The authors have declared that no competing interests exist.
Conceived and designed the experiments: SG FE MU. Analyzed the data: SG FE MU. Wrote the paper: SG FE MU.
The effects of prenatal Zinc Deficiency (ZD) and Vitamin A Deficiency (VAD) on birthweight are controversial and their interaction has not been investigated.
To assess the independent and interaction effects of prenatal zinc and vitamin A deficiencies on birthweight in rural Sidama, Southern Ethiopia.
A community-based prospective cohort study design was employed. Six hundred fifty pregnant women in their second or third trimester were randomly selected and their serum zinc and retinol concentrations were determined. About 575 subjects were successfully followed until delivery and birthweight was measured within 72 hours after delivery. The association between the exposures and birthweight was examined using log-binomial and liner regression analyses. Potential interaction between ZD and VAD was examined using Synergy Index (SI).
The mean birthweight (± standard deviation) was 2896 g (±423). About 16.5% (95% CI: 13.5–19.6%) of the babies had Low Birthweight (LBW). Prenatal ZD and VAD were not significantly associated to LBW with Adjusted Relative Risk (ARR) of 1.25 (95 CI: 0.86–1.82) and 1.27 (95% CI: 0.86–1.87), respectively. Stratified analysis on the basis of gestational trimester showed that the occurrence of the deficiencies neither in the second nor third trimester were associated to LBW. The deficiencies did not show synergetic interaction in causing LBW [SI = 1.04 (95% CI: 0.17–6.28)]. Important risk factors of LBW were maternal illiteracy [RR = 1.80 (95% CI: 1.11–2.93)], female sex of the newborn [RR = 1.79 (95% CI: 1.19–2.67)], primiparity [RR = 1.16 (95% CI: 1.02–1.35)], short maternal stature [RR = 1.63 (95% CI: 1.06–2.51)] and maternal thinness [RR = 1.52 (95% CI: 1.03–2.25)]. In the linear regression model, elevated CRP was also negatively associated to birthweight.
LBW is of public health significance in the locality. The study did not witness any independent or interaction effect of prenatal ZD and VAD on birthweight.
Low birthweight (LBW) is the single most important predictor neonatal survival and a significant determinant of post-neonatal infant mortality, childhood morbidity and cognitive development
In Ethiopia a handful of studies attempted to determine the prevalence of LBW. A community-based study in Southwestern Ethiopia found 10% prevalence
Studies endeavored to evaluate the effect of prenatal zinc supplementation on birthweight concluded equivocally. A recent meta-analysis of Randomized Control Trials (RCTs) concluded that taking zinc during pregnancy does not prevent LBW but slightly reduces preterm birth
Pertaining vitamin A, a meta-analysis concluded that prenatal vitamin A supplementation does not significantly reduce risk of LBW
The purpose of the current study is to investigate the independent and interaction effects of prenatal zinc and vitamin A deficiencies on birthweight in rural Sidama, Southern Ethiopia. The study also assessed the prevalence and general determinants LBW. Despite the existence of many RCTs and observational studies which evaluated the effect of prenatal zinc and vitamin A status on birthweight, the current study is worth documentable as it has been conducted in area with high prevalence of zinc and vitamin A deficiencies. Further the potential interaction effect of the two deficiencies on birthweight had not been studied before.
The study was conducted based on cohort data of 575 pregnant women in the aforementioned locality. Earlier, another article
This is a community-based prospective cohort study. Pregnant women were classified based on their prenatal serum zinc and vitamin A statuses and followed until birth. Birthweight was measured within 72 hours of birth.
