Prevalence and determinants of anemia among young (15–24 years) women in Ethiopia: A multilevel analysis of the 2016 Ethiopian demographic and health survey data

Misganaw Gebrie Worku; Getayeneh Antehunegn Tesema; Achamyeleh Birhanu Teshale

doi:10.1371/journal.pone.0241342

. 2020 Oct 30;15(10):e0241342. doi: 10.1371/journal.pone.0241342

Prevalence and determinants of anemia among young (15–24 years) women in Ethiopia: A multilevel analysis of the 2016 Ethiopian demographic and health survey data

Misganaw Gebrie Worku ^1,^*, Getayeneh Antehunegn Tesema ², Achamyeleh Birhanu Teshale ²

Editor: Frank T Spradley³

PMCID: PMC7599045 PMID: 33125382

Abstract

Background

Anemia is a major global public health problem that had tremendous impacts on human health, social and economic development. African countries contribute to the highest-burden of anemia among women, particularly in adolescent females and young women. Anemia among young women remains a public health problem in most parts of Africa, including Ethiopia. Therefore, this study aimed to investigate the prevalence and determinants of anemia among young women in Ethiopia.

Methods

A secondary data analysis was conducted based on the 2016 Ethiopian Demographic and Health Survey (EDHS) data. A total weighted sample of 5796 young women (15–24 years) was included in this study. We employed a multilevel analysis to assess factors associated with anemia since the EDHS has hierarchical nature. Deviance, Intraclass Correlation Coefficient (ICC) and Median Odds Ratio (MOR) were used for model comparison as well as for assessing model fitness. Variables with a p-value of less than 0.20 at bivariable multilevel analysis were considered for the multivariable multilevel analysis. In the multivariable multilevel analysis variables with p-value ≤ 0.05 were declared to be a significant factor associated with anemia, and the Adjusted Odds Ratio (AOR) with the 95% Confidence Interval (CI) were reported to assess the strength and direction of the association.

Results

The overall prevalence of anemia among young women was 21.7% (95%CI = 20.7%, 22.8%). In the multivariable multilevel binary logistic regression analysis; being Muslim religion follower [adjusted odds ratio (AOR) = 1.31, 95%CI = 1.07, 1.70] and being protestant religion follower [AOR = 1.31; 95%CI = 1.01, 1.71], being rural dweller [AOR = 1.34; 95%CI = 1.02, 1.78], and being married [AOR = 1.46; 95%CI = 1.22, 1.74] were significantly associated with higher odds of anemia among young women. While, modern contraceptive use (AOR = 0.66; 95%CI = 0.53, 0.83) were significantly associated with lower odds of anemia among young women.

Conclusion

In this study, the prevalence of anemia among young women was high. Being a follower of Muslim and protestant religions, being married women, modern contraceptive use and being from the rural area were found to be significant determinants of anemia among young women. Therefore, giving special attention to these high-risk groups and distributing modern contraceptives for those in need of it could decrease this devastating public health problem in young women.

Background

Anemia is a global public health problem that affects both developing and developed countries with a high impact on human health, social and economic growth [1]. It is prevalent at all stages of life, but it is more prevalent in female adolescents and young women [1]. Young women including adolescent females are susceptible to anemia because of their biological demands for micronutrients associated with rapid body growth and the depletion of these nutrients due to parasitic infestations [2]. Anemia is also common in puberty due to the onset of menstruation, which alters an individual’s iron status by generating more demand for iron, blood loss and pro-inflammatory processes due to menstrual cycles [3].

Globally, it was estimated that one-third of the total population (32.9%) is suffered from anemia with sub-Sahara African countries contributed to the highest anemia burden [4]. More than half of young women worldwide have suffered from anemia and this figure is significantly higher than the World Health Organization’s cut-off value for identifying anemia as a public health problem [5]. Approximately one-quarter of young women in developing countries are anemic [6]. Most African and other low and middle-income countries contribute to the highest-burden of anemia among young women [5]. Anemia burden among young women is also common in sub-Saharan African countries which ranges from 13.7% in Ethiopia to 61.5% in Ghana [5]. Ethiopia also shares the high burden of anemia in young women which ranges from 24% to 38%, with an average rate of 29%[7]. Anemia in young women is a serious condition which impedes them from reaching their full potential by reducing educational achievement, labor productivity as well as their cognitive capacity and affect their mental health [1, 8]. Besides, in pregnant women, the risk of birth complications and the delivery of low birth-weight infants increases with anemia [9].

According to different studies, many factors such as educational status, marital status, wealth status, nutritional status, occupation, type of toilet facility, source of drinking water, contraceptive use, distance from the health facility, and region are associated with anemia in young women [3, 10, 11]. The extra needs of nutrients because of rapid growth and physical change in young women commonly result in nutritional deficiencies which are the common causes for anemia.

Despite its common occurrence in young women, most previous studies focused on anemia among the reproductive age group (15 to 49 years) [12, 13] and to our knowledge, there is a scarcity of information on the prevalence of anemia among young women and its determinants in Africa including Ethiopia. Anemia due to nutritional deficiency rises at the beginning of puberty and associated physical and physiological changes that occur in adolescents and young women that place a major demand on their nutritional requirements, making them more vulnerable to nutritional deficiency anemia [2]. As many literatures reported, the potential factors affecting reproductive age and young women’s anemia are not similar, as young age is the time where nutritional demand is highest. Besides, this study was conducted based on nationally representative Ethiopian Demographic and Health Survey (EDHS) data with a larger sample size that could provide valid information for countries, particularly sub-Saharan African countries and other low- and middle-income countries that had similar socio-economic and socio-cultural patterns. Therefore, this study aimed to investigate the prevalence of anemia and its determinants among young women in Ethiopia. The findings of this study could help to inform policymakers as well as governmental and non-governmental organizations about the magnitude of this problem as well as the potential factors associated with anemia to plan intervention strategies.

Methods

Study area

The study was conducted in Ethiopia which is located at the horn of Africa between 3⁰ and 15⁰ north latitude and 33⁰ and 48⁰ east longitude. The country encompasses 1.1 million sq. Km. Its topographic feature ranges from 4550 meters above sea level to 110 meters below sea level. The current population of Ethiopia is estimated to be 115,286,168 and about 30% of this population is in the young age groups. Ethiopia is administratively divided into nine regional states (Tigray, Afar, Amhara, Oromia, Somali, Benishangul-Gumuz, Southern Nations Nationalities and People Region (SNNPR), Gambella and Harari) and two city administrations (Addis Ababa and Dire Dawa) which is again subdivided into 68 zones, 817 districts and 16,253 kebeles (the country’s lowest administrative units) (Fig 1).

Data source

We used the Ethiopian demographic and health survey (EDHS) 2016 data for this study. A multistage stratified cluster sampling technique was employed to select the study participants using the 2007 population and housing census as a sampling frame. In the first stage, a total of 645 Enumeration Areas (EAs) (202 were from urban areas and the rest from rural areas) were selected while in the second stage, a fixed number of 28 households were selected per each EAs. In the EDHS 2016, a total of 16650 households, 12688 men, and 15683 women were successfully interviewed. For this study, a total weighted sample of 5796 young women aged 15 to 24 years was included (Fig 2). The detailed sampling procedure is presented in the EDHS 2016 report [14].

Study variables

Outcome variable

This study was based on hemoglobin level adjusted by altitude and smoking, which was already provided in the EDHS data. The hemoglobin level found in the survey data set was already adjusted for altitude using the adjustment formula (adjust = − 0.032*alt + 0.022*alt2 and adjHb = Hb—adjust (for adjust > 0)). The outcome variable for this study was anemia level among young women (women in the age group of 15–24 years), which was measured based on women pregnancy status; for pregnant women a hemoglobin value of <11 g/dL was considered as anemic and a non-pregnant woman with a hemoglobin value of <12 g/dL was considered anemic [2].

Independent variables

For this study, both individual and community-level factors were included as independent variables. The individual-level variables considered for our study were; the age of respondent, educational level, religion, marital status, occupation, wealth status, sex of household head, type of toilet facility, source of drinking water, Body Mass Index (BMI), distance from the health facility, family size, modern contraceptive use, and media exposure. Whereas residence, region and community poverty level were the community level variables included in this study (Table 1).

Table 1. Description and measurement of the independent variable.

