Determinants of anemia among pregnant women attending antenatal care in Horo Guduru Wollega Zone, West Ethiopia: Unmatched case-control study.

BACKGROUND: Anemia is a common clinical problem contributing to increased maternal and fetal morbidity and mortality during pregnancy. Anemia can be caused by different factors apart from known diseases. The main aim of this study was to identify determinants of anemia among pregnant women attending antenatal care at the public health facilities of Horo Guduru Wollega Zone, West Ethiopia, 2017.
METHODS: Health facility-based unmatched case-control study was conducted among 191 anemic and 382 non-anemic pregnant women from September 7, 2017, to October 25, 2017, in Horo Guduru Wollega Zone, West Ethiopia. Data were collected using pre-tested questionnaires from nine health facilities. Hemoglobin level determination, hemo-parasite diagnosis, venereal disease research laboratory (VDRL) test, and stool examination were done in the laboratories of the respective health centers. Cleaned and coded data were entered and analyzed using SPSS version 20. Frequency, proportion, mean and standard deviation were computed to summarize the data and presented by tables and bar graphs. Multivariate binary logistic regression analysis was used to determine the association of predictors and response variables at P ≤ 0.05. Adjusted odds ratio with 95% CI was used to show the strength of association between predictors and outcome variables.
RESULTS: A total of 573 pregnant women were enrolled in this study. Monthly income < 500 Ethiopian birr (AOR = 9.16, 95% CI: 4.23, 19.82), heavy menstrual bleeding (AOR = 2.38, 95%CI: 1.38, 4.09), taking iron supplement irregularly (AOR = 2.87, 95%CI:1.41, 5.84), Mid-upper Arm Circumference (MUAC) < 23 cm (AOR = 3.42, 95%CI: 2.07, 5.63), low dietary diversity score (AOR = 12.30, 95%CI: 4.64, 32.72), medium dietary diversity score (AOR = 3.40, 95%CI:1.48, 7.84) and intestinal helminthic infections (AOR = 6.31, 95%CI: 3.44, 11.58) were significantly associated with anemia during pregnancy.
CONCLUSION: Average monthly income < 500 Ethiopian birr, heavy menstrual bleeding, low and medium dietary diversity score, taking of iron supplements irregularly, MUAC < 23 cm and intestinal helminthic infections were identified as independent determinants of anemia during pregnancy. Therefore, improving dietary diversity intake, routine deworming and empowering women on taking iron regularly are vital to prevent anemia during pregnancy.

Introduction

Anemia implies a reduction in the oxygen-carrying capacity of the blood as a result of fewer circulating erythrocytes than normal or a decrease in the concentration of hemoglobin (Hb). Anemia during pregnancy is defined as a hemoglobin concentration less than 11gram per deciliter (g/dl) and classified as mild (10.0–10.9g/dl), moderate (7.0–9.9g/dl) and severe <7g/ dl. Currently, World Health Organization (WHO) recognized that the hemoglobin value less than 11.0 g/dl at 1st and 3rd trimesters and less than 10.5 g/dl in the 2nd trimester is used to define anemia [1].

Anemia is a common public health problem affecting one- third of the world’s population. It is more common in women who are young, poor and pregnant [2]. It is among the most clinical problem contributing to increased maternal and fetal morbidity and mortality during pregnancy [3]. Anemia among pregnant women is more prevalent in developing countries than in developed countries [4].

The causes of anemia in pregnancy are multi-factorial. Iron folate, amino acids, vitamin A, C and other vitamin B complex deficiencies, intestinal helminthic infections, malaria, and chronic illnesses are among the most common causes [5]. The other risk factors include poverty, grand parity, too early pregnancies, too many children, frequent pregnancy spacing of less than one year, low socioeconomic status, illiteracy, late booking for antenatal care and gestational age [6, 7].

Globally, 56 million pregnant women were anemic and 20% of maternal deaths were caused by anemia. It was 35–75% among pregnant women in developing countries and 18% in developed countries. Africa (61.3%) and southeast Asia (52.5%) are regions with the highest rate of anemia during pregnancy in the world [8].

In Ethiopia, the prevalence of anemia among pregnant women was 22% which is more common in rural areas. According to the Central Statistical Agency of Ethiopia 2011 report [9], anemia is still a public health problem in the country. Anemia during pregnancy is widely distributed in different regions of Ethiopia especially in Somali (49.9%), Afar (40.4%) and Dire Dawa (33.2%).

Although a lot of researches have been conducted about anemia during pregnancy in Ethiopia, there is still a paucity of published data on determinants of anemia among pregnant women in the current study area. The study is; therefore, aimed to identify determinants of anemia among pregnant women in Horo Guduru Wollega Zone, West Ethiopia.

