Micronutrient deficiencies, particularly anaemia, are more likely to affect children and reproductive-aged women. Through a cross-sectional survey using multi-stage cluster-random sampling techniques, the study assessed the current anaemia status among adolescent girls, pregnant and lactating women as well as the associated factors with anaemia in this population in South-coastal Bangladesh. The average age of women was 24.0 and 15.2 years for girls. Half of the pregnant, 46% of lactating-women and 38% of adolescent-girls were assessed as anaemic. Around 20% of the respondents reported consumed more than five food groups, in last 24-hours. Risk of mild anaemia was higher among Hindu girls. Pregnant-women who washed hands after using toilet and who received 4 + ANC visits [aOR 0.35, 95% CI: 0.16–0.77, p = 0.009] had lower likelihood of having any form of anaemia. Pregnant-women who consumed > 5 food groups had less risk of anaemia (aOR: 0.14, 95% CI:0.05–0.37, p < 0.001). Second and third trimester pregnant women were more likely to be anaemic. Lactating-women who consumed > 5 food groups, who always washed hands before food preparation, received 4 + ANC visits, consumed > 90 IFA, had decreased risk of anaemia. Appropriate measures should be taken to address the substantial prevalence of anaemia among this vulnerable group.
Article
Anaemia among adolescent girls, pregnant and lactating women in south coastal region of Bangladesh: prevalence and associated factors
https://doi.org/10.21203/rs.3.rs-3085323/v1
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Anaemia is a global public health concern affecting almost one-third of the world’s population [1]. It is an adverse health condition in which the body has a lower amount of red blood cells (RBCs) and hemoglobin (Hb) concentration than an established cut-off point set by World Health Organization, impairing the oxygen carrying capacity of the RBCs to the tissue [2]. It can appear at any stage of the human life cycle. However, the physiological vulnerability (intense growth and development, menstrual blood loss, and fetal growth during pregnancy) of the adolescent girls and reproductive aged women make them the worst sufferers of anaemia when compared to men and females at other life stages [3–6]. The global prevalence of anaemia is 29% among the reproductive aged non-pregnant women, whereas it is 38% among the pregnant women [7]. Even though, the prevalence is heterogeneously distributed across the world, yet the low-and-middle-income countries (LMICs) bear greater burden of anaemia [7].
A multifaceted etiology is involved in developing anaemia. However, iron deficiency anaemia (IDA) accounts for approximately 50% of all cases of anaemia in women across the globe due to inadequate consumption or absorption of iron-rich foods, increased need for iron during the course of growth and pregnancy, menstrual iron loss, and intestinal parasite infections, [2]. It can be interchangeably used with anaemia [5]. Besides, deficiencies of certain nutrients including vitamin B12, folate, riboflavin, vitamin A, vitamin C, copper, as well as protein-energy malnutrition may lead to anaemia [2, 3, 6]. Moreover, certain genetic disorders such as thalassemia, sickle cell anaemia, chronic inflammation, deficiency of glucose-6-phosphate-dehydrogenase (G6PD), and ovalocytosis can give rise to anaemia [2]. Infectious diseases like intestinal worm infestation, malaria, tuberculosis, AIDS, schistosomiasis, tropical sprue also contribute to anaemia [2, 3]. Nevertheless, a wide range of aspects encompassing social, economic, demographic, political, ecological, biological, anthropometric, and lifestyle factors play an important role in developing anaemia. [1, 3, 4, 7–9].
Anaemia is adversely related to maternal and child health. It impairs cognitive development and motor function during the early stage growth. Individuals suffering from anaemia experience fatigue and loss of productivity which eventually yields poor work performance, producing a substantial economic burden to the family and the nation [2, 3]. On the verge of extreme conditions, anaemia increases the risk of morbidity and mortality, especially among pregnant and perinatal mothers resulting in miscarriages, stillbirths, prematurity and low birth weight babies [2]. Furthermore, intergenerational transfer of poor iron pools from iron-deficient pregnant women to their children is a concerning issue since it increases the risk of developing iron deficiency and anaemia in infants [3]. Therefore, iron supplementation plays a crucial role during pregnancy in improving birth weight and length of the gestational period [5].
The highest prevalence of anaemia was found among children and women living in South Asia, Central and Western Africa [6]. Bangladesh is one of the South Asian developing countries having a long history of struggling with anaemia which still remains a major concern [8]. At the national level, 42.4% of reproductive-aged women were anaemic where 35.8% were mildly anaemic. Anaemia was highly prevalent among pregnant (49.6%) and lactating (47.8%) women than in non-pregnant or non-lactating women (40%) [10]. Another study conducted among adolescent girls suggested that around 52% were anaemic with 46%, 5% and 0.2% being mildly, moderately and severely anaemic respectively [4]. In Bangladesh, the prevalence of iron deficiency anaemia (IDA) was found lower constituting 19% of total anaemia prevalence according to the National Micronutrient Survey 2011-12. It also reported that only 4.8% of non-pregnant and non-lactating women (15–49 years of age) were suffering from IDA while it was lower (1.8%) among school-going children (12–14 years) [11]. Though the dietary intake of iron only met 8–18% RDAs of children and women of reproductive age, yet the presence of higher groundwater iron can produce a salutary effect in lowering IDA [9, 11]. However, till date limited information and heterogeneous findings on the distribution of the anaemia prevalence and its determinants are evident in Bangladesh. Moreover, the lower prevalence of IDA is suggestive of other possible determinants that can explain the occurrence of anaemia in Bangladesh. Thus, the present study analyzes the socioeconomic determinants, demographic factors, WASH practices, reproductive history and dietary information to find any association of these variables which encountered significant associations with the prevalence of anaemia in many studies.
Study design and participants
A cross-sectional study design was undertaken from November to December 2021, at several coastal communities in Bangladesh where a nutrition and water sanitation-related programme namely the “Max Nutri-WASH” had been delivered precisely. Twenty-four Upazilas under three districts (Khulna, Patuakhali, and Satkhira) in the South Coastal areas of Bangladesh were selected as the study sites. The participants of the study were subdivided into three sub-groups: adolescent girls (10–19 years), pregnant, and lactating women. To investigate the anaemia status and its association with other contributing factors among the participants, a quantitative study approach was robustly employed.
Sampling procedure and sample size
A multi-stage cluster random sampling technique was used to obtain a representative population sample in the Max Nutri-WASH program zones. During the first stage of sampling, three districts from MAX-Nutri-WASH program area under the program districts was randomly selected. Eight Upazilas out of the twenty-four were chosen randomly from the pre-selected districts during the second phase of sampling. The next stage involved selecting a predetermined number of participants from each target group using systematic sampling technique. The sample size necessary for each study participant group was calculated based on the estimated prevalence of anaemia (39%) [12], desired precision of at least 5% per sub-groups (adolescent girl, pregnant and lactating women), and a 95% confidence interval. A total of 400 participants from each group was determined as the sample size, using the following formula for sample size calculation:
Sample population comprised of 375 pregnant and lactating mothers within both categories, along with 400 adolescent girls, for a total of 1150 study participants (Fig. 1).