Independent variables and their description/categorization
Individual level variables
Age Group	Current age of the women and re-coded in to two categories with values of “0” for 15–19, “1” for 20–24.
Religion	Re-coded in four categories with a value of “0” for Muslim, “1” for Orthodox, “2” for protestant, and “3” for other religious groups (combining catholic, traditional and the other religious categories as most young women in this category are small in number).
Wealth Index	The datasets contained wealth index that was created using principal components analysis coded as “poorest”, “poorer”, “Middle”, “Richer”, and “Richest in the EDHS data set.” For this study we recoded it in to three categories as “poor” (includes the poorest and the poorer categories), “middle”, and “rich” (includes the richer and the richest categories)
Occupation	Re-coded in two categories with a value of “0” for not working, and “1” for working.
Distance to health facility	The variable distance to health facility recorded as a big problem and not a big problem in the dataset was retained without change, which is respondents’ perception during the survey whether they perceived the distance from the health facility to get self-medical help as a big problem or not.
Media exposure	A composite variable obtained by combining whether a respondent reads newspaper/magazine, listen to radio, and watch television with a value of “0” if women were not exposed to at least one of the three media, and “1” if a woman has access/exposure to at least one of the three media.
Educational status	This is the minimum educational level a woman achieved and re-coded into three groups with a value of “0” for no education, “1” for primary education, and “2” for secondary and above (combining secondary and higher education categories together).
Marital status	This was the current marital status of women and recoded in two categories with a value of “0” for unmarried (includes those who were never in union, divorced, widowed, and separated), and “1” for “married” (includes those living with a partner and those who are married)
Type of toilet facility	Recoded into two categories as “unimproved “includes and “improved”, using the DHS guide.
Source of drinking water	By using the DHS guide it was recoded into two categories as “unimproved” and “improved source”
Sex of household	The variable sex of household head was recorded as male and female in the dataset and we used without change.
Modern contraceptive	Recoded into two categories with a value of 0 for “no” if a woman doesn’t use any of the modern contraceptive methods, and 1 for “Yes” if a women use any of the modern contraceptive methods. of either of or combination of the following methods (female sterilization, male sterilization, contraceptive pill, intrauterine contraceptive device, injectables, implants, female condom, male condom, diaphragm, contraceptive foam and contraceptive jelly, lactational amenorrhea method, standard days method, and respondent-mentioned other modern contraceptive methods (including cervical cap, contraceptive sponge,))
Family size	Recoded in to two categories as 1–5, and greater than 5.
Body mass index	Re-coded in to three categories with values of 0 for underweight (<18.5Kg/m²), 1 for normal (18.5 to 24.9 Kg/m²), and 2 for overweight (>25Kg/m²).
Community-level variables
Community poverty level	Measured by proportion of households in the poor (combination of poorer and poorest) wealth quintile derived from data on wealth index. Then it was categorized based on national median value as: low (communities in which <50% of women had poor socioeconomic status) and high (communities in which ≥50% of women had poor socioeconomic status) poverty level.
Type of place of residence	The variable place of residence recorded as rural and urban in the dataset was used without change.
Region	The variable region was corded in to 11 categories in the dataset and we was retained without change.

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Data management and analysis

Data extraction, recoding and analysis (both descriptive and analytical) were done using STATA version 14 software. The data were weighted before any statistical analysis to restore the representativeness of the data and to get a reliable estimate and standard error. A multilevel binary logistic regression analysis was done to identify significant determinants of anemia to consider the hierarchical nature of EDHS data. In EDHS, women were nested within-cluster and women within the same cluster are more likely to share similar characteristics than women in another cluster, which violates the independent assumptions of the standard logistic regression model such as the independent and equal variance assumptions. Four models were constructed; the first model (the null model) constructed only with the presence of outcome variable without independent variables, the second model (Model I) fitted the individual-level variables only with the outcome variable, third model (Model II) fitted community-level variables only with the outcome variable, and the final model (model III) fitted both individual and community level variables with the outcome variable. The Intraclass Correlation Coefficient (ICC), and Median Odds Ratio (MOR) were checked to indicate whether there was clustering or not. Model comparison/fitness was done using deviance (-2 log-likelihood) and the Proportional Change in Variance (PCV) since these models were nested, and the model with the lowest deviance was chosen. Both bivariable and multivariable multilevel logistic regression were done and variables with p-value <0.2 in the bivariable analysis were considered for multivariable analysis. Finally, variables with P-value <0.05 in the multivariable analysis were considered as significant factors associated with anemia.

Ethical consideration

Since the study was a secondary data analysis, based on publically available survey data, ethical approval and participant consent were not necessary. However, we asked the DHS Program and permission was granted to download and use the data for this study from http://www.dhsprogram.com. The Institution Review Board approved procedures for DHS public-use datasets do not in any way allow respondents, households, or sample communities to be identified. There are no names of individuals or household addresses in the data files. The document was submitted to the University of Gondar ethical review board (one of the major University in Ethiopia) and the ethical review board approved that ethical clearance is not needed for such type of study, since it is based on nationally representative EDHS data.

Results

Sociodemographic characteristics of respondents

Individual-level factors

A total sample of 5796 young women was included in this study. More than half (54.61%) of the respondents were aged 15 to 19 years and 54.67% of respondents had primary education. Regarding wealth status and religion, 48.09% of respondents were from rich households and about 43.01% of respondents were practicing orthodox Christian religion. About 64.18% of respondents were from households with an improved water source and 83.78% of participants were from households with an unimproved toilet facility. Concerning family size, the majority (58.99%) of women were from a family size of 1 to 5 and 72.59% of women were not currently working (Table 2).

Table 2. Sociodemographic characteristics of the respondents in Ethiopia, 2016 (N = 5796).

Variables		Frequency (%)
Individual-level factors
Age (years)	15–19	3165(54.61%)
Age (years)	20–24	2631(45.39%)
Highest education level	No education	1164(20.08%)
	Primary education	3168(54.67%)
	Secondary and above	1464(25.25%)
Wealth index	Poor	1932(33.33%)
	Middle	1077(18.58%)
	Rich	2787(48.09%)
Occupation	No	4207(72.59%)
Occupation	Yes	1589(27.41%)
Religion	Muslim	1758(30.33%)
	Orthodox	2493(43.01%)
	Protestant	1416(24.43%)
	Other ^*	129(2.23%)
Marital statues	Unmaried	3591(61.97%)
Marital statues	Maried	2205(38.03%)
Family size	1–5	3361(58.99%)
Family size	>5	2435(42.01%)
Body mass index	Underweight	1405(24.24%)
	Normal	4129(71.24%)
	Overweight	262(4.52%)
Type of toilet facility	Unimproved	4856(83.78%)
Type of toilet facility	Improved	940(16.22%)
Source of drinking water	Unimproved	2076(35.82%)
Source of drinking water	Improved	3720(64.18%)
Modern contraceptive use	No	943(16.27%)
Modern contraceptive use	Yes	4853(83.73%)
Sex of household head	Male	4388(75.71%)
Sex of household head	Female	1408(24.29%)
Media exposure	No	2897(49.98%)
Media exposure	Yes	2899(50.02%)
Distance to health facility	Big problem	2814(48.54%)
Distance to health facility	Not big problem	2982(51.46%)
Community level factors
Residence	Urban	1331(22.97%)
Residence	Rural	4465(77.03%)
Community poverty level	Low	2832(48.86%)
Community poverty level	High	2964(51.14%)
Region	Tigray	465(8.03%)
	Afar	52(0.90%)
	Amhara	1340(23.12%)
	Oromia	2113(36.46%)
	Somali	162(2.81%)
	Beni Shangul	58(1.01%)
	SNNPR	1180(20.36%)
	Gambella	17(0.30%)
	Harari	13(0.23%)
	Addis Ababa	362(6.25%)
	Dire Dawa	32(0.54%)

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* = Catholic, traditional, other.

Community-level factors

The majority (77.03%) of the respondent were rural dwellers and 36.46% of respondents were from the Oromia region. More than half (51.14%) of the participants were from communities with a higher poverty level (Table 2).

Prevalence of anemia among young women in Ethiopia

In this study, the prevalence of anemia among young women was 21.7% (95% CI: 20.7%, 22.8%). Young women from Somalia (56.80%) and Afar (43.93%) region had a higher prevalence of anemia and those from Addis Ababa had a lower prevalence of anemia (Fig 3).

