Prevalence and factors associated with Iron deficiency anaemia among children aged 6-23 months in southwestern Uganda.

doi:10.21203/rs.3.rs-2742978/v2

Download PDF

Research Article

Prevalence and factors associated with Iron deficiency anaemia among children aged 6-23 months in southwestern Uganda.

https://doi.org/10.21203/rs.3.rs-2742978/v2

This work is licensed under a CC BY 4.0 License

Version 2

posted

You are reading this latest preprint version

Iron deficiency anemia is still a global public health concern with the highest burden among children 6 to 23 months due to their rapid growth spurt exceeding breastmilk supply. Therefore, nutritional supply is a key source of iron to attain the required nutrients for better growth and development.

This was a cross-sectional descriptive study done at Ishaka Adventist Hospital (IAH) and Kampala International University Teaching Hospital (KIUTH) from April to July 2022. Participants were consecutively enrolled in the study. Structured questionnaires, 24-hour dietary recall, and clinical assessment were used to obtain data. Data analysis was done using the Statistical Package for Social scientists (SPSS) V22.0. Bivariable and multivariable analysis was done using logistic regression for associations with significance set at P-value <0.05.

A total of 364 participants were enrolled, with majority males 198(54.4%) and born at term 333(91.5%). The modal age was 12-17 months [163(44.8%)] with a mean age of 14.1 months (SD 5.32). The overall prevalence of IDA was 151/364 (41.5%). The factors associated with IDA included male sex (aOR 1.61), current episode of diarrhoea (aOR 1.71), poor meal frequency (aOR 1.78), no vegetable consumption (aOR 2.47) and consuming fruits once (aOR 1.97) in 7 days preceding the study.

The study finds a high prevalence of IDA among infants 6-23 months with at least four in 10 being affected. Screening for IDA should be recommended in male children with current diarrhea, poor intake of fruits and vegetables, and poor meal frequency. The Mentzer index is an equally good alternative screening test for IDA.

Pediatrics

anemia

iron deficiency

Mentzer index

Iron deficiency (ID) is the commonest micronutrient deficiency worldwide. It affects over 42% of all children (Özdemir, 2015; WHO, 2013) in both developed and developing countries. In Europe, ID prevalence ranges between 2% to 9%, while in the USA, it varies from 6.6% to 15.2% for ID and from 0.9% to 4.4% for iron deficiency anaemia (IDA) for children aged1-3 years(Hernell et al., 2015). The African region is greatly affected with about 60% of children under 5 years anaemic with 50% due to ID. Sub-saharan Africa has a prevalence of 52% for ID with a range of 56.8%- 62.5% (Fufa & Gutema, 2019; Muriuki et al., 2020).

In Uganda, there has been a general decline in anaemia prevalence among children under 5 years from 64% in 2000 to 53% in 2016(UBOS, 2016). Despite the decline, it’s still ranked by World Health Organisation (WHO) as a severe public health concern and children less than 24 months are the most affected (greater than 70% prevalence )(GAIN and UNICEF., 2019; Menon & Yoon, 2015).

IDA is caused by inadequate dietary intake in the face of rapid growth, highly marked nutrient loss, impaired absorption, or altered nutrient metabolism (Chaparro & Suchdev, 2019; Jennifer, 2020). It may cause permanent disruption in the mental and motor functioning of the children affected. These include learning difficulties, pseudotumor cerebri, sleep disturbance, sixth nerve palsy, breath-holding spells, deficit in attention, disorders in behaviour, reduction in perception, retardation in developmental tests both in mental and motor, and reduced auditory and visual functions. These effects can persist for over 12 years even after treatment(Betsy et al., 2000; Özdemir, 2015). Prevention of premature delivery, exclusive breastfeeding during the first 6 months, provision of safe and iron-rich complementary foods from 6 months through 2 years, and avoiding whole cow's milk in the first 12 months are key strategies for the prevention of IDA(Beatrice et al., 2019; Faraj et al., 2017; Özdemir, 2015).

