Prevalence, Morphological Classification, and Determinants of Anaemia among Pregnant Women Attending Antenatal Care at Korle Bu Teaching Hospital

IRASS Journal of Applied Medical and Pharmaceutical Sciences https://irasspublisher.com/journal-details/IRASSJAMPS ISSN (Online) 3049-0901 This is an open access article under the CC BY-NC license 7 JOURNAL COVER PAGE Prevalence, Morphological Classification, and Determinants of Anaemia among Pregnant Women Attending Antenatal Care at Korle Bu Teaching Hospital Aquel Rene Lopez1*, Nana Akosua Ayisibea Offei2, Akwasi Afriyie Achampong3, Julia Kwakoa Karikari4 *1-2-3 School of Allied health Science, Baldwin University College Accra 1-4 Sinel Specialist Hospital, Tema Corresponding Author: Aquel Rene Lopez School of Allied health Science, Baldwin University College Accra Article History Received: 18 / 10 / 2025 Accepted: 03 / 12 / 2025 Published: 13 / 12 / 2025 Abstract: Background: Anaemia in pregnancy remains a pressing public health concern in lowand middle-income countries. This study assessed the prevalence, morphological classification, and associated risk factors of anaemia among pregnant women attending antenatal care at Korle Bu Teaching Hospital, Ghana. Methods: A cross-sectional study was conducted involving 297 pregnant women. Sociodemographic, clinical, and dietary data were collected using structured questionnaires. Haematological parameters were analyzed to classify anaemia morphologically. Associations between anaemia and various risk factors were explored using logistic regression. Results: The prevalence of anaemia was 47.8%, with normocytic normochromic anaemia being the most common type (62.7%), followed by microcytic hypochromic (34.5%) and macrocytic anaemia (2.8%). Anaemia was significantly associated with the second trimester, short interpregnancy intervals (≤2 years), self-reported infections, poor knowledge about anaemia, physically strenuous work, and inadequate folate supplementation. Folic acid use was protective, reducing the odds of anaemia by 72%. While most participants had inadequate intake of ironand vitamin-rich foods, only folate deficiency was significantly linked to anaemia risk. Morphological patterns revealed that microcytic hypochromic anaemia correlated more with nutritional deficiencies, while normocytic anaemia was associated with infections and gestational stage. Conclusion: Anaemia in pregnancy at this tertiary facility is common, with multifactorial causes involving infections, short birth spacing, poor nutritional status, and inadequate supplementation. Targeted interventions including early antenatal care, nutritional support, infection prevention, and education on anaemia risks are essential to mitigate its burden. Keywords: Fungal infections, Dermatophytosis, Superficial mycoses, Skin infections, Hair infections, Nail infections, Etiology, Epidemiology, Treatment, Prevention. How to Cite: Lopez, A. R., Offei, N. A. A., Achampong, A. A. & Karikari , J. K. (2025). Prevalence, Morphological Classification, and Determinants of Anaemia among Pregnant Women Attending Antenatal Care at Korle Bu Teaching Hospital. IRASS Journal of Applied Medical and Pharmaceutical Sciences, 2(12), 7-27. Introduction The World Health Organization (WHO) defines anaemia as a condition in which the number of red blood cells and consequently, their oxygen carrying capacity is insufficient to meet the body’s physiologic needs (WHO, 2011). The WHO defines anaemia as decreased concentration of haemoglobin level less that 11g/dL (WHO, 2015). With no regards to economic status, anaemia affects the global population qualifying it as a public health problem (De Benoist & Mclean, 2008). It affects roughly a third of the world’s population (Chaparro & Suchdev, 2019). In the quantitative sense, anaemia globally affects 1.62 billion people corresponding to 24.8% of the population with the lowest prevalence in men (12.7%) followed by the elderly (23.9%), school age children (25.4%), non-pregnant women (30.2%), pregnant women (41.8%) and then pre-school age children (47.7%) according to De Benoist and Mclean’s estimates from 1993 to 2005 from the survey data of WHO’s 192 member states extracted from their database. Due to the vulnerability of women and children to anaemia, many researches and surveys on anaemia have been centred around them particularly, pregnant women. The WHO in their annual health report in 2021 stated that, in 2019 the global prevalence of anaemia was 29.9% among women of reproductive age, 29.6% among non pregnant women and 36.5% among pregnant women acknowledging a slow global decline in pregnant women from 40.9% in 2000 (WHO, 2021e). Pregnancy-related anaemia is a worldwide health problem affecting low-, middleand high-income countries impacting on health and socio-economic progress (Okia et al., 2019). It is estimated that 2 pregnancy-related anaemia has highest prevalence in South East Asia (48.7%) and Africa (46.3%), medium prevalence in the Eastern Mediterranean Region (38.9%) and lowest prevalence in the Western Pacific (24.3%), the Americas (24.9%) and Europe (25.8%) (WHO, 2016). It is imperative from the above data to ascertain that; pregnant women are one of the groups most vulnerable to anaemia. This is attributable to the fact that even in physiological conditions, pregnancy imposes significant demands on the woman’s body and IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 8 triggers many physiologic adaptations which lead to a gradual increase in blood volume (Agarwal & Rets, 2021) by 40 to 45% on average with subsequent increase in red cell mass by 15 to 20% which is relatively smaller than that of the plasma volume and hence a net reduction in the concentration of haemoglobin (Hb) by 1-2g/dL, classified as physiological anaemia of pregnancy (Gebreweld, Bekele, & Tsegaye, 2018). In Ghana, it is estimated that 45% of pregnant women are anaemic (Ghana Statistical Service (GSS) ICF International, 2015). Diverse circumstances contribute to anaemia in pregnant women (Ndegwa, 2019a). Associated risk factors include poor nutrition, chronic infections, lack of access to health care facilities, poor compliance with micronutrient supplementation among others (Dorsamy, Bagwandeen, & Moodley, 2020). Since iron-deficiency anaemia is the most prevalent form of anaemia worldwide, most researches have seemed to target iron deficiency anaemia, finding its prevalence, associated risk factors and measures of prevention with little or no regard to the other forms of anaemia. This is backed by the study (WHO, 2020) that states ―Among the known causes of anaemia, iron deficiency is the most common cause. The terms anaemia, iron deficiency and irondeficiency anaemia (IDA) are too often used interchangeably, masking the need to address the full scope of causes of anaemia. Although iron deficiency leads to decreased 3 haemoglobin and production of red blood cells, which in turn decreases haemoglobin concentrations and haematocrit (used to identify anaemia), there are many other causes of anaemia that do not involve iron. There are multiple determinants of anaemia, and successful anaemia reduction efforts must identify the major contributing factors in order to develop and implement an evidence-based package of interventions that may achieve effective results.‖ Those other forms of anaemia fall within the morphological classifications: macrocytic and normochromic anaemia (aside microcytic anaemia comprising mainly of irondeficiency anaemia). This study aims to not only measure the prevalence of the morphological classifications of anaemia but also to relate them to corresponding risk factors or aetiology. Methods Study design and setting We conducted a facility-based cross-sectional study at the Korle Bu Teaching Hospital (KBTH), the largest tertiary referral hospital in Ghana, located within the Ablekuma South Sub-Metropolitan District of the Greater Accra Region. The study population consisted of pregnant women attending antenatal care (ANC) services at KBTH during the study period. Study population All pregnant women presenting for ANC were eligible for recruitment. Women were enrolled across all trimesters to ensure representation of the physiological and haematological variations that occur throughout gestation. Inclusion criteria  Ghanaian pregnant women receiving ANC at KBTH.  