Random effect model and model fitness

The random-effect model was assessed using ICC, MOR, and PCV. In the null model the ICC value which was 0.22, indicates that 22% of the total variation of anemia in young women was due to differences between clusters/communities. Besides, the highest MOR value which was 2.53 indicates that there was significant clustering of anemia in young women. Moreover, the highest PCV (0.72) in the final model (model III) revealed that about 72% of the variation in anemia was explained by both individual and community-level factors. Regarding model fitness, the final model (model III), which incorporates both individual and community level factors, was the best-fitted model since it had the lowest deviance (5945.24) (Table 3).

Table 3. Random effect model and model fitness for the assessment of anemia among young women in Ethiopia.

Parameter	Null model	Model I	Model II	Model III
Community-level variance	0.946	0.410	0.305	0.015
ICC	0.22	0.11	0.08	0.07
MOR	2.53(2.27–2.80)	1.84(1.66–2.03)	1.70(1.54–1.88)	1.63(1.48–1.82)
PCV	Reff	0.57	0.68	0.72
Model fitness
Log likelihood	-3156.66	-3029.84	-3005.15	-2972.62
Deviance	6313.32	6059.68	6010.30	5945.24

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Determinant of anemia among young women in Ethiopia

We used the final model (the best-fitted model) to assess the determinants of anemia among young women in Ethiopia.

All variables except sex of the household head were significant in the bivariable analysis (had p<0.20). In the multivariable analysis, both individual-level factors (religion, marital status and modern contraceptive use) and community-level factors (residence and region) were found to be significant determinants of anemia among young women. The odds of having anemia were 1.31 [adjusted odds ratio (AOR) = 1.31; 95%CI = 1.07, 1.70], and 1.31 [AOR = 1.3; 95%CI 1.01, 1.71] times higher among women who practiced Muslim and protestant religions respectively as compared with those who practicing orthodox Christian religion. The odds of developing anemia in young women was 1.46 [AOR = 1.46; 95%CI = 1.22, 1.74] times higher among married women as compared with their counterparts. A young woman who used modern contraceptives had 34% (AOR = 0.66; 95%CI = 0.53, 0.83) lower odds of developing anemia compared with those who do not use modern contraceptives. Being a woman from a rural area had 1.34 [AOR = 1.34; 95%CI = 1.02, 1.78] times higher odds of anemia as compared with those from urban. The odds of developing anemia were higher among women in Somali [AOR = 3.63; 95% CI = 2.39, 5.51], Dire Dawa [AOR = 1.52; 95% CI = 1.01, 2.30], and Afar (AOR = 2.02; 95%CI = 1.31, 3.11) regions and lower among women from Amhara (AOR = 0.60; 95%CI = 0.39, 0.92) and Beni-shangul (AOR = 0.60; 95%CI = 0.37, 0.93) regions as compared with women from Addis Ababa (Table 4).

Table 4. Bi variable and multivariable multilevel analysis for the assessment of determinants of anemia among young women in Ethiopia, 2016.

Variables		Anemia		COR (95%CI)	AOR (95%CI)	p- value
Variables		Yes	No	COR (95%CI)	AOR (95%CI)	p- value
Age (years)	15–19	631	2534	1	1
Age (years)	20–24	627	2004	0.06(1.01, 1.31)	1.07(0.90, 1.26)	0.34
Highest education level	No education	325	839	1	1
	Primary education	699	2469	0.57(0.48, 0.68)	0.93(0.77, 1.12)	0.45
	Secondary and above	234	1230	0.40(0.32, 0.50)	0.81(0.65, 1.03)	0.09
Wealth index	Poor	524	1408	1	1
	Middle	220	857	0.62(0.50, 0.78)	0.89(0.70, 1.12)	0.34
	Rich	514	2273	0.46(0.38, 0.54)	0.85(0.66, 1.08)	0.18
Occupation	No	956	3251	1	1
Occupation	Yes	302	1287	0.74(0.63, 0.86)	0.93(0.79, 1.09)	0.40
Religion	Orthodox Christian	399	2094	1	1
	Muslim	497	1261	3.07(2.56, 3.70)	1.31(1.07, 1.70)	0.01
	Protestant	307	1109	1.53(1.21, 1.92)	1.31(1.01, 1.71)	0.83
	Other ^*	55	74	1.71(0.93, 3.15)	1.30(0.71, 2.36)	0.90
Marital status	Unmaried	676	2915	1	1
Marital status	Maried	582	1623	1.58(1.37, 1.81)	1.46(1.22, 1.74)	0.00
Family size	1–5	740	2621	1	1
Family size	>5	519	1916	0.99(0.87, 1.14)	1.08(0.93, 1.25)	0.30
Body mass index	Normal	885	3244	1	1	0.92
	Underweight	320	1085	1.10(0.95, 1.28)	1.01(0.86, 1.17)
	Overweight	53	209	0.71(0.52, 0.98)	0.79(0.57, 1.09)	0.15
Type of toilet facility	Unimproved	1091	3765	1
Type of toilet facility	Improved	167	773	0.74(0.62, 0.89)	0.86(0.71, 1.06)	0.18
Source of drinking water	Unimproved	539	1534	1	1
Source of drinking water	Improved	719	3001	0.69(0.59, 0.81)	0.98(0.83, 1.16)	0.87
Modern contraceptive use	No	1089	3764	1	1
Modern contraceptive use	Yes	170	773	0.66(0.53, 0.82)	0.66(0.53, 0.83)	0.00
Media exposure	No	2179	2179	1	1
Media exposure	Yes	2358	717	0.58(0.51, 0.68)	0.88(0.74, 1.04)	0.16
Distance to health facility	Big problem	677	2136	1	1
Distance to health facility	Not big problem	581	2401	0.76(0.65, 0.88)	0.97(0.83, 1.13)	0.74
Residence	Urban	219	1112	1	1
Residence	Rural	1034	3425	2.01(1.61, 2.48)	1.34(1.10, 1.78)	0.03
Community poverty level	Low	524	2308	1	1
Community poverty level	High	735	2229	2.22(1.83, 2.70)	0.90(0.70, 1.15)	0.41
Region	Addis Ababa	50	312	1	1
	Tigray	77	388	1.25(0.86, 1.83)	0.81(0.53, 1.22)	0.31
	Afar	23	29	5.80(3.97, 8.49)	2.02(1.31, 3.11)	0.001
	Amhara	200	1140	1.03(0.69, 1.52)	0.60(0.39, 0.92)	0.02
	Oromia	556	1557	2.18(1.52, 3.13)	0.95(0.63, 1.43)	0.82
	Somali	91	72	9.73(6.70, 14.11)	3.63(2.39, 5.51)	0.00
	Beni Shangul	10	48	1.23(0.80, 1.90)	0.60(0.37, 0.93)	0.02
	SNNPR	234	942	1.40(0.96, 2.04)	0.67(0.43, 1.03)	0.07
	Gambella	5	13	2.37(1.58, 3.57)	1.19(0.78, 1.85)	0.43
	Harari	3	10	2.11(1.33, 3.24)	1.19(0.76, 1.84)	0.43
	Dire Dawa	8	23	2.37(1.57, 3.57)	1.52(1.01, 2.30)	0.04

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* = Catholic, traditional, other.

Discussion

Anemia among young women is a major public health problem in low and middle-income countries [5]. This study aimed to investigate the prevalence and determinants of anemia among young women in Ethiopia. In this study, the prevalence of anemia among young women was 21.70% (95% CI: 20.66%, 22.78%), which is in agreement with other studies conducted in Armenia and East Timor [5]. The prevalence in this study was greater than a previous study in Ethiopia that found anemia in 13.7% of young women [5]. This might indicate the poor management and implementation of health policy in Ethiopia and also the variation of anemia prevalence across population subgroups. Also, this could be due to the increased risk of chronic disease and other pathological conditions that may increase the risk of anemia over time [15]. The finding in this study was also greater than the anemia prevalence in Rwanda, with greater than the 15.6% anemia found among young women in Rwanda [5]. This might be because of the socioeconomic and sociocultural differences between populations of different African countries. However, the prevalence in our study was smaller than studies reported in sub-Saharan African countries (Burkina Faso, Benin and democratic republic of Congo) [5]. This might be due to the variation in the availability of foodstuffs, health care services access and utilization, and living conditions [16].