The study was conducted from January to October 2011 in 18 randomly selected rural kebeles of Sidama zone, Southern Ethiopia. A kebele is the smallest administrative unit in Ethiopia comprising roughly 1000 households. In Sidama zone, of the total population nearing three million, 95% dwells in rural areas. The livelihood of 85% of the population depends on subsistent farming. Nearly half of the population lives in the midlands (1750 to 2300 m above sea level (ASL)); whereas 30% and 20% dwell in the highlands (>2300 m ASL) and lowlands (<1750 m ASL), respectively. On average a household in Sidama has 4.9 dwellers, 0.3 hectares of land and 0.5 heads of livestock. The detail description of the study area has been given elsewhere
Pregnant women whose zinc and vitamin A statuses were determined at their second or third trimester and who later gave singleton live-births were eligible for the study. Babies visited after 72 hours of birth were excluded. Women whose exposure was determined in the first trimester were also excluded as the fetal weight gain in first trimester is known to be minimal. Flowchart of the cohort from exposure assessment to outcome ascertainment is given as follows (
The baseline study was designed to enroll 750 pregnant women. The basis of the sample size calculation has been given elsewhere
As described elsewhere
As described in the previous paper
The occurrence of births in the cohort were promptly identified and reported by prearranged local community health promoters and birthweight was measured within 72 hours of birth by trained health extension workers. Weight was measured to the nearest 100 g using calibrated Docbel BRAUN® scale.
Blood samples were collected, stored, transported and processed following standard procedures. Six ml of blood was collected from antecubital vein using plain and closed SARSTEDT® blood collection system and stainless steel needles. The blood was allowed to clot for 20 minutes and centrifuged at 3000 rotations per minute for 10 minutes. Serum was extracted into screw-top vials within 40 minutes of sample collection. During this time few obviously hemolyzed samples were identified and discarded. In the entire process, the samples were protected from dust and direct light. In the field the samples were kept in icebox. The same day they were transported in icebox and kept frozen at −20°C until analyzed.
Serum zinc and retinol concentrations were determined at Ethiopian Health and Nutrition Research Institute using Varian SpectrAA® Flame Atomic Absorption Spectrometer and Shimadzu® High Performance Liquid Chromatography, respectively. C-Reactive Protein level (CRP) was determined qualitatively using latex HumaTex® kit.
Data entered, screened and principally analyzed using SPSS 19.0. Additional analysis was made via STATA/SE 11.0. Independent t-test and one-way Analysis of Variance (ANOVA) were used to compare birthweight across categories of independent variables. Two of the major assumptions of ANOVA (homoscedasticity and normality of the dependent variable) were checked to be satisfied.
Wealth index was computed using Principal Component Analysis (PCA) as a composite indicator of living standard. A total of 23 variables related to ownership of selected household assets, size of agricultural land, quantity of livestock, materials used for housing construction, and ownership of improved water and sanitation facilities were considered for the analysis. Ultimately, seven principal components having eigenvalues greater than one were identified. Wealth index value was calculated by summing up the scores for the seven principal components. Ultimately, the five categories (poorest, poorer, middle, richer, and richest) were generated by splitting the wealth index values into 5 equal classes.
Log-binomial regression was used to control confounders and to model the risk LBW as function of multiple factors. In accordance with the framework of Kramer
Linear regression analysis was also used to control confounders and to assess the association between birthweight and various covariates. However, in this case only the direct factors were modeled as the r-squared value for indirect factors was found to be low. As the case of the log-binomial model, independent variables that turned out to be significant in bivariate linear models were considered for multivariate analysis. The major assumptions of the analysis (normality, homoscedasticity and independence error terms, linearity between dependent and independent variables and absence of multicollinearity) were not violated. The fitness of the multivariate model was assessed using the adjusted r-squared value.
Potential interaction between ZD and VAD in causing LBW was measured on additive scale. The additive scale is preferred as it is known to be correlated with biological interaction
The study was conducted in confirmation of national and international ethical guidelines for biomedical research involving human subjects. Ethical clearance was secured from the institutional review board of Addis Ababa University. Informed written consent was taken from the study subjects. Nutrition education was given to all subjects and anemic women were given iron-folate supplementation.
