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. 2019 Nov 21;14(11):e0225148. doi: 10.1371/journal.pone.0225148

Magnitude and factors associated with anemia among pregnant women attending antenatal care in Bench Maji, Keffa and Sheka zones of public hospitals, Southwest, Ethiopia, 2018: A cross -sectional study

Tesfaye Abera Gudeta 1,*, Tilahun Mekonnen Regassa 2, Alemayehu Sayih Belay 1
Editor: Russell Kabir3
PMCID: PMC6872185  PMID: 31751368

Abstract

Background

Anemia during pregnancy is a common public health problem globally and it defined as the hemoglobin concentration of less than 11 g/dl. Anemia during pregnancy has maternal and perinatal diverse consequences and it increase the risk of maternal and perinatal mortality. The aim of this study is to assess magnitude and factors associated with anemia among pregnant women attending antenatal care in Bench Maji, Keffa and Sheka zones of public hospitals, South west, Ethiopia, 2018.

Methods

A cross-sectional study was employed on 1871 pregnant mothers from selected hospitals. All third trimester pregnant women attending antenatal care at Mizan-Tepi University Teaching Hospital, Tepi, Gebretsadik Shawo and Wacha public hospitals were included in the study. Data was entered to Epidata version 3.1 and exported to SPSS version 21 for analysis. Logistic regression analysis was carried out to identify independently associate factors at confidence interval of 95% and significance level of P-value <0.05.

Result

The magnitude of anemia in this study from the total study participant was 356 (19.0%). Among anemic pregnant women, 330 (92.7%), 21(5.9%) and 5(1.4%) were mild anemia, moderate anemia and severe anemia respectively. Age group 20–24 [AOR 6.28(2.40–16.42)], 25–29 [AOR = 6.38 (2.71–15.01)], 30–34 [AOR = 5.13 (2.27–11.58) and age ≥35 years [AOR = 2.53 (1.07–5.98)], educational status (read and write) [AOR 2.06, 95% CI (1.12–3.80)], gestational age(term)[AOR 1.94, 95% CI (1.27–2.96)], Caffeine (coffee and tea) and alcohol use occasionally [AOR 2.01, 95% CI (1.14–3.55)] and [AOR 2.59, 95% CI (1.49–4.52)] respectively, nutritional status (under nutrition) [AOR 3.00, 95% CI (2.22–3.97)] and family size (>6) [AOR 2.66, 95% CI (1.49–4.77)] were factors associated with anemia.

Conclusion

The magnitude of anemia found to be high. Age, educational status of the mother, gestational age, caffeine and alcohol use, Nutritional status and family size were factors significantly associated with anemia. To prevent adverse outcome of anemia, health care providers should work on these factors.

Introduction

World Health Organization (WHO) has defined anemia during pregnancy as the hemoglobin concentration of less than 11 g/dl [1]. Depending on hemoglobin concentration, anemia during pregnancy is classified as severe if the hemoglobin level is less than 7.0 g/dl, moderate when it falls between 7.0–9.9 g/dl, and mild from 10.0–11 g/dl [2–4]. The symptoms and signs of anemia are vague and nonspecific, including pallor, easy fatigability, headache, palpitations, tachycardia, and dyspnea. Angular stomatitis, glossitis, and koilonychia (spoon nails) may be present in long-standing severe anemia [5].

According to WHO, anemia is considered of a severe public health implication if its rate of ≥40% [6]. Anemia during pregnancy is a main public health problem worldwide, particularly in developing countries where there is inadequate diet and poor prenatal vitamins and iron and folic acid intake[7] and it affects the physical health and mental development of individual causing low productivity and poor economic development of a country[7,8].

Globally, every year anemia causes more than 115,000 maternal and 591,000 perinatal deaths [3]. Worldwide, anemia affects more than half billion reproductive age women [9–12]. It is the most common problem during pregnancy, therefore, 56% of pregnant women in low and middle income countries have anemia. Because of this reason, anemia during pregnancy contributes to 23% of indirect causes of maternal deaths in developing countries [8].

The prevalence of anemia was found be highest among pregnant women in developing countries, particularly in sub- Sahara Africa (57%), in South-East Asia (48%) and lowest prevalence (24.1%) was reported among pregnant women in South America [6].

Anemia in pregnancy has maternal and perinatal diverse consequences and it increase the risk of maternal and perinatal mortality [13, 14]. It also brings different obstetrical problems like; prematurity, low birth weight[15], abortion, intrauterine fetal death and perinatal mortality [16] and other maternal health problems like; impaired immune function, poor work capacity, fatigue, increased risk of cardiac diseases and mortality[8,14].

Even though there is different contributing factors for anemia like genetic, nutritional, and infectious disease factors, iron deficiency is the most common cause of 75% of anemia cases [8,17–20]. Iron deficiency anemia is common in pregnant women and it affects the development of the once country through decreasing the physical and cognitive development of children and productivity of adults [20].

The prevalence of anemia in pregnancy has remained unacceptably high and still it is a major public health concern in Ethiopia despite the fact that routine iron and folic acid supplementation during pregnancy was provided by the skilled providers [21]. This is due to the fact that poor nutritional intake, repeated infections, menstrual blood loss, and frequent pregnancies are common in Ethiopia which is associated with poor socio economic conditions during pregnancy [22, 23] and poor antenatal care follows up during pregnancy [24].