The multilevel logistic regression analysis showed that young women who practice Muslim and protestant religion, married, rural residence, modern contraceptive use, and being women from Afar, Amhara, Somalia, Beni-shangul, and Dire Dawa were significantly associated with anemia. The odds of developing anemia among women who practice Muslim religion were higher as compared with Orthodox Christian religion followers. This is consistent with a previous study done in Ethiopia [11]. The possible explanation could be due to the deeply rooted cultural and religious beliefs in food restrictions like pork meat, fish meat, goat meat and bacon and other potential dietary nutrients that are the best source of iron, vitamin B12 and folate which are not allowed to be used culturally in Muslim religions [17]. Besides, the increased chances of anemia among Muslim religious followers might be due to the restriction of the use of different hormonal contraceptives, which could minimize the risk of developing anemia [18]. Married young women had higher odds of anemia as compared to unmarried women. This is in contrast with the finding of prior studies [3, 13, 19]. This may be because married women can give birth and are vulnerable to pregnancy and birth-related bleeding, as well as complications that may raise the risk of anemia [20].

The study at hand also revealed that being women from rural areas was associated with a higher likelihood of anemia. This is in agreement with a prior study done in Ethiopia [3]. This might be attributed to inadequate access to dietary supplements, due to limited access to maternal health care services, in rural women [12]. In addition, parasitic infections such as hookworm and malaria are widespread in rural residents due to their lifestyles (such as walking barefooted and poor personal hygiene) which are the leading causes of anemia in Ethiopia [21]. Women who used modern contraceptives had lower odds of developing anemia as compared to those who didn’t use modern contraceptives. This finding was supported by a study conducted in Rwanda [22]. This could be justified by the protective effects of modern contraceptives on menstrual bleeding, pregnancy and birth-related hemorrhages [23]. Concurrent iron supplementation is also available particularly for those women who have used oral contraceptives, which is very important for the prevention of anemia [23].

Moreover, in this study, the probability of developing anemia differed across regions, this may be attributed to differences in the source of food and difference in the availability of the varieties of foods in different regions [24]. Additionally, the difference in anemia risk across regions may be related to the availability and use of health services, and the disparity in the distribution of communicable diseases (such as malaria, visceral leishmaniasis, and hookworm, which are common in lowland areas) across different regions, which are considered as the most common causes of anemia. Furthermore, the regional variation of anemia may be related to the low socio-economic status of some regions especially those found in border areas of Ethiopia, which may lead to inadequate access to foods that are rich in iron [11].

Strength and limitation of the study

The study has many strengths, first, the study was based on a weighted nationally representative data with a large sample size. Also, the analysis was done using the multilevel analysis to accommodate the hierarchical nature of the EDHS data to get a reliable estimate. Moreover, since it is based on the national survey data, the study has the potential to give insight for policy-makers and program planners to design appropriate intervention strategies both at national and regional levels. However, this study had limitations in that the EDHS survey was based on respondents’ self-report, this might have the possibility of recall bias. Besides, since this study was based on survey data, we are unable to show the temporal relationship between anemia and independent variables. Moreover, since this study was based on information available on the survey, other confounders such as infections (the presence of malaria, intestinal parasites, and HIV/AIDS) were not adjusted. Moreover, it is difficult to assess some important variables such as age at first childbearing and any prophylaxis given during pregnancy as this information is recorded for those who gave birth and those who were/are pregnant respectively (missing for those who did not give birth and not pregnant).

Conclusion

In this study, the prevalence of anemia among young women was high. Both individual and community-level factors were associated with anemia in young women. Being a follower of Muslim and protestant religions, being married women, modern contraceptive use, being from rural area and region were found to be significant determinants of anemia among young women. Therefore, giving special attention to these high-risk groups such as rural dwellers and those in border regions, as well as distributing modern contraceptives for those in need of it could decrease this devastating public health problem in young women.

Acknowledgments

We greatly acknowledge MEASURE DHS for granting access to the Ethiopia Demographic and Health Surveys data.

Abbreviations

CI: Confidence Interval
CSA: Central Statistical Agency
DHS: Demographic Health Survey
EA: Enumeration Ar
EDHS: Ethiopian Demographic Health Survey
ICC: Intraclass Correlation Coefficient
LLR: Likelihood Ratio
PCV: Proportional change in Variance
WHO: World Health Organization

Data Availability

Data is available online and you can request it from www.measuredhs.com. The authors did not have any special access privileges that others would not have.

Funding Statement

The authors received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0241342.r001

Decision Letter 0

Frank T Spradley

5 Aug 2020

PONE-D-20-18515

Prevalence and determinants of Anemia among young (15-24 years) women in Ethiopia; A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data

PLOS ONE

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Reviewer #1: This is a fine paper and will be useful to the field, however I have some comments:

1) The manuscript need English editing.

2) In table 3; it will be better if author add extra column for p value.

Reviewer #2: Prevalence and determinants of Anaemia among young (15-24 years) women in Ethiopia; A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data. This study is an overview demographic data from Ethiopia were association with anaemia and demographics are made.

I have two major concerns:

As these outcome are interesting and important for national policy makers, I am doubting if it is eligible for the international readers of PLOSONE this as outcomes might be region specific.

Secondly I do not understand why this study is needed, with regards to this age group, are young woman not part of the reproductive age group? What makes them different?

Abstract:

Background:

Line 28: Is this for all of Africa or only sub-sharan Africa? As I believe the needs are not as much possible in northern Africa. Please rephrase.

Line 30:I do not understand the difference between young woman and and woman in the reproductive age group. Is this not the same group? Why is there a difference?

Method:

Line 34 what kind of determinants?

Line 35 MOR/ ICC; please no abbreviations in the abstract without explanation.

Line 36 double (..) .

Line 36-38 this can be shortened not all needed in my perspective in the abstract. What is the definition of young woman’s? I can’t find that In the method.

Results/conclusion: strong and usefull conclusion.

Main manuscript:

Background: The terms young woman and adolescents are used all over the manuscript. However it is unclear what the exact definitions are.

Line 75-78 unclear sentences, which cut-off? Please define more specific.

Line79: Which population? Please define more specific.

Overall line 75-87 this alinea needs to be restructured, the data presenting on adolescents and young woman reproductive are not used in a structured way. Please rephrase and structure.

Line 89-92: This is a line-up most likely from a previous study. Please summarise the only needed information.

Line 93: This is a repetition of what is said in the first alinea. Please rephrase and restructure.

Line 95-96: the reason for his study is that most study look to the reproductive woman, it is unclear for me why this young woman are not part of that see previous comments. I addition: UDAID data 2000 shows that 16% of the woman between 15-19 years have been mothers. Moreover Adolescent childbearing trends and sub-national variations in Ethiopia: a pooled analysis of data from six surveys Yared Mekonnen et al. BMC Pregnancy and Childbirth volume 18, Article number: 276 (2018) shows similar data. Can the author explain why this study is needed next to a study on woman in the reproductive age ?

Line 99: Abbreviation not explained.

Methods:

Line 107-111 can this be displayed in a graph, that makes it easier for the reader to understand.

Line 113: add abbreviation (EDHS) as it used in the next sentence.

Line 113-126 can this be added in a graph/ figure with a flow diagram. That makes it easier for the reader to oversee what happened.

Outcome variable line 128: please define young woman.

Line 129-131 I do not understand this sentence and I am questioning if the sentence is needed. Moreover there is no difference between in mild-moderate-and severe anaemia in the study. So the author should remove this sentence.

Line 132: Reference 14; is this correct? And please add in writing which adjustment is done.

Line 133: Reference 13; correct? This is the WHO definition of anaemia please add the WHO as reference. Independent variable: line 136-140: please add definitions of the variable or add a reference. For example what is wealth status? What includes media exposure?? What includes modern contraceptives? Please rephrase.

Line 138 typo double (,,). Data management and analysis: 148-149 Descriptive (no needed information) please take out.

Line 152-154: this is a difficult statistical method, I cannot comment on it, as I am not familiar with the method.

Results:

Overall percentage can be given in one decimal.

Line 164: weighted sample not needed- please take out. The age range 15-24 can be taken out here, as this will be added to the method section.

The structure of line 165-173: could the author structural outcomes better. As a suggestion group in individual medical- social-economics and community. And use this structure as well in table 1.

Line 181-184: is this difference significant? Figure 1: what is the yellow line, please adjust figure.

Line 186-194: I can not comment on this, as my I do not have enough knowledge on statistics to do so.

Line 196-213/ Table 3: regions: why is all compared to Addis? Nutrition status: why all compared to malnutrition and not to none? Why with occupation display no below yes. Same for contraceptive and media exposure. Please display in a constituent manner. Distance to health facility: not a big problem? What does that mean? How is this defined??