Materials and methods

Study setting and context

An institutional-based unmatched case-control study was conducted in randomly selected 8 health facilities. These facilities were Jima Rare health center, Goban health center, Kombolcha health center, Ayale health center, Harato health center, Gudane health center, site 20 health center, site 24 health center, and Shambu hospital. The study was conducted from September 7, 2017, to October 25, 2017.

Study population

Our study population was categorized into cases and controls. Cases were all pregnant women who were attending ANC follow up at the selected public health facilities whose Hb level fall in our anemia definition whereas controls were all pregnant women who were attending ANC follow up at the selected public health facilities whose Hb fall in our non-anemic definition. Anemia during pregnancy was defined and classified based on WHO [1] and Ethiopian ANC follow-up guidelines for different gestational ages. Accordingly, women in the first and third trimester whose Hb level was < 11g/dl and women, in the second trimester, whose Hb level was < 10.5 g/dl0 were defined to be anemic for cases. Pregnant women at any gestational age (GA) were included in the study. GA of pregnant women was classified into trimesters i.e. GA below 12 weeks: first trimester, GA of 13–24 weeks: second trimester and GA above 24 weeks: third trimester. The gestational age was calculated from last normal menstrual period (LNMP) which was determined by antenatal care providers. In Ethiopia, health extension workers register pregnant women of any GA with their last normal menstrual period at home, thus, GA is not usually missed.

Pregnant women who were taking anti-helminthic drugs within the past two weeks, very sick and unable to give information, those with confirmed acute and/ chronic disease-causing anemia and those under invasive anemia treatment except iron folate were excluded from this study.

Sample size determination and sampling procedure

The sample size was calculated using OpenEpi software for unmatched case-control study by taking 95% confidence level, 80% power and a ratio of controls to cases 2:1 (r = 2), P1 = 42.03 and P2 = 57.97 by using OR = 1.9 [10]. Based on this, the intestinal parasitic infection was taken as the main exposure variable with a proportion of 57.97 among cases and 42.03% among controls with OR = 1.90 which gives a sample size of 347. Lastly, by considering a design effect of 1.5 and adding 10% non-response rate, the final sample size was 573. From this, cases were 191 and controls were 382. The study participants were consecutively enrolled until the planned sample size was achieved. A 2: 1 control to case ratio was applied and study participants were recruited proportionally from each health facilities based on the number of pregnant women attending ANC.

Data collection

The questionnaire was developed from previous literatures and modified to the current context of the study based on the conceptual framework and study variables [6, 10 and 11]. The questionnaire was first prepared in English language and translated to ‘Afan Oromo’ which is the local language at the study sites and retranslated back to English language for consistency. Before the actual data collection, the questionnaire was pre-tested on 19 pregnant women (5% of the total sample size) who were attending ANC in an un-selected health facility, Shambu health center.

Minimum Dietary Diversity for Women (MDD-W) was calculated from 24 hours’ dietary recall data. All foods consumed day before the study were categorized into 10 food groups. Consuming a food item from any of the groups was assigned as” Yes” and if not consumed assigned as” No”. Dietary diversity score of 10 points was computed by adding all values of the groups. Then, the added values were categorized as low (≤3), medium (4–6) and high (≥7) dietary intake [12]. Study participants were screened for nutritional status by measuring MUAC (Mid-Upper Arm Circumference) by using tape meter.

Specimen collection and processing

Blood samples were collected following aseptic procedures for hemoglobin determination using microhematocrit centrifugation technique. Briefly, blood was collected into two-third of the micro-hematocrit tube with anti-coagulant and centrifuged for 5 minutes and then hemoglobin was determined by dividing hematocrit value by three [13]. The hemoglobin cut-off value for anemia during pregnancy was determined according to the WHO [1] and Ethiopian ANC follow-up guidelines. Thick and thin blood films were made from collected blood samples and stained by Giemsa staining technique for hemo-parasite diagnosis [14] and VDRL test [15] was done to identify Syphilis infection following standard operating procedures. Further, formalin-ether concentration technique was used for diagnosing ova and larvae of helminths [14].

Data quality control

One senior midwife who was working in ANC department of each selected health facilities and three Health Officers were recruited as supervisors who were under the whole supervision of the principal investigator. Two days of training was conducted for data collectors and supervisors to aid for clarity, consistency, and reliability of measurements. Collected data were checked for consistency and completeness daily and pre-analytical, analytical and post-analytical laboratory data quality were controlled accordingly.