Of 650 eligible pregnant women followed, 575 (88.5%) were included in the ultimate analysis. The exclusion was on the bases of loss to follow-up (34), birthweight measurement taken after 72 hours of birth (22), fetal loss (9), multiple birth (6) and early neonatal death (4). The retained and excluded subjects were not statistically different in terms of wealth index, agro-ecological zone, literacy, CRP status, maternal height, maternal MUAC, prenatal serum zinc and retinol concentrations
Key variables | Excluded subjects (n = 75) | Retained subjects (n = 575) | Test statistic and |
Wealth index | |||
Poorest | 17 | 112 | |
Poorer | 12 | 105 | |
Middle | 18 | 125 | |
Richer | 13 | 119 | |
Richest | 15 | 114 | |
Agro-ecological zone | |||
Lowlands | 22 | 122 | |
Midlands | 36 | 299 | |
Highlands | 17 | 154 | |
Literacy | |||
Literate | 26 | 194 | |
Illiterate | 49 | 381 | |
CRP status | |||
CRP positive | 7 | 50 | |
CRP negative | 68 | 525 | |
Mean (± sd) maternal height (cm) | 155.7±5.9 | 156.5±6.9 | t = 0.893, |
Mean (± sd) maternal MUAC (cm) | 22.4±2.2 | 22.4±1.9 | t = 0.296, |
Mean (± sd) serum retinol (µmol/l) | 0.88±0.38 | 0.82±0.42 | t = 1.239, |
Mean (± sd) serum zinc (µmol/l) | 8.26±1.50 | 7.91±1.51 | t = 1.926, |
During the baseline survey 304 (52.9%) and 271 (47.1%) of the women were in their second and third gestational trimesters. Their mean age (± standard deviation) was 28.5 years (±5.4). Nearly half, 299 (52.0%), were from the midlands and the remaining 154 (26.8%) and 122 (21.2%) were from the highlands and lowlands, respectively. About two-third, 381 (66.3%), were illiterates and four-fifth, 462 (80.3%), were housewives. Among babies weighed, 289 (50.3%) were males.
The mean birthweight (± standard deviation) was 2896 g (±423). About 16.5% (95% CI: 13.5–19.6%) of the babies were born with LBW.
Maternal literacy showed affirmative influence on birthweight. Weight of babies born to literates (3023 g±428) was significantly higher than illiterates (2831 g±405)
On average, male babies weigh more than females by 103 g (95% CI: 34–172 g)
Variables | Birthweight | Crude RR | Adjusted RR | |
Low | Normal | |||
Women involvement in IGA | ||||
Yes | 6 | 69 | 1r | 1r |
No | 89 | 411 | 2.23 (1.01–4.90)* | 2.07 (0.94–4.55) |
Literacy | ||||
Literate | 19 | 175 | 1r | 1r |
Illiterate | 76 | 305 | 2.04 (1.27–3.27)* | 1.80 (1.11–2.93)* |
Wealth index quintiles | ||||
Poorest | 26 | 86 | 1.89 (1.04–3.43)* | 1.52 (0.83–2.78) |
Poorer | 20 | 85 | 1.55 (0.83–2.91) | 1.27 (0.68–2.41) |
Middle | 20 | 105 | 1.30 (0.69–2.46) | 1.13 (0.60–2.13) |
Richer | 15 | 104 | 1.03 (0.52–2.03) | 0.93 (0.47–1.83) |
Richest | 14 | 100 | 1r | 1r |
Two-way walking distance from the nearby health facility | ||||
0–30 minutes | 80 | 411 | 1r | - |
Longer than 30 minutes | 15 | 69 | 1.10 (0.66–1.81) | - |
Staple diet | ||||
Enset (Enset ventricosum) based | 59 | 302 | 1r | - |
Cereal based | 36 | 178 | 1.03 (0.71–1.50) | - |
Sex of the baby | ||||
Male | 32 | 256 | 1r | 1r |
Female | 63 | 223 | 1.98 (1.34–2.94)* | 1.79 (1.19–2.67)* |
Parity | ||||
Primipara | 24 | 65 | 1.23 (1.07–1.40)* | 1.16 (1.02–1.35)* |
