Introduction
Anemia is a health condition characterized by a low level of hemoglobin (HGB) in which blood has fewer red blood cells (RBC). A low HGB level impairs blood from delivering oxygen to the body tissues [
1]. The causes of anemia are a genetic defect, infections (malaria, hookworm, and bone marrow disease), deficiency of iron, vitamins, folate, copper, and total nutritional deficiencies. Nutritional deficiency anemia is the most common type [
2,
3].
Anemia is associated with a defect in birth outcomes including miscarriage, preterm delivery, placental abruption, a low birth weight, higher risk of prenatal and maternal mortality [
6,
7]. Anemia can reduce physical activities, cognitive capacities, and reduced work productivity [
8]. Anemia, the most public health concern worldwide, affected 27% (1.93 billion people) of the world’s population in 2013. Hence, it is a common public health issue and accounts for more than 89% of the burden in the developing countries. According to 2011 the WHO estimated, anemia affects around 800 million children and women of reproductive age globally [
9,
10].
The global prevalence of anemia in pregnant women was 38.2% and for all women of reproductive age was 29.4% [
5,
9]. In Africa, anemia affects 35% of women of reproductive age [
9,
11]. Its prevalence is even higher in low-income countries such as Ethiopia due to several contributing factors [
12,
13]. The symptoms of anemia are strongly associated with the quality of life, a poor-quality diet due to poverty, socioeconomic status, residence, education, and pregnancy status [
4]. Besides, due to sex-specific experiences, such as pregnancy, bleeding during childbirth, lactation, and menstruation in women of reproductive age (15–49 years), there is an increased risk of developing anemia as compared to their male counterparts [
14].
Anemia is diagnosed when hemoglobin levels fall below 12 g/dl in adult non-pregnant women and below 11 g/dl during pregnancy [
1]. The two main causes of anemia are classified by timing; namely immediate causes and distal causes. The proximal factors are mainly attributable to micronutrient deficiencies [
15], physiological adaptations during pregnancy [
16], and infections such as malaria [
17], hookworm, and HIV [
18]. Besides these immediate risk factors of anemia, distal factors that operate at the household and community levels include maternal age [
4], education status [
13], marital status, occupation [
19], rural/urban residence [
20], household wealth index [
18,
21], hormonal contraceptive use, and body mass index [
10,
22,
23].
Former studies in Ethiopia focused on children, pregnant and lactating women’s nutrition, and associated factors [
12,
24,
25] and identified factors linked to anemia such as residence, wealth status, and modern contraceptive users. However, these studies are small-scale and are limited to specific localities [
12,
21,
25‐
28]. Many former studies showed us the wealth index and residence area are significantly associated with anemia separately [
29]. These former studies did not explain the urban–rural differentiation on the interaction between anemia and wealth index.
Therefore, this study aims to analyze the urban–rural differential in the association between household wealth index and anemia among women of reproductive age in Ethiopia. The Ethiopian Demographic and Health Survey (EDHS) is the only source of compressive national data on several characteristics of women of reproductive age (15–49 years). The authors decided to investigate the differentials in anemia among women of reproductive age, using data from the 2016 EDHS.
Discussion
This study uses a country-level, representative data in Ethiopia to describe urban–rural differential in the association between household wealth index and anemia among women in the reproductive age group. This study provides evidence linking specific anemia factors related to the reproductive age group of women. Since successful anemia prevention strategies should rely on evidence-based approaches, the result of this study should represent recommended public health interventions and policies aimed at a target age group. And then reduce the burden and consequences of anemia in this group.
The prevalence of anemia among women in Ethiopia is 24% in 2016 [
30], making it a moderate public health problem according to the WHO threshold [
34]. The results suggest that level of household wealth was associated with anemia in women who live in rural areas. The prevalence of anemia in women varies significantly between urban and rural and region to region in the communities [
18]. In Ethiopia, anemia among the reproductive age group increased 17% in 2011 to 24% in 2016 [
30].
In our study, the authors showed that the impact of economic status and residency was the single contributor to anemia among reproductive-age women in Ethiopia. This study found that 29.6% of women of reproductive age who come from poor house wealth status were anemic. Of the total participants, 25.1% of the reproductive age group of women who live in rural areas experience anemia. The prevalence of anemia (29.6% and 25.1%) revealed by this study is higher than the national average (24%). The magnitude of anemia in rural residency is higher than in urban. In this study, the wealth status of women’s households associated with the development of anemia. Women who had the lowest wealth statuses (AOR = 1.37; 95% CI 1.14–1.65) increase the chance of developing anemia in rural residency. This finding is consistent with other studies in low and middle-income countries. These studies found that the associated factors of anemia among women living in a poor wealth status have anemia than those living in the heights wealth status [
11,
18,
20,
22,
23,
33].
Because those from the lowest wealth status in the countryside cannot purchase the quality or quantity of foods when compared with those from higher wealth status. Lower-income households purchase less healthful foods when compared with higher wealth. It is plausible that women from low wealth status homes, as with urban residents, may have diversified diets and supplements, thereby decreasing their chance of nutrition-related anemia [
32,
35,
36].
Another fact also the most reported dietary consumption of the household in rural residency is monotonous foodstuff and low diet diversification [
1,
32]. Women who belong to a low wealth status experienced inadequate food resources, food did not last, did not afford balanced meals, reduced meal size, or skipped meals [
37,
38]. The women’s knowledge of different vitamin and mineral-containing foods and their benefit may be other contributors [
19].
We observed a place of residency-specific variations in the association of anemia among women with similar household wealth status. Residency may mediate anemia difference in the same wealth status in the Ethiopian reproductive women age group. Our study showed associations between the low socioeconomic status of those who live in rural and anemia. In rural residency, women have attributed disparities in health service provision and access, disease risk, fertility preferences [
37,
39,
40]. On the other round, farming can increase the chance of anemia-inducing infectious diseases such as malaria, intestinal parasites like schistosomiasis, and hookworm, and such exposures may be more common in rural residency [
33,
41].
In this study, there were significant differences in anemia between urban and rural areas with similar socioeconomic status. The cause of urban–rural difference was related to the sociocultural conditions of the participant. The potential cause of this may be restricted access to diverse micronutrient-rich diets (food taboo), not access to mass media, and nutrition information for women who live in rural can exacerbate anemia. Multiple deficiencies tend to cluster within individuals, and the synergistic effect of these deficiencies plays in the development of anemia in rural residency [
39,
42,
45,
46]. Other than residency and socioeconomic status, potential predictors of anemia include being within the younger age category, having no education, being married, and not using hormonal contraceptives, which have been reported in several other studies [
4,
9,
10,
18,
23,
24,
33,
46].
Strengths and limitations
This study used population-based data with large sample size and representative of all regions of Ethiopia. Due to the cross-sectional nature of the EDHS data, the cause-effect and the temporal relationship could not be established based on these study findings. Similarly, essential factors such as family size, gravidity, and parity, religion, current breastfeeding, smoking, and HIV factors were not incorporated these variables in the analysis.
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