Data collection tools
A standardized structured questionnaire was formulated to collect data from the study participants. It was developed in English and later translated into Bengali, keeping the meaning unchanged. Data was collected on socio-demographic information from the participants regarding their age, religion, level of education, occupation, family size, media exposure, and region of livings etc. For collecting WASH related information, questions were asked regarding the usage of safe water for drinking and other household chores (washing, cooking, bathing etc), handwashing after toilet, before preparing foods, type of toilet facilities. Besides, pregnant and lactating women were interviewed to collect information about their pregnancy conditions, ANC check-ups, and Iron and Folic acid supplementation (IFA) during their current and previous pregnancies. The Minimum Dietary Diversity-Women (MDD-W) indicator was developed based on preceding 24-hour dietary recall from a list of ten selected food groups to assess the micronutrient adequacy of women's diets [13]. The wealth index was constructed based on principal component analysis (PCA) of the key socioeconomic variables and classified households into poorest, poorer, middle, richer, richest [14].
Data collection procedure
The research team trained the field staff on the survey questionnaire and relevant interview skills before collecting the data. They received a comprehensive training on the Hemocue 301- haemoglobin measurement device. Soon after finishing the training, they pretested the questionnaire at a neighbouring location before starting the actual data collection. Participant provided information by a face-to-face interview based on the pre-set questionnaire. Interviews were conducted upon receiving a written consent from the study participants in a convenient location for them.
Haemoglobin measurement
The haemoglobin concentration in blood capillaries has been used to detect anaemia utilising the Hemocue 301 machine (Hemocue AB, Angleholm, Sweden). The disposable lancet punctured the fingertip of the middle, ring, or index finger, after disinfecting with chlorohexidine gluconate at 0.5 percent. The exact first drop of blood was discarded. Gentle pressure was applied to extract the second drop. Once the blood drop appeared, the micro cuvette was immersed into it to allow capillary action to refill it with the blood specimen. Excess blood was wiped out from the edges of the micro cuvettes with a piece of cotton. After turning on the hemocue photometer, the micro cuvette holder was drawn out. The blood-filled microcuvette was put onto the holder, and the holder was stabilized. After 10–20 seconds, hemoglobin values appeared on the digital display.
The WHO threshold for hemoglobin concentration to be considered anaemic (Hb < 11 g/dL for pregnant and Hb < 12 g/dL for non-pregnant women) was used in this study. Based on Hb levels, this anemia was further divided into mild, moderate, and severe categories for pregnant (10.0 to 10.9 g/dL, 7.0-9.9 g/dL, and 7.0 g/dL, respectively) and non-pregnant women (11.0-11.9 g/dL, 8.0-10.9 g/dL, and 8.0 g/dL, respectively) [15].
Ethical consideration
The research was approved by the Research Review Committee (RRC) and Ethical Review Committee (ERC) of the institutional review board (IRB) of the icddr,b. This research was conducted in collaboration with the Helsinki Declaration. Before beginning the interview, the informed consent was obtained from all subjects and/or their legal guardians of the participants. They were given assurance that confidentiality will be maintained for all the gathered information.
Statistical analyses
Descriptive statistics was applied to collectively describe background characteristics. The effect of each independent variable on the anaemia outcome (no anaemia, mild anaemia, and moderate or severe anaemia) was determined through bivariate and multivariate analysis. In the multivariate analysis, multinomial logistic regression models was used where the predictor variables (with p < 0.25 in the bivariate analysis and low multi-collinearity) were taken into consideration [16]. The results were presented as adjusted odds ratios (aORs) along with 95% confidence intervals (CIs). P-values of less than 0.05 were considered as statistically significant. STATA 14.1 was used for all statistical analysis.
Background characteristics of the study participants
Table 1 presents the socio-economic characteristics of the adolescent girls, pregnant women, and lactating women. The mean age of the adolescent girls, pregnant and lactating women were 15.2 (1.7), 24.2 (5.5), and 24.6 (5.6) years respectively. The majority of participants in these three groups were Muslim, received a secondary level of education, and unemployed. Only 10% of the pregnant and lactating women were employed. Average MDD-W was around 3.3 among all three participant’s group. Around eighty percent of all participants did not consume food from five or more food groups. An equal proportion of adolescent girls and lactating women (around 63%) had improved toilet facilities in their homes whereas half of the pregnant women’s household used improved latrine. In case of handwashing practice, over half of the participants always washed their hands before preparing food and about ninety percent always washed their hands after using toilet. Around 80% of pregnant women were in second or third trimester of pregnancy. Among all the pregnant women, 75% received ANC 1–3 times, and 23.4% consumed more than 90 IFA tablets. Almost half of lactating women received ANC check-up for 1–3 times during their last pregnancy and 54% of them consumed more than 90 IFA tablets.