In Ethiopia, about 17% of reproductive age women are anemic and 22% of them were pregnant [25]. Despite its known adverse effect on the pregnant women and children, there is no updated data available in the study area. Since no study was conducted in the study area, the finding of this study will be important to design appropriate interventions to reduce the high burden of the disease in the area and country at large. Therefore, this study is aimed at determining the magnitude of anemia in pregnant women and identifying its associated factors in the hospitals of Bench Maji, Keffa and Sheka zones Southwest Ethiopia.

Methods and materials

Study area and period

The study was conducted in public hospitals of Bench Maji, Sheka and Keffa zones namely, Mizan Tepi University teaching hospital (MTUTH), Tepi general hospital, Wacha hospital and Gebretsadik Shawo hospital from January 15- March 30/2018. MTUTH is located in Bench Maji zone on 560 kms from Addis Ababa. The two hospitals: Gebretsadik Shawo and Wacha hospitals are found in kefa zone at a distance of 441 and 520 kms away from Addis Ababa respectively, while Tepi general hospital is located in Sheka zone, 565 Kms away from capital city of Ethiopia, Addis Ababa.

Study design

Facility based cross-sectional study design was used.

Source and study population

All pregnant women who attending antenatal care at MTUTH, Tepi hospital, Gebretsadik Shawo hospital and Wacha hospital were considered as source of population and all pregnant women those fulfilled the inclusion criteria were considered as study population.

Inclusion and exclusion criteria

All third trimester pregnant women attending antenatal care at MTUTH, Tepi, Gebretsadik Shawo and Wacha public hospitals were included in the study; however pregnant women who were critically ill and unable to communicate during data collection were excluded from the study.

Sample size determination

The sample size was determined by using a single population proportion sample size calculation formula considering the following assumptions. d = margin of error of 2% with 95% confidence interval, estimated prevalence of anaemia is 23% [26] and considering non response rate of 10%. Then the final sample size became 1871.

Sampling technique

All hospitals found in three zones were included in the study. The total sample size (1871) was allocated to the four public hospitals. The sample size allocation was based on the source of population from each hospital. The source of population of each hospital was taken from antenatal follow up report. Then the average was considered as source of population. The study participants were consecutively taken from each hospital until the sample size was achieved.

Operational definitions and definition of terms

Anemia in pregnancy: In this study, anemia defined as hemoglobin level less 11 g/dl during third trimester. Woman with hemoglobin less 11g/dl was coded 1 whereas woman who was not anemic coded as 0.

Pregnant women are classified as non-anemic if hemoglobin ≥11.0 g/dl, mild anemic if the range is 10 to 10.9 g/dl, moderate anemic if the range is 7 to 9.9 g/dl and severely anemic if hemoglobin is below 7.0 g/dl.

Data collection instruments/tool

The data was collected using pre-tested questionnaire and anthropometric measurements. The questionnaire was developed based on tools that were applied in different related literatures (12–18). Questionnaires were developed in English and translated to Amharic by experts and translated back to English to see consistency of the question. The questionnaire contains sections for assessing anemia, demographics and associated factors.

Data collectors

Twelve data collectors who bachelor degree holder midwives were recruited. Four supervisors who had master degree holders in maternal health were recruited.

Data collection procedure

Data was collected through face to face interview, measurements and reviewing of medical record of the mother by using pre-tested structured questionnaire and check list by trained data collectors. Last normal menstrual period (LNMP) was confirmed from her chart and client report. Gestational age was calculated based on the last normal menstrual period (LNMP).

When LNMP-based gestational age is unknown, we relied on obstetric ultrasonography measures. Nutritional status was assessed by using Mid-upper arm circumference (MUAC) measurement. MUAC < 21cm considered as undernourished.

Data processing and analysis

EPI data Statistical software version 3.1 and Statistical Package for Social Sciences (SPSS) software version 21.0 was used for data entry and analysis. After organizing and cleaning the data, frequencies & percentages was calculated to all variables that are related to the objectives of the study. Variables with P- value of less than 0.25 in binary logistic regression analysis was entered into the multivariable logistic regression analysis to control confounds so that the separate effects of the various factors associated with anemia could be assessed. Odds ratio with 95% confidence interval was used to examine associations between dependent & independent variables. P value less than 0.05 was considered significant. Finally the result was presented by using tables, charts and narrative form.

Data quality control measures

The quality of the data was assured by using validated pre-tested questionnaires. Prior to the actual data collection, pre-test was done on 5% of the total study eligible subjects and have similar characteristics at Mizan health center and necessary amendments was made.

The validity of the tool was checked by face validity. Data collectors were trained intensively on the study instrument and data collection procedure that includes the relevance of the study, objective of the study, confidentiality, informed consent and interview technique. The data collectors worked under close supervision of the supervisors to ensure adherence to correct data collection procedures.

Supervisors checked the filled questionnaires daily for completeness. Every morning, supervisors and data collectors conducted morning session to solve if there is any faced problem as early as possible and to take corrective measures accordingly. Moreover, the data was carefully entered and cleaned before the beginning of the analysis.

Ethical considerations

Ethical approval was obtained from Mizan-Tepi University. Further permission was obtained from each hospital. After explaining the objectives of the study in detail, written informed consent was taken from all study participants.

Result

Socio-demographic characteristics

All the sampled mothers were participated (100% response rate). A total of 853(45.6%) participants were rural residents, 481(25.7%) were illiterates, 1808(96.7%) were married, 483(79.3%) were house wives and the family size of 1421(75.9%) participants were four children or less (Table 1).