Provision of written informed consent. Exclusion criteria  Declined consent.  Known hereditary anaemias (e.g., sickle cell disease, thalassaemia), as these conditions could confound morphological classification of anaemia. Sample size and sampling The minimum sample size required for this study is determined by the formula: N = Z2 x p(1p) d2 Where Z is the confidence level at 95% of the value, 1.96 p is the expected proportion in population based on recent surveys d is the absolute error, preferably, 5% (0.05) According to the Ghana Statistical Service, the prevalence of pregnancy anaemia is 40.5%, thus, p = 0.405 Therefore, N = (1.96)2 x 0.405(10.405) 0.052 N = 370.29 = 370 Hence a convenience sample of 370 participants was used for the study. Data collection Biological sample collection and laboratory analysis Three millilitres of venous blood were collected into EDTA tubes following standard aseptic procedures. Samples were analysed at the KBTH Haematology Laboratory using a Biobase three-part automated haematology analyser to obtain full blood count parameters, including haemoglobin concentration, MCV, MCH, and MCHC. To confirm anaemia morphology, peripheral blood smears were prepared using 3 μL of whole blood and stained using the Leishman technique. Slides were examined under oil immersion (×100 objective) by trained laboratory scientists. Morphological classification of anaemia Anaemia was defined as haemoglobin <11.0 g/dL. Morphological classes were determined using MCV and MCH values and confirmed by microscopic smear examination:  Microcytic hypochromic anaemia: MCV < 80 fL and MCH < 27 pg  Normocytic normochromic anaemia: MCV 80–95 fL  Macrocytic anaemia: MCV > 95 fL Data management and statistical analysis Data were entered into SPSS version 28.0.1. Descriptive statistics (means, standard deviations, frequencies, and proportions) summarized baseline characteristics. Bivariate associations between anaemia status and sociodemographic, clinical, nutritional, and knowledge variables were assessed using chi-square tests. Variables with p < 0.05 at bivariate level were entered into multivariable logistic regression IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 9 models to estimate adjusted odds ratios and 95% confidence intervals. A multinomial logistic regression model was further used to assess predictors of morphological classes of anaemia. Statistical significance was defined as p < 0.05. Ethical considerations Ethical approval was obtained from the Ethical and Protocol Review Committee. All participants provided written informed consent after receiving information about the study aims, procedures, risks, and confidentiality safeguards. Unique identification codes were used to maintain anonymity; electronic data were stored on password-protected systems with secure cloudbased backups. Results Sociodemographic characteristics of the pregnant women A total of 297 pregnant women attending antenatal care at Korle Bu Teaching Hospital were enrolled. The mean age was 27 years (range 16–44), with women aged 25–29 years representing the largest subgroup (33.7%). Adolescents (<20 years) constituted 7.7% of the study population, indicating a continued occurrence of early pregnancy within the catchment area as shown in Table 1. Most participants identified as Christian (76.8%), with the remaining 23.2% identifying as Muslim. Nearly all women (98.7%) lived in nuclear family households, consistent with typical urban living arrangements in metropolitan Accra. Educational attainment varied substantially: 48.5% had completed basic education, 29.0% had secondary education, 6.7% had tertiary education, while 15.8% had no formal education. These trends reflect the persistent disparities in women’s educational status in urban Ghana and have important implications for health literacy and care-seeking behaviours. In terms of occupation, 55.6% of respondents were selfemployed, 28.3% were formally employed, and 16.2% were unemployed. Notably, 34.4% reported engaging in physically strenuous work—an important consideration given its potential contribution to adverse maternal outcomes, including anaemia. Awareness regarding anaemia was moderate: 57.6% of participants reported knowledge of anaemia, and 56.2% recognized increased susceptibility during pregnancy. Nearly all respondents (98.7%) acknowledged the need for increased dietary intake during pregnancy, reflecting good acceptance of nutritional guidance despite gaps in broader anaemia-related knowledge. The socio-demographic profile reflects a predominantly young, urban population with heterogeneous educational attainment and varying levels of health awareness. These characteristics are consistent with demographic patterns observed among antenatal populations in other urban Ghanaian centres and underscore the importance of targeted maternal health education and nutritional counseling. Table 1: Sociodemographic characteristics of pregnant women Sociodemographic characteristics Frequency (N=297) Percentage % Maternal age <20 23 7.7% 20-24 82 27.6% 25-29 100 33.7% 30-34 54 18.2% 35-39 32 10.8% >/=40 6 2.0% Religion Christianity 228 76.8% Islam 69 23.2% African Traditional Religion 0 0.0% Other 0 0.0% Sociodemographic characteristics Frequency (N=297) Percentage % Education No formal education 47 15.8% Basic education 144 48.5% Secondary 86 29.0% IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 10 Tertiary 20 6.7% Family type Nuclear 293 98.7% Joint 0 0.0% Extended 4 1.3% Employment status Employed 84 28.3% Self-employed 165 55.6% Unemployed 48 16.2% Nature of work Light and normal 162 65.6% Exhaustive 85 34.4% Knowledge about anaemia Yes 171 57.6% No 126 42.4% Knowledge about Yes 167 56.2% vulnerability of pregnant No 130 43.8% women to anaemia Knowledge about need for Yes 293 98.7% double diet No 4 1.3% Clinical characteristics of pregnant women The clinical profiles of the 297 pregnant women enrolled in the study demonstrated considerable variation across gestational age, obstetric history, and maternal health indicators. As shown in Table 2, 21.9% of participants were in their first trimester, while 39.4% and 38.7% were in their second and third trimesters, respectively. A substantial proportion (69.7%) were multigravidae, consistent with demographic trends reported in similar studies conducted in sub-Saharan Africa, where multiparity remains common among women attending antenatal clinics (Belachew & Legesse, 2006; Bh et al., 2017) Approximately 63.3% had attended at least one previous antenatal visit at the time of recruitment, while 36.7% were presenting for the first time. This pattern aligns with findings from other Ghanaian and regional cohorts, where late initiation of antenatal care persists as a public health concern (Frimpong et al., 2022). Regarding the timing of the first ANC visit, 44.0% of women began care during the second trimester, with only 33.0% initiating in the first trimester, echoing earlier reports highlighting delayed ANC uptake among pregnant women in West Africa. The majority of participants (93.9%) reported no apparent infection at the time of assessment, whereas 6.1% acknowledged the presence of an infection. Maternal infections—particularly malaria, urinary tract infections, and helminthic infestations—are well-established contributors to anaemia during pregnancy, and similar prevalence rates have been documented across the region (Bashawri et al., 