| Variables | Adolescent girls n (%) | Pregnant women n (%) | Lactating women n (%) | |
|---|---|---|---|---|
| Age | ||||
| (Mean ± SD) | (15.2 ± 1.7) | (24.2 ± 5.5) | (24.6 ± 5.6) | |
| Religion | ||||
| Muslim | 299 (74.75) | 303 (80.8) | 292 (77.9) | |
| Non-Muslim | 101 (25.25) | 72 (19.2) | 83 (22.1) | |
| Educational Status | ||||
| Primary | 25 (6.3) | 75 (20.0) | 74 (19.7) | |
| Secondary | 336 (84.0) | 217 (57.9) | 224 (59.7) | |
| Higher | 39 (9.8) | 83 (22.1) | 77 (20.5) | |
| Employment status | ||||
| Employed | 12 (3.0) | 40 (10.7) | 34 (9.1) | |
| Unemployed | 388 (97.0) | 335 (89.3) | 341(90.9) | |
| Family members | ||||
| (Mean ± SD) | (4.7 ± 1.6) | (4.6 ± 2.0) | (5.6 ± 2.1) | |
| < 5 members | 215 (53.8) | 224 (59.7) | 115 (30.7) | |
| ≥ 5 members | 185 (46.3) | 151 (40.3) | 260 (69.3) | |
| MDD-W | ||||
| (Mean ± SD) | (3.3 ± 1.5) | (3.4 ± 1.6) | (3.3 ± 1.4) | |
| < 5 food group | 321 (80.3) | 282 (75.2) | 310 (82.7) | |
| ≥ 5 food groups | 79 (19.8) | 93 (24.8) | 65 (17.3) | |
| Toilet facilities | ||||
| Improved | 252 (63.0) | 186 (49.6) | 237 (63.2) | |
| Unimproved | 148 (37.0) | 189 (50.4) | 138 (36.8) | |
| Washed hand before food preparation | ||||
| Occasional | 186 (46.5) | 173 (46.1) | 157 (41.9) | |
| Always | 214 (53.5) | 202 (53.9) | 218 (58.1) | |
| Washed hand after toilet | ||||
| Occasional | 45 (11.3) | 45 (12.0) | 42 (11.2) | |
| Always | 355 (88.8) | 330 (88.0) | 333 (88.8) | |
| Media exposure | ||||
| No | 54 (13.5) | 80 (21.3) | 71 (18.9) | |
| Yes | 346 (86.5) | 295 (78.7) | 304 (81.1) | |
| Pregnancy Trimester | ||||
| 1st Trimester | - | 73 (19.5) | - | |
| 2nd Trimester | - | 160 (42.7) | - | |
| 3rd Trimester | - | 142 (37.9) | - | |
| ANC Visit | ||||
| 1–3 times | - | 250 (75.8) | 211 (56.3) | |
| 4 + times | - | 80 (24.2) | 164 (43.7) | |
| IFA intake | ||||
| IFA ≤ 90 | - | 206 (76.6) | 173 (46.1) | |
| IFA > 90 | - | 63 (23.4) | 202 (53.9) | |
| Wealth Index | ||||
| Poorest | 80 (20.0) | 92 (24.5) | 72 (19.2) | |
| Poorer | 85 (21.3) | 63 (16.8) | 73 (19.5) | |
| Middle | 77 (19.3) | 67 (17.9) | 83 (22.1) | |
| Richer | 78 (19.5) | 75 (20.0) | 78 (20.8) | |
| Richest | 80 (20.0) | 78 (20.8) | 69 (18.4) | |
| Region | ||||
| Patuakhali Sadar | 61 (15.3) | 57 (15.2) | 58 (15.5) | |
| Rangabali | 30 (7.5) | 31 (8.3) | 32 (8.5) | |
| Galachipa | 53 (13.3) | 42 (11.2) | 44 (11.7) | |
| Batiaghata | 23 (5.8) | 16 (4.3) | 20 (5.3) | |
| Dumuria | 142 (35.5) | 118 (31.5) | 129 (34.4) | |
| Satkhira Sadar | 34 (8.5) | 53 (14.1) | 17 (4.5) | |
| Tala | 44 (11.0) | 43 (11.5) | 56 (14.9) | |
| Kalaroa | 13 (3.3) | 15 (4.0) | 19 (5.1) | |
| n, number; %, percentage | ||||
| - no observation | ||||
Prevalence of anaemia among study participants
The prevalence of anaemia among adolescent girls, pregnant and lactating women was around 38%, 50%, and 46% respectively (Fig. 2). Mild anaemia was found to be higher among lactating women (28%) than that of pregnant women (25%) and adolescent girls (23%). Higher prevalence of moderate or severe anaemia was found among pregnant women (25%), in comparison to the lactating women (17%) and adolescent girls (15%).
Associated factors of anaemia among adolescent girls
The multiple multinomial logistic analyses in Table 2 showed the factors associated with anaemia among adolescent girls in this study. Non-muslim adolescent girls had 2.1 (aOR: 2.13, 95%CI: 1.05–4.31, p = 0.036) times higher odds of being mild anaemic than those who practiced Islam. Those who belonged to larger family (≥ 5 members), were 2.2 times (aOR: 2.24, 95% CI: 1.16–4.31, p = 0.016) more likely to be moderately/severely anaemic than those who had smaller families (< 5 members). Girls with media exposure had a 67% (aOR: 0.33, 95% CI: 0.15–0.74, p = 0.006) lower likelihood of having moderate or severe anaemia than those who were not exposed. Adolescent girls residing in Rangabali (aOR: 0.21, 95% CI: 0.06–0.79, p = 0.021), Dumuria (aOR: 0.25, 95% CI: 0.09–0.67, p = 0.006), and Tala (aOR: 0.10, 95% CI: 0.02–0.48, p = 0.004) had lower odds of being moderately or severely anaemic than those living in the Patuakhali Sadar. Similarly, girls who lived in Rangabali (aOR: 0.31, 95% CI: 0.09-1.00, p = 0.049), and Dumuria (aOR: 0.37, 95% CI: 0.16–0.87, p = 0.023) had less likelihood of being mildly anaemic.
| Characteristics | Mild Anaemia | Moderate/severe Anaemia | |||
|---|---|---|---|---|---|
| aOR [95%CI] a | P-Value | aOR [95%CI] a | P-Value | ||
| Religion | |||||
| Muslim | Reference | Reference | |||
| Non-Muslim | 2.13 [1.05–4.31] | 0.036 | 1.24 [0.48–3.19] | 0.653 | |
| Family members | |||||
| < 5 members | Reference | Reference | |||
| ≥ 5 members | 1.09 [0.65–1.84] | 0.732 | 2.24 [1.16–4.31] | 0.016 | |
| MDD-W | |||||
| < 5 food group | Reference | Reference | |||
| >=5 food groups | 1.35 [0.73–2.50] | 0.340 | 0.65 [0.26–1.64] | 0.364 | |
| Toilet facility | |||||
| Unimproved | Ref | Ref | |||
| Improved | 0.61 [0.37–1.02] | 0.062 | 0.80 [0.43–1.52] | 0.501 | |
| Hand-wash before food preparation | |||||
| Occasional | Reference | Reference | |||
| Always | 1.35 [0.80–2.29] | 0.260 | 0.84 [0.45–1.57] | 0.576 | |
| Media exposure | |||||
| No | Reference | Reference | |||
| Yes | 0.58 [0.27–1.23] | 0.157 | 0.33 [0.15–0.74] | 0.006 | |
| Wealth Index | |||||
| Poorest | Reference | Reference | |||
| Poorer | 0.71 [0.32–1.57] | 0.397 | 0.99 [0.40–2.47] | 0.984 | |
| Middle | 0.73 [0.33–1.64] | 0.447 | 0.51 [0.18–1.45] | 0.206 | |
| Richer | 0.89 [0.40–1.95] | 0.767 | 0.81 [0.30–2.14] | 0.667 | |