Parous | 71 | 415 | 1r | 1r |
CRP status during pregnancy | ||||
Negative | 78 | 447 | 1r | 1r |
Positive | 17 | 33 | 2.29 (1.48–3.54)* | 1.26 (0.76–2.09) |
MUAC | ||||
≥220 mm | 49 | 368 | 1r | 1r |
<220 mm | 46 | 112 | 2.08 (1.45–2.99)* | 1.52 (1.03–2.25)* |
Maternal height | ||||
≥145 cm | 71 | 429 | 1r | 1r |
<145 cm | 24 | 51 | 2.25 (1.52–3.34)* | 1.63 (1.06–2.51) * |
Maternal age | ||||
15–24 years | 21 | 106 | 1.09 (0.58–2.02) | - |
25–34 years | 60 | 296 | 1.11 (0.65–1.89) | - |
35–49 years | 14 | 78 | 1r | - |
Agro-ecological zone | ||||
Lowlands | 14 | 108 | 0.87 (0.58–1.32) | - |
Midlands | 51 | 248 | 0.59 (0.32–1.06) | - |
Highlands | 30 | 124 | 1r | - |
ANC during the pregnancy | ||||
Yes | 51 | 231 | 1r | - |
No | 44 | 249 | 0.83 (0.57–1.20) | - |
The weight of babies born to women who had elevated CRP during pregnancy (2748 g±429) was significantly lower than their counterparts (2910 g±429)
Stunting (height <145 cm
The risk of LBW was not significantly different across categories of maternal age, agro-ecological zone, ANC follow up, type of staple diet and distance from the nearby health facility (
Standard cutoff points were applied to define prenatal ZD (serum zinc <7.6 µmol/l
Variables | Birthweight | Crude RR | Adjusted RR | |
Low | Normal | |||
Vitamin A status | ||||
Normal | 48 | 299 | 1r | 1r |
Deficient | 47 | 181 | 1.49 (1.03–2.15)* | 1.25 (0.86–1.82) |
Zinc status | ||||
Normal | 34 | 225 | 1r | 1r |
Deficient | 61 | 255 | 1.47 (1.01–2.16)* | 1.27 (0.86–1.87) |
Zinc-VA interaction | ||||
Normal zinc and Normal VA | 20 | 155 | 1r | 1r |
Zinc deficient and VA normal | 28 | 144 | 1.42 (0.84–2.43) | 1.30 (0.72–2.31) |
VA deficient and zinc normal | 14 | 70 | 1.46 (0.78–2.74) | 1.31 (0.66–2.61) |
Zinc deficient and VA deficient | 33 | 111 | 2.01 (1.20–3.34)* | 1.76 (1.00–3.11) |
Previous studies witnessed the likelihood of trimester specific effects of micronutrient deficiencies on birthweight
In order to investigate the possibility of synergetic interaction of the two deficiencies in causing LBW, the study subjects were categorized into four groups based on vitamin A and zinc deficiency statuses and analyzed accordingly (
In the bivariate linear regression model altitude of the kebeles, number of ANC visits, diastolic blood pressure during pregnancy were not associated to birthweight
The final model explained 20.9% of the variability in birthweight (
Variables | Unstandardized Coefficients | Standardized Coefficients | t | P | |
Beta | SE | Beta | |||
Constant | −871.3 | 416.6 | −2.092 | 0.037 | |
Sex (0 = Female, 1 = Male) | 101.7 | 31.8 | −0.120 | −3.194 | 0.001 |
Nullyparous (0 = Primipara, 1 = Parous) | 128.7 | 51.9 | 0.110 | 2.481 | 0.013 |
Maternal age (years) | 3.7 | 3.4 | 0.049 | 1.091 | 0.276 |
Serum zinc (µg/dl) | 1.6 | 1.6 | 0.037 | 0.977 | 0.329 |
Serum retinol (µmol/l) | −0.1 | 1.4 | −0.003 | −0.086 | 0.932 |
Body height (cm) | 10.8 | 2.4 | 0.172 | 4.458 | 0.000 |
CRP (0 = Positive, 1 = Negative) | 180.2 | 63.7 | 0.107 | 2.830 | 0.005 |
MUAC (cm) | 70.5 | 8.9 | 0.305 | 7.941 | 0.000 |
significant variables in the model.