2002; Means, 2019). These clinical characteristics provide essential insight into the obstetric and health-related determinants of anaemia in pregnancy. Consistent with global literature, gestational age, interpregnancy spacing, and infection status remain critical clinical predictors of anaemia risk, underscoring the importance of early ANC initiation and routine screening throughout pregnancy. Table 2:Clinical characteristics of the pregnant women Clinical characteristics Frequency (N = 297) Percentage (%) Gestational age first trimester 69 21.9% Second trimester 119 39.4% Third trimester 115 38.7% ANC visits First time 109 36.7% Had earlier visit(s) 188 63.3% Gravida Primigravida 90 30.3% Multigravida 207 69.7% Gravidity First pregnancy 89 30.0% Second pregnancy 51 17.2% IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 11 Third pregnancy 69 23.2% Fourth pregnancy 48 16.2% Fifth and above pregnancy 40 13.5% Birth spacing </= 2years 79 26.6% >2years 129 43.4% No birth 89 30.0% Existing infection Yes 19 6.1% No 355 93.9% Consumption of nutrient rich foods and supplements The consumption patterns of nutrient-rich foods and supplements among pregnant women in this study reveal important gaps in dietary quality and micronutrient intake. As shown in Table 3, the majority of women reported inadequate daily consumption of iron-rich foods, fruits, and vegetables, despite recognising the importance of increased dietary intake during pregnancy. Only a subset of participants consistently consumed foods such as beans, leafy vegetables, eggs, fish, and fortified cereals, indicating suboptimal adherence to recommended antenatal nutrition practices. Supplement intake showed similar variability. Although iron and folic acid supplementation is routinely provided during antenatal care in Ghana, adherence among participants was inconsistent. Several women reported irregular intake of these supplements, which may contribute to the persistence of anaemia and other micronutrient deficiencies in pregnancy. This pattern aligns with previous findings from urban Ghana, where adherence to antenatal supplements is often limited by gastrointestinal side effects, forgetfulness, and misconceptions about supplement safety (Gyamfi et al., 2020; Adu-Afarwuah et al., 2017). The low consumption of nutrient-dense foods is particularly concerning given the increased physiological demands of pregnancy. Evidence indicates that insufficient intake of iron-rich foods, vitamin-C-rich fruits, and folate-containing vegetables substantially elevates the risk of anaemia, preterm birth, and intrauterine growth restriction (WHO, 2021; Black et al., 2013). Moreover, dietary insufficiency combined with suboptimal supplement adherence exacerbates micronutrient depletion, especially in populations with high baseline anaemia prevalence. Table 3: Consumption of nutrient rich foods and supplements Frequency Percentage (%) Daily eating frequency Twice a day 52 17.5% Thrice a day 201 67.7% Four times a day 14 4.7% More frequently 30 10.1% Fruits Daily 116 39.1% At least twice a week 103 34.7% Weekly 43 14.5% Rarely 35 11.8% Green leafy vegetables Daily 97 32.7% At least twice a week 113 38.0% Weekly 45 15.2% Rarely 42 14.1% Milk Daily 49 16.5% At least twice a week 57 19.2% Weekly 53 17.8% Rarely 138 46.5% Red meat Daily 60 20.2% At least twice a week 84 28.3% IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 12 Prevalence of Anaemia Among Pregnant Women 47.81% 52.19% Weekly 62 20.9% Rarely 91 30.6% Iron supplement Yes 175 58.9% No 122 41.1% Iron supplement frequency Just as prescribed 158 90.3% Not as frequently as prescribed 17 9.7% Multivitamin Yes 149 50.2% No 148 49.8% Multivitamin frequency Just as prescribed 147 98.7% Not as frequently as prescribed 2 1.3% Folate supplement Yes 104 35.0% No 193 65.0% Folate supplement frequency Just as prescribed 103 99.0% Not as frequently as prescribed 1 1.0% Prevalence of anaemia among pregnant women The pie chart below represents the prevalence of anaemia among pregnant women as derived from this study. Of the 297 pregnant women 142(47.8%) were anaemic, presenting Hb<11.0g/dL and 155(52.2%) being normal. The mean and median Haemoglobin level was 11.1g/dL and 11.0g/dL, respectively with standard deviation ± 2.0g/dL. Figure 1: Prevalence of anaemia in pregnant women Bivariate association between demographic characteristics of the women and anaemia The bivariate analysis examined the relationship between socio-demographic characteristics and anaemia status among the 297 pregnant women enrolled in the study. The results showed that age, education level, maternal occupation, religion, and family type were not significantly associated with anaemia (p > 0.05). Although anaemia prevalence varied across categories, none of the differences reached statistical significance. Anaemia prevalence was highest among women aged 25– 29 years, who also constituted the largest age group in the cohort. Women with no formal education showed a slightly higher proportion of anaemia compared with their more educated counterparts, consistent with patterns reported in other maternal health studies; however, the association was not statistically significant in the present analysis. Occupational status similarly demonstrated no significant association with anaemia. Women engaged in self-employment and physically demanding work had marginally higher anaemia prevalence, but the relationship did not reach significance. This aligns with previous findings from Ghanaian urban antenatal populations, where occupational differences often fail to independently predict maternal anaemia once dietary and obstetric factors are considered. IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 13 Religion and family structure also showed no significant associations with anaemia. Although women from nuclear households constituted the vast majority of the study population, anaemia distribution across household types did not differ significantly. The bivariate findings indicate that demographic factors alone did not significantly predict anaemia within this antenatal population. This underscores the stronger influence of nutritional intake, parity, gestational age, infection status, and supplementation practices factors examined in the subsequent multivariate analyses. Table 4: Bivariate association and multivariate regression between demographic characteristics of pregnant women and anaemia Demographic characteristics Not anaemic n(%) Anaemic n(%) χ2 Pvalue Odds Ratio 95% CI pvalue Maternal age 10.84 0.055 <20 9(39.1%) 14(60.9%) 20-24 36(43.9%) 46(56.1%) 25-29 64(64.0%) 36(36.0%) 30-34 28(51.9%) 26(48.1%) 35-39 14(43.8%) 18(56.3%) >/=40 Educational level 4(66.7%) 2(33.3%) 17.13 0.001 None 22(46.8%) 25(53.2%) 1.379 0.29-6.62 0.688 Basic 61(42.4%) 83(57.6%) 2.063 0.51-8.37 0.311 Secondary 57(66.3%) 29(33.7%) 0.917 0.22-3.80 0.905 Tertiary 15(75.0%) 5(25.0%) 1 Religion 0.000 0.998 Christianity 119(52.2%) 109(47.8%) Islam 36(52.2%) 33(47.8%) Family type 0.008 0.930 Nuclear 153(52.2%) 140(47.8%) Extended 2(50.0%) 2(50.0%) Demographic characteristics Not anaemic n(%) Anaemic n(%) χ2 pvalue Odds Ratio 95% CI pvalue Employment 4.888 0.087 Employed 48(57.1%) 36(42.9%) Self employed 77(46.7%) 88(53.3%) Unemployed 30(62.5%) 18(37.5%) Nature of work 3.853 0.050 IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 14 Light and normal 88(54.3%) 74(45.7%) 0.59 0.31-1.10 0.094 Exhaustive 35(41.2%) 50(58.8%) 1 Bivariate association between knowledge and anaemia The pregnant women’s availability of knowledge concerning anaemia turned out to have a significant association with their anaemia status (Chi 8991, p=0.003). Majority of those who exhibited a fair knowledge about anaemia, 102(59.6%), were not anaemic while most of those who had no knowledge about anaemia, 73(57.9%) were anaemic. Likewise, whether or not they knew that pregnant women are vulnerable