Explanation for original studies
For this review, a total of 874 articles were searched from major medical electronic data bases and other sources. Because of duplication, 456 articles were excluded. Then after screening, 379 studies were excluded because of inconsistent with our review. The remaining 39 studies full text were assessed based on eligibility criteria and 12 articles were removed because of irrelevancy (Fig-1). Moreover, 27 full articles were critical appraised using Newcastle‒Ottawa quality assessment scale. After critical appraisal, three articles [43–45] were excluded because of poor methodological quality scored. Finally, to estimate pooled prevalence of malnutrition and its predictors among pregnant women in Ethiopia, 24 studies were considered (Fig-1). From the included articles, 23 of them were published from 2012 to 2019 whereas one of them was un-published article. These articles were from six regional state and two cities of Ethiopia. Eight studies were done in Oromo regional state [25, 26, 28, 30, 31, 33, 46, 47], six articles in Amhara region [32, 48–52], four articles from South Nation and Nationality of People (SNNP) [27, 34, 53, 54], two articles in Tigray [29, 55] and in Addis Ababa (AA) [56], Dire Dawa [57], Gambella [58] and Ethiopian Somalia [59] shared single articles for each.
In regarding to criteria to classify as malnutrition, 87.5% of the included articles use MUAC [25, 27–33, 35, 46, 48–54, 56–59] and the remaining 12.5% of the extracted studies use BMI (below 18.5 kg/cm2) [26, 47, 55]. Those studies which used MUAC, six of them considered malnutrition when MUAC below 21 cm, nine of them considered it when MUAC below 22 cm whereas the rest six considered when MUAC below 23 cm. Concerning to study design, 91.6% of the included articles were cross sectional design [26–33, 35, 46–51, 53–59] and the rest were cohort [25] and case control [52], single article for each. Thirteen studies were done institutional based while the remaining eleven were done in community.
Table 1
Descriptive summary of 24 studies included in the review of predictors of malnutrition among pregnant women in Ethiopia 2012–2019
Author | Publication year | Region | Criteria | Cutoff point | Study design | Study setting | Sample size | Prevalence % | Study participants | NOSS score |
Derso et al | 2017 | Amhara | MUAC | < 23 | Crosssectional | Institution | 348 | 35.8 | Reproductive age | 6 |
Dadi AF et al | 2019 | Amhara | MUAC | < 22 | Crosssectional | Community | 940 | 14.4 | Reproductive age | 6 |
Belete Y et al | 2016 | Oromo | MUAC | < 22 | Crosssectional | Community | 424 | 34 | Adolescent | 6 |
Behailu Z | Un-p | AA | MUAC | < 23 | Crosssectional | Institution | 342 | 34.2 | HIV positive | 5 |
Asefa et al | 2012 | Oromo | MUAC | < 23 | Cohort | Institution | 956 | 47.2 | Reproductive age | 8 |
Alemayehu A et al | 2016 | Somalia | MUAC | < 21 | Crosssectional | Institution | 360 | 18.9 | Reproductive age | 5 |
Diddana TZ | 2019 | Amhara | MUAC | < 23 | Crosssectional | Community | 604 | 19.5 | Reproductive age | 7 |
Kumera G et al | 2018 | Amhara | MUAC | < 22 | Crosssectional | Institution | 409 | 16.2 | Reproductive age | 6 |
Kefiyalew et al | 2014 | Oromo | BMI | < 18.5 | Crosssectional | Institution | 258 | 11.62 | Reproductive age | 5 |
Kedir et al | 2014 | Oromo | MUAC | < 22 | Crosssectional | Community | 1802 | 19.06 | Reproductive age | 7 |
Hailu S et al | 2019 | Oromo | MUAC | < 21 | Crosssectional | Institution | 422 | 47 | Reproductive age | 7 |
Hadgu et al | 2013 | Tigray | BMI | < 18.5 | Crosssectional | Institution | 376 | 42.3 | HIV positive | 5 |
Gizahewu A et al | 2019 | SNNPR | MUAC | < 22 | Crosssectional | Institution | 211 | 24.6 | Reproductive age | 5 |