Data analysis

Data were cleaned, coded and entered into SPSS software version 20 for analysis. Outcome variables were dichotomized into 1 = case and 0 = control. Binary logistic regression models were used to determine the association between predictors and outcome variables. Bivariate analysis was carried out for each independent variable to identify the presence of association with response variable at P < 0.25 [16]. Multivariate logistic regression was used to control the possible confounding factors at P ≤ 0.05. Adjusted odds ratio with 95% confidence (AOR, 95%CI) was used to infer the results and all data analyses were done according to standard protocols [17-19].

Ethics considerations

The study was conducted after it was ethically reviewed and approved by the Research and Ethical Review Committee of Wollega University. Then, an official letter of co-operation was written to selected health facilities and permission was obtained. The ethical review committee approved informed verbal consent documented by a witness after the objectives had been explained. Participants’ right during the interview for either not to participate or to withdraw at any stage of the interview was guaranteed. All the information obtained from the study participants were coded to maintain confidentiality and positive results were immediately communicated with clinicians for appropriate intervention.

Results

Socio-demographic characteristics of study participants

A total of 573 pregnant women participated in the study. The mean age of respondents was 27(±5.4) years in cases and 26.8 (±5) years in controls. More than half of the participants, (59.2% (113/191) of cases and 52.6% (201/382) of controls, were farmers. The proportion of anemic pregnant mothers, 44.5% (85/191) with average monthly income < 500 ETB were more than four times of their counterparts, 10.5% (40/382) ().

Maternal obstetric factors

Most of the study participants, 98% (185/188) of cases and 96.3(366/380) of controls, were married with a mean age of 19(± 2.3). Clinically, 63.9% (122/191) of cases and 63% (241/382) of controls were at their third trimester. The proportion of heavy menstrual bleeding (using more than 7 tampons per menstrual period) was two times more in cases than in controls (32% and 16%, respectively) (Table A in ).

Maternal dietary factors

Based on the dietary diversity score, more than half of cases (66% (126/191)) and controls (67.3%(257/382)) were classified under medium dietary diversity score, whereas 4.2% (8/191) and 30% (57/191) of cases, and 26%(99/382) and 6.8%(26/382) of controls were classified under high and low dietary diversity scores, respectively (Table B in ).

Infection related factors

The proportion of malaria infection was almost twelve times in cases, 6% (11/191) than controls, 0.5% (2/382). VDRL test was positive in 3.7% (14/191) of cases and 10% (19/382) of controls. Intestinal helminthic infections were diagnosed in 39.9% (76/191) of cases and 6.5% (25/382) of controls ( and ).

Hygiene and sanitation related factors

Majority of the study participants i.e. 87.4% (167/191) of cases and 91.9% (350/382) of Controls utilized latrine and 70.2% (134/191) cases and 64.4% (246/382) controls used to dispose of solid waste in open field. The source of drinking water was tap water for 45.5% (87/191) of cases and 52.6% (201/382) of controls ().

Status of anemia

Mild anemia was the most prevalent form of anemia accounting for 60% followed by moderate anemia 39% and severe anemia 1%. The mean hemoglobin level was 9.7 ± 0.69 gm/dl among the cases and 13 ± 1.1 gm/dl among control groups.

Inferential statistics

Multivariable binary logistic regression analysis was done to identify independent predictors of anemia at P ≤ 0.05. Hosmer and Lemeshow goodness of model fit test showed a good model fit (P = 0.98) and the VIF of covariates in this study ranged between 1–1.2 which is in the acceptable range for multicollinearity which means there was no correlation among predictors of anemia and; therefore, there was no correlation between gestational age and other risk factors of anemia. This indicates that risk factors of anemia were not changeable based on differences in gestational age.

Average monthly income < 500 ETB showed statistically significant association with anemia among pregnant women (AOR = 9.16, 95% CI: 4.23, 19.82). Anemia was more prevalent among those with heavy menstrual bleeding before index pregnancy than their counterparts (AOR = 2.38, 95%CI: 1.38, 4.09). Pregnant women who took iron supplements irregularly were almost 3 times more likely to be anemic than their counterparts (AOR = 2.87, 95%CI: 1.41, 5.84). A strong association was also seen between the occurrence of anemia and low dietary diversity score of 24 hours recall (AOR = 12.3, 95%CI: 4.64, 32.72). Likewise, there was also a significant association between medium DDS and occurrence of anemia among pregnant women (AOR = 3.40, 95%CI: 1.48, 7.84). Gestational age was not significant predictor of anemia (P > 0.05) ().

Anemia was almost 6 times more common among pregnant women who had intestinal helminthic infection than those with no intestinal helminthic infection (AOR = 6.31, 95%CI: 3.44, 11.58). Pregnant women infected with Ascaris Lumbricoides, Tricuris Trichiura, Hookworm and Hymenolepis nana were significantly affected by anemia (AOR = 6.81, 95%CI: 3.35, 13.85, AOR = 8.12, 95% CI: 2.85, 23.16, AOR = 13.03, 95%CI: 5.24, 32.45, AOR = 4.88, 95%CI: 1.38, 17.14), respectively (.

