The objectives of this study were to identify the describes of the background characteristics of WRA in Rwanda with anemia and to therefore identify associated risk factors. According to the analysis, the prevalence of anemia among WRA in Rwanda was 19.2%. Although the anemia prevalence in Rwanda was lower than many other countries in the Sub-Saharan Africa region (2,9), it is still considered a public health problem according to WHO criteria (23). In addition, the prevalence increased between 2010 and 2015 and varied across population subgroups (10,24). In this study, it was found to vary with age, province of residence, education level, marital status, the type of contraceptive method used as well as the economic and nutrition status. Our study showed that women who were obese or rich, as well as those who slept under a mosquito net or used hormonal contraceptives were less likely to have anemia while those who were underweight, used intrauterine devices as a contraceptive method, and lived in the Southern or Eastern provinces were more likely to have anemia, than were individuals in their respective comparison groups.
Similar to studies in other settings including Ethiopia and Pakistan, our analysis found that poor and undernourished women were more likely to have anemia (25,26). Anemia is a multifaceted problem where nutrition and economic status work in synergy. Evidence suggests that improved economic status is associated with appropriate nutrition conditions (27), lower infection morbidity (26), increased access to health services as well as other favourable living conditions (27,28), all of which in turn influence anemia. Malnourished women have greater risk of iron deficiency, the most common proximate cause of anemia (1) and malnutrition is often associated with poor socio-economic status (29). Interventions that aim to empower women economically should be considered in order to reduce anemia prevalence. Moreover, malnutrition management programs should ensure that iron supplementation is sustained within intervention packages.
In this study, the use of hormonal contraceptives was associated with lower risk of anemia among WRA, while the use of IUD was associated with higher risk. Similar findings were seen in other studies conducted in 14 different low- and middle-income countries including Tanzania and Ethiopia (25,30,31). Another study conducted in seven countries also found that hormonal contraceptive users had higher haemoglobin and ferritin levels compared to non-users (32). Using hormonal contraceptive can be resulted in less bleeding during the menstruation, which ultimately reduces blood loss over time (33,34).
A study conducted in Pakistan also observed higher anemia risk among IUD users (35). IUD may increase uterine blood flow as well as volume of bleeding during and duration of menstruation periods, especially during the first months of usage, which in turn increase the likelihood of anemia (36,37). In addition, some research has found that IUD users have a reduction in hemoglobin content and iron saturation/ ferritin levels, which may trigger or worsen existing anemia (32,38). While more investigations are needed to understand the real physiological mechanisms, our study findings supported the existing evidence that IUD use is among the risk factors of anemia in WRA. Clinical guidelines should consider specifying treatments for IUD-induced bleeding (39) as well recommending iron supplementation for IUD users especially during the first months of usage.
Geographic area of residence was found to be associated with anemia, with women in the Eastern and Southern provinces being more likely to have anemia. The Eastern and Southern provinces in Rwanda are considered to be high malaria endemic regions; higher risk of malaria also translates to higher anemia risk (40). Similar associations between anemia and geographic location have been found in Tanzania (30). In Rwanda, iron supplementation during pregnancy is less common in the Eastern province than in other provinces (10). Interventions should consider including iron supplementation, promotion of foods rich in iron and other micronutrients, as well as to prevent malaria (12,41). The most affected geographic areas should be prioritized.
Consistent with the results from other studies, sleeping under mosquito nets was associated with lower likelihood of anemia in our study, which makes sense given that malaria itself is a risk factor of anemia (42). As mosquito net coverage and usage remain challenges in many developing countries (43–45), malaria prevention strategies including efforts to ensure the availability as well as proper use of mosquito nets in the community should be integrated in anemia prevention programs.
Widowers or women separated from their husbands were more likely to have anemia. Traditionally men are breadwinners in many developing societies (46). Widows and women separated from their husbands lack support to sustain their families, predisposing them to economic deprivation, poverty, malnutrition and low access to health services (27–29). In addition, our analysis showed a correlation between marital status and age (r= 0.63). Older age was found to be associated with anemia in some studies (25). While further investigations are needed to better understand the possible associations between marital status, age and anemia status, our findings suggest that old women, especially widows, may face many other health problems that are understudied. Special attention and priority should be given to understanding the health needs of this vulnerable group.
Our study found that women with lower education levels had slightly higher prevalence of anemia, although statistical significance was not found. Other studies have found education level to be a risk factor for anemia (25,30). The differences in settings of the studies could be related to the discrepancy. In the 2014/2015 Rwanda DHS, only 19 percent of women had no education; while 67 percent were reported in Ethiopia in 2005 and 27 percent in Tanzania in 2010 (10,47,48), the variation in the sample composition could have affected the analysis outcome.
Interestingly, this study found that about 40% of the women classified as “rich” also had anemia. This result was inconsistent with other evidence. Despite economic improvement in Rwanda over recent decades, about 39% of the population remained living under poverty line (49,50). Further investigation found that DHS, the Ministry of Local Government and Social Affairs in Rwanda used different socioeconomic classification methodologies. The DHS used five categories: poorest, poor, middle, rich and richest, based on the durable goods owned by a household such as television, mobile telephone and other household characteristics such as access to electricity and source of drinking water (10), while the Rwanda Ministry of Local Government and Social Affairs uses four categories for social stratification: very poor, poor, middle and rich (51,52). In recent years, there has been considerable debate over whether the stratification systems truly reflect the economic status of the population (53,54). Acknowledging that the limitations of the stratifications may cause discrepancies, the Rwanda government is currently revising the categorization to reflect the true population economic status (52).
This study successfully identified some risk factors among WRA in Rwanda and proposed some recommendations. However, the results must be seen in light of some limitations. This study could only use variables that were in the DHS, due to the nature of secondary data analysis. Qualitative information could provide increased understanding of the attitudes and practices related to variations in food consumption patterns. However, the DHS survey used a national representative sample was conducted with standardized quality assurance measures in both data collection and management to ensure reliability and validity of the results (55,56), which could improve the generalizability of the results of our analysis.