to anaemia had a significant association with anaemia status (Chi 7.693, p=0.006) with majority who had the knowledge, 99(59.3%) having normal Hb while majority (74(56.9%)) without that knowledge being anaemic. There was no significant association between knowledge about need for pregnant women to take a double diet with anaemia status (Chi 0.846, p=0.358). Table 5: Association and regression between knowledge about anaemia and anaemia status Subject Not anaemic n(%) Anaemic n(%) χ2 Pvalue Odds Ratio 95% CI pvalue Anaemia 8.991 0.003 Yes 102(59.6%) 69(40.4%) 0.44 0.57-3.46 0.436 No 53(42.1%) 73(57.9%) 1 Vulnerability t o 7.693 0.006 anaemia Yes 99(59.3%) 68(40.7%) 1.45 0.19-11.27 0.720 No Need for double diet 56(43.1%) 74(56.9%) 0.846 0.358 1 Yes 152(51.9%) 141(48.1%) No 3(75.0%) 1(25.0%) Bivariate association between clinical characteristics of the women and anaemia Gestational age had a significant association with anaemia status (Chi 7.333, p=0.026). Majority of the pregnant women in the study, 117(39.4%) were in their second trimester most of which were anaemic (67(57.3%)). The first and third trimesters however saw the majority (40(61.5%) and 65(56.5%) respectively) being non anaemic. Birth spacing as well had a significant effect on the haematological status of the women (Chi 10.212, p=0.001). Anaemia was more prevalent among those who had given birth at most two years ago with majority 48(60.8%) being anaemic and with 3 times odds (OR 3.13(1.53-6.40) p=0.002) of being anaemic compared to those with >2 years birth space. Most of those who had had a previous birth more than two years ago, 80(62.0%) had normal Hb. Also, the presence of existing infection had a significant impact on the Hb status of the women (Chi 4.567, p=0.032). Of those that testified of having an infection, majority, 13(72.2%) , turned out to be anaemic. Most of those without infection, 150(53.8%) had normal Hb. There was no significant association between ANC visits (Chi 2.754, p=0.097), gravida status (Chi 0.248, p=0.619) and gravidity (Chi 2.551, p=0.636) and anaemia. Most of the women who had earlier ANC visits had normal Hb as opposed to most of the first timers who were anaemic. IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 15 Table 6: Association and regression between clinical characteristics of women and anaemia Clinical characteristics Not anaemic n(%) Anaemic n(%) χ2 Pvalue Odds Ratio 95% CI pvalue Gestational age 7.333 0.026 First trimester 40(61.5%) 25(38.5%) 0.58 0.27-1.26 0.167 Second trimester 50(42.7%) 67(57.3%) 1.36 0.70-2.66 0.362 Third trimester 65(56.5%) 50(43.5%) 1 ANC visits 2.754 0.097 First time 50(45.9%) 59(54.1%) Had earlier visits 105(55.9%) 83(44.1%) Gravida 0.248 0.619 Primigravida 45(50.0%) 45(50.0%) Multigravida 110(53.1%) 97(46.9%) Gravidity 2.551 0.636 First pregnancy 44(49.4%) 45(50.6%) Second pregnancy 28(54.9%) 23(45.1%) Third pregnancy 36(52.2%) 33(47.8%) Fourth pregnancy 29(60.4%) 19(39.6%) Fifth and above 18(45.0%) 22(55.0%) Clinical characteristics Not anaemic n(%) Anaemic n(%) χ2 Pvalue Odds Ratio 95% CI pvalue Birth spacing 10.212 0.001 </=2years 31(39.2%) 48(60.8%) 3.13 1.53-6.40 0.002 >2years Infection 80(62.0%) 49(38.0%) 4.576 0.032 1 Yes 5(27.8%) 13(72.2%) 3.22 0.989-10.47 0.052 IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 22 who did not acknowledge an infection. Indeed, malaria has been associated with both normocytic and microcytic anaemia in pregnancy, depending on the context (Quintero et al., 2011; Bashawri et al., 2002). Overall, the evidence from our study and others highlights the importance of infection prevention (e.g. mosquito net use, prompt treatment of malaria and other infections) as part of anaemia control in pregnancy. Dietary and nutritional factors: Nutritional intake and supplement use are modifiable factors that can influence anaemia in pregnancy. In our cohort, nearly all women reported eating at least two meals a day and consuming fruits, vegetables, and protein to varying degrees (Table 3). However, the use of prenatal supplements was not universal. Only about 58.9% of participants reported taking iron supplements, about 50.2% took multivitamins, and only 35.0% were taking folic acid supplements (Table 3). These figures from Table 3 suggest that a substantial proportion of the women were not adhering to or not receiving certain key supplements (particularly folic acid) during their pregnancy. This gap in supplementation is reflected in our anaemia outcomes. Bivariate analysis (Table 7) showed that both folate supplementation and multivitamin use had significant associations with anaemia status, whereas most purely dietary factors (meal frequency, and consumption frequency of fruits, green leafy vegetables, milk, red meat) did not show statistically significant differences (p > 0.05 for those, Table 7). Specifically, women who took folate supplements had much lower prevalence of anaemia than those who did not. As shown in Table 7, 71.2% of pregnant women who were on folate supplements were not anaemic, compared to only 44.8% non-anaemic among those without folate supplementation (in other words, 55.2% of non-supplementers were anaemic). This difference was highly significant (χ² = 23.07, p < 0.001), and corresponded to a markedly reduced risk: folate supplement use was associated with a ~72% lower odds of anaemia (unadjusted OR = 0.28, 95% CI 0.14–0.57). The beneficial impact of folic acid is not surprising, given that folate deficiency can cause megaloblastic anaemia and that folate is crucial for the increased red cell production in pregnancy. The fact that only one-third of our participants took folate may have contributed to both the high overall anaemia rate and the specific cases of macrocytosis/macrocytic anaemia we did observe. Similarly, multivitamin supplementation (which typically included iron and folic acid among other vitamins) was associated with better haemoglobin status. Among women who took prenatal multivitamins, 59.1% were not anaemic, whereas among those who did not take multivitamins the majority (54.7%) were anaemic (χ² = 5.659, p = 0.017; Table 7). This indicates a protective effect of multivitamins in general. However, when adjusted for other factors in multivariate analysis, multivitamin use itself was not a significant independent predictor (Table 7, adjusted OR ~1.02, p > 0.05), possibly because its effect overlaps with folate and iron supplementation (i.e. women on multivitamins often were on iron/folate too). Interestingly, iron supplementation on its own did not show a statistically significant association with anaemia in this study (p ≈ 0.08 in χ² test, Table 7). There was a positive trend – among women who were taking iron, 55.4% were non-anaemic (i.e. 44.6% were anaemic), whereas among those not on iron supplements, only 47.5% were non-anaemic (52.5% anaemic). This suggests that iron supplements did confer some benefit, but the difference wasn’t large enough to reach significance, possibly due to issues of adherence or the presence of other limiting nutrients. It’s worth noting that most women were at least receiving iron (nearly 59% as noted), and those not on iron might include women who started pregnancy with better iron status or who couldn’t tolerate supplements. The lack of a clear iron effect could also indicate that iron deficiency, while common, was not the only cause of anaemia here – other factors like folate deficiency and infections played a big role, as evidenced by their strong associations. As for dietary intake, we did not find significant differences in anaemia rates based on how frequently women consumed fruits, leafy greens, dairy, or meat (Table 7). For example, women who ate green leafy vegetables daily had about the same anaemia prevalence as those who ate them weekly or rarely (the proportions varied in the expected direction but not significantly, Table 7). A likely