Discussion:

I miss out in the discussion very clear statements why this outcome is 1) different than other woman previous investigated in Ethiopia? 2) is that surprising or not? What did others find in SSA for these age groups? Are you in line with that and if yes or no what are the difference? What are the clear limitations: limitations are stated very minimal. Conclusion: the conclusion is strong.

Line 217: Armenia-Timor: why a comparison tot his places?

Line 218: our country, what was the rate?

Line 219: Rate of comorbidity? This comment is based on which knowledge please explain

Line 236-249: this alinea has a lot of repetitive statements. Please rephrase and structure.

Line 247-249: Please add this to the section on rural areas in line 237-238

Line 254 ( see comment line 236-249)

Imitations: There is no data on age of first child, time between sampling and delivery. So major presumptions are made, but ideally this information would be available to say more about why are these women at risk. Or data on nutrition habits to underline the statements and suggestion. Moreover there is no data on malaria prevalence in this group. Or the availability of prophylaxis during pregnancy. All factors, which can be of major influence. The limitations need rephrasing and suggested limitations should be added.

Reviewer #3: This article covers an important global health concern. However, I believe the manuscript will benefit from a comprehensive language editing.

Please pay particular attention to the following and review the sentences:

Lines 25, 75, 95, 113, 129, 132,140, 150, 167. 170, 199, 229, 234, 238, 244, 253 and 257

Reviewer #4: Great work with potential impact on policy change.

However, the discussion needs to be written with clarity and better understanding. Most of the explanations given for the reported findings are difficult to comprehend.

There are also too many grammatical and spelling errors. The manuscript will benefit from review by a native English speaker.

Reviewer #5: Prevalence and determinants of Anemia among young (15-24 years) women in Ethiopia; A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data

The authors present findings from an analysis of data to determine the prevalence of anemia young women who participated in the 2016 Demographic Health Survey in Ethiopia. The key findings are the prevalence and identification of determinants of anemia among the study participants. The main strength of the study is the large sample size of women whose data were analyzed. However, the paper has several issues that the authors need to address before the paper can be suitable for publication in the journal.

The first issue is that the paper would need substantial English language editing; there are many editorial errors in the paper. The specific issues that require revision in the different components of the paper are provided below:

Abstract

1. The statement that there is a high prevalence of anemia in young persons (line 29) as a justification for the study is contradictory because If there is already high prevalence of anemia among young women why have the authors conducted another study among this same population? This should be clarified.

2. The statement ‘The overall prevalence of anemia among young women were 21.7% (line 40) should read ‘…was 21.7%’.

Background

1. There is need to clarify that the vulnerable population being referred to in line 69 are female adolescents and young women; this is necessary because male adolescents also suffer from anemia. This point should be clarified throughout the manuscript.

2. The statement ‘over half of young women worldwide are suffered...’ line 75 should read ‘… have suffered’

3. The statement ‘…and African as well...’ line 76 is not clear and should be revised.

4. If the statement ‘approximately one quarter of adolescents…’ line 78 is referring to female adolescents this should be clarified

5. There are many repetitive statements about the fact that sub-Sahara Africa has contributed to the high burden of anemia, this should be revised.

6. The authors have listed the socio-demographic factors (lines 89-92) that contribute to anemia in Ethiopia, but examples are not provided to illustrate this point. Some examples should be provided to illustrate this point.

7. The statement ‘Due to rapid growth…’ line 93 is a repetition because this point has been made earlier

8. The sentence ‘…and up to our knowledge’ line 96 should read ‘…to our knowledge’

9. The data for the study were extracted from the 2016 EDHS; is this the latest survey in the country? Have there been other surveys since the one in 2016? If there has been a more recent survey, the authors need to justify why they have used the 2016 survey as source of data for this study. This is should be clarified

Methods

1. An important information missing about the study area is the population of Ethiopia and more importantly the population of young persons in the country.

2. The reference to altitude and smoking (line 132) is not clear; how do these variables relate to the issue investigated. This should be clarified.

Results

1. The statement ‘of women were not had work’ line 170-171 is not clear and should be revised

2. The word ‘afar’ line 183 should read ‘Afar’

3. The use of the phrase ‘followers of Muslim and protestant religion’ line 203 are not clear. A better phrase may be people who practice Islam or Moslems and protestant Christians. This should be revised.

4. The statement ‘… with their counterparts’ line 207 should read ‘with their counterparts who do not’

5. The figure showing prevalence of anemia should have a number and reference should be made to it in the text

Discussion

1. I suggest that the authors provide the figure being referred to in the statement ‘but greater than the previous reported in our country’ line 218

2. The authors should give examples of the food types being referred to in line 228 and support this statement with appropriate reference

3. The statement i.e. barefooted line 241 should be revised to read walking barefooted

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: KEHINDE OKUNADE

Reviewer #5: Yes: Ademola J. Ajuwon

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PLoS One. 2020 Oct 30;15(10):e0241342. doi: 10.1371/journal.pone.0241342.r002

Author response to Decision Letter 0

25 Aug 2020

Date: August 2020

Author's point to point response to editor and reviewers comments

Title: Prevalence and determinants of Anemia among young (15-24 years) women in Ethiopia; A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data

Manuscript number: PONE-D-20-18515

Subject: Submitting a revised version of the manuscript

We would like to thank the reviewers and editor for sharing their view and novel scholarly experiences. The comments are very imperative which we strongly believe in improving the manuscript. We try to address all the comment raised by the revivers and academic editor line by line in the main document. The point-by-point responses for each of the comments, questions, and the revised manuscript are provided in the attached documents.

Thank you for considering our manuscript again.

Response to editor’s comment

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Author’s response: We revised our manuscript based on journals style.

2. During our internal evaluation of the manuscript, we found significant text overlap between your submission and the following previously published works, some of which you are an author.

Author’s response: Thank you. We revise the manuscript in advance and re write the overlapped texts.

3. Thank you for stating the following financial disclosure as “None”. Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

Author’s response: Thank you. For this particular study the authors received no specific funding from any organization and we included this statement in the cover letter.

Author’s response: Thank you for the comment. We consider your comment and we put the ethics statement in the method section of the revised manuscript. Also, the ethics statement putted in the manuscript and in the online submission system is line.

Response to reviewer’s comments

Response to reviewer #1

Dear reviewer we really thank you for your constructive comments and suggestion and we addressed the point you raised.

1. The manuscript need English editing.

Author’s response: Thank you. We extensively edit our manuscript and grammatical errors are corrected.

2. In table 3; it will be better if author add extra column for p value.

Author’s response: we accepted the comment and we have included the p- value in table 3 of the revised manuscript.

Response to reviewer #2

1. I am doubting if it is eligible for the international readers of PLOSONE this as outcomes might be region specific.

Author’s response: Thank you for raising this important issue. This study is based on the nationally representative data with larger sample size from the nine regions and two-city administration of Ethiopia. The finding of this study might be very important for national policy makers to give appropriate intervention for this devastating public health problem which is especially common in young women. Also, the findings of this study might be important for other countries particularly sub-Saharan African countries and other lower and middle income countries which had almost similar socioeconomic and sociocultural patterns with our country. Moreover, other researchers and scholars might be used it as a base line for future studies.

2. I do not understand why this study is needed, with regards to this age group, are young woman not part of the reproductive age group? What makes them different?

Author’s response: Dear reviewer thank you for your important concern. As you know, young women are parts of reproductive age women. However, young women and adolescent females are susceptible to anemia because of their biological demands for micronutrients associated with rapid physical growth and the depletion of these nutrients due to parasitic infestations. Anemia is also common in puberty due to the onset of menstruation, which alter an individual's iron status by generating more demand for iron, and blood loss. Moreover, anemia in young women is a serious condition, which impedes them from reaching their full potential by reducing educational achievement, labor productivity, as well as their cognitive capacity and affect their mental health, which might indirectly affect the future generation, because this women are responsible for the continuity of the generation. Studies also revealed that the prevalence (high prevalence) and the potential factors affecting anemia among reproductive age and young women might not be similar. Therefore, we believe that interventions on these age groups can have a great advantage to increase the academic achievements of women, their labor productivity, and their competitions in every aspect in the society. In addition, interventions at these age groups can prevent future occurrence of anemia and make them healthy throughout their reproductive age. Therefore, we aimed to assess anemia in in these age group women (15-24 years).

3. Line 28: Is this for all of Africa or only sub-sharan Africa? As I believe the needs are not as much possible in northern Africa. Please rephrase.

Author’s response: Thank you. It is for most part of African country and modified in the revised manuscript.

4. Line 30: I do not understand the difference between young woman and woman in the reproductive age group. Is this not the same group? Why is there a difference?