Table 1. Socio-demographic characteristics of women attending antenatal care in public hospitals of Benchi-Maji, Kaffa and Sheka zones, Southwest Ethiopia, 2018.

Variables Category Frequency Percent (%)
Age 15–19 168 9.0
20–24 808 43.2
25–29 547 29.2
30–34 221 11.8
35+ 127 6.8
Residence Rural 853 45.6
Urban 1018 54.4
Educational status Unable to read and write 481 25.7
Able to read write 393 21.0
Primary education 609 32.5
Secondary education 246 13.1
College and above 142 7.6
Marital status Married 1808 96.7
Single 36 1.9
Divorced 5 0.3
Widowed 10 0.5
Separate 12 0.6
Religion Orthodox 837 44.7
Muslim 387 20.7
Protestant 637 34.0
Other 10 0.5
Occupation Housewife 1483 79.3
Merchant 170 9.1
Gov’t employee 117 6.3
Non-gov’t employee 18 1.0
Daily labor 83 4.4
Family size ≤4 1421 75.9
5–6 347 18.5
≥7 103 5.5
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Variables related to obstetric characteristics

Around half 834 (44.6%) of the study participants were primigravida and almost all 1785(95.4%) of the pregnancy were intended and also 1700 (90.9%) of the pregnancies were term pregnancy.

Majority 1726 (92.3%) of the participants have antenatal care (ANC) follow-up and only 424(25.1%) of participants were started antenatal follow up during their first trimester. And also the majority 1570 (83.9%) were take iron foliate during current pregnancy (Table 2).

Table 2. Variables related to obstetric characteristics among women attending ANC in public hospitals of Benchi-Maji, Kaffa and Sheka zones, Southwest, Ethiopia, 2018.

Variables Category Frequency Percent (%)
Gravida 1 834 44.6
2–4 944 50.5
>4 93 5.0
Parity Primiparous 883 47.2
Multiparous 988 52.8
Pregnancy status Intended 1785 95.4
Unintended 86 4.6
Gestational age Less than 37 weeks 171 9.1
≥ 37 weeks 1700 90.9
ANC follow-up Yes 1726 92.3
No 145 7.7
Among mothers who have ANC follow up, At what month ANC started? 1–3 months 424 25.1
4–6 months 1185 70.0
7–9 months 83 4.9
Number of ANC visit One visit 86 5.0
Two visit 168 9.7
Three 423 24.5
Four and above visit 1049 60.8
Iron foliate intake Yes 1570 83.9
No 301 16.1
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Variables related to pregnancy complication and medical illness

A total of 252(13.5%) of participants developed pregnancy-related complication during current pregnancy, 78 (31%), 31(12.3%),21 (8.3%), and 52 (20.6%) were developed preeclampsia, placenta previa, abruptio placenta and antepartum hemorrhage respectively. A total of 281 (15%) faced medical illness during current pregnancy. 1357(72.5%) women were not malnourished based on their mid-upper arm circumference (MUAC) measurement (Table 3).

Table 3. Variables related to pregnancy complication and medical illness among women attending ANC in public hospitals of Benchi-Maji, Kaffa and Sheka zones, Southwest, Ethiopia, 2018.

Variables Category Frequency Percent (%)
Complications on current pregnancy Yes 252 13.5
No 1619 86.5
Pregnancy related complications
 Gestational hypertension Yes 5 2
No 247 98.0
Preeclampsia Yes 78 31
No 174 69.0
Eclampsia yes 36 14.3
No 216 85.7
Placenta Previa Yes 31 12.3
No 221 87.7
Abruptio placenta Yes 21 8.3
No 231 91.7
Antepartum hemorrhage Yes 52 20.6
No 200 79.4
Medical related illness on current pregnancy Yes 281 15.0
No 1590 85.0
Medical illnesses Malaria Yes 156 8.3
No 1715 91.7
HIV Positive 51 2.7
Negative 1820 97.3
ART* status Started 51 100
Nutritional status (Using MUAC*) Under nutrition (MUAC<21cm) 514 27.5
Normal 1357 72.5
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*ART = Anti-Retroviral Treatment

MUAC = Mid-Upper Arm Circumference

Variables related to behavioral factors

From the total study participants, 1516 (81%) used to drink caffeine (coffee and tea) on a daily basis, and 1272 (68.0%) were never drinking alcohol. Regarding the nutritional status 1252 (66.9%) and 1210 (64.7%) were get dietary counseling and additional diet during current pregnancy respectively (Table 4).

Table 4. Variables related to behavioral factors among women attending ANC in public hospitals of Benchi-Maji, Kaffa and Sheka zones, Southwest, Ethiopia, 2018.

Variables Category Frequency Percent (%)
Caffeine intake (coffee & tea) during index pregnancy Never 167 8.9
Daily 1516 81.0
Weekly 28 1.5
Occasionally 160 8.6
Alcohol intake during index pregnancy Never 1272 68.0
Daily 27 1.4
Weekly 86 4.6
Occasionally 486 26.0
Mother counseled on dietary practice during current pregnancy Yes 1252 66.9
No 619 33.1
Get additional diet during current pregnancy Yes 1210 64.7
No 661 35.3
Mothers faced physical harassment during current pregnancy
 Yes 129 6.9
No 1742 93.1
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Magnitude of anemia

The magnitude of anemia in this study from the total study participants (1871) was about 356 (19.0%) at 95 CI (17.2%-20.7%). Among anemic pregnant women, 330 (92.7%), 21(5.9%) and 5(1.4%) were mild anemia, moderate anemia and severe anemia respectively (Fig 1).