explanation is that nearly all participants had relatively similar diets (most ate these foods at least occasionally), and dietary recall may not capture quantity or bioavailability of nutrients. It may also be that supplementation (or lack thereof) overshadowed the contribution of diet in this particular cohort. Nonetheless, the trends did generally favor those with more frequent intake of ironand vitamin-rich foods – for instance, those who rarely ate green vegetables or fruits tended to have higher anaemia percentages than those who ate them more often (Table 7). Overall, our findings highlight that nutritional supplementation, especially with folic acid (and by extension a full prenatal multivitamin), is critical in preventing anaemia in pregnancy. A comprehensive approach addressing all potential deficiencies is needed. This aligns with the recommendations of Khan et al. (2010), who identified lack of adequate supplement use as a significant contributor to maternal anaemia. Ensuring better compliance with iron and folate supplementation, as well as improving overall diet quality, could substantially reduce anaemia among pregnant women in Accra. Factors Associated with Different Classes of Anaemia Understanding the factors linked to each morphological class of anaemia can provide insights into the underlying causes. We performed a multinomial logistic regression (Table 8) to determine how various risk factors associate with microcytic, normocytic, and macrocytic anaemia specifically (with nonanaemic women as the reference group). For microcytic hypochromic anaemia, two factors stood out as significant in our analysis: folate supplementation and birth spacing. Lack of folate supplementation was unexpectedly associated with increased risk of microcytic anaemia. Women who were taking folate had dramatically lower odds of developing microcytic anaemia than those who were not taking folate (adjusted OR = 0.22, 95% CI 0.09–0.53; p = 0.001, Table 8). This translates to about a 78% reduction in risk for microcytic anaemia among folate users. At first glance, this is surprising because microcytic anaemia is most commonly caused by iron deficiency, not folate deficiency (Massey, 1992). One possible interpretation is that women who diligently took folic acid might also have been more compliant with iron supplementation and overall antenatal care, thus improving their iron status indirectly. In contrast, women who did not take folate might represent generally poorer compliance or access to care, which could coincide with untreated iron deficiency. It is also possible some cases of microcytic anaemia were actually multifactorial (mixed iron and folate deficiency), so folate helped prevent those cases from manifesting as microcytosis. The second significant factor for microcytic anaemia was short birth interval. Women whose previous birth was IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 23 ≤2 years before the current pregnancy had a much higher likelihood of microcytic anaemia than those with >2 years between pregnancies (OR ~4.8, 95% CI ~2.0–11.4; p < 0.001, Table 8). This finding dovetails with our earlier result that short birth spacing increases overall anaemia risk, and it specifically indicates that closely spaced pregnancies are prone to iron-deficiency anaemia (which manifests as microcytic hypochromic blood pictures). Singal et al. (2018a) likewise identified interpregnancy interval under 2 years as a significant risk factor for microcytic anaemia, since the maternal iron reserves have insufficient time to recover. Iron supplementation itself did not show a significant effect in the microcytic model (Table 8) – the odds of microcytic anaemia were slightly lower for women on iron, but not to a meaningful extent (OR ~0.78, p = 0.59). This again might be due to widespread iron use in both anaemic and non-anaemic groups or varying adherence. Existing infection was also not significantly associated with microcytic anaemia in our multinomial results (OR ~1.34, p = 0.746), although the odds ratio >1 hints that infections could contribute to microcytosis in some cases (for instance, chronic inflammation can cause functional iron deficiency). In our context, infections (like malaria) likely caused more of normocytic anaemia (discussed below) than microcytic. It is worth noting, however, that malaria can sometimes present with microcytic anaemia due to iron sequestration and destruction of red cells – Bashawri et al. (2002) documented microcytic hypochromic anaemia in malaria cases. In our cohort, any such effect of infection on microcytosis was minimal compared to its effect on normocytosis. In summary, microcytic anaemia in these pregnant women was most strongly linked to inadequate folate (possibly a proxy for overall care) and short pregnancy spacing, reinforcing the need for nutritional support and family planning to prevent iron-deficiency anaemia. For normocytic normochromic anaemia, the analysis identified infection, short birth spacing, folate supplementation, and gestational age as significant factors (Table 8). These align with the notion that normocytic anaemia often results from systemic or multifactorial stressors. The presence of an infection had the largest impact: pregnant women who had an infection were over four times more likely to have normocytic anaemia than uninfected women (adjusted OR ~4.2, p < 0.01, derived from Table 8). This strong association supports the concept of anaemia of inflammation – infections (malaria, HIV, tuberculosis, etc.) trigger inflammatory pathways that lead to a drop in haemoglobin, usually without changing red cell indices (Nobili et al., 2014). Our finding is consistent with Quintero et al. (2011), who noted that even acute infections like malaria can cause significant anaemia in pregnancy (often normochromic unless coexistent iron deficiency). Short birth spacing was also associated with higher odds of normocytic anaemia (OR ~3.0 for ≤2 year interval vs >2 years). This indicates that close successive pregnancies not only cause iron-deficiency anaemia but can also lead to generalised anaemia (normocytic) perhaps through overall nutritional depletion and stress on the body. We also found that being in the second trimester (as opposed to third) significantly increased the risk of normocytic anaemia (OR ~2.0 vs third trimester; OR ~1.9 vs first trimester, per Table 8). In fact, second-trimester women were more prone to normocytic anaemia than to microcytic anaemia in our data. This again reflects the contribution of physiological anaemia of pregnancy (which is normocytic) in the mid-gestation period. By the third trimester, women who remain anaemic may increasingly include iron-deficient cases (microcytic), but in the second trimester much of the anaemia is dilutional or inflammationrelated, hence normocytic. Folate supplementation showed a protective effect for normocytic anaemia as well – folate users had about an 82% lower odds of normocytic anaemia compared to nonusers (adjusted OR ~0.18, p < 0.01, from Table 8). Folate is crucial for overall red blood cell production, so supplementation likely prevented many cases of mild normochromic anaemia that can develop when pregnant women become folate-deficient (even if iron is sufficient). It is notable that folate deficiency can cause macrocytosis; the fact that folate use is associated here with normocytic anaemia reduction suggests folate also helps prevent the early stages of anaemia that manifest as normocytic before progressing to macrocytic. On the other hand, consistent with the overall results, iron supplementation did not significantly affect the odds of normocytic anaemia in the adjusted model (Table 8). Normocytic anaemia is less directly tied to iron status and more to factors like infections and hemodilution, which explains why iron alone wasn’t a key determinant for this class in our