| Richest | 0.70 [0.31–1.58] | 0.386 | 0.83 [0.30–2.28] | 0.718 | |
| Region | |||||
| Patuakhali Sadar | Reference | Reference | |||
| Rangabali | 0.31 [0.09-1.00] | 0.049 | 0.21 [0.06–0.79] | 0.021 | |
| Galachipa | 0.54 [0.21–1.37] | 0.195 | 0.38 [0.13–1.07] | 0.068 | |
| Batiaghata | 0.30 [0.08–1.15] | 0.079 | 0.28 [0.06–1.34] | 0.111 | |
| Dumuria | 0.37 [0.16–0.87] | 0.023 | 0.25 [0.09–0.67] | 0.006 | |
| Satkhira Sadar | 0.53 [0.18–1.56] | 0.247 | 0.67 [0.22–2.11] | 0.499 | |
| Tala | 0.36 [0.13-1.00] | 0.050 | 0.10 [0.02–0.48] | 0.004 | |
| Kalaroa | 0.89 [0.19–4.21] | 0.878 | 1.50 [0.33–6.92] | 0.602 | |
| aOR: adjusted odds ratio; CI: Confidence Interval | |||||
| aadjusted for Religion, Family members, MDD-W, Toilet facility, Hand-wash before food preparation, Media exposure, Wealth Index, and Region. | |||||
Associated factors of anaemia among pregnant women
Table 3 presents the factors associated with anaemia among the pregnant women. Women with higher educational attainment were more likely to have mild anaemia than those with primary education (aOR: 4.72, 95% CI: 1.58–14.11; p = 0.006). Pregnant women who consumed diversified diet (≥ 5 food groups) had 86% lower likelihood of being mildly anaemic (aOR: 0.14, 95%CI: 0.05–0.37, p < 0.001). The pregnant women who always washed their hands after using toilet had lower odds of suffering from mild (aOR: 0.23, 95%CI: 0.08–0.68, p = 0.008) and moderate or severe (aOR: 0.16, 95%CI: 0.06–0.44, p < 0.001) anaemia in comparison to the women who did washed their hands occasionally. Pregnant women in their second trimester (aOR: 9.66, 95%CI: 2.88–32.41; p < 0.001) and third trimester (aOR: 13.49, 4.02–45.21; p < 0.001) of pregnancy were more likely to be mildly anaemic. However, higher odds of being moderately or severely anaemic was also observed among women in their second trimester (aOR: 9.48, 95%CI: 2.89–31.03; p < 0.001) and third trimester (aOR: 10.28, 3.07–34.44; p < 0.001). In addition, women who had received ANC at least four times had a 65% (aOR: 0.35, 95%CI: 0.16–0.77, p = 0.009) and 76% (aOR: 0.24, 95%CI: 0.10–0.56, p = 0.001) lower likelihood of being mildly and moderately or severely anaemic respectively. Again, pregnant women who belonged to wealthiest strata were more likely to experience mild anaemia than those in the poorest quintile (aOR: 3.61, 95% CI: 1.25–10.41; p = 0.017). In comparison to Patuakhali Sadar, pregnant women living in Satkhira Sadar (aOR: 0.22, 95%CI: 0.06–0.79, p = 0.02) and Tala (aOR: 0.09, 95%CI: 0.02–0.49, p = 0.005) had a higher chance of developing moderate or severe anaemia.
| Characteristics | Mild Anaemia | Moderate/severe Anaemia | |||
|---|---|---|---|---|---|
| aOR [95%CI] | P-Value | aOR [95%CI] | P-Value | ||
| Educational Status | |||||
| Primary | Reference | Reference | |||
| Secondary | 1.16 [0.46–2.88] | 0.756 | 0.62 [0.27–1.44] | 0.270 | |
| Higher | 4.72 [1.58–14.11] | 0.006 | 1.43 [0.47–4.31] | 0.530 | |
| MDD-W | |||||
| < 5 food group | Reference | Reference | |||
| ≥ 5 food groups | 0.14 [0.05–0.37] | < 0.001 | 0.67 [0.32–1.42] | 0.294 | |
| Toilet facility | |||||
| Unimproved | Reference | Reference | |||
| Improved | 0.63 [0.32–1.25] | 0.190 | 0.65 [0.31–1.34] | 0.246 | |
| Washed hand after toilet | |||||
| Occasional | Reference | Reference | |||
| Always | 0.23 [0.08–0.68] | 0.008 | 0.16 [0.06–0.44] | < 0.001 | |
| Pregnancy Trimester | |||||
| 1st Trimester | Reference | Reference | |||
| 2nd Trimester | 9.66 [2.88–32.41] | < 0.001 | 9.48 [2.89–31.03] | < 0.001 | |
| 3rd Trimester | 13.49 [4.02–45.21] | < 0.001 | 10.28 [3.07–34.44] | < 0.001 | |
| Antenatal Care (ANC) Visit | |||||
| 1–3 times | Reference | Reference | |||
| 4 + times | 0.35 [0.16–0.77] | 0.009 | 0.24 [0.10–0.56] | 0.001 | |
| Wealth Index | |||||
| Poorest | Reference | Reference | |||
| Poorer | 1.73 [0.58–5.14] | 0.322 | 1.21 [0.41–3.55] | 0.728 | |
| Middle | 2.42 [0.85–6.88] | 0.097 | 1.56 [0.56–4.39] | 0.398 | |
| Richer | 3.61 [1.25–10.41] | 0.017 | 2.03 [0.68–6.07] | 0.203 | |
| Richest | 2.83 [0.95–8.45] | 0.063 | 2.10 [0.70–6.34] | 0.188 | |
| Region | |||||
| Patuakhali Sadar | Reference | Reference | |||
| Rangabali | 0.70 [0.15–3.23] | 0.646 | 0.36 [0.08–1.60] | 0.180 | |
| Galachipa | 0.80 [0.24–2.63] | 0.712 | 0.40 [0.11–1.41] | 0.153 | |
| Batiaghata | 1.09 [0.21–5.59] | 0.919 | 1.84 [0.42–8.06] | 0.418 | |
| Dumuria | 0.88 [0.33–2.39] | 0.809 | 0.69 [0.26–1.77] | 0.436 | |
| Satkhira Sadar | 0.47 [0.14–1.56] | 0.216 | 0.22 [0.06–0.79] | 0.020 | |
| Tala | 0.36 [0.10–1.32] | 0.124 | 0.09 [0.02–0.49] | 0.005 | |
| Kalaroa | 0.98 [0.16–6.06] | 0.981 | 1.10 [0.22–5.41] | 0.908 | |
| aOR: adjusted odds ratio; CI: Confidence Interval. | |||||
| a adjusted for Educational Status, MDD-W, Toilet facility, Washed hand after toilet, Pregnancy trimester, Antenatal Care (ANC) Visit, Wealth Index, and Region. | |||||
Associated factors of anaemia among lactating women