Author’s response: Thank you for the important issue you raised. As we stated above, young women are parts of reproductive age group women. Nevertheless, they are at greater risks of anemia due to their extra needs of micro and macronutrients because of their rapid physiological growth at this age. Besides, if these young women are affected by this public health problem they might be loss their academic achievement and face mental and developmental problems, so they may lose their potential for contributing the development of the country as well as for their personal development. Because of this and the above-mentioned reasons, studying anemia in young population is very crucial.

5. Line 34 what kind of determinants?

Author’s response: Determinant indicate the individual and community level factors that affect anemia in young women and the statement indicating this is found everywhere in the revised version of our manuscript.

6. Line 35 MOR/ ICC; please no abbreviations in the abstract without explanation.

Author’s response: Thank you. Abbreviations are explained when first introduced in the abstract section.

7. Line 36 double (..) .

Author’s response: Thank you. We accepted the comment and we removed the double punctuation.

8. Line 36-38 this can be shortened not all needed in my perspective in the abstract. What is the definition of young woman’s? I can’t find that In the method.

Author’s response: young women that we used in this study is to mean women in the age group 15-24 years and we incorporated it in the method section of the Main manuscript (see in the method section line 132 in the revised manuscript).

9. The terms young woman and adolescents are used all over the manuscript. However it is unclear what the exact definitions are.

Author’s response: Thank you. In general for our study young women were used for the analysis of this data. Usually adolescent women and young women have some difference. Adolescent women usually to mean women of age less than 20, might be from “10 to 19” or “13 to 19” years of old depending on different literatures. However, young women was to mean women from 15 to 24 years of age. Anemia may have a great health impact both in adolescent and young women, but the reason for using young women data for this study was since the EDHS data considers women in the age group 15- 49 years and studies , especially those done using DHS considers women in the age groups 15 to 24 as young women. The information for those adolescent women of less than 15 years are not available in the EDHS data and we prefer to use these age groups (15-24) as young women in this study.

10. Line 75-78 unclear sentences, which cut-off? Please define more specific.

Author’s response: Thank you. It is the WHO cut of point to define anemia as a public health problem. According to WHO, if the prevalence of anemia is greater than 5% it is considered as public health problem and we rephrase the statement in the revised version of our manuscript.

11. Line 79: Which population? Please define more specific

Author’s response: Thank you. This amount referred is from the total population of the world and we revised it in the manuscript.

12. Overall line 75-87 this alinea needs to be restructured, the data presenting on adolescents and young woman reproductive are not used in a structured way. Please rephrase and structure.

Author’s response: Thank you for this very important concern. We take the comment and rephrase the full paragraph in the revised version of our manuscript.

13. Line 89-92: This is a line-up most likely from a previous study. Please summarize the only needed information.

Author’s response: Thank you. We accept the comment and we summarize the paragraph in the revised version of our manuscript.

14. Line 93: This is a repetition of what is said in the first alinea. Please rephrase and restructure.

Author’s response: Thank you. We amended the statement and removed repetitive sentence.

15. Line 95-96: The reason for his study is that most study look to the reproductive woman, it is unclear for me why this young woman are not part of that see previous comments. Can the author explain why this study is needed next to a study on woman in the reproductive age?

Author’s response: Thank you again. Studying prevalence and determinant of anemia in this young women had many clinical implications. The reason for studying anemia prevalence and associated factor in this age group is that the health impact of anemia differ among young women (15-24 years) and reproductive age (15-49 years) women due to the rapid growth and physiological changes occurring in young women resulting extra needs of macro and micronutrients. These extra needs of nutrients commonly result in nutritional deficiencies which are the common causes for anemia. Also the potential factors affecting anemia among reproductive age and young women are not similar as reported by different studies. For these reason and reasons what have indicated in the above comment we have conducted this study at these population subgroups (15-24 years). Also, unlike other study we have considered both the individual and community level factors.

16. Line 99: Abbreviation not explained.

Author’s response: Thank you. We expanded the abbreviation in the revised manuscript

Method

17. Line 107-111 can this be displayed in a graph that makes it easier for the reader to understand.

Author’s response: Thank you for your important issue and we display this information with graph to make it easier for reader in the revised manuscript (see Figure 1).

18. Line 113: add abbreviation (EDHS) as it used in the next sentence.

Author’s response: Thank you. We added an abbreviation in the revised version of our manuscript.

19. Line 113-126 can this be added in a graph/ figure with a flow diagram. That makes it easier for the reader to oversee what happened.

Author’s response: Thank you for your important issue and we display this information with flow diagram to make it easier for reader (see figure 2).

20. Outcome variable line 128: please define young woman.

Author’s response: Thank you. We define young women as those aged 15 to 24 years of age and included in the method section of the revised manuscript.

21. Line 129-131 I do not understand this sentence and I am questioning if the sentence is needed. Moreover there is no difference between in mild-moderate-and severe anemia in the study. So the author should remove this sentence.

Author’s response: Thank you. From the EDHS report anemia is coded as no anemia, mild anemia, moderate and severe anemia, so we recode it as anemic and non-anemic. Also we edited and removed unnecessary information in the revised version of our manuscript.

22. Line 132: Reference 14; is this correct? And please add in writing which adjustment is done.

Author’s response: Thank you. The hemoglobin level was measured and adjusted for altitude using the adjustment formula (adjust = − 0.032*alt + 0.022*alt2 and adjHb = Hb - adjust (for adjust > 0). We used this, which was already provided in the EDHS data. We remove this reference here since it was not appropriately cited here.

23. Line 133: Reference 13; correct? This is the WHO definition of anemia please add the WHO as reference.

Author’s response: Thank you. We corrected the reference in the revised version of our manuscript.

24. Independent variable: line 136-140: please add definitions of the variable or add a reference. For example what is wealth status? What includes media exposure?? What includes modern contraceptives? Please rephrase.

Author’s response: Thank you for your important information and we put all the information about our independent variables in table (see table 1 on page18-20).

25. Line 138 typo double (,,).

Author’s response: Thank you. We correct the double punctuation in the revised manuscript.

26. 148-149 Descriptive (no needed information) please take out.

Author’s response: Thank you. The statement about descriptive statics in the data management and analysis part is removed in the revised manuscript.

Results

27. Overall percentage can be given in one decimal.

Author’s response: Thank you. We put the overall prevalence with one decimal in the revised version of our manuscript.

28. Weighted sample not needed- please take out. The age range 15-24 can be taken out here, as this will be added to the method section

Author’s response: Thank you. We removed the phrase “weight sample” and the age range of 15-29 also taken out from the result section and we included it in the method section of our revised manuscript.

30. The structure of line 165-173: could the author structural outcomes better. As a suggestion group in individual medical- social-economics and community. And use this structure as well in table 1.

Author’s response: Thank you. We restructure the result section as individual level and community level factors in the revised version of our manuscript. This correction also made to table 1.

31. Line 181-184: is this difference significant? Figure 1: what is the yellow line, please adjust figure

Author’s response: Thank you. The difference in the prevalence of anemia among young women higher in Somalia (56.80%) and Afar (43.93%) and lowest in Addis Ababa and this difference is found to be statically significant with non-overlapping 95%CI for the prevalence of anemia across this regions of Ethiopia. The figure is readjusted and here we incorporate the graph to indicate the variation in the range of prevalence of anemia among young women in different region of Ethiopia.

32. Line 196-213/ Table 3: regions: why is all compared to Addis? Nutrition status: why all compared to malnutrition and not to none? Why with occupation display no below yes. Same for contraceptive and media exposure. Please display in a constituent manner. Distance to health facility: not a big problem? What does that mean? How is this defined??

Author’s response: Thank you. Regarding the question about nutritional status we take the comment and amend it. Previously we were used malnutrion (underweight) as a reference, but we reanalyzed and women with normal BMI used as a reference to compare prevalence of anemia between people with normal nutritional status to those of malnutrition.

The variable occupation, contraceptive and media exposure no and yes displayed in the constituent manner in the revised version of our manuscript (see table 4 on page 23-25).

Regarding region, we compared anemia among young women across different region of Ethiopia and Addis Ababa was used as the reference, the reason for using Addis Ababa is that as compared to other regions of Ethiopia the prevalence of anemia was lowest in this city administration (Addis Ababa) compared to other regions. Therefore, we prefer the comparison of anemia in other regions to Addis Ababa.