Fig 1. Magnitude of anemia among women attending antenatal care in Bench Maji, Keffa and Sheka zone of public hospitals, Southwest Ethiopia, 2018.

Fig 1

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This figure shows that the magnitude of anemia in pregnancy which was 19.0%.

Factors associated with anemia

Mothers who in age group 20–24 [AOR 6.28 (2.40–16.42)], 25–29 [AOR = 6.38 (2.71–15.01)], 30–34 [AOR = 5.13 (2.27–11.58) and ≥35 years [AOR = 2.53 (1.07–5.98)] were more likely developed anemia as compared to younger age group (15–19). Mothers who have no formal education but read and write were two times more likely to have anemia as compared to mothers whose educational level of diploma and above [AOR 2.06, 95% CI (1.12–3.80)]. A pregnant mother who has gestational age ≥37weeks were two times more likely faced anemia as compared to preterm pregnancy [AOR 1.94, 95% CI (1.27–2.96)]. Pregnant mother who occasionally used caffeine (coffee and tea) and alcohol were two [AOR 2.01, 95% CI (1.14–3.55)] and two & half [AOR 2.59, 95% CI (1.49–4.52)] respectively times more likely developed anemia as compared to mothers never used this substance. Under nourished pregnant women were three times more likely developed anemia as compared to mothers who were well nourished in their nutritional status [AOR 3.00, 95% CI (2.22–3.97)]. Mothers who have larger family size (>6) were three times more likely faced anemia as compared to small family size [AOR 2.66, 95% CI (1.49–4.77)] (Table 5).

Table 5. Factors associated with anemia among mothers attending antenatal care in public hospitals of Benchi-Maji, Kaffa and Sheka zones, Southwest, Ethiopia, 2018.

Variable Category Anemia COR (95% CI) AOR (95% CI)
No Yes
Age 15–19 132 36 1 1
20–24 649 159 0.90(0.60–1.35)
0
0)
0		 6.28 (2.40–16.42) *
25–29 430 117 0.99(0.66–1.52) 6.38 (2.71–15.01)*
30–34 188 33 0.64(0.38–1.09) 5.13 (2.27–11.58)*
35+ 116 11 0.35(0.17–0.71) 2.53 (1.07–5.98)*
Residence Rural 647 206 0.54(0.43–0.69) 1.37(0.98–1.92)
Urban 868 150 1 1
Educational status Cannot read and write 355 126 2.30 (1.36–3.88) 1.73(0.923–3.23)
Read and write 301 92 1.98 (1.16–3.38) 2.06(1.12–3.80)*
Primary education 535 74 0.90(0.52–1.54) 0.87(0.48–1.62)
Secondary school 201 45 1.45(0.81–2.59) 1.70(0.89–3.26)
Diploma and above 123 19 1 1
Parity Primiparous 740 143 1 1
Multiparous 775 213 1.42 (1.13–1.80) 1.40 (0.99–1.98)
Gestational age Preterm (<37weeks) 101 70 1 1
Term (> = 37 weeks) 1414 286 0.29 (0.21–0.41) 1.94(1.27–2.96)*
ANC follow up Yes 1432 294 1 1
No 83 62 3.64 (2.56–5.17) 1.56(0.90–2.71)
Intake Iron foliate Yes 1310 260 1 1
No 205 96 2.36 (1.79–3.11) 1.26(0.82–1.96)
Current pregnancy complications
 Yes 177 75 2.02(1.50–2.72) 1.3610.94–1.98)
No 1338 281 1 1
Mothers’ HIV status Negative 1477 343 1 1
Positive 38 13 1.47(0.78–2.80) 1.82(0.89–3.72)
Caffeine intake (Coffee and tea) Never 136 31 1 1
Daily 1256 260 0.91(0.60–1.37) 0.69 (0.43–1.09)
Weekly 19 9 2.08(0.86–5.03) 1.61(0.60–4.30)
Occasionally 104 56 2.36(1.42–3.93) 2.01(1.14–3.55) *
Alcohol intake Never 1073 199 1 1
Daily 20 7 1.89(0.79–4.52) 1.05(0.45–1.01)
Weekly 55 31 3.04(1.91–4.84) 1.06 (0.38–3.00)
Occasionally 367 119 1.75(1.35–2.26) 2.59(1.49–4.52)*
Counseled on dietary practice Yes 1020 232 1 1
No 495 124 1.10(0.86–1.40) 1.01(0.65–1.56)
Get additional diet during pregnancy Yes 993 217 1 1
No 522 139 1.22(0.96–1.55) 0.89(0.58–1.35)
Nutritional status Well-nourished 1171 186 1 1
Under nourished 344 170 3.11(2.45–3.96) 3.00(2.22–3.97)*
Family size < = 4 1150 271 1 1
5–6 291 56 0.82(0.60–1.12) 1.054 .693 1.604
>6 74 29 1.66(1.06–2.61) 2.66(1.49–4.77)*
History of medical illness Yes 236 45 0.78(0.56–1.10) 0.76(0.51–1.12)
No 1279 311 1 1
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* = Statistically significant

AOR = Adjusted Adds Ratio, COR = Crude Odds Ratio.