Discussion

Anemia is one of the most public health important diseases among pregnant women in Ethiopia [9] and in developing countries in general [20]. Anemia has multifactorial causes and the risk factors are different across populations. Here we identified six determinants of anemia among pregnant women who were attending ANC in the specific study sites.

More than half of anemic pregnant women had a mild type of anemia which was followed by moderate and severe anemia in this study. This is comparative with the studies conducted in Asosa zone, Gilgel Gibe dam area, and East Wollega Zone, Ethiopia [21, 22 and 23]. But, it is not comparative with the studies conducted in Tikur Anbessa Specialized hospital, Wolayita Sodo town and Mekelle town, Ethiopia [5, 10, and 24]. This difference might be due to the difference in determinants of anemia from one geographic area to another geographical area and sample size of the studies. Further, the differences in study design could also contribute to the observed inconsistencies.

An average monthly income of the household was identified as a significant predictor of anemia among pregnant women in this study. This finding is consistent with another study conducted in Azezo health center and Sidama Zone, Ethiopia [6, 25]. In contrast, this finding is different from a study done at Nekemte health center, Gilgel Gibe dam area, Buta Jira General Hospital, and Dera district, Ethiopia [11, 22, 26 and 27]. This difference could possibly be due to the difference in the economic status among the participants as low family income leads to food insecurity with the consequence of malnutrition which in turn leads to iron deficiency anemia [28].

Heavy menstrual bleeding (using more than seven sanitary pads per menstrual period) before the current pregnancy was identified as one independent factor for the occurrence of anemia among pregnant women. Anemic pregnant women who had heavy menstrual bleeding were almost twice of their counterparts in this study. This finding is in agreement with a study conducted at the Federal Medical Center Owemi, Nigeria [29], Otona Hospital, Wolayita Soddo town and Buta Jira hospital, Ethiopia [10, 26]. Excess blood flow leads to iron storage depletion and causes iron deficiency anemia which commonly occurs in pregnant women with short interbirth intervals.

Irregular use of iron supplements was identified as one of the determinants of anemia in the current study which is comparative with reports from East Wollega, Ethiopia [23], Kathmandu tertiary level hospital in the United States [30] and Pumwani maternity hospital in Kenya [31]. Regular use of iron supplements is vital to prevent anemia as the demand for iron is higher due to the increased blood supply during pregnancy.

Pregnant women with mid-upper arm circumference (MUAC) less than 23 cm (malnourished) were more at risk of being anemic. This finding is in line with the results of the studies conducted in Kenya [31] and other parts of Ethiopia like Gilgel Gibe dam area, Dessie town, and urban areas of east Ethiopia [22, 32, and 33]. Measuring MUAC is a routine activity for screening malnutrition during ANC follow up in Ethiopia. Malnutrition is one of the commonest contributing factors for iron deficiency anemia.

Pregnant women with low (≤3) and medium (4–6) dietary diversity score were more at risk of developing anemia when compared with those with dietary diversity score >6. This finding was supported by a study conducted in Mekele town, Ethiopia [24] and another study conducted from South Ethiopia [34]. Minimum dietary diversity score (MDDS) is used as the proxy measure of nutritional quality of pregnant women. Since pregnancy is a period demanding physiologically high nutrition, it is advisable to diversify the diet than the usual one. Low average monthly income and food taboos during pregnancy in rural communities might cause this low and medium dietary diversity scores in the study area which in turn result in anemia.

Consistent with previous studies conducted in different regions of the world; Kenya [31], India [35] and Nigeria [36], and other parts of Ethiopia [10, 23, 29,37], intestinal helminthic infection was one strong driving factor of anemia during pregnancy in the current study. Ascaris Lumbricoides and Hookworms were the predominant intestinal helminths infections among pregnant women in the current study. This finding is comparable with the studies conducted in East Wollega zone and Lemo district, Ethiopia [23, 34]. Intestinal helminths cause loss of appetite, reduce absorption, bleeding and share food uptake which in turn leads to iron deficiency anemia. Since the majority of the study participants were farmers and rural residents, they had a high chance of exposure to these intestinal helminthic infections due to walking barefooted and poor hygiene of food and water.

In contrary to the current study, variables like age, residence, family size, ANC follow up, trimester, malaria infection and interbirth interval showed statistically significant association with anemia among pregnant women in the previous studies conducted in Ethiopia [10, 21, 32, 33, 38 and 39]. This difference might be due to the fact that determinants of anemia varied from one geographical area to another geographical area due to the differences in the nutritional, altitudinal, economic and educational status of the study participants.