study. Finally, regarding macrocytic anaemia, our study had very few cases (only 4 women had macrocytic anaemia, representing 2.8% of all anaemic cases). Consequently, we did not find any factor that was significantly associated with macrocytic anaemia in the multinomial analysis (Table 8). None of the examined predictors (education, age, supplements, etc.) showed a meaningful adjusted relationship with macrocytic outcomes, likely due to the small numbers and possibly because those few macrocytic cases might each have had distinct causes (e.g. one might be B12< deficient, another folate deficient, another due to an underlying condition). The rarity of macrocytic anaemia in our cohort could be attributed to the moderate folate status – although only a third took folate supplements, many might still get some folate from diet, and Ghana’s antenatal care does recommend folic acid which some women took, preventing widespread macrocytosis. Our findings concur with other studies in the region that report macrocytic anaemia is uncommon among pregnant women (Asafo Akowuah et al., 2022). From a public health standpoint, the lack of significant predictors for macrocytic anaemia suggests that the standard interventions (folate supplementation, improved nutrition) are broadly keeping overt macrocytic anaemia low, or that a larger sample would be needed to identify specific risk factors. Future research with a bigger sample of macrocytic cases could explore associations (for example, dietary habits or malabsorption issues) that we could not assess here. For now, ensuring all pregnant women receive folic acid supplementation remains the best strategy to prevent macrocytic anaemia, even though it was not a large problem in this study. Overall, the discussion above integrates our findings with the existing literature and highlights how the data in our tables and figures support these interpretations. The tables (Tables 1–8) provide the quantitative evidence for each point – from the prevalence rates to the statistical associations – and the figures (Figure 1 and Figure 2) illustrate the overall anaemia burden and morphological breakdown. As shown in Table 8 and the related analyses, addressing identified risk factors such as short birth intervals, infections, and insufficient supplementation (especially folate) could substantially reduce both the overall prevalence of anaemia and its most common forms among pregnant women in Accra. The consistency of many of our findings with other studies reinforces their validity, while any contrasting observations (such IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 24 as the timing of peak anaemia in pregnancy) offer useful insights for tailoring local antenatal care practices. Conclusions In this cross-sectional study of pregnant women at Korle Bu Teaching Hospital, nearly half of the participants were found to be anaemic (47.8%, 142/297), underscoring the high burden of anaemia in this population (Figure 1). Among the anaemic cases, normocytic normochromic anaemia was the most common morphological type (62.7%), followed by microcytic hypochromic anaemia (34.5%) and a small proportion of macrocytic anaemia (2.8%) (Figure 2). These findings indicate that while irondeficiency (typically manifesting as microcytic hypochromic anaemia) is prevalent, a majority of the anaemia cases in this cohort were normocytic, pointing to multifactorial or non-iron causes in many women. Several key risk factors for anaemia in pregnancy were identified across sociodemographic, clinical, and nutritional domains.Lower maternal educational attainment, engagement in physically exhaustive work, and poor knowledge about anaemia (including unawareness that pregnant women are particularly vulnerable to anaemia) emerged as significant contributors to the development of anaemia. In contrast, other sociodemographic characteristics such as maternal age, religion, family structure, and employment status showed no statistically significant association with anaemia in this study. Gestational age and pregnancy spacing were important determinants. Women in their second trimester had higher rates of anaemia compared to those in first or third trimesters. Similarly, a short inter-pregnancy interval (≤ 2 years since the last birth) was strongly associated with anaemia – women with close birth spacing had roughly three times the odds of being anaemic compared to those with a longer interval between pregnancies. The presence of an active infection during pregnancy (such as malaria or other illnesses) was also linked to significantly lower haemoglobin levels, with a majority (72.2%) of those reporting an infection being anaemic. On the other hand, clinical factors like gravidity (number of pregnancies) and number of antenatal clinic visits were not significantly related to anaemia risk in our cohort. Adequate micronutrient intake, particularly folate, was found to be protective. Insufficient folate supplementation (and by extension, multivitamin use) was the only dietary-related factor that showed a significant association with anaemia. Women who did not take folic acid supplements had a markedly higher prevalence of anaemia, with folate supplementation associated with a significantly reduced likelihood of anaemia (OR ~0.28). By contrast, adherence to iron supplementation, overall meal frequency, and the consumption of ironand vitamin-rich foods (e.g. green leafy vegetables, fruits, milk, red meat) did not demonstrate a significant statistical association with anaemia in this analysis. It is notable, however, that most women had suboptimal daily intake of these nutrient-rich foods (as shown in Table 3), indicating that dietary insufficiencies were common even if they did not directly translate into differential anaemia outcomes in the study. This suggests that factors like folate (which is critical for red blood cell production) and possibly overall nutritional status play a more prominent role in anaemia risk than the frequency of consuming specific foods alone, or that our sample size was not large enough to detect smaller effects of diet and iron pill adherence. Importantly, analysis of anaemia by morphological class revealed distinct patterns of association with risk factors. Short birth spacing and inadequate folate supplementation were more strongly linked to microcytic hypochromic anaemia, consistent with the notion that closely spaced pregnancies and folate/iron deficiencies can deplete maternal reserves and lead to smaller, pale red cells. In contrast, normocytic normochromic anaemia was most strongly associated with second-trimester status and infections. In fact, the influence of infection and mid-gestation on anaemia was more pronounced for normocytic cases than for microcytic cases, suggesting that inflammation or other pregnancy-related changes (rather than nutrient deficiencies alone) underlie much of the normocytic anaemia. Notably, poor folate status was also implicated as a contributor to normocytic anaemia, indicating overlap in how nutritional deficits can manifest in different morphological forms. No specific predictors were identified for the few macrocytic anaemia cases observed, likely due to their low number (only 2.8% of anaemic women) limiting statistical power. Overall, these findings highlight that anaemia in pregnancy at this setting is multifactorial – while iron/folate deficiency remains central, other factors like infections, pregnancy timing, birth spacing, and educational empowerment significantly impact haemoglobin levels. Recommendations 1. Based on the above findings, we propose the following recommendations to improve antenatal care and maternal health, focusing on prevention, early detection, and education: 2. Invest in robust health education for women of reproductive age and pregnant women. Antenatal care (ANC) sessions should include counseling on anaemia risk factors particularly highlighting the importance of adequate birth spacing and infection prevention and on practical preventive measures (nutrition, hygiene, prompt treatment of illness). Empowering women with knowledge about anaemia has proven benefits, as our study showed that better awareness is associated with lower anaemia risk. Regular community health talks and one-on-one counseling during clinic visits can ensure that women are aware of the need for nutrient-rich diets, the usefulness of supplements, and the vulnerabilities of pregnancy (e.g. higher risk of anaemia). 