Discussion

The world health organization estimates that the highest proportion of individuals affected by anemia are in Africa and also in Ethiopia anemia is a severe problem for both pregnant and non-pregnant women of childbearing age [6]. Therefore, this study was planned to assess the magnitude and associated factors of anemia among pregnant women.

The magnitude of anemia in the study area was 19.00%. The magnitude of anemia in pregnant women in this study area is higher than the study done in Addis Ababa (10.1%) [27]. The difference might be to socioeconomic difference, culture of dietary practice and awareness about anemia during pregnancy. The main cause of anemia in pregnancy is nutritional deficiency. So, giving attention during antenatal care about additional diet and supplementation of iron folate are very crucial in reducing the magnitude of anemia among pregnant mothers.

The magnitude of anemia in this study is lower as compared with the studies done in Malaysia (33%) [28], Gana (51%) [29], and in Ethiopia: Tigray(36.1%) [30], Nekemte town (52%) [31], Adama (28.1%) [32], Gode town (56.8%)[33], Bisidimo (27.9) [34], Jijiga town (63.8%)[35] and Ilu Abba bora zone (31.5%) [36]. This difference might be due to the study period and the attention given for focused antenatal care and supplementation of iron sulfate throughout the pregnancy.

The magnitude of this study is consistent with the studies done in India (20%) [37], Mekele town (19.7) [38], Mizan Aman general hospital (23.5%) [39] and Limo district (23%) [26].

In this study, factors influencing magnitude of anemia were identified. Advanced maternal age was statistically associated with anemia during pregnancy. The finding of this study is congruent with the studies done in Ghana and Jijiga [29, 35]. As maternal age increases, the mother may face pregnancy and labour related complications, and other illness which may predispose the mother for anemia. Mothers who haven’t any formal education were more likely develop anemia as compared to formally educated mothers. This finding is similar with study carried out in Malaysia and Tigray [28, 30]. It is obvious that as educational status increases, the life style, socio-economic status and diseases prevention knowledge and skilled also improved.

This study also identified other factors associated with anemia; gestational ages greater or equal to 37weeks were more likely faced anemia. Around 37 and above weeks, the demand of iron is increased which might be the cause for anemia. Mothers who have family size greater than six were more likely develop anemia as compared to mother who have less than five. This finding is consistent with the studies done in Jigjiga and Ilu Abba Bora zone [35, 36].

Pregnant women of Mid Upper Arm Circumference (MUAC) less than 21cm were more likely to be anemic as compared to women not malnourished. The result of this study is comparable with the study conducted in Adama town, Jigjiga town, Gode town and Ilu Abba Bora zone [32–36]. The similarity could be due the facts that under nutrition occur as a result of micro and macro nutrient deficiency and also anemia may occur as complication of malnutrition.

Strength and limitation of this study

The study was carried out through close supervision and follow up during data collection period, and the analysis was generated from huge sample which increases its representativeness were considered as strength of the study. The study was facility based study; it is difficult to generalize for the community and the study might encounter inter observer error during measurements were considered as limitation of this study.

Conclusion

The magnitude of anemia found to be high. Age, educational status of the mother, gestational age, caffeine and alcohol use, Nutritional status and family size were factors significantly associated with anemia. To prevent adverse outcome of anemia, health care providers should work on these factors.

Supporting information

S1 Table. Description of variables and measurement for the study in Bench Maji, Keffa and Sheka zones of public hospitals, Southwest, Ethiopia, 2018: This table shows that the description and measurements of dependent and some independent variables.

(DOCX)

Click here for additional data file. (16.2KB, docx)
S1 File. Anemia SPSS data.

This SPSS data is a data which all statistical analysis was done from it.

(SAV)

Click here for additional data file. (6.9MB, sav)

Acknowledgments

We would like to express our deepest gratitude to our data collectors, supervisors, zonal health department, hospital directors and study participants for their valuable contribution in the realization of this study.

Abbreviations

AOR

Adjusted Odds Ratio

ANC

Ante Natal Care

COR

Crude Odds Ratio

LNMP

Last Normal Menstrual Period

MUAC

Mid Upper Arm Circumference

SPSS

Statistical Package for Social Science

WHO

World Health Organization

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The budget of this study was funded by Mizan-Tepi University.

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Decision Letter 0

Russell Kabir

10 Sep 2019

PONE-D-19-15567

Magnitude and factors associated with anemia among pregnant women of Bench Maji, Keffa and Sheka zone Public hospitals, Southwest, Ethiopia, 2018: A cross sectional study

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Partly

Reviewer #4: Partly

Reviewer #5: Yes

Reviewer #6: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: No

Reviewer #5: Yes

Reviewer #6: No

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: No

Reviewer #5: Yes

Reviewer #6: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The author has been successful in addressing the research aim through research study design of facility based cross-sectional study and methodological soundness. The strength of the study is the sample size when considering several specific geographical locations around Ethiopia although selected hospitals have been taken into account. However, reviewing the article found me insufficiency of variables in terms of anemia and its magnitude. There could be more justified variables to address the issue more authentically. Furthermore, statistical analysis could be higher in terms of stating significant association between the variables with random effect so that there could be less bias in the study. References should be more contemporary to support the statements.