Table 4 has depicted about the factors associated with anaemia among lactating women. Employment status was associated with moderate-to-severe anaemia; women who were employed had lesser likelihood of being anaemic (aOR: 0.06, 95%CI: 0.01–0.61, p = 0.017). Among the Lactating women, those who consumed foods from 5 or more food groups had 72% (aOR: 0.28, 95%CI: 0.12–0.65, p = 0.003) and 92% (aOR: 0.08, 95%CI: 0.02–0.36, p = 0.001) lower odds of being mildly and moderately or severely anaemic respectively. Mild anaemia was associated with hand washing before preparing foods; women who regularly washed hands had less likelihood (aOR: 0.37, 95%CI: 0.20–0.67, p = 0.001) of having mild anaemia compared to those who washed their hand occasionally. Furthermore, lactating women had a lower odd of being moderately or severely anaemic if they always washed their hands after toilet usage (aOR: 0.27, 95%CI: 0.09–0.78, p = 0.016). Media exposure reduced the possibilities of developing moderate or severe anaemia among the lactating women (aOR: 0.35, 95%CI: 0.15–0.85, p = 0.020). Both types of anaemia were negatively associated with the frequency of ANC visits and IFA intake. Lactating women who received 4 or more ANC visits during their past pregnancy were at 70% lower odds of being mildly (aOR = 0.30, 95%CI: 0.17–0.55, p < 0.001), and moderately or severely anaemic (aOR: 0.28, 95%CI: 0.13–0.58, p < 0.001). In terms of their IFA intake, those who consumed more than 90 tablets had 55% (aOR: 0.45, 95%CI: 0.25–0.79, p = 0.005) lower chance of having mild anaemia and 81% (aOR: 0.19, 95%CI: 0.09–0.39, p < 0.001) lower chance of having moderate or severe anaemia. Lactating women who resided in Rangabali (aOR: 0.14, 95%CI: 0.04–0.50, p = 0.003), Galachipa (aOR: 0.24, 95%CI: 0.08–0.71, p = 0.01), Dumuria (aOR: 0.24, 95%CI: 0.09–0.61, p = 0.003), Kalaroa (aOR: 0.16, 95%CI: 0.03–0.82, p = 0.028) had lower odds of having mild anaemia. On the other hand, lactating women who had greater chance of developing moderate or severe anaemia belonged to Rangabali (aOR: 0.19, 95%CI: 0.05–0.81, p = 0.024), Dumuria (aOR: 0.16, 95%CI: 0.05–0.58, p = 0.005). Conversely, non-muslim lactating women had a 3.8 (aOR: 3.75, 95%CI: 1.26–11.22, p = 0.018) times higher likelihood of having moderate-to-severe anaemia than muslim women. Besides, lactating women of middle wealth quintile had 3.3 times (aOR: 3.26, 95%CI: 1.35–7.89, p = 0.009) higher odds of being mildly anaemic.
| Characteristics | Mild Anaemia | Moderate/severe Anaemia | |||
|---|---|---|---|---|---|
| aOR [95%CI] | P-Value | aOR [95%CI] | P-Value | ||
| Educational Status | |||||
| Primary | Reference | Reference | |||
| Secondary | 0.90 [0.41–1.99] | 0.803 | 0.58 [0.23–1.46] | 0.246 | |
| Higher | 0.95 [0.34–2.65] | 0.926 | 0.74 [0.22–2.43] | 0.618 | |
| Employment status | |||||
| Unemployed | Reference | Reference | |||
| Employed | 0.64 [0.22–1.84] | 0.407 | 0.06 [0.01–0.61] | 0.017 | |
| Religion | |||||
| Muslim | Reference | Reference | |||
| Non-Muslim | 2.18 [0.92–5.14] | 0.076 | 3.75 [1.26–11.22] | 0.018 | |
| Family members | |||||
| < 5 members | Reference | Reference | |||
| ≥ 5 members | 1.40 [0.75–2.60] | 0.287 | 0.88 [0.42–1.83] | 0.725 | |
| MDD-W | |||||
| < 5 food group | Reference | Reference | |||
| ≥ 5 food groups | 0.28 [0.12–0.65] | 0.003 | 0.08 [0.02-.0.36] | 0.001 | |
| Toilet facility | |||||
| Unimproved | Reference | Reference | |||
| Improved | 1.01 [0.56–1.82] | 0.975 | 0.72 [0.35–1.46] | 0.363 | |
| Washed hand before food preparation | |||||
| Occasional | Reference | Reference | |||
| Always | 0.37 [0.20–0.67] | 0.001 | 0.78 [0.37–1.65] | 0.515 | |
| Washed hand after toilet | |||||
| Occasional | Reference | Reference | |||
| Always | 0.72 [0.27–1.91] | 0.514 | 0.27 [0.09–0.78] | 0.016 | |
| Media exposure | |||||
| No | Reference | Reference | |||
| Yes | 0.72 [0.33–1.57] | 0.405 | 0.35 [0.15–0.85] | 0.020 | |
| Antenatal Care (ANC) Visit | |||||
| 1–3 times | Reference | Reference | |||
| 4 + times | 0.30 [0.17–0.55] | < 0.001 | 0.28 [0.13–0.58] | 0.001 | |
| IFA intake | |||||
| IFA ≤ 90 | Reference | Reference | |||
| IFA > 90 | 0.45 [0.25–0.79] | 0.005 | 0.19 [0.09–0.39] | < 0.001 | |
| Wealth Index | |||||
| Poorest | Reference | Reference | |||
| Poorer | 1.24 [0.51–3.05] | 0.634 | 0.64 [0.21–1.94] | 0.427 | |
| Middle | 3.26 [1.35–7.89] | 0.009 | 2.05 [0.70–6.05] | 0.192 | |
| Richer | 1.83 [0.70–4.79] | 0.221 | 2.87 [0.93–8.89] | 0.067 | |
| Richest | 1.61 [0.58–4.52] | 0.363 | 2.72 [0.79–9.37] | 0.113 | |
| Region | |||||
| Patuakhali Sadar | Reference | Reference | |||
| Rangabali | 0.14 [0.04–0.50] | 0.003 | 0.19 [0.05–0.81] | 0.024 | |
| Galachipa | 0.24 [0.08–0.71] | 0.01 | 0.33 [0.09–1.16] | 0.083 | |
| Batiaghata | 2.51 [0.49–12.78] | 0.268 | 2.31 [0.28–18.79] | 0.435 | |
| Dumuria | 0.24 [0.09–0.61] | 0.003 | 0.16 [0.05–0.58] | 0.005 | |
| Satkhira Sadar | 0.29 [0.07–1.21] | 0.089 | 0.36 [0.05–2.52] | 0.306 | |
| Tala | 0.45 [0.16–1.25] | 0.126 | 0.69 [0.20–2.44] | 0.568 | |
| Kalaroa | 0.16 [0.03–0.82] | 0.028 | 0.39 [0.07–2.18] | 0.282 | |
| aOR: adjusted odds ratio; CI: Confidence Interval. | |||||
| a adjusted for Educational status, employment status, religion, family members, MDD-W, toilet facility, washed hand before food preparation, washed hand after toilet, media exposure, antenatal care (ANC) visit, IFA intake, wealth index, and region. | |||||
Anaemia is still a major cause for public health concern in Bangladesh. The current study aimed to determine the prevalence of anaemia among adolescent, pregnant and lactating women in south coastal region of the country. It additionally investigated the potential factors of anaemia among these population group. Prevalence of anaemia were found among 38% of adolescent girls, 50% of pregnant and 46% of lactating women. We found the percentage of mild anaemia was 23%, 25% and 28% among adolescent girls, pregnant and lactating women respectively. Pregnant and lactating women had higher rate of moderate/severe form of anaemia than the adolescent girls. Above findings also aligned with to the Bangladesh Demographic and Health Survey (BDHS) 2011 [10].