The study was facility-based which couldn’t be generalized to all pregnant women left in the community (didn’t attend antenatal care follow up). Dietary diversity score of 24 hours recall might leads to recall bias and the amount of diet also couldn’t be measured. There might also be a social desirability problem to explain income level and some foods that were seen as low food status within the community. Having these limitations, we believe that the results of this study can contribute to policymakers and clinicians to prevent anemia during pregnancy.

Conclusion

This study identified determinants of anemia among pregnant women in the study area. Average monthly income < 500 ETB, heavy menstrual bleeding before the index pregnancy, low and medium dietary diversity score, MUAC < 23 cm, taking iron supplementation irregularly and intestinal helminthic infections were identified as independent predictors of anemia. Early identification of determinants of anemia and appropriate interventions have paramount importance in fighting anemia to help mothers enjoy their pregnancy. Strengthening health education and counseling on diversifying dietary intake, increasing inter birth interval, routine stool examination, de-worming, and hygiene are valuable. Further large scale community-based studies are recommended.

Supporting information 1: Supporting Tables Table A and Table B.

(DOCX)

Click here for additional data file.

Supporting information 2: Questionnaires used to collect data from pregnant women.

(DOCX)

Click here for additional data file.

31 Jul 2019

PONE-D-19-15457

Determinants of Anemia among Pregnant Women Attending Antenatal Care in Horo Guduru Wollega Zone, West Ethiopia: Unmatched case-control study

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Reviewer #1: This article is on the determinants for anemia in pregnant women in Ethiopia.

The study design includes a case-control study.

This article includes some limitations.

Women were recruited at ANC visit. The inclusion criteria were unclear especially regarding which ANC visit. What was the gestational age at inclusion? How was gestational age assessed? These are important criterias to mention and to discuss: Hb changes over the course of pregnancy (Ouedraogo et al.). Different cut-offs have been proposed according to the timing in pregnancy. This is not explained nor discussed, although this introduces some change in women included or not in the case/control group.

Also, what are guidelines in Ethiopia regarding anemia, malaria, iron/folic acid supplements, treatments for helminths, and their timing of administration? That would influence the level of anemia according to gestational age, and risk factors according to gestational age.

Some parts are too detailed for a scientific article. For example, data quality control, SOPs, etc. As well as some parts of data analysis.

100% response rate: this is strange. All women accepted to participate?

Severity of anemia should be described.

The language should be revised.

The results should refer to the tables explicitly. The p-value should be added in the tables were appropriate.

Some abbreviations in the tables are not explained (for example, MUAC, DDS).

Intestinal helminthic infections and the type of helminths infection are both included in the multivariate analyses, as presented. However, they are highly correlated, and it makes no sense to include both of them.

The number of tables should be reduced.

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13 Aug 2019

Dear editor and reviewers

PONE-D-19-15457

Determinants of Anemia among Pregnant Women Attending Antenatal Care in Horo Guduru Wollega Zone, West Ethiopia: Unmatched case-control study

First of all, we would like to thank you for providing the reviewers’ comments which are very constructive and crucial. We have incorporated all the point by point below. We have formatted the manuscript based on the PLOSONE guidelines. We have edited the English language online since we cannot afford to pay for editing agents. We have cleaned the manuscript as well. We have marked “red” the changes made in the manuscript and we have a separate file for “manuscript with track changes” and “clean manuscript”. We have also attached a “rebuttal letter” which responds editor and reviewers’ comments and/suggestions point by point. Further another document is also added as additional material to minimize the number of tables.

Response to editor

1. We have included literatures from abroad and thus our manuscript currently does not look a replication of previous works done in Ethiopia.

2. We have copyedit manuscript for language usage, spelling, and grammar. The language in the manuscript looks better than it was before

3. We have included additional information regarding the survey or questionnaire used in the study and we ensure that we have provided sufficient details that others could replicate the analyses. The validation and pre-test regarding the questionnaire is included in the manuscript.

4. We have corrected the P value reference to "p<0.001"

5. We have changed our declaration regarding data availability to “All data and supporting documents are available freely without restriction”. We have added questionnaires used freely.

Response to the reviewers

1. Women were recruited at ANC visit. The inclusion criteria were unclear especially regarding which ANC visit. What was the gestational age at inclusion? How was gestational age assessed? These are important criterias to mention and to discuss: Hb changes over the course of pregnancy (Ouedraogo et al.). Different cut-offs have been proposed according to the timing in pregnancy. This is not explained nor discussed, although this introduces some change in women included or not in the case/control group.

Response: we have included clear inclusion criteria in the manuscript. The gestational age was assessed by the participants’ record books and patients’ response. The women were recruited in any ANC visit with any gestational age. Anemia definition cut-off value was categorized based on gestational age in both cases and controls as clearly described in the manuscript.