Concerning distant to health facility it is based on respondents response for the question whether the women perceive distance from the health facility as a big problem or not big problem (see table 1 on page 18-20).

Discussion

33. I miss out in the discussion very clear statements why this outcome is 1) different than other woman previous investigated in Ethiopia? 2) is that surprising or not? What did others find in SSA for these age groups? Are you in line with that and if yes or no what are the difference? What are the clear limitations: limitations are stated very minimal.

Author’s response: Thank you. We consider your comment in the revised manuscript (see the discussion section line 217-230 on page 10 and the strength and limitation section).

34. Line 217: Armenia-Timor: why a comparison to this places?

Author’s response: Thank you. We compare our finding with study done in Armenia-Timor since it is part of low and middle income countries with similar finding to our finding. The socio economic status of this region might not be far from those of Ethiopia and comparison to this region may not have significant problem.

35. Line 218: our country, what was the rate?

Author’s response: Thank you. We included the rate in the previous study conducted in our country and rewrite the statement in the revised version of our manuscript.

36. Line 219: Rate of comorbidity? This comment is based on which knowledge please explain

Author’s response: Thank you. Here the “rate of comorbidity” was to mean the increased rate of chronic diseases and other pathological condition which are the possible cause of anemia of chronic disease.

37. Line 236-249: this alinea has a lot of repetitive statements. Please rephrase and structure

Author’s response: Thank you. We avoid the repetitive idea, statement and rephrase the paragraph in the revised version of our manuscript.

38. Line 247-249: Please add this to the section on rural areas in line 237-238

Author’s response: Thank you. We take the comment and included this statement as the explanation for the difference in anemia prevalence between urban and rural resident. Also it is an important justification for regional variation of anemia in Ethiopia.

39. Line 254

Author’s response: Thank you. We consider the comment and amended it in the revised version of our manuscript.

40. There is no data on age of first child, time between sampling and delivery. So major presumptions are made, but ideally this information would be available to say more about why are these women at risk. Our data on nutrition habits to underline the statements and suggestion. Moreover there is no data on malaria prevalence in this group. Or the availability of prophylaxis during pregnancy. All factors, which can be of major influence. The limitations need rephrasing and suggested limitations should be added.

Author’s response: thank you for raising this very important issue. For the analysis of this study we have used young women from 15 to 24 years of age. We have included women in this age group that might be pregnant or not and also this women might or might not have bear child so the variables like age at first child bearing and any prophylaxis given during pregnancy are not complete information for this analysis, which means all women included for this study not have given child birth or may not have history of pregnancy, so it is impossible to assess the above mentioned variables for this age group. Also data on malaria and nutritional habit are not available in the EDHS data. Finally, we have incorporated all these as limitation in the revised version of our manuscript.

Response to reviwer#3

1. This article covers an important global health concern. However, I believe the manuscript will benefit from a comprehensive language editing

Author’s response: we really thank you for your constructive comments. We extensively edited the spelling and grammatical errors.

2. Please pay particular attention to the following and review the sentences: Lines 25, 75, 95, 113, 129, 132,140, 150, 167, 170, 199, 229, 234, 238, 244, 253 and 257

Author’s response: Thank you for this important comment. We have looked and corrected all the spelling and grammatical errors line by line in the revised version of our manuscript.

Response to reviewer #4

1. The discussion needs to be written with clarity and better understanding. Most of the explanations given for the reported findings are difficult to comprehend.

Author’s response: Thank you. We take look at the comment and we amend the discussion, particularly the explanation given for our finding (we extensively rephrased in the revised version of the manuscript).

2. There are also too many grammatical and spelling errors. The manuscript will benefit from review by a native English speaker.

Author’s response: Thank you. We extensively edited the spelling and grammatical errors. Also the manuscript is checked by language experts in our institution.

Response to reviewer #5

1. The first issue is that the paper would need substantial English language editing; there are many editorial errors in the paper.

Author’s response: Thank you. The manuscript is extensively reviewed by all the author for spelling and grammatical errors. Also language experts in our institution look and edited our manuscript.

Abstract

2. The statement that there is a high prevalence of anemia in young persons (line 29) as a justification for the study is contradictory because If there is already high prevalence of anemia among young women why have the authors conducted another study among this same population?

Author’s response: Thank you. These studies were not based on a nationally representative data and most did not consider the community level factors. In addition, we clarified and rewrite the statement about the burden and magnitude of anemia among young women in the revised manuscript.

3. The statement ‘The overall prevalence of anemia among young women were 21.7% (line 40) should read ‘…was 21.7%’

Author’s response: Thank you for your important issue. We removed the verb “were” which are grammatically incorrect and replaced by the correct verb “was”.

Main manuscript

Background

4. There is need to clarify that the vulnerable population being referred to in line 69 are female adolescents and young women; this point should be clarified throughout the manuscript.

Author’s response: Thank you for your important issue. We corrected all the venerable population is in this manuscript is about female adolescent and young women in the revised version of our manuscript. We made the correction throughout the manuscript.

5. The statement ‘over half of young women worldwide are suffered...’ line 75 should read ‘… have suffered’

Author’s response: Thank you. We replace the inappropriately used verb “are suffered” with grammatically correct verb “have suffered”.

6. The statement ‘…and African as well...’ line 76 is not clear and should be revised.

Author’s response: Thank you. We take the comment and rephrased the indicated statement.

7. If the statement ‘approximately one quarter of adolescents…’ line 78 is referring to female adolescents this should be clarified

Author’s response: Thank you. We clarified this statement as it is being about female adolescent

8. There are many repetitive statements about the fact that sub-Sahara Africa has contributed to the high burden of anemia, this should be revised

Author’s response: Thank you for this important comment. We amended the repetitive statement that provides information about anemia burden and prevalence in sub Saharan Africa.

9. The authors have listed the socio-demographic factors (lines 89-92) that contribute to anemia in Ethiopia, but examples are not provided to illustrate this point. Some examples should be provided to illustrate this point.

Author’s response: Thank you. We have listed different factors including socio economic factor that may affect anemia among young women. Some of which was reported as a factor affecting anemia magnitude in previous Ethiopian studies and we have cited such studies in the revised manuscript.

10. The statement ‘Due to rapid growth…’ line 93 is a repetition because this point has been made earlier

Author’s response: Thank you. We replace and rewrite the repeated word “due to rapid growth” in the revised version of our manuscript.

11. The sentence ‘…and up to our knowledge’ line 96 should read ‘…to our knowledge’

Author’s response: Thank you. The phrase ‘up to our knowledge’ replaced by ‘to our knowledge’ in the revised version of the manuscript.

12. The data for the study were extracted from the 2016 EDHS; is this the latest survey in the country? Have there been other surveys since the one in 2016? If there has been a more recent survey, the authors need to justify why they have used the 2016 survey as source of data for this study. This is should be clarified.

Author’s response: Thank you. The data extracted for this survey was obtained from EDHS 2016 since this is the most recent survey conducted in our country.

Methods

13. An important information missing about the study area is the population of Ethiopia and more importantly the population of young persons in the country.

Author’s response: Thank you. We incorporate the missed information about study area. Also we have incorporated important information about recent population of Ethiopia in the revised version of our manuscript.

14. The reference to altitude and smoking (line 132) is not clear; how do these variables relate to the issue investigated.

Author’s response: Thank you. We take the comment and rephrased and justified the statement in the revised version of our manuscript. Also, the hemoglobin value recorded in the EDHS data was adjusted for altitude and smoking, since it is affected by the level of oxygen saturation at different altitude. Also Smoking increase hemoglobin (Hb) concentration mediated by exposure of carbon monoxide. Carbon monoxide binds to Hb to form carboxyhemoglobin, an inactive form of hemoglobin having no oxygen carrying capacity. Carboxyhemoglobin also shift the Hb dissociation curve in the left side, resulting in a reduction in ability of Hb to deliver oxygen to the tissue. To compensate the decreased oxygen delivering capacity, smokers maintain a higher hemoglobin level than non-smokers. So the minimum hemoglobin cutoff values should be adjusted for smokers to compensate for the masking effect of smoking on the detection of anemia and in the EDHS data the reported anemia level is already adjusted for this two variables. The reference cited here is in appropriately placed and we removed it.

Results

15. The statement ‘of women were not had work’ line 170-171 is not clear and should be revised

Author’s response: Thank you. The statement about young women who had no work to mean that young women who were not have a job during the survey and we clarified in the revised version of our manuscript.

16. The word ‘afar’ line 183 should read ‘Afar’

Author’s response: Thank you. We amend “afar” with the correct spelling “Afar”.