Unfortunately, biomarkers for ID diagnosis like serum ferritin are not routinely available and affordable in developing countries(Sazawal et al., 2014). RDW and Mentzer index are indices that have been identified as valid surrogates in the detection of IDA(SriLestari et al., 2014; Wang, 2016). RDW is a measure of the heterogenicity of red cell size currently generated by automated blood cell counters (Mukesh et al., 2015). It is regarded as a cost-effective and sensitive test to differentiate iron deficiency anaemia from other types of microcytic anaemia if ferritin and iron studies are not available (Jennifer, 2020; Wang, 2016). Studies have found that when compared with serum ferritin, RDW in the presence of microcytosis had a sensitivity of 82.3% - 99%, specificity of 69.4% - 90%, positive predictive value of 73% - 90.5%, negative predictive value of 73% - 98.9%. and accuracy of 73% - 75% (Krawiec & Pac-Kozuchowska, 2020; Purnamasidhi et al., 2019; Sarah et al., 2018; Sazawal et al., 2014; Zafar et al., 2019). Its increase is considered the earliest haematological manifestation of IDA(Sazawal et al., 2014)

On another hand, Mentzer index, which is the mean corpuscular volume divided by red cell count, has also been suggested as a valid test for IDA screening in developing countries with a value >13 suggestive of IDA (Garg et al., 2016; SriLestari et al., 2014; WHO, 2011). When compared with serum ferritin, it has a sensitivity of 93% and a specificity of 84%(SriLestari et al., 2014). This study, therefore, determined the prevalence and factors associated with iron deficiency anaemia among children 6-23 months and compared the relationship between the Mentzer index and the combination of RDW in the presence of microcytosis in the diagnosis of IDA.

Study area:

The study was carried out at IAH and KIUTH located in Bushenyi-Ishaka municipality, Bushenyi district, Southwestern Uganda. IAH is a mission hospital under the Seventh-day Adventist Church while KIUTH is a private hospital owned by Kampala International University. Bushenyi-Ishaka municipality is situated 358 km west of Kampala, the capital city of Uganda. The majority of the indigenous residents are subsistence farmers and small-scale business owners.

Research design and methodology

The study was a hospital-based descriptive cross-sectional study using a quantitative study design. It was carried out from April – July 2022. Inclusion criteria were children 6-23 months and caregivers who consented to the study. Children who had received blood transfusion 3 months before the study and iron supplementation within a month prior to the study were excluded. The sample size was calculated using the Kish Leslie formula (1965), N=P (1-P)/d2, where N is the sample size; P is the expected prevalence; and d is the margin of error. The sample size of 364 participants was based on the prevalence of 36.6% in Amuria, eastern Uganda(Nicole et al., 2020). Using consecutive enrolment, children 6- 23 months were enrolled in the study from the respective outpatient and in-patient departments until the required sample size was obtained. Caregivers were given explanations about the study protocols and informed consent was obtained. Age was confirmed using the child’s date of birth and for those who came with child health cards, the age was verified from the cards. A questionnaire was used to collect information about demographic information (age, sex, gestation, age at birth, weight, length, maternal age, and occupation), medical factors, dietary factors, and use of blood boosters, particularly iron supplements.

From each child, 2 milliliters of venous blood were collected into an EDTA-containing vacutainer after disinfecting the skin area with an alcohol swab. The sample was immediately transported to the lab where an automated coulter counter (BC 3000 Plus Mindray Auto Haematology Analyzer, Shenzhen, China) was used to perform a complete blood cell count (CBC).

Anaemia status was defined as haemoglobin (Hb) of less than 11.0 g/dl for ages 6 months to 59 months. It was classified as mild (10-10.9g/dl), moderate (7.0-9.9g/dl) and severe (< 7.0g/dl) (Ocan et al., 2018; WHO, 2015) as recommended by WHO. The Mentzer index was derived by dividing the mean cell volume by red cell blood count as obtained in CBC. A Mentzer index value of > 13 in the presence of haemoglobin concentration less than 11g/dl was suggestive of iron deficiency anaemia. (WHO, 2011). Additionally, microcytosis was determined by the mean corpuscular volume of <74Fentoliters or on a peripheral film if the mean corpuscular volume (MCV) was normal or high (Mccarthy et al., 2017; Simbauranga et al., 2015). Thus, IDA was diagnosed as Hb<11g/dl, with RDW >14 in the presence of microcytosis or Mentzer index >13 with Hb<11g/dl. All tests were done from KIUTH laboratory.