2. Also, what are guidelines in Ethiopia regarding anemia, malaria, iron/folic acid supplements, treatments for helminths, and their timing of administration? That would influence the level of anemia according to gestational age, and risk factors according to gestational age.

Response: We used WHO and Ethiopian ANC follow up guideline to define anemia in pregnant women Factors like malaria, iron/Folic acid supplements and deworming prophylaxis administration status those included on anemia guideline in Ethiopia were incorporated in the study.We have used Ethiopian ANC follow-up guideline to analyze our data regarding anemia and other factors

3. Some parts are too detailed for a scientific article. For example, data quality control, SOPs, etc. As well as some parts of data analysis. 100% response rate: this is strange. All women accepted to participate? Severity of anemia should be described. The language should be revised.

Response: We have briefly summarized the detailed parts like data quality control and SOPs and the data analysis. The response rate was 100% since we used consecutive sampling technique. We enrolled pregnant women consecutively until the sample size was reached. Thus we have removed the phrase “100% response rate”. Severity of anemia was described as Mild, moderate and severe in the manuscript. We have edited the language well.

4. The results should refer to the tables explicitly. The p-value should be added in the tables were appropriate. Some abbreviations in the tables are not explained (for example, MUAC, DDS).

Response: The results refer the tables clearly. All P-values were added in the tables where appropriate and all abbreviations are explained.

5. Intestinal helminthic infections and the type of helminths infection are both included in the multivariate analyses, as presented. However, they are highly correlated, and it makes no sense to include both of them. The number of tables should be reduced.

Response: We have removed the “intestinal helminthic infection” from the multivariate analysis. We have reduced the number of tables from 6 to 4 tables. We separately submitted the removed tables as “Supporting Table ST1”

Submitted filename: 7. Rebutal letter.docx

Click here for additional data file.

4 Oct 2019

PONE-D-19-15457R1

Determinants of Anemia among Pregnant Women Attending Antenatal Care in Horo Guduru Wollega Zone, West Ethiopia: Unmatched case-control study

PLOS ONE

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Reviewer #1: Thank you for Editing your manuscript.

There is still a major comment which is gestational age at enrolment. Gestational age at enrolment should be described. Indeed, the definition of anemia changes over pregnancy, and iron supplementts, anti-helminthic treatments, IPTp, etc are prescribed to the women during pregnancy. Thus, depending on the timing during pregnancy of enrolment in the study, risk factors may change. This should be discussed in the manuscript.

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Reviewer #1: No

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4 Oct 2019

Dear editor and reviewers

PONE-D-19-15457R1

Determinants of Anemia among Pregnant Women Attending Antenatal Care in Horo Guduru Wollega Zone, West Ethiopia: Unmatched case-control study

First of all, we would like to thank you for providing the reviewers’ comments which are very constructive and crucial. We have incorporated all the point by point below. We have highlighted “red” the changes made in the manuscript and we have a separate file for “manuscript with track changes” and a clean manuscript “manuscript”. We have also attached a rebuttal letter “Response to reviewers” which responds reviewers’ comments and/suggestions point by point.

Response to the reviewers

1. There is still a major comment which is gestational age at enrolment. Gestational age at enrolment should be described. Indeed, the definition of anemia changes over pregnancy, and iron supplementts, anti-helminthic treatments, IPTp, etc are prescribed to the women during pregnancy. Thus, depending on the timing during pregnancy of enrolment in the study, risk factors may change. This should be discussed in the manuscript.

Response: Pregnant women at any gestational age (GA) were included in the study. GA of pregnant women was classified into trimesters i.e. GA below 12 weeks: first trimester, GA of 13- 24 weeks: second trimester and GA above 24 weeks: third trimester. The gestational age was calculated from last normal menstrual period (LNMP) which was determined by antenatal care providers. In Ethiopia, health extension workers register pregnant women of any GA with their last normal menstrual period at home, thus, GA is not usually missed. The proportion of gestational age among the study participants is already described in the manuscript and supporting files.

GA was not a significant predictor of anemia among cases and multicollinearity test was done by using VIF to assess presence of collinearity among independent variables and the value of VIF was within the acceptable range which showed no collinearity. Therefore, there was no correlation between GA and other risk factors of anemia in our study which means the risk factors of anemia were not changeable based on differences in gestational age.

Submitted filename: 6. Response to reviewers.docx

Click here for additional data file.