17. The use of the phrase ‘followers of Muslim and protestant religion’ line 203 are not clear. A better phrase may be people who practice Islam or Moslems and protestant Christians. This should be revised.

Author’s response: thank you. We rewrite the phrase “follower of Muslim and protestant religion” as people who practice Muslim and protestant Christian religion in the revised version of our manuscript.

18. The statement ‘… with their counterparts’ line 207 should read ‘with their counterparts who do not’.

Author’s response: Thank you. We address the issue in the revised version of our manuscript.

19. The figure showing prevalence of anemia should have a number and reference should be made to it in the text.

Author’s response: Thank you. We had made correction to the figure and cited in the main document of the manuscript.

Discussion

20. I suggest that the authors provide the figure being referred to in the statement ‘but greater than the previous reported in our country’ line 218

Author’s response: Thank you. We included the figure (number) which was reported in the previous study in our country in the revised version of our manuscript.

21. The authors should give examples of the food types being referred to in line 228 and support this statement with appropriate reference.

Author’s response: Thank you. We have incorporated some food type which might be restricted by some religion and culture that associated with malnutrition which is one possible cause of anemia. For example restriction of some red meat like; pork meat, fish meat, goat meat, bacon which are the possible source of iron by some culture and religion like by Islamic religion may be considered as a predisposing factor for anemia. We have included this culturally or religiously restricted food in the revised version of our manuscript.

22. The statement i.e. barefooted line 241 should be revised to read walking barefooted

Author’s response: thank you. The word ‘barefooted’ revised to read as ‘walking barefooted’ in the revised version of the manuscript.

Attachment

Submitted filename: Response to reviewer.docx

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PLoS One. doi: 10.1371/journal.pone.0241342.r003

Decision Letter 1

Frank T Spradley

29 Sep 2020

PONE-D-20-18515R1

Prevalence and determinants of Anemia among young (15-24 years) women in Ethiopia; A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data

PLOS ONE

Dear Dr. Worku,

There are remaining comments from some reviewers that require your attention and must be addressed in your revised manuscript.

Please submit your revised manuscript by Nov 13 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Frank T. Spradley

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

**********

6. Review Comments to the Author

Reviewer #1: This is a fine paper and will be useful to the field, and the results are interesting.

I don’t have any comment

Reviewer #2: Dear author,

Thanks for the major revisions to the manuscript. However I still have major concerns see them in detailed explained hereafter. But most important; I still mis out in your introduction and discussion. Why your study was essential to do? And what does it bring clearly new to this research field? Your methods and numbers are good but without that message very clear I am doubting for the eligibility for international readers. Please adjust that as you stated nicely in the explanations given to my comments.

• Reviewer 2 Comment 1 eligibility for international readers;

o Thanks for your clear response please add this information to the introduction

o Suggestion 1: change in the abstract line 27 particular in including

o Suggestion 2: line 99 add the age range of productive age (define)

o Suggestion 3: so explain why these two groups are different. Reproductive age and young woman and why your study is needed.

o Suggestion 4: line 100” determinates in Ethiopia” change to in Africa (or LMIC) including Ethiopia

• Reviewer 2 Comment 9: thanks for clarifying these definitions

o Suggestions: line 73 young woman and adolescents female. Change in including adolescent females

• Reviewer 2 Comment 15: see like the statement at comment 1. Clear clarification but please add this information to your introduction. To me it is still not clear why this study needed to be done. Please clarify clearly in the introduction and aim of the study.

• Reviewer 2 Comment 22: please state this calculation in the method section. Because you still used it and now it is taken out fully. That is incorrect. Please change.

• Reviewer 2 Comment 31:

o line 181-184: please add the CI to the groups you compare with as well and the p value. Now the sentence is not complete. Or take out all the CI and just give the P value. But the statement reads incorrect in the way it is stated now.

o Please add the CI to figure 3.

• Reviewer 2 Comment 32 : please add in section 181-184 to which area it was compared. Compared to addis… etc.

• Reviewer 2 Comment 34: This comparison to Timor is still out of place in my perspective. Please refrase. Either put this statement together with the comparison at line 225 or take out.

• Reviewer 2 Comment 35: thanks for this change. However to me it is still not clear why your study was important when you have these numbers already. Please rephrase and explain what your study showed more. Because in the way it reads now like you redid the study.

• Reviewer 2 Comment 40: line 275: add these variables which you stated in your explanation there aswell.

Reviewer #3: (No Response)

Reviewer #4: (No Response)

Reviewer #5: Prevalence and determinants of Anemia among young (15-24 years) women in Ethiopia; A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data

There is substantial improvement in the presentation of the revised manuscript. The authors have addressed all the issues and queries I raised in my previous review of the manuscript. However, in re-reading the manuscript, I detected some minor editorial errors which require the authors attention.

1. In line 80, the word ‘where’ should be replaced by the word ‘with’ to make the sentence clearer.

2. The statement on line 133 and 134 should be presented in past tense ‘for pregnant women…was considered as anemic…’

3. In line 165, the first letter of the university should start with a capital letter, to read ‘University of Gondar’; the authors should also clarify if this institution is in Ethiopia.

4. The statement on 226 needs revision; it should read ‘…greater than the 15.6% anemia found among young women in Rwanda’

5. The author should clarify which country is being referred to on line 227; is this Ethiopia or Rwanda? This should be revised.

6. The statement on line 262 should read ‘…which are common in lowland areas’

7. The word on line 330 should read ‘References’ not ‘reference’

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Osama Mohammed Al-Amer

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: KEHINDE OKUNADE

Reviewer #5: Yes: Professor Ademola J. Ajuwon

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PLoS One. 2020 Oct 30;15(10):e0241342. doi: 10.1371/journal.pone.0241342.r004

Author response to Decision Letter 1

9 Oct 2020

We have included information about the importance of this study in the introduction section of the revised version of the manuscript as indicated by reviewers. Also we address all the reviewers comment accordingly.

Attachment

Submitted filename: Response to reviewer.docx

Click here for additional data file.^{(20.5KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0241342.r005

Decision Letter 2

Frank T Spradley

14 Oct 2020

Prevalence and determinants of Anemia among young (15-24 years) women in Ethiopia; A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data

PONE-D-20-18515R2

Dear Dr. Worku,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Frank T. Spradley

Academic Editor

PLOS ONE

PLoS One. doi: 10.1371/journal.pone.0241342.r006

Acceptance letter

Frank T Spradley

19 Oct 2020

PONE-D-20-18515R2

Prevalence and determinants of Anemia among young (15-24 years) women in Ethiopia: A multilevel analysis of the 2016 Ethiopian Demographic and Health Survey data

Dear Dr. Worku:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Frank T. Spradley

Academic Editor

PLOS ONE

Associated Data

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

Supplementary Materials

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Data Availability Statement

Data is available online and you can request it from www.measuredhs.com. The authors did not have any special access privileges that others would not have.

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PERMALINK

Prevalence and determinants of anemia among young (15–24 years) women in Ethiopia: A multilevel analysis of the 2016 Ethiopian demographic and health survey data

Misganaw Gebrie Worku

Getayeneh Antehunegn Tesema

Achamyeleh Birhanu Teshale

Roles

Abstract

Background

Methods

Results

Conclusion

Background

Methods

Study area

Fig 1. Map of the study area (using ArcGIS version 10.6 software).

Data source

Fig 2. Flow diagram showing the sampling procedure.

Study variables

Outcome variable

Independent variables

Table 1. Description and measurement of the independent variable.

Data management and analysis

Ethical consideration

Results

Sociodemographic characteristics of respondents

Individual-level factors

Table 2. Sociodemographic characteristics of the respondents in Ethiopia, 2016 (N = 5796).

Community-level factors

Prevalence of anemia among young women in Ethiopia

Fig 3. Anemia prevalence by region among young women in Ethiopia; 2016.

Random effect model and model fitness

Table 3. Random effect model and model fitness for the assessment of anemia among young women in Ethiopia.

Determinant of anemia among young women in Ethiopia

Table 4. Bi variable and multivariable multilevel analysis for the assessment of determinants of anemia among young women in Ethiopia, 2016.

Discussion

Strength and limitation of the study

Conclusion

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Frank T Spradley

Roles

Author response to Decision Letter 0

Decision Letter 1

Frank T Spradley

Roles

Author response to Decision Letter 1

Decision Letter 2

Frank T Spradley

Roles

Acceptance letter

Frank T Spradley

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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