LBW is considered as a problem great enough to trigger public health action when its incidence exceeds 15%
Due to the community-based nature of the study it was only possible to weigh newborns within 72 hours of birth. As birthweight is known to decline by 5–7% in the first three days of life
In Ethiopia very few studies attempted to determine the prevalence of LBW. Most were conducted in major referral hospitals. The reported prevalence figures ranged from 8.6 to 15.4%
The study did not witness significant association between prenatal zinc status and infants' birthweight. The finding is in confirmation of the conclusion a meta-analysis that maternal zinc supplementation does not enhance birthweight
Observational studies on the relationship between maternal vitamin A and birthweight in apparently health subjects concluded divergently. A study in Israel reported that cord retinol along with gestational age explained more than a quarter of the variability of birthweight
In the current study the concurrent presence of VAD and ZD during pregnancy showed marginally insignificant effect on LBW (95% CI of 1.00–3.11). Nevertheless, it is important to interpret the finding in consideration of the fact that the sample size of the study was only calculated for the evaluation of the independent effect of the deficiencies on birthweight. Hence, in the measurement of the joint effects of the deficiencies on birthweight, the power of the study might have been compromised. Accordingly, in this area, further studies with optimal sample size are evidently required.
The fact that maternal zinc and retinol concentrations were measured only once during the entire pregnancy can potentially over or under estimate their association with birthweight as the exposure status to the deficiencies might not be fixed. Nevertheless, among women who were at their second gestational trimester during the baseline survey, follow-up survey conducted during their third trimester showed no significant change in their dietary diversity, food frequency and consumption of animal source foods. This might be taken as supporting evidence that their exposure status had not been assorted remarkably.
The linear regression model explained merely 20% of the variability in birthweight. This might have happened as some of the key predictors of low birthweight like weight gain during pregnancy, pre-pregnancy weight and malaria during pregnancy were missed from the model. A study showed that in the developing world the aforementioned factors can roughly explain 40% of the variability of birthweight
Further, both in the linear and log binomial models, gestational duration has not been included as a covariate despite the fact that it is an important predictor of birthweight. This was due to the obvious difficulty of measuring gestational age in rural areas of developing countries where access to ultrasound is limited and estimation based the date of last menstrual period lacks accuracy. The exclusion of the variable from the regression analyses might have compromised the comprehensiveness of the models.
Several studies witnessed the positive contribution of superior household wealth status in reducing the burden of LBW
In the current study male babies weigh more than females by about 100 gm and the risk of LBW was 1.8 times raised in females. Previous studies in Ethiopia and abroad concluded likewise
Both in the log-binomial and linear regression models maternal MUAC was a strong correlate of birthweight. Especially in the linear model, removing the variable from the equation reduces the r-squared value from 21% to 12%. Even the study might have underestimated the association as pregnant women are commonly enrolled into supplementary and therapeutic feeding programs based on their MUAC. Studies in India
Maternal height was also a strong predictor of birthweight. This is consistent to the understanding that in the developing world approximately 12% of low birthweight can be explained by maternal short stature
Unlike several studies that witnessed the beneficial effect of ANC in reducing the burden of LBW
In the linear regression model elevated CRP during pregnancy was an important predictor of birthweight. The finding is in confirmation of the result of a systematic review that in the developing world approximately 4% of the burden of LBW is attributed to general illnesses during pregnancy and an extra 10% can be linked to malaria
The prevalence of low birthweight was 16.5%. LBW is of public health significance in the locality. Prenatal vitamin A and zinc deficiencies occurring in the second or third trimesters were not associated with increased risk of LBW. Similarly, the two deficiencies did not show synergetic interaction in causing LBW. Important risk factors of LBW were maternal thinness and stunting, primiparity, female sex of newborn and elevated CRP.
Special thanks go to all study subjects who volunteered for the study. The authors acknowledge Ethiopian Health and Nutrition Research Institute for conducting the laboratory analyses.