Gebre et al | 2018 | Oromo | MUAC | < 21 | Crosssectional | Community | 900 | 24 | Reproductive age | 7 |
Endalifer et al | 2019 | Tigray | MUAC | < 22 | Crosssectional | Institution | 321 | 22.3 | Reproductive age | 6 |
Kumera et al | 2018 | Amhara | MUAC | < 22 | Crosssectional | Institution | 234 | 41 | Reproductive age | 5 |
Shiferaw et al | 2019 | SNNPR | MUAC | < 23 | Crosssectional | Community | 382 | 44.9 | Reproductive age | 6 |
Shenka et al | 2018 | Dire Dawa | MUAC | < 22 | Crosssectional | Institution | 387 | 18.2 | Reproductive age | 6 |
Serbesa et al | 2019 | Oromo | BMI | < 18.5 | Crosssectional | Institution | 304 | 30.3 | Reproductive age | 6 |
Regassa et al | 2012 | SNNPR | MUAC | < 22 | Crosssectional | Community | 1094 | 31.4 | Reproductive age | 7 |
Nigatu et al | 2018 | Gambella | MUAC | < 21 | Crosssectional | Community | 338 | 28.6 | Reproductive age | 6 |
Mariyam AF et al | 2018 | Oromo | MUAC | < 21 | Crosssectional | Community | 616 | 31.8 | Reproductive age | 7 |
Tadesse et al | 2017 | Amhara | MUAC | < 23 | Case control | Community | 448 | 30.35 | Reproductive age | 8 |
Moges et al | 2015 | SNNPR | MUAC | < 21 | Crosssectional | Community | 417 | 35.5 | Reproductive age | 6 |
In addition, eleven articles employed simple random technique to select study participants while seven of them used systematic random sampling whereas cluster and consecutive sampling method reported by two articles for each. A total of 12,893 pregnant women were included in this review. 87.5% of the included articles done on reproductive aged pregnant women [25–27, 29–33, 35, 46–54, 57–59] where as 8.3% of the articles done on HIV positive reproductive aged pregnant women [55, 56] and single study conducted among adolescent aged pregnant women [28]. All included articles had 95% and above response rate (Table-1).
In regarding risk bias assessment, 19 (79%) studies had high quality scores and 5 (21%) had low quality scores. Representation and case-definition biases were the most commonly noted. To determine the influence of low methodological quality/high risk of bias on our estimates of pooled prevalence we estimated pooled prevalence without the low-quality studies. The confidence intervals of our estimates of pooled prevalence with and without these studies overlapped, indicating no significant difference between them. These results suggest that the majority of the primary study authors have met high quality standards. This lends credibility to our findings (Appendix-1).
Pooled prevalence of malnutrition among pregnant women in Ethiopia
The pooled burden of malnutrition among pregnant women in Ethiopia was 29.07% (95% CI: 24.84, 33.30) (Fig-2). Even though there was incompatible use of criteria to classify malnutrition among pregnant women, the pooled burden were almost consistent. The pooled estimate of malnutrition among studies which considered MUAC was 29.2% 95%CI: 24, 33. Whereas among studies which used BMI was 27.9% (95%CI: 9, 46). In this review, I2 test statistics showed a significant level of heterogeneity (I2 = 90.6%, p < 0.001). Therefore, to estimate the pooled burden of malnutrition among pregnant women and to examine factors associated with it, random effect model was indicated. In addition, subgroup analysis and meta-regression were employed using different study characteristics to identify potential source of heterogeneity. Furthermore, symmetric funnel plot and Egger’s test were undertaken to assess publication bias. But, both of them were failed to indicate observed publication bias (symmetric funnel plot (Fig-3) and Egger’s test p-value = 0.439 (95% CI: 0.32, 1.545).