3. Given the significant contribution of infections (particularly malaria in our region) to anaemia in pregnancy, existing programs for infection control should be intensified. This includes preventive measures such as providing free or subsidized insecticide-treated bed nets to all pregnant women and ensuring they are educated on their consistent use. Routine screening for common infections (e.g. malaria, helminths, urinary tract infections) should be integrated into ANC protocols, especially in endemic areas, so that infections are detected and treated early. Intermittent preventive treatment for malaria and deworming in pregnancy, as per local guidelines, should be strictly implemented. Strengthening infection screening and treatment during pregnancy will help reduce the proportion of normocytic anaemia attributable to chronic infections. IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 25 4. Health policies should ensure that essential micronutrient supplements are readily accessible to all pregnant women from the earliest antenatal visits. In our context, folic acid and multivitamins emerged as crucial, so these (along with iron supplements) should be provided free of charge or highly subsidized as soon as pregnancy is confirmed. Early initiation and strict compliance with prenatal iron-folate supplementation regimens should be encouraged through follow-up and possibly reminder systems, as supplementation was a vital determinant of anaemia status in this study. ANC clinics can adopt strategies like directly observed supplement intake or weekly pill counts to improve adherence. By improving both access and adherence to supplementation, we can address nutritional gaps that contribute to maternal anaemia. 5. Family planning and spacing of pregnancies should be promoted as a key strategy to prevent anaemia and improve maternal outcomes. Counseling on postpartum family planning should be a routine part of antenatal and postnatal care. Women (and their partners) should be informed about the benefits of waiting at least 2 years after a birth before conceiving again, as closely spaced pregnancies were associated with significantly higher anaemia risk in our findings. Strengthening family planning services and access to effective contraception will empower women to achieve healthy spacing between pregnancies, thereby allowing time to rebuild nutritional stores (iron, folate) and reduce physiological stress, ultimately lowering the risk of anaemia in subsequent pregnancies. 6. Given that physically strenuous labor was linked to anaemia in our cohort, it is important to advise that pregnant women avoid excessive strenuous work and receive adequate rest. Families and communities should be sensitized to support expectant mothers by sharing workloads and reducing heavy physical tasks for them. Additionally, even though our study did not find a statistically significant link between dietary frequency and anaemia, most women reported inadequate intake of ironand vitamin-rich foods (Table 3). This highlights the need for continued nutritional support and counseling. Dietary improvement programs – for example, nutrition workshops or cooking demonstrations at ANC clinics – can encourage increased consumption of iron-rich foods (leafy greens, beans, meat), folate sources, and fruits. Where diet alone is insufficient due to socio-economic constraints, linking women with nutritional support programs or fortified foods is recommended. Ensuring a balanced diet and mitigating extreme physical strain during pregnancy are general health measures that, alongside medical interventions, will contribute to better haemoglobin levels and pregnancy outcomes. Limitations 1. Like all research, this study has limitations that must be acknowledged when interpreting the results: 2. The study’s sample (n = 297) was slightly below the initially calculated target (370) and was drawn from a single tertiary hospital’s ANC clinic. This relatively small, facility-based sample may limit the power to detect associations, particularly for less common forms of anaemia such as macrocytic anaemia, and it may affect the generalizability of the findings to all pregnant women in the wider community. The convenience sampling of women attending ANC (excluding those who do not seek antenatal care) means the results might not capture the full spectrum of anaemia risk in the general pregnant population. 3. Key data on risk factors were collected through participant self-report (questionnaires), including dietary intake frequencies, supplement adherence, and history of infections. Such self-reported information is subject to recall bias and social desirability bias. For instance, some women might not accurately remember or may over/under-report their intake of certain foods or use of supplements. Similarly, without objective verification, participants’ reports of ―no infection‖ could be incorrect if they had asymptomatic or undiagnosed infections. The lack of biochemical validation for nutritional status (e.g. no serum ferritin or folate levels measured) means we inferred deficiencies from self-report and morphological blood indices rather than confirming them biochemically. 4. The study did not include laboratory screening for infections in all participants – it depended on the women’s own knowledge and reporting of having an infection. This is a limitation because conditions like malaria, helminth infections, or other illnesses can be present without clear symptoms, potentially leading to misclassification of some anaemic women as ―no infection‖ when in fact an occult infection contributed to their anaemia. Future studies should incorporate routine screening (e.g. blood film for malaria, stool tests for parasites, etc.) to more accurately assess the impact of infections on anaemia in pregnancy. 5. This research was cross-sectional, capturing a single time-point in pregnancy for each participant. As a result, we can identify associations between risk factors and anaemia status, but we cannot establish causality or the temporal sequence of events. For example, while we observed that infections and second trimester were associated with anaemia, we cannot definitively conclude that the infection or being in second trimester caused the anaemia – it is possible that anaemia itself (or other unmeasured factors) could predispose to infections, or that women who are anaemic early might progress differently. Longitudinal studies or trials would be needed to confirm causal relationships and the directionality of these associations. Despite these limitations, the study provides valuable insight into the prevalence and morphological types of anaemia in pregnancy and identifies actionable risk factors within the Ghanaian context. The findings can inform targeted interventions such as educational programs, improved supplement distribution, infection control in pregnancy, and family planning services to help reduce anaemia and improve maternal health outcomes. By addressing the modifiable factors highlighted and strengthening antenatal care strategies accordingly, health practitioners and policymakers can IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 26 work towards lowering the burden of anaemia among pregnant women. Conflict of interest There is no conflict of interest References 1. World Health Organization. (2011). Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. WHO. 2. World Health Organization. (2015). WHO guideline: Iron supplementation in postpartum women. WHO. 3. de Benoist, B., McLean, E., Egli, I., & Cogswell, M. (Eds.). (2008). Worldwide prevalence of anaemia 1993– 2005: WHO global database on anaemia. WHO. 4. Chaparro, C. M., & Suchdev, P. S. (2019). Anemia epidemiology, pathophysiology, and etiology in lowand middle-income countries. Annals of the New York Academy of Sciences, 1450(1), 15–31. https://doi.org/10.1111/nyas.14092 5. World Health Organization. (2021). World health statistics 2021. WHO. 6. Okia, C. C., Aine, B., Kiiza, R., Omuba, P., Wagubi, R., Muwanguzi, E., et al. (2019). Prevalence, morphological classification, and factors associated with anemia among pregnant women at Itojo Hospital, Uganda. Journal of Blood Medicine, 10, 351–357. https://doi.org/10.2147/JBM.S216613 7. Ndegwa, S. K. (2019). Anaemia and its associated factors among pregnant women attending antenatal clinic at Mbagathi County Hospital, Nairobi, Kenya. African Journal of Health Sciences, 32(1), 59–73. 8. Dorsamy, V., Bagwandeen, C., & Moodley, J. (2020). The prevalence, risk factors and outcomes of anaemia in South African pregnant women: A systematic review and meta-analysis (Protocol). Systematic Reviews, 9(1), 40. https://doi.org/10.1186/s13643-020-01288-4 9. World Health Organization. (2020). Global anaemia reduction efforts among women of reproductive age: Impact, achievement of targets and the way forward. WHO. 10. World Health Organization. (2016). Global Health Observatory data repository: Prevalence of anaemia in pregnant women (by WHO region). WHO. 11. Ghana Statistical Service, Ghana Health Service, & ICF International. (2015). Ghana demographic and health survey 2014. GSS, GHS, & ICF. 12. Gebreweld, A., & Tsegaye, A. (2018). Prevalence and factors associated with anemia among pregnant women attending antenatal clinic at St. Paul’s Hospital Millennium Medical College, Addis Ababa. Journal of Nutritional Medicine & Diet Care, 4(1), Article 23. https://doi.org/10.23937/2572-3278.1510023 13. Belachew, T., & Legesse, Y. (2006). Risk factors for anaemia among pregnant women attending antenatal clinic at Jimma University Hospital, Southwest Ethiopia. Ethiopian Medical Journal, 44(3), 211–220. 14. Berhe, A., Kassa, G. M., et al. (2017). Prevalence of anemia and associated factors among pregnant women in Adigrat, northern Ethiopia. BMC Research Notes, 10, 312. https://doi.org/10.1186/1756-0500-10-312 15. Frimpong, O. B., Asamoah‐Frimpong, J., Baffoe‐ Nyarko, I., Abdul‐Tawab, A., Laryea, E. B., et al. (2022). Effect of a quality improvement initiative on antenatal care utilization in Ghana. African Journal of Reproductive Health, 26(1), 49–61. 16. Bashawri, L. A., Mandil, A. A., Bahnassy, A. A., & Ahmed, M. A. (2002). Malaria: Hematological aspects and the pattern of anemia in pregnancy. Annals of Saudi Medicine, 22(5–6), 372–377. 17. Frayne, J., & Pinchon, D. (2019). Anaemia in pregnancy. Australian Journal of General Practice, 48(3), 125–129. 18. Means, R. T. Jr. (2019). Normal hematologic changes in pregnancy and their impact on anaemia. Hematology/Oncology Clinics of North America, 33(3), 481–486. 19. Gyamfi, J., Ofori, S. A., et al. (2020). Pregnant women’s perceptions and adherence to iron-folate supplementation in urban Ghana. Journal of Pregnancy, 2020, 9718797. 20. Adu-Afarwuah, S., Lartey, A., & Dewey, K. G. (2017). Adherence to micronutrient supplementation in pregnancy: Perspectives from Ghana. Maternal & Child Nutrition, 13(2), e12252. https://doi.org/10.1111/mcn.12252 21. Black, R. E., Victora, C. G., Walker, S. P., et al. (2013). Maternal and child undernutrition and overweight in low-income and middle-income countries. The Lancet, 382(9890), 427–451. https://doi.org/10.1016/S01406736(13)60937-X 22. World Health Organization. (2021). Global anaemia estimates, 2019. In Anaemia in women and children – 2021 edition. WHO. 23. Abusharib, M. S. (2019). Prevalence and types of anaemia among pregnant women in Khartoum, Sudan. Sudan Journal of Medical Sciences, 14(3), 126–134. 24. Behere, R. V., Deshmukh, P. R., et al. (2021). High prevalence of microcytic anemia among pregnant women in rural India: A cross-sectional study. International Journal of Community Medicine and Public Health, 8(4), 1788–1794. https://doi.org/10.18203/23946040.ijcmph20211233 25. Singal, N., Gupta, S., et al. (2018). Short interpregnancy interval as a risk factor for iron-deficiency anemia in pregnancy. Journal of Obstetrics and Gynaecology of India, 68(3), 201–206. https://doi.org/10.1007/s13224017-1082-0 26. Asafo Akowuah, E., et al. (2022). Normocytic normochromic anaemia as the predominant morphological type among pregnant women in Ashanti Region, Ghana. Ghana Medical Journal, 56(1), 30–37. IRASS Journal of Applied Medical and Pharmaceutical Sciences Vol-2, Iss-12 (December2025): 7-27 Vol-2, Iss-12 (December-2025) 27 https://doi.org/10.4314/gmj.v56i1.5 27. Anlaakuu, P., & Anto, F. (2017). Prevalence of anemia and associated factors among pregnant women in Sunyani Municipality, Ghana. AIMS Public Health, 4(3), 268–279. https://doi.org/10.3934/publichealth.2017.3.268 28. Sumaila, U. (2019). Maternal education and anemia in pregnancy: A cross-sectional study in Northern Nigeria. Annals of Medical and Health Sciences Research, 9(5), 666–670. 29. Mekonnen, F. A., Ambaw, B. S., & Neri, G. T. (2018). Housewives have a lower risk of anaemia in pregnancy than employed women: A comparative cross-sectional study in Ethiopia. BMC Hematology, 18, 8. https://doi.org/10.1186/s12878-018-0117-8 30. Tibambuya, B. A., Ganle, J. K., & Ibrahim, M. (2019). Anaemia at antenatal care initiation and associated factors among pregnant women in Kumbungu District, Ghana. Pan African Medical Journal, 33, 325. https://doi.org/10.11604/pamj.2019.33.325.18258 31. Wemakor, A. (2019). Determinants of anaemia in pregnant women attending a tertiary hospital in northern Ghana. BMC Pregnancy and Childbirth, 19, 495. https://doi.org/10.1186/s12884-019-2625-x 32. Lestari, E. W., Susanti, A. I., & Wayan, M. (2018). Knowledge of pregnant women about anaemia and its relationship with iron supplement adherence in Indonesia. European Journal of Molecular & Clinical Medicine, 5(1), 20–25. 33. Abbas, A. (2020). Short birth interval and maternal anaemia in a Nigerian cohort. International Journal of Gynecology & Obstetrics, 149(1), 141–147. https://doi.org/10.1002/ijgo.13100 34. Kejela, T., Oljira, L., & Tesfaye, E. (2020). Short birth interval (<24 months) as a risk factor for anemia among pregnant women in western Ethiopia. Contraception and Reproductive Medicine, 5, 30. https://doi.org/10.1186/s40834-020-00133-0 35. Viveki, R. G., Halappanavar, A. B., Viveki, P. R., Halki, S. B., Maled, V. S., & Deshpande, P. S. (2012). Prevalence of anaemia and its epidemiological determinants among pregnant women in a rural community of Karnataka, India. Al Ameen Journal of Medical Sciences, 5(3), 216–223. 36. Nobili, E., Leo, R., Sardo, S., et al. (2014). Anaemia of chronic disease in pregnancy: The role of inflammation and hepcidin. Journal of Maternal-Fetal & Neonatal Medicine, 27(7), 706–710. https://doi.org/10.3109/14767058.2013.830507 37. Quintero, J. P., Siqueira, A. M., Tobón, A., et al. (2011). Malaria-related anaemia: A Latin American perspective. Memórias do Instituto Oswaldo Cruz, 106(Suppl 1), 91– 104. https://doi.org/10.1590/S0074-02762011000900012 38. Khan, Y., Bhutta, Z. A., & Ahmed, T. (2010). Irondeficiency anemia in pregnancy: Challenges and solutions. Nutrition Reviews, 68(Suppl 1), S21–S24. https://doi.org/10.1111/j.1753-4887.2010.00335.x 39. Massey, A. C. (1992). Microcytic anemia: Differential diagnosis and management. Medical Clinics of North America, 76(3), 549–566. https://doi.org/10.1016/S00257125(16)30335-6.