Among Bangladeshi women, sociodemographic characteristics play a significant role in determining anaemia. Higher levels of education are likely to result in socioeconomic benefits like healthier dietary habits and health care since there is a lack of qualified workforce. Maternal anaemia was found to be substantially correlated with education (p = 0.002), income (p = 0.001), and dwelling area (p = 0.031) in a prior study conducted in the city of Dhaka [17]. Since participants in our study who lived in Rangabali, Dumiria, Tala, and Sathkhira Sadar in particular showed a lower risk of anaemia than those in other regions, we can infer that geographic location is a significantly vital factor in the development of anaemia. Similarly, the educational level can influence health care concerns and dietary intake among people, which may help to reduce anaemia prevalence, particularly in pregnant women. Women with lower education may have less access to prenatal and postnatal healthcare, making them more vulnerable to comorbid conditions like anaemia [18]. An earlier study conducted in Bangladesh revealed that women with no formal education were more likely to be anaemic than those with secondary or higher education (p < 0.01). [8]. However, our study found that pregnant women with higher levels of education had a greater odd of having anaemia than pregnant women with lower levels of education. The current study showed that, in contrast to earlier research, pregnant women with higher wealth indices had a higher likelihood of developing anaemia than pregnant women with lower wealth indices. People from wealthy households may have frequent access to expensive junk food and develop unhealthy eating habits which is also positively correlated with rise in income levels. Numerous research outcome [3, 19, 20] demonstrated how economic factors affect anaemia. In our study, anaemia in adolescent girls and lactating women was not significantly correlated with income index. Nevertheless, another factor that has been linked to anaemia in women is employment. In line with a previous study [16, 21], our study found that lactating mothers who were employed had lower odds of having anaemia.
The mass media is regarded as a valuable resource for learning more about health-related programs that has improved women's access to health care, increased their understanding of nutrition, and encouraged them to eat diversified nutritious diet [22, 23]. The current study noted lower risk of moderate/severe anaemia among adolescent girls and lactating women who were exposed to mass media. The importance of mass media was also acknowledged in the earlier studies in reducing the risk of anaemia [22, 24]. Moreover, the present study found that adolescent girls who had a family size of five and more were more likely to have moderate/severe anaemia, which is consistent with earlier study [25, 26]. This might be due to the low care per family member in the large family resulting from the income constraint to obtain diets with variety of food rich in micronutrients such as iron [25].
According to our study, non-muslim adolescent girls and lactating women showed significantly higher risk of having mild anaemia and moderate/severe anaemia than the muslim women, which was consistent with another study conducted in Bangladesh [8], and India [19] but no significant association was found in Nepal [27]. This difference of anaemia across the religion may be due to different dietary practices and food taboos [19]. The availability of dietary iron may vary in certain religious groups due to specific belief systems in food consumption which restricts their intake of iron rich foods [28]. The majority of non-muslims in Bangladesh are Hindus, and most of them follow a vegetarian diet. In contrast, muslims in this country consume more foods from animal source than non-muslims.
During pregnancy, anaemia can act as a risk factor and impose life threatening consequences on mother as well as the fetus [29]. This is likely because of the growing need for iron as the pregnancy develops and the depletion of iron reserves in the majority of the women during the second and third trimesters [30]. During pregnancy, particularly after the first trimester, there is a need for the maternal blood volume to expand for supporting fetal growth. A previous study found that the prevalence of moderate-to-severe anaemia increased significantly after 5 months of gestation and the risk amplifies in the later stages of pregnancy [24]. In the present study, women in second and third pregnancy trimester were more likely to be anaemic which aligns with earlier studies conducted in Bangladesh [17], Cameroon [31], Ethiopia [32]. The current study found that pregnant and lactating women who received antenatal care (ANC) four or more times during their pregnancy had a lower risk of being anemic, which is consistent with earlier studies [31, 33]. This may be due to routine diagnosis of anaemia during the ANC visit, scheduled counselling on nutrition related knowledge, supplementation and treatment [31]. We also found a negative association between iron and folic acid (IFA) intake with anaemia among lactating women during their preceding pregnancy. A study conducted in India found that IFA supplementation was similarly inversely related to the incidence of anaemia, with a regular use of IFA or folic acid supplements in the preceding trimester leading to a 74% decreased risk of anaemia (OR: 0.26, p = 0.001) [34]. It is strongly recommended by WHO for daily supplementation of oral iron and folic acid to reduce the risk of anaemia during pregnancy and prevent the occurrence of low birth weight [2].
Water, Sanitation, and Hygiene (WASH) practices are considered one of the interventions for the prevention and control of anaemia [35]. Particularly in Bangladesh due to the tropical temperature, not washing hands properly after excretion, before preparing meals or consuming food, and using unsanitary latrines could result in gastrointestinal parasitic infestation [8, 22, 36–38]. Poor general health and/or chronic blood loss through gastrointestinal parasite infestation can be possibly considered for the association of unhygienic practice of using toilets with developing anaemia [8]. A previous study finding showed that anaemia was prevalent among the adolescent girls as around 32% of which 39.52% anaemic girls were infected with intestinal parasites compared to the 30.63% non-anaemic cases [37]. A multi-country study among women of reproductive age in Bangladesh, Maldives and Nepal found that access to safe drinking water (such as tap water and tube wells) was discovered to be a slenderly protective factor for lowering the cases of anaemia among women in Nepal and Bangladesh [15]. Our present study also found that frequent handwashing after the toilet, and before preparing foods reduced the risk of anaemia among pregnant and lactating women.
Inappropriate eating habits may contribute to the development of anaemia where low dietary diversity plays a significant role. In our study, anaemia among pregnant and lactating women was linked to the consumption of low-diversified diet which was consistent with earlier study [31, 32]. The physiological state of high demanding nutrient during pregnancy and lactation period suggested women to consume a diversified diet to achieve nutrient adequacy to prevent the development of micronutrient deficient anaemia [32]. Unlike with other studies conducted in India, and Kenya [36, 39], anaemia was not significantly associated with dietary diversity. It might be due to the presence of lower rate of anaemia among adolescent girls.