16 Oct 2019

Determinants of Anemia among Pregnant Women Attending Antenatal Care in Horo Guduru Wollega Zone, West Ethiopia: Unmatched case-control study

PONE-D-19-15457R2

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21 Oct 2019

PONE-D-19-15457R2

Determinants of Anemia among Pregnant Women Attending Antenatal Care in Horo Guduru Wollega Zone, West Ethiopia: Unmatched case-control study

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Table 1

Sociodemographic characteristics of study participants who were attending ANC in the public health facilities of Horo Guduru Wollega Zone, West Ethiopia from September 7 to October 25, 2017 (n = 573).

Variables		Frequencies (%)
		Cases	Controls
Age	15–19	6(3.1)	20(5.2)
	20–24	52(27.2)	91(23.8)
	25–29	67(35.1)	152(39.8)
	30–34	40(21.1)	78(13.6)
	35–39	21(11)	38(10)
	40–44	5(2.6)	3(0.8)
Marital status	Never married	3(1.6)	2(0.5)
	Married	181(94.8)	369(96.6)
	Widowed	4(2.1)	4(1)
	Divorced	3(1.)6	7(1.8)
Residence	Urban	73(38.2)	168(44)
	Rural	118(61.8)	214(56)
Family size	<5	115(60.2)	240(62.8)
	≥5	76(40)	142(37.2)
Occupation of respondent	Governmental employee	26(13.6)	77(20.2)
	Farmer	113(59.2)	201(52.6)
	Merchant	32(16.8)	58(15.2)
	Daily laborer	11(5.8)	14(3.7)
	Other	9(4.7)	32(8.4)
Occupation of husband	Governmental employee	39(20.4)	98(25.7)
	Farmer	115(60)	199(52)
	Merchant	20(10.5)	55(14.4)
	Daily laborer	13(6.8)	23(6)
	Other	4(2.1)	7(1.8)
Income	<500	85(44.5)	40(10.5)
	500–1499	53(27.7)	146(38.2)
	1500–2499	22(11.5)	54(14)
	2500–3499	13(6.8)	39(10.2)
	>3500	18(9.4)	103(27)
Educational status	No education	59(31)	74(19.3)
	Primary school	75(39.3)	151(39.5)
	Secondary school	24(12.6)	63(16.5)
	Above secondary school	33(17.3)	94(24.6)

Table 2

Diseases related factors of anemia among pregnant women who were attending ANC follow up in the selected public health facilities of Horo Guduru Wollega Zone, West Ethiopia from September 7 to October 25, 2017(n = 573).

Variables			Frequencies (%)
			Cases	Controls
Malaria	Yes		11(5.8)	2(0.5)
	No		180(94.2)	380(99.5)
Diarrhea in the last 2 weeks	Yes		22(11.5)	21(5.5)
	No		169(88.5)	361(94.5)
Syphilis infection	Yes		19(10)	14(3.7)
	No		172 (90)	368(96.3)
Intestinalhelminthicinfection	Yes		76(39.9)	25(6.5)
	No		115(60.1)	357(93.5)
	Ascaris Lumbricoides	Yes	29(15)	12(6.3)
		No	161(84.7)	371(96.8)
	Tricuris Trichiura	Yes	14(7.4)	5(1.3)
		No	176(92.6)	378(98.7)
	Hookworm	Yes	27(14)	6(1.56)
		No	163(85.8)	377(98.4)
	Hymenolepis nana	Yes	8(4.2)	4(1)
		No	182(95.8)	379(98.9)

Table 3

Hygiene and sanitation-related factors of anemia in pregnant women attended ANC follow up in the selected public health facilities of Horo Guduru Wollega Zone, West Ethiopia from September 7 to October 25, 2017 (n = 573).

Variables		Frequencies (%)
		Cases	Controls
Using latrine	Yes	167(87.4)	351(91.9)
	No	24(12.6)	31(8.1)
Hand washing facility with latrine	Yes	36(18.8)	104(27.2)
	No	139(72.8)	264(72.8)
Solid waste disposal site	Open-pit	41(21.5)	90(23.6)
	Open field	134(70.2)	246(64.4)
	Sanitary landfill	15(7.4)	46(12)
Source of drinking water	Tap water	87(45.5)	201(52.6)
	Protected spring	56(29.3)	115(30)
	Unprotected spring	32(16.8)	42(11)
	River	14(7.3)	20(5.2)
	Other	2(1)	4(1)
Treatment for the not potable water source	Yes	78(75)	150(82.8)
	No	79(76)	137(75.6)
Handwashing before food preparation	Yes	190(99)	381(96.9)
	No	1(0.5)	1(0.3)

Table 4

Multivariate binary logistic regression analysis of determinants of anemia among pregnant women in the selected public health facilities of Horo Guduru Wollega Zone, West Ethiopia from September 7 to October 25, 2017(n = 573).