Reviewer #2: Edition with typology needs major revision

1. the introduction section need to have some sort of flow (what is anemia, the manifestation and how it is been diagnosed and then the magnitude of the problem and finally why you were interested studying on anemia n on the flow and the typology

2. In the method section, there was no description on how the study facilities were selected, and the study population was not stated correctly(those were sample population and not the study population because the were those from whom the study participants were selected

In addition the outcome variable should be clearly stated i.e. to which option was 1 given, was it for Yes or No, this is critical because your results are going to be written based on your outcome description

3. Result section: the analysis was not computed correctly and needs to be done again.

The discussion, and conclusion to be evaluated after reanalysis

Reviewer #3: Comment No 1 - Page 1:

Comment 1:

First:

In the Abstract, result section, arrange the percents in descending order.

Second:

Specify the older age group

Comment 2: Page 10

First:

Here, in this place you should state the magnitude of the research problem, and the study hypotheses, and the study objectives.

None of these are present.

Comment 3:Page 10

Add analytical, Facility based, cross sectional study.

Comment 4 , page 11:

Is it in proportionate to total population size in each of the 4 hospital.

Comment 5: Page 12 - line 8

midwives.

Comment 6: Page 12, line 24.

Rewrite multinomial Logistic regression

Comment 7: Page 14, line 1

You are studying 4 dimensions in relation to anemia among women as follows:

1-Socio-demographic characteristics. (Table 1).

2- Indicators related to obstetric characteristics. (Table 2).

3-Indicators related to pregnancy complication and medical illness.(Table 3) and,

4- Indicators related to behavioral factors. (Table 4).

So, you should cross tabulate each of these indicators with the anemia status among women, NOT to show them in frequency table.

It is better to construct 8 tables, after each of the cross tabulation table mentioned above, you have to construct the logistic regression table related to each of them.

Comment 8: Page 14, Line 3:

Rephrase the sentence to read like this:

The response rate was 100% where all the anticipated participants (1871) were participated in the study .

A total of 853(45.6%) participants were rural residents, 481(25.7%) were illiterates, 1808(96.7%) were married, 483(79.3%) were housewives and the family size of 1421(75.9%) participants was four children or less (Table 1).

Comment 9: Page 15, Table 2 :

It is better to show in a cross tabulation table presenting anemia status by obstetric characteristics among women..... instead of showing it in a frequency table.

Comment 10: Table 2:

Row (Gestational age) insert ≥ instead of >=37 weeks

Comment 11 - table 2:

Insert space (Among mothers who have ANC follow up, At what month ANC started? (4-6month) and (7-9month)

Comment 12, Table 2 :

Number of ANC visit - (left side alignment)

Comment 13,Table 2 :

Left side alignment (Iron foliate intake).

Comment 14 , Page 16 - Line 1

Change to: Indicators related to pregnancy complication and medical illness.

Comment 15 - page 16 - line 6:

Rephrase:

(13.5%) of participants developed pregnancy-related complication during current pregnancy, 78 (31%), 31(12.3%),21 (8.3%), and 52 (20.6%) were developed preeclampsia, placenta previa, abruptio placenta and antepartum hemorrhage respectively. A total of 281 (15%) faced medical illness during current pregnancy.

Comment 16 - Table 3:

It is better to show in a cross tabulation table presenting anemia status by pregnancy complication and medical illness among women..... instead of showing it in a frequency table.

Comment 17 - Table 3:

Rephrase:

Indicators of Pregnancy Complication and Medical Illness Presented among Pregnant Women Attending ANC in Public Hospitals of

Benchi-Maji, Kaffa And Sheka Zones, Southwest, Ethiopia, 2018.

Comment 18 - Table 3 - column 2:

Change category to indicators

Comment 19 , Table 3 - Center the table column heads.

Comment 20: table 3 - Last row - it is not necessarily to present started/not started) in a table, but if you would like to, make the corresponding value (not started) as (not applicable- not zero).

Comment 20, page 17:

Rephrase:

From the total study participants, 1516 (81%) used to drink caffeine (coffee and tea) on a daily basis, and 1272 (68.0%) were never drinking alcohol. Regarding the nutritional status1252 (66.9%) and 1210 (64.7%) were get dietary counseling and additional diet during current pregnancy respectively. 1357(72.5%) women were not malnourished based on their mid-upper arm circumference (MUAC) measurement.

Comment 21 - page 17,Table 4

Rephrase the title :

Distribution of Behavior Related Indicators among Pregnant Women Attending ANC in Public .......

It is better to show in a cross tabulation table presenting anemia status by behavioral factors among women..... instead of showing in a frequency table.

Comment 22 - Change column two head to indicators.

Comment 23, Last row, (Nutritional status using MUAC) this is not the suitable place to present this variable, because title of the table is related to behavioral factors among women attending ANC in public

hospitals. That , Nutrition status is not a behavioral factor. Table 3 could be a suitable place to show it since it presents the related to pregnancy complication and medical illness.

Comment 24 , table 4 - last row, change Under nutrition (MUAC<21cm) to Malnourished.

Comment 25, page 18 - line 1.

In table 4, You show a total of 514 respondents as being anemic , and here you state them to be 356 (19%); make the suitable corrections.

Comment 26, page18, line 2

These percents are not represent the (Among the anemic women) anemia; these percents are presenting the anemia categories ( severe , moderate and mild anemia respectively) among the total respondents. Make both corrections.

Comment 27:page 18, line 7.

Write it as OR (odds ratio), not AOR.