However, the study has some limitations, including the inability to diagnose iron deficiency anemia due to the lack of data on absolute dietary iron consumption or serum ferritin levels. Being cross-sectional in nature, the data should be utilized with caution while interpreting the temporal association between the socio-demographics and anemia. Additionally, we did not collect information on further health issues including a family history of thalassemia, a malaria infection, an obstetrical issue, helminth infections, etc. Our understanding would be improved by supplementary research on these topics, therefore greater investigation peeking into the causes of anemia is required in order to identify the most appropriate measures. Attention must be paid to the high prevalence of anaemia in adolescent girls, pregnant and lactating women. To improve the status of anaemia in these vulnerable populations in the southern area of Bangladesh, dietary diversity, supplementation with multiple micronutrient, and social behavior change communication should be advocated.
Our study acknowledges the grave importance of addressing anaemia as a major health concern among the adolescent girls, pregnant and lactating women in Bangladesh. The lack of dietary diversity, higher educational attainment, infrequent antenatal care, lower intake of IFA, pregnancy trimester, non-muslim religion and irregular WASH practices contribute to the development of anaemia. Even though the national strategy to control and prevent anaemia in Bangladesh encompasses a wide range of interventions, yet the implementation lacks strategic grounds. Thus, it is essential to understand the gap and introduce effective sustainable solutions considering it’s contributing factors along with running massive supplementation programs and awareness campaigns.
AIDS- Acquired Immune Deficiency Syndrome, ANC- Antenatal Care, BDHS- Bangladesh Health and Demographic Survey, G6PD- Glucose-6-Phosphate Dehydrogenase, Hb- Hemoglobin, IDA- Iron Deficiency Anaemia, IFA- Iron and Folic Acid Supplementation, LMIC- Low- and Middle-Income Countries, MDD-W- Minimum Dietary Diversity Women, RBC- Red Blood Cell, WASH- Water Sanitation and Hygiene, WHO- World Health Organization
Acknowledgments
The study was conducted in collaboration with Max Foundation, Bangladesh. We acknowledge with gratitude the commitment of all investigators from all of the collaborating organization. icddr,b is also grateful to the Governments of Bangladesh, Canada, Sweden, and the UK for providing core support.
Author contributions
The authors’ responsibilities were as follows: GA, RH, ABB, AHA, HR and ZI; Conceptualization, Funding acquisition, Investigation, Resources, Methodology, GA, ABB, AHA, and HR; Project administration, Supervision, Validation, GA, ABB, AHA, RH, and SDA; Data curation, Formal Analysis, Software; GA, RH, SDA and AHA; Writing – original draft GA, RH, SDA, KSK AHA, RIM, KAI, HR and ZI; Writing – review & editing. All authors read and approved the final manuscript.
Funding
The research project was supported Max Foundation, Bangladesh. The funder was not involved with the data collection or data analysis.
Conflicts of interest
The authors report no conflicts of interest.
Data Availability
The data described in the manuscript will be made available as per reasonable request to the corresponding authors.
- Sunuwar, D.R. et al. Prevalence and factors associated with anemia among women of reproductive age in seven South and Southeast Asian countries: Evidence from nationally representative surveys. PLoS ONE15, e0236449. https://doi.org/10.1371/journal.pone.0236449 (2020).
- World Health Organization. Global nutrition targets 2025: anaemia policy brief (WHO/NMH/NHD/14.4). WHO (2014).
- Balarajan, Y., Ramakrishnan, U., Özaltin, E., Shankar, A. H. & Subramanian, S.V. Anaemia in low-income and middle-income countries. The Lancet 378, 2123-2135. https://doi.org/10.1016/s0140-6736(10)62304-5 (2011).
- Mistry, S.K. et.al. An outline of anemia among adolescent girls in Bangladesh: findings from a cross-sectional study. BMC Hematol.17, 13. https://doi.org/10.1186/s12878-017-0084-x (2017).
- Tolentino, K. & Friedman, J. F. An update on anemia in less developed countries. Am J Trop Med Hyg. 77, 44–51. https://doi.org/10.4269/ajtmh.2007.77.44 (2007).
- World Health Organization. Worldwide prevalence of anaemia 1993-2005: WHO global database on anaemia. Geneva:WHO. https://apps.who.int/iris/handle/10665/43894 (2008).
- Gautam, S., Min, H., Kim, H. & Jeong, H.S. Determining factors for the prevalence of anemia in women of reproductive age in Nepal: Evidence from recent national survey data. PLoS ONE14, e0218288. https://doi.org/10.1371/ journal.pone.0218288 (2019).
- Kamruzzaman, M., Rabbani, M.G., Saw, A., Sayem, M.A. & Hossain, M.G. Differentials in the prevalence of anemia among non-pregnant, ever-married women in Bangladesh: multilevel logistic regression analysis of data from the 2011 Bangladesh Demographic and Health Survey. BMC Women's Health15, 54. https://doi.org/10.1186/s12905-015-0211-4 (2015).
- Rahman, S. et al. Determinants of iron status and Hb in the Bangladesh population: the role of groundwater iron. Public Health Nutr. 19, 1862-1874. https://doi.org/10.1017/S1368980015003651 (2016).
- National Institute of Population Research and Training (NIPORT), Mitra and Associates, & ICF International. Bangladesh Demographic and Health Survey 2011. Dhaka, Bangladesh and Calverton, Maryland, USA: NIPORT, Mitra and Associates, and ICF International. https://dhsprogram.com/pubs/pdf/fr265/fr265.pdf (2013).
- International Centre for Diarrheal Disease Research Bangladesh (icddr,b), United Nations Children’s Fund (UNICEF), Global Alliance for Improved Nutrition (GAIN), & Institute of Public Nutrition. National Micronutrients Status Survey 2011–12, Final Report. Dhaka, Bangladesh: Centre for Nutrition and Food Security, icddr,b. http://www.icddrb.org/what-we-do/publications/cat_view/52-publications/10043-icddrb-documents/10058-icddrb-reports-and-working-papers/14275-survey-reports (2013).
- Ara, G. et.al. Effectiveness of micronutrient-fortified rice consumption on anaemia and zinc status among vulnerable women in Bangladesh. PLoS ONE14, e0210501. https://doi.org/10.1371/journal.pone.0210501 (2019).
- FAO. Minimum dietary diversity for women. Rome. https://doi.org/10.4060/cb3434en (2021).
- Vyas, S. & Kumaranayake, L. Constructing socio-economic status indices: how to use principal components analysis. Health policy and planning21, 459-468. https://doi.org/10.1093/heapol/czl029 (2006).
- Rahman, M.A. et al. Prevalence of and factors associated with anaemia in women of reproductive age in Bangladesh, Maldives and Nepal: Evidence from nationally-representative survey data. PLoS ONE16, e0245335. https://doi.org/10.1371/journal.pone.0245335 (2021).