Subgroup analysis
Subgroup analysis was done using publication year, region, study design, study setting, sampling technique, classification criteria, study participant and sample size. Regarding to regional burden, one third of pregnant women were suffered from malnutrition in SNNPR and Amhara regional states (33.9% 95% CI: 25, 42 and 30.4% (95% CI: 17, 34 respectively). In Oromo region, 30.4% (95%CI: 21, 39) of pregnant women experienced under nutrition. The pooled prevalence of malnutrition among HIV positive pregnant women was 38.1% (95%CI: 30, 46) whereas among reproductive aged pregnant women reported 28.2% (95%CI: 23, 32) of malnutrition. According to publication year, studies published in 2017 and before reported 30.4% (95%CI: 23, 37) of pooled burden of malnutrition whereas studies published after 2017 evidenced 27.6% (95%CI: 22, 33) of malnutrition among pregnant women.
In addition, articles done in cross sectional design reported 28.2% (95%CI: 23, 32) of pooled burden of malnutrition. But, studies done in cohort and case control indicated 38.6% (95%CI: 22, 55) of pooled burden of malnutrition. Furthermore, studies selected their study participant using systematic sampling technique showed pooled prevalence of 30.7% (95%CI: 23, 38) whereas studies used simple random sampling technique evidenced 30.6% (95%CI: 25, 35) while studies used cluster and consecutive showed 24.4% (95%CI: 14, 34) of pooled prevalence of malnutrition among pregnant women in Ethiopia. Ones more, studies with sample size of < 400 reported pooled prevalence of 29.1% (95CI: 23, 35) and studies which had > 400 sample size indicated 28.9% (95%CI: 22, 35) of pooled burden of malnutrition which was almost in line with studies having < 400 sample size (Table-2).
Table 2
Sub group analysis which describes pooled prevalence of malnutrition among pregnant women with different study characteristics in Ethiopia from 2012–2019
Subgroup | | No of studies | prevalence (95%CI) | Heterogeneity statistics | I2 | p-value |
Region | Amhara | 6 | 25.9(17,34) | 58.34 | 90.4 | < 0.001 |
Oromo | 8 | 30.4(21,39) | 108.67 | 91.0 | < 0.001 |
SNNPR | 4 | 33.9(25,42) | 64.67 | 89.3 | < 0.001 |
Others | 6 | 27.2(19,34) | 17.36 | 82.7 | < 0.001 |
Publication year | 2017 and below | 10 | 30.4(23,37) | 116.18 | 90.9 | < 0.001 |
After 2017 | 13 | 27.6(22,33) | 120.95 | 89.1 | < 0.001 |
Criteria used | MUAC | 21 | 29.2(24,33) | 186.62 | 89.3 | < 0.001 |
BMI | 3 | 27.9(9,46) | 52.63 | 94.2 | < 0.001 |
Study design | Cross sectional | 22 | 28.2(23, 32) | 213.34 | 89.2 | < 0.001 |
Others | 2 | 38.6(22,55) | 10.71 | 89.6 | < 0.001 |
Sampling technique | Simple random | 11 | 30.6(25,35) | 69.75 | 85.7 | < 0.001 |
Systematic random | 7 | 30.7(23,38) | 55.66 | 89.2 | < 0.001 |
Others | 6 | 24.2(14,34) | 85.01 | 92.1 | < 0.001 |
Study participant | Reproductive age | 22 | 28.2(23,32) | 220.88 | 89.0 | < 0.001 |
HIV patient | 2 | 38.1(30,46) | 2.48 | 59.6 | 0.116 |
Sample size | < 400 | 12 | 29.1(23,35) | 123.33 | 89.1 | < 0.001 |
≥ 400 | 12 | 28.9(22,35) | 120.41 | 88.9 | < 0.001 |
Meta regression
In addition to subgroup analysis, meta-regression was done to identify potential source of heterogeneity. Both continuous and categorical study characteristics including: publication year, sample size, mean age of the women, criteria for classification, region, study design and sampling technique were considered. But none of these variables were found to be statistically significant (Table-3).