Comment 28, Table 5:

Delete column 3 (No, Yes) because none of the Odds Ratio analysis requires reference to this frequency.

Comment 29: Table 5, column 4,

First: It is not clear for me what you mean by the crude Odds Ration (COR).

Second:

Delete this column since you did not refer to this column content finding while discussion.

Third:

Better to delete this column and show the Beta (B) value instead.

Comment 30:Table 5

Rewrite Exp(B) - odds Ration instead of COR (In the last column)

Comment 40:

State your hypotheses first then continue with your discussion from there.

Comment 41: page 20 last line

You did not present any of the paper's [33 -37] main findings and/or conclusion in the introduction part. then, you show your discussion deferring to them. That will not help to see how they are related and/or differ from your study main findings and conclusion.

Comment 42 , page 21,

Where are the findings of these papers? It is the paper No. 24 that you lastly refer to in the introduction. Refer to the papers that you show in the introduction.

Comment 43 : page 21, (Strength and limitation of this study)

Strength of the study is how much it findings can contribute to stability and improvement of the pregnant women.

Reviewer #4: This cross-sectional study investigates the prevalence of and risk factors for anemia among 1871 pregnant women in South-West Ethiopian hospitals. The results show that 19% of the women had anemia and that anemia was associated with factors such as age, gestational age, family size, nutritional status, and caffeine and alcohol consumption. The authors conclude that health care providers should target these risk factors to reduce the problem of anemia during pregnancy.

The strengths of this study include the large sample size and the thoroughly-planned patient interviews. Although the manuscript is in general easy to understand, the grammar could be improved. My main concerns with the manuscript relate to the description of the recruitment process, the data presentation, and the interpretation the results. These concerns are detailed in the comments below.

Major comments

1. The manuscript does not contain information about the number of patients at each stage of the recruitment process. How many patients were screened for eligibility? (For example, how many women, regardless of their stage of pregnancy, received antenatal care at the four hospitals?) How many patients were excluded for ineligibility? I encourage the authors to consult the STROBE guideline.

2. The authors state that the response rate was 100%. This statement suggests that all eligible patients were willing to participate in the study. Is this true? Maybe the authors mean that they managed to recruit 1871 participants as planned?

3. The data collection procedure could be clarified. The authors explain that 12 midwives conducted the interviews and collected the data at 4 hospitals, but how were potential participants contacted and identified? For example, did the 12 midwives inform patients of the study during ordinary antenatal care visits? If so, were interviews conducted at the same visit or on a later occasion? Are the authors sure that the 12 midwives managed to identify all patients who potentially met the inclusion criteria, or could some patients have been missed because there were other midwives working at the hospitals?

4. The associations between anemia and its risk factors are examined using only odds ratios. As odds ratios measure relative effect instead of absolute effect, odds ratios do not necessarily convey the importance of risk factors from a public health perspective, which this study aims to do. The authors could fix this problem by including percentages in the third and fourth columns of Table 5, so that anemic and non-anemic patients can be easily compared.

5. The authors report the overall percentage of anemic patients at 4 hospitals. I encourage the authors also to report the percentage anemic patients by hospital, as this could differ.

6. The variable “Education status” is defined as a composite of both literacy (able/not able to read and write) and level of education (primary, secondary, or college). This definition is inappropriate because the categories are overlapping; a patient with a secondary education must be able to read and write. Even so, the results show that each patient is categorized according to only literacy or only level of education. The authors should explain this variable and probably redefine it. Furthermore, does level of education mean level of completed education?

7. Table 5 shows that a few variables (age, residence, and gestational age) have a reversed association with anemia after adjustment for confounding. Can the authors explain these results?

8. In Paragraph 1 of the discussion, the authors write that “…additional diet and supplementation of iron folate are very crucial in reducing the magnitude of anemia among pregnant mothers”. Although this may be common knowledge, the authors do not relate this statement to their own data. Perhaps they could comment on the fact that most anemic women in their study were receiving “additional diet”, were receiving iron and folate supplements, and were not undernourished.

9. The authors cite several previous studies of the prevalence of anemia. Were these studies conducted in hospital settings too?

10. In the discussion, the authors conclude that the observed 19% prevalence of anemia is high. However, the authors mention only one previous study that has shown a lower prevalence. As that study and the other studies that the authors cite were all conducted in Ethiopia or other low- to middle-income countries, the authors could further contextualize their results by relating them to the prevalence of anemia in high-income counties. The authors could also compare their results to the WHO’s definition of a severe public health issue, which the authors mention in the introduction.

11. The study has a few limitations that are not mentioned in the discussion. First, some variables are measured quite imprecisely, such as nutritional status, which is dichotomous and determined by upper-arm circumference. Second, some of the data are obtained in face-to-face interviews, which contain sensitive questions, so answers may not be reliable. Third, the blood tests do not specify the type of anemia.

12. The authors conclude that healthcare professionals can reduce the problem of anemia during pregnancy by targeting a number of risk factors: advanced age, advanced gestational age, education, caffeine and alcohol use, family size, and nutritional status. The authors should reconsider this conclusion for a number of reasons. First, the data do not actually show that advanced age is associated with a higher risk of anemia. Instead, the data show that teenage pregnancy is associated with a lower risk, although only after adjustment for confounding. This distinction is important, and it contradicts previous research (Adebisi & Strayhorn. Fam Med 2005;37(9):655-62), which should be discussed. Second, gestational age is not a modifiable risk factor, so it is unclear how healthcare professionals would work with this risk factor. Third, occasional consumption of caffeine or alcohol was indeed associated increased risks of anemia, but more frequent consumption was not clearly associated with anemia. This lack of dose-response relationships suggests that something other than caffeine and alcohol is driving the associations. Fourth, family size could be a socioeconomic indicator, reflecting income rather than biologic changes due to having had many pregnancies. In addition, there was only an association among women with a family size >6, who constituted only 5.5% of the study population.