Variables		Frequencies(%)		COR(95%CI)	AOR(95%CI)	P value
		Cases	Controls
Income	<500	85(44.5)	40(10.5)	12.16(6.5,22.74)*	9.16(4.23,19.82)	<0.001***
	500–1499	53(27.7)	146(38.2)	2.08(1.15, 3.75)*	1.83(0.88, 3.81)	0.11
	1500–2499	22(11.5)	54(14)	2.33(1.15, 4.72)*	1.83(0.78, 4.29)	0.17
	2500–3499	13(6.8)	39(10.2)	1.91(0.86, 4.26)	2.53(0.97, 6.63)	0.06
	>3500	18(9.4)	103(27)	1	1
Menstrual period	≥8 days	46(24)	32(8.4)	3.5(2.12, 5.67)*	2.11(0.97, 4.59)	0.06
	<8 days	145(76)	350(91.6)	1	1
Heavy menstrual bleeding	Yes	61(31.9)	61(16)	2.47(1.64, 3.72)*	2.38(1.38, 4.09)	0.002**
	No	130(68.4)	321(83.8)	1	1
Parity	Nulliparous	53(28)	132(34.5)	1	1
	Primipara	40(20.9)	80(20.9)	1.24(0.76, 2.04)	2.52(0.99, 6.44)	0.054
	Multipara	45(23.7)	92(24)	1.22(0.76,1.97)	1.82(0.72, 4.59)	0.20
	Grandpara	53(28)	78(20.4)	1.69(1.06, 2.72)*	2.28(0.91, 5.74)	0.08
Abortion	Yes	28(14.7)	34(8.9)	1.76(1.03, 2.99)*	0.92(0.44, 1.94)	0.83
	No	163(85.3)	348(91)	1	1
Birth interval	<2 years	26(13.7)	21(5.5)	2.87(1.55, 5.30)*	2.22(0.85, 5.76)	0.10
	≥2 years	116(61)	272(71)	1	1
ANC follow up	Yes	147(77)	350(91.6)	1	1
	No	44(23)	32(8.4)	3.27(1.99, 5.37)*	1.99(0.75, 5.31)	0.17
Trimester	First	12(6.3)	42(11)	1
	Second	55(29)	120(31.3)	1.47(0.96, 2.24)
	Third	123(64.7)	221(57.7)	1.41(0.79, 2.51)
Bleeding	Yes	22(11.6)	13(3.4)	3.7(1.82,7.51)*	1.25(0.41, 3.76)	0.69
	No	169(88.5)	369(96.6)	1
Nausea and vomiting	Yes	63(33)	89(23.3)	1.62(1.10, 2.38)*	0.98(0.54, 1.82)	0.97
	No	128(67)	293(76.7)	1	1
Took iron	Yes	104(54.5)	273(71.5)	1	1
	No	87(45.8)	109(28.5)	2.09(1.46, 3.01)*	1.29(0.69, 2.39)	0.43
Taking iron supplement daily	Yes	63(60.6)	239(87.6)	1	1	1
	No	41(39.4)	34(12.4)	4.58(2.69, 7.79)*	2.87(1.41, 5.84)	0.004**
Frequency of eating vegetables	≤3/week	56(29.3)	175(45.8)	1	1
	≥3/week	135(70.7)	207(54.2)	2.04(1.41, 2.95)*	1.33(0.72, 2.47)	0.36
MUAC	<23	96(50.3)	58(15.2)	5.72(3.84, 8.53)*	3.42(2.07, 5.63)	<0.001**
	≥23	95(49.7)	324(84.8)	1	1	*
DDS	Low	57(30)	26(6.8)	27.13(11.5,63.9*	12.3(4.64, 32.72)	<0.001**
	Medium	126(66)	257(67.3)	6(2.86,12.86)*	3.40(1.48, 7.84)	*
	High	8(4.2)	99(25.9)	1	1	0.004**
Ascaris Lumbricoides	Yes	29(15.2)	12(3.14)	5.57(2.7, 11.19)*	6.81(3.35,13.85)	<0.001***
	No	47(24.6)	13(3.4)	1	1
Tricuris Trichiura	Yes	14(7.3)	5(1.3)	6.01(2.13,16.96*	8.12(2.85, 23.16)	<0.001***
	No	176(92)	378(98.9)	1	1
Hookworm	Yes	27(14)	6(1.57)	4.17(1.24, 14.0)*	13(5.24,32.45)	<0.001***
	No	49(25.6)	19(4.97)	1	1
Hymenolepis nana	Yes	8(4.2)	4(1)	10.41(4.22, 25.7)	4.88(1.38, 17.14)	0.01*
	No	68(35.6)	21(5.49)	1	1

*P < 0.05

**P< 0.01

***P< 0.001

MUAC: Mid-upper arm circumference, DDS: Dietary diversity score