthweight less than 2.5 kg; whereas, a control was a newborn that weighs 2.5-4.0 kg. Cases and controls were recruited on an ongoing basis until the required sample sizes were fulfilled. Data were collected by interviewing mothers, reviewing medical records and measuring the anthropometry of the mothers and the newborns. Bivariable and multivariable logistic regression analyses were used to identify risk factors of LBW. The outputs of the analyses are presented using adjusted odds ratio (AOR) with the respective 95% confidence interval (CI). Results: Mothers with no formal education had two times increased odds of delivering LBW babies than women with formal education [AOR = 2.20 (95% CI: 1.11, 4.38)]. Mothers with no history of nutrition counseling during pregnancy had three times increased odds of giving LBW babies than those who were counseled [AOR = 3.35 (95% CI: 1.19, 9.43)]. Non-married women had higher odds of giving LBW newborns as compared to married ones [AOR = 3.54 (95% CI: 1.83, 6.83)]. Mothers from food insecure households had about four times higher odds of LBW as compared to food secure mothers [AOR = 4.42 (95% CI: 1.02,22.25)]. In contrast to mothers who had the recommended four or more antenatal care (ANC) visits, those who were not booked had three times increased odds of giving to LBW baby [AOR = 3.03 (95% CI: 1.19,7.69)]. Conclusion: Improving the socio-economic status of mothers, enhancing the utilization of ANC and strengthening the integration of nutrition counseling into ANC help to reduce LBW.
The study was carried out in three secondary-care public hospitals – Fiche, Kuyu and Dera –found in North Shewa zone, Oromia region, central Ethiopia. As of 2016, North Shewa zone had an estimated population size of 1.5 million. The zone is administratively divided in to 13 districts and has the aforementioned 3 functional hospitals, 62 health centers, 268 health posts. In 2016, the total health facility deliveries in the zone were 38,131. Unmatched case-control study with controls-to-case ratio of 4:1 was conducted from January 01 to March 30, 2017. Singleton live births in the three hospitals during the study period, irrespective of the duration of pregnancy and mode of delivery, were considered eligible for the study. Birthweight of every child was measured and newborns who weigh less than 2.5 kg were taken as cases; whereas, a similar group of children with a birthweight of 2.5 to 4.0 Kg were categorized as a controls. Multiple births, macrosomic babies (birthweight greater than 4.0 kg), mothers or newborns in critical medical conditions and babies weighed more than an hour after birth were excluded. Optimal sample size was determined via the online OpenEpi statistical program [24]. The computation was made using double population proportion formula assuming 95% confidence level, 80% power, control-to-case quotient of 4, and odds ratio (OR) of 2 to be detected as significant. The calculation was separately made for four potential predictors (maternal age (>///< 22 cm)) of LBW and the maximum was taken as the ultimate sample size of the study. The expected proportions of controls exposed for the aformentioned factors were extracted from a study conducted in Southeastern Ethiopia [25]. Ultimately the sample size 94 cases and 376 controls was determined. Between Jan to Mar 2017, cases and controls were recruited on an ongoing basis until the required sample size was fulfilled for both groups. The data were collected by interviewing the mothers, reviewing medical records and measuring the anthropometry of the mothers and the newborns. Six trained midwives working in the delivery wards of the three hospitals collect the data using structured and pretested questionnaire prepared in Afan Oromo language. Eligible mothers were interviewed face to face within 24 h after delivery. Socio-demographic and economic information was assessed using standard questions extracted from the DHS questionnaire [26]. The medical records of the mothers were reviewed and relevant information including last-normal menstrual period and ultrasound dating of pregnancy were extracted to the questionnaire. The frequency of consumption of eleven major food groups during the pregnancy was measured using a Food Frequency Questionnaire (FFQ) based on the mothers’ recall. On the other hand, the level of household food insecurity was assessed using the Household Food Insecurity Access Scale (HFIAS) of the Food and Nutrition Technical Assistance (FANTA) project. The scale categorized the subjects into four ordinal groups – secure; mild, moderate and severe insecurity [27]. The weight of the newborns was measured within the first hour of birth using a calibrated Seca scale and rounded to the nearest 100 g. MUAC of mother was measured to the nearest 0.1 cm using MUAC tape. Anthropometric measurements were taken in duplicates by an observer and ultimately the average of the duplicates was registered. The independent variables of the study include socio-demographic factors (maternal age, education, occupation, wealth index, residence, marital status, religion, ethnicity), reproductive factors (gestational age, prior history of LBW, parity, birth-to-birth interval, utilization of antenatal care (ANC), reported illness during pregnancy), nutritional factors (maternal MUAC, household food security status, exposure to nutrition counseling during the pregnancy, frequency of consumption of major food groups, restriction of diet during pregnancy due to food taboo, history prenatal iron supplementation), work load during pregnancy and infant’s sex. The dependent variable was birthweight status dichotomized into LBW or normal birthwieght. The collected data were checked for completeness, coded and entered into Epi info version-3.5, and then exported to the Statistical Package for Social Sciences (SPSS), version 20 for analysis. Wealth index was computed as a composite indicator of living standard based on ownership of selected household assets, size of agricultural land, number of livestock owned, materials used for housing construction, and ownership of improved water and sanitation facilities. The analysis was made using the Principal Component Analysis (PCA). The generated principal component was divided into three wealth classes. The socio-demographic and other background profiles of the cases and controls were compared using chi-square test. Prior to analysis the assumptions of chi-square test were checked. When smaller expected frequencies were encountered, re-categorization of variables or merger of the levels was made. Factors associated with LBW were identified using bivariable and multivariable logistic regression models. Independent variables that demonstrated near to statistically significant association (p-value less than 0.25) with the outcome variable in the bivariable models, were considered as candidate variables for the multivariable logistic regression models. In order to reduce over adjustment bias, direct and indirect predictors of LBW were fitted separately into two multivariable models [3]. In the ultimate multivariable models the level of multicolinearity was evaluated using variance inflation factor and found within a tolerable range. The goodness-of-fit assessed using Hosmer–Lemeshow test. The study was approved by the Institutional Review Board (IRB) of College of Medicine and Health Sciences, Hawassa University. Data were collected after taking informed consent from the mothers.
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