13. The authors state that “[t]he funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript”. However, the authors do not mention who the funders are.

Minor comments

14. In the introduction, I encourage the authors provide contextual information about the study location. For example, how does South-Western Ethiopia relate to the rest of the country with respect to economy and demographics?

15. The authors recruited 1871 patients based on a sample-size calculation for estimating the proportion of women with anemia. Although this calculation is not wrong, it is superfluous because the authors do not use confidence intervals or p-values when analyzing the proportion of women with anemia. When confidence intervals and p-values are not used, there are no formulas to determine an appropriate sample size. Nevertheless, the decision not to use confidence intervals or p-values was a good one, because the authors recruited all eligible patients rather than a random sample.

16. The authors report that significant associations were observed between anemia and categorical variables with >2 levels, such as caffeine intake and alcohol intake, based on the p-value/confidence interval for individual odds ratios (Table 5). This method is common but considered incorrect in statistics because it increases the risk of a type 1 error. To avoid this error, the conventional method is to use likelihood ratio tests, which test whether at least one odds ratio is different from 1.

17. Should parity and family size be included in the same regression model (Table 5), due to the risk of collinearity?

18. In Table 1, “orthodox” could be clarified as orthodox Christian.

19. Does the variable “family size” refer to number of children or size of household?

20. The abbreviation ART is not defined in Table 3. Since ART status refers only to patients with HIV (instead of to all patients, like the other variables), this information could be placed in a foot note.

21. The results of the study would be easier to read if the five tables were combined into one. This could easily be done by replacing the “category” column in Table 5 with a “total” column for anemia status. The “category” column could then be incorporated into the “variable” column. In the second right-most column, crude odds ratios can be provided for all variables, even those that are not included in the multivariable analysis.

22. Figure 1 can be removed because it shows only the percentages of participants with and without anemia.

23. I interpret the variable “Get additional diet during current pregnancy” as the patient is eating more food than before the pregnancy. Is this interpretation correct? The authors may want to relabel this variable and ensure that the label is the same in both Tables 4 and 5.

24. The authors are correct that the generalizability of their results is limited by the fact that the study was hospital-based. However, it is not correct that generalizability is improved by a large sample size. A large sample size improves precision (reduces widths of confidence intervals and sizes of p-values).

25. Please paginate the manuscript.

Reviewer #5: As the author mentions- Gestational age was calculated based on the last normal menstrual period (LNMP)

It would be better to add 'using Naegele's rule' (https://ipfs.io/ipfs/.../wiki/Naegele's_rule.html) and give credit to

Franz Karl Naegele (1778–1851), the German obstetrician who devised the rule. Or it would be better to write the formula and cite it.

Few grammatical errors need to be corrected.

Reviewer #6: Data availability is clear

Ethical part is also clear

Should correct some spelling errors.

Should be clearon methodology,it is still not clear

Focus on sample size calculation

**********

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Reviewer #1: No

Reviewer #2: Yes: Dereje Birhanu (MPH), Assistant professor, Bahir Dar University

Reviewer #3: Yes: Ilham Abdalla Bashir Fadl

Reviewer #4: Yes: Jonathan Bergman

Reviewer #5: Yes: Lila Bahadur Basnet

Reviewer #6: Yes: Manita Pyakurel

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PLoS One. 2019 Nov 21;14(11):e0225148. doi: 10.1371/journal.pone.0225148.r002

Author response to Decision Letter 0

24 Oct 2019

We are revised all reviewers`comments and questions point to point. we uploaded our response to reviewers` comments and questions separately with other files.

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Decision Letter 1

Russell Kabir

30 Oct 2019

Magnitude and factors associated with anemia among pregnant women attending antenatal care in Bench Maji, Keffa and Sheka zonesPublic hospitals, Southwest, Ethiopia, 2018: A cross sectional study

PONE-D-19-15567R1

Dear Mr. Gudeta,

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Acceptance letter

Russell Kabir

12 Nov 2019

PONE-D-19-15567R1

Magnitude and factors associated with anemia among pregnant women attending antenatal care in Bench Maji, Keffa and Sheka zones Public hospitals, Southwest, Ethiopia, 2018:  A cross sectional study

Dear Dr. Gudeta:

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Description of variables and measurement for the study in Bench Maji, Keffa and Sheka zones of public hospitals, Southwest, Ethiopia, 2018: This table shows that the description and measurements of dependent and some independent variables.

    (DOCX)

    Click here for additional data file. (16.2KB, docx)
    S1 File. Anemia SPSS data.

    This SPSS data is a data which all statistical analysis was done from it.

    (SAV)

    Click here for additional data file. (6.9MB, sav)
    Attachment

    Submitted filename: Reviewer comment on anemia to plos one.docx

    Click here for additional data file. (19KB, docx)
    Attachment

    Submitted filename: Response to reviewers comments and questions.docx

    Click here for additional data file. (25.9KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.

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