Table 3
Meta regression for the included studies to identify potential source of heterogeneity for the pooled burden of malnutrition among pregnant women in Ethiopia 2012–2019
Variables | Coefficients | p-value |
Study year | 0.3048 | 0.891 |
Sample size | -0.00087 | 0.941 |
Mean age | -0.3702 | 0.910 |
Classification criteria | | |
MUAC | 1.425 | 0.833 |
Region | | |
Amhara | -1.374 | 0.829 |
SNNPR | 6.773 | 0.348 |
Oromo | 3.209 | 0.591 |
Study design | | |
Cross section | -10.554 | 0.180 |
Sampling technique | | |
Simple random | 6.320 | 0.254 |
Systematic random | 6.470 | 0.287 |
Predictors of malnutrition among pregnant women in Ethiopia
In addition to estimating pooled prevalence of malnutrition among pregnant women in Ethiopia, this review also examined the predictors of malnutrition including: maternal age, income, residence, marital status, educational status, women decision, substance abuse, water source, toilet possession, family size, dietary diversity, number of meal, dietary advice, family planning, pregnancy intention, antenatal care follow up, parity, gestational age, any illness and iron supplementation. Among these factors, only maternal education, income, pregnancy intention, number of meal, dietary diversity, antenatal care and iron supplementation were significantly associated with the pooled prevalence of malnutrition among pregnant women in Ethiopia (Fig-4, 5&6).
The association between maternal education and malnutrition were stated in ten of the included articles [27–31, 33, 48, 54, 56, 57]. The odds of malnutrition was 1.6 times higher among illiterate pregnant women than women who had formal education (OR = 1.60, 95% CI: 1.01, 2.53).
Monthly family income was another factors significantly associated with malnutrition in which its relation described in five original studies [27, 34, 47, 48, 54]. The likely hood of malnutrition among pregnant women who had monthly income of less than 1000 Ethiopian birr was 3 times higher than their counterparts (OR = 3.07, 95% CI: 1.36, 6.92) (Fig-4).
This analysis also showed that dietary diversity was significantly associated with the pooled burden of malnutrition among pregnant women which was cited in five of original studies [27, 31, 50, 54, 57]. Pregnant women who recorded as poor dietary diversity were 2.89 times more likely to be malnutrition than pregnant women who had good dietary diversity (OR = 2.89, 95% CI: 1.28, 6.53). The overall pooled burden of malnutrition among pregnant women was significantly associated with ante natal care follow up in which its association recorded in five included articles [28, 30, 34, 50, 54]. The odds of malnutrition were 2.53 times higher among pregnant women who had no ante natal care follow up than pregnant women who had ante natal care follow up (OR = 2.53, 95% CI: 1.18, 5.42). Moreover, this review found that iron supplementation during pregnancy was protective for malnutrition among pregnant women. Its protective effect was listed in two of the included articles [29, 33]. Pregnant women who supplied with iron during pregnancy were 0.63 times risk of being malnutrition than their counterparts (OR = 0.63, 95% CI: 0.45, 0.88). So, iron supplementation had 37% of reduction in risk of malnutrition among pregnant women (Fig-5).
Furthermore, the present review evidenced that number of meal was significantly associated with malnutrition among pregnant women in which its connection stated in three original articles [27, 28, 56]. The odds of malnutrition among pregnant women who had less than tree meal per day was 4.63 times higher than pregnant women who had three and above meal per day (OR = 4.63, 95% CI: 3.00, 7.15). Ones more, the overall pooled burden of malnutrition among pregnant women was significantly associated with pregnancy intention in which its relation listed in three of included studies [31, 48, 54]. The likely hood of malnutrition among pregnant women was 1.33 times higher among women whose pregnancy was planned than pregnant women whose pregnancy was unplanned (OR = 1.33, 95% CI: 1.01, 1.37) (Fig-6).
But, including maternal age, residence, marital status, women decision, substance abuse, water source, toilet possession, family size, dietary advice, family planning, parity, gestational age and illness during pregnancy were not associated with the pooled prevalence of malnutrition among pregnant women.