- Lakew, Y., Biadgilign, S. & Haile, D. Anaemia prevalence and associated factors among lactating mothers in Ethiopia: evidence from the 2005 and 2011 demographic and health surveys. BMJ Open5, e006001. https://doi.org/10.1136/bmjopen-2014- 006001 (2015).
- Chowdhury, H.A. et al. Factors associated with maternal anaemia among pregnant women in Dhaka city. BMC Women's Health15, 77. https://doi.org/10.1186/s12905-015-0234-x (2015).
- Ickes, S.B., Hurst, T.E. & Flax, V.L. Maternal literacy, facility birth, and education are positively associated with better infant and young child feeding practices and nutritional status among Ugandan children. The Journal of Nutrition145, 2578-2586. https://doi.org/10.3945/jn.115.214346 (2015).
- Lokare, P.O., Karanjekar, V.D., Gattani, P.L. & Kulkarni, A.P. A study of prevalence of anemia and sociodemographic factors associated with anemia among pregnant women in Aurangabad city, India. Ann Nigerian Med. 6, 30-4. https://doi.org/10.4103/0331-3131.100213 (2012).
- Bharati, P., Som, S., Chakrabarty, S., Bharati, S. & Pal, M. Prevalence of Anemia and Its Determinants Among Nonpregnant and Pregnant Women in India. Asia Pacific Journal of Public Health20, 347-359. https://doi.org/10.1177/10105395083227 (2008).
- Abdelbagi, O.M., Hassan, B., Eltayeb, R., ALhabardi, N. & Adam, I. Prevalence of anaemia and its associated factors among lactating mothers in eastern Sudan: a cross-sectional study. Transactions of The Royal Society of Tropical Medicine and Hygiene116, 1123-1128. https://doi.org/10.1093/trstmh/trac037 (2022).
- Keokenchanh, S. et al. Prevalence of anemia and its associate factors among women of reproductive age in Lao PDR: evidence from a nationally representative survey. Anemia2021. https://doi.org/10.1155/2021/8823030 (2021).
- Chourasia, A., Pandey, C.M. & Awasthi, A. Factors influencing the consumption of iron and folic acid supplementations in high focus states of India. Clinical Epidemiology and Global Health5, 180-184. https://doi.org/10.1016/j.cegh.2017.04.004 (2017).
- Perumal, V. Reproductive risk factors assessment for anaemia among pregnant women in India using a multinomial logistic regression model. Tropical Medicine & International Health19, 841-851. https://doi.org/10.1111/tmi.12312 (2014).
- Tesfaye, M., Yemane, T., Adisu, W., Asres, Y. & Gedefaw, L. Anemia and iron deficiency among school adolescents: burden, severity, and determinant factors in southwest Ethiopia. Adolesc Health Med Ther.6, 189-196. https://doi.org/10.2147/AHMT.S94865 (2015).
- Tirore, L.L. et al. Factors associated with anaemia among women of reproductive age in Ethiopia: Multilevel ordinal logistic regression analysis. Maternal & Child Nutrition17, e13063. https://doi.org/10.1111/mcn.13063 (2021).
- Harding, K.L., Aguayo, V.M., Namirembe, G. & Webb, P. Determinants of anemia among women and children in Nepal and Pakistan: An analysis of recent national survey data. Maternal & Child Nutrition14, e12478. https://doi.org/10.1111/mcn.12478 (2018).
- Madjdian, D.S., Azupogo, F., Osendarp, S.J., Bras, H. & Brouwer, I.D. Socio‐cultural and economic determinants and consequences of adolescent undernutrition and micronutrient deficiencies in LLMICs: a systematic narrative review. Annals of the New York Academy of Sciences1416, 117-139. https://doi.org/10.1111/nyas.13670 (2018).
- Pappas, G., Akhtar, T., Gergen, P.J., Hadden, W.C. & Khan, A.Q. Health status of the Pakistani population: a health profile and comparison with the United States. American journal of public health91, 93-98. https://doi.org/10.2105/ajph.91.1.93 (2001).
- Barrett, J.F., Whittaker, P.G., Williams, J.G. & Lind, T. Absorption of non-haem iron from food during normal pregnancy. Bmj309, 79-82. https://doi.org/10.1136/bmj.309.6947.79 (1994).
- Jugha, V. T., Anchang-Kimbi, J. K., Anchang, J. A., Mbeng, K. A. & Kimbi, H. K. Dietary Diversity and Its Contribution in the Etiology of Maternal Anemia in Conflict Hit Mount Cameroon Area: A Cross-Sectional Study. Front Nutr.7, 625178. https://doi.org/10.3389/fnut.2020.625178 (2021).
- Lebso, M., Anato, A. & Loha, E. Prevalence of anemia and associated factors among pregnant women in Southern Ethiopia: A community based cross-sectional study. PLoS ONE12, e0188783. https://doi.org/10.1371/journal.pone.0188783 (2017).
- Mihiretu, A. Factors associated with anemia among lactating mothers in subsistence farming households from selected districts of Jimma zone, south western Ethiopia: a community based cross-sectional study. Journal of Nutrition and Food Sciences7, 595. https://doi.org/10.4172/2155-9600.1000595 (2017).
- Varghese, J. S., Swaminathan, S., Kurpad, A. V. & Thomas, T. Demand and supply factors of iron-folic acid supplementation and its association with anaemia in North Indian pregnant women. PLoS ONE14, e0210634. https://doi.org/10.1371/journal.pone.0210634 (2019).
- Gautam, S., Min, H., Kim, H. & Jeong, H. S. Determining factors for the prevalence of anemia in women of reproductive age in Nepal: Evidence from recent national survey data. PLoS ONE14, e0218288. https://doi.org/10.1371/journal.pone.0218288 (2019).
- Siva, P. M., Sobha, A. & Manjula, V. D. Prevalence of Anaemia and Its Associated Risk Factors Among Adolescent Girls of Central Kerala. J Clin Diagn Res.10, LC19–LC23. https://doi.org/10.7860/JCDR/2016/20939.8938 (2016).
- Banu, H., Khanum, H. & Hossain, M.A. Relationships between anaemia and parasitic infections in adolescent girls of Bangladesh. Bangladesh Journal of Zoology42, 91-103. https://doi.org/10.3329/bjz.v42i1.23340 (2014).
- Kothari, M. T. et al. Exploring associations between water, sanitation, and anemia through 47 nationally representative demographic and health surveys. Ann N Y Acad Sci.1450, 249–267. https://doi.org/10.1111/nyas.14109 (2019).
- Nelima, D. Prevalence and determinants of Anaemia among adolescent girls in secondary schools in Yala division Siaya District, Kenya. Universal Journal of Food and Nutrition Science3, 1-9. https://doi.org/10.13189/ujfns.2015.030101 (2015).
No competing interests reported.