Ethics approval and consent of participants

The research study followed the declaration of Helsinki of 1964. Ethical Approval was obtained from the Kampala International University-western campus Research Ethics committee with a registration number KIU-2021-56. Institutional consent was sought and informed consent for the infants was obtained from the parents/ legal guardians before enrolment to the study.

Data Analysis

Descriptive analysis using frequencies and percentages was used to analyze independent and dependent variables using SPSS version 22.0. The association between independent and dependent variables was determined using binary logistic regression for both bivariable and multivariable analysis with p-value significance set at <0.05. The relationship between the Mentzer index and RDW in the presence of microcytosis was established using the Spearman correlation coefficient. The test of significance was determined at a P - value of 0.05.

Study participants:

Children attending care at IAH and KIUTH were enrolled in the study between April and July 2022. The study profile is shown in Figure 1.

Baseline characteristics

A total of 364 caregiver-child pairs were enrolled in the study. Majority of the participants were males 196(53.8%), born at term 333(91.5%) with a birthweight of ≥2.5kg 326(89.6%). The modal age was 12-17 months of age, 163 (44.8%) with a mean age of 14 months (skewness 0.048, SD 5.32) and the caregivers were mostly 21-30 years of age 248(68.1%) with the highest level of education being tertiary 147(40.4%) and 101(27.7%) were formally employed. This is shown in Table 1.

Table 1: Socio- demographic characteristics of children aged 6-23 months and their caregivers attending KIUTH and IAH, Bushenyi- Ishaka municipality.

Variables		Frequency (%)	Percentage
Age	6-11 months	113	31.0
	12-17 months	163	44.8
	18-23 months	88	24.2
Sex	female	168	46.2
	male	196	53.8
Gestation age at birth	Premature	31	8.5
	Term	333	91.5
Birth weight	<2.5kg	38	10.4
	≥2.5kg	326	89.6
Maternal age	≤20	14	3.8
	21-30	248	68.1
	31-40	90	24.7
	>40	12	3.3
Maternal level of education	At most primary	111	30.5
	secondary	106	29.1
	tertiary	147	40.4
Maternal occupation	housewife	79	21.7
	formal employment	101	27.7
	business	77	21.2
	peasant	107	29.4

Prevalence of anaemia and iron deficiency anaemia among study participants

Among the study participants, 55.2% (201/364) had anaemia with haemoglobin <11g/dl, and 44.5% (151/364) participants had iron deficiency anaemia. Three- quarters (75.1% (151/201)) of anaemia was due to ID.

Severity of anaemia and IDA among the study participants with anaemia

Most participants with IDA had moderate anaemia 78(51.7%) followed with those having mild anaemia 57(37.7%) while those with non-IDA had majority with mild anaemia 27(54%). This is shown in Table 2.

Table 2: A table showing the severity of anaemia and iron deficiency anaemia among study participants

*SEVERITY*	*IDA*	*Non- IDA (%)*	*Total (%) N=201*
*Mild*	57(37.7)	27(54)	84(41.8)
*Moderate*	78(51.7)	13(26)	91(45.3)
*Severe*	16(10.6)	10(20)	26(12.9)

Factors associated with IDA

At bivariable analysis, male sex (cOR1.65), vegetable consumption in the last 7 days (cOR 2.50), fruit in the 7 days preceding the study (cOR 1.81), acceptable meal frequency (cOR 1.38) and having a current episode of diarrhoea (cOR 1.68) were statistically associated with IDA. Poor dietary diversity was noted to increase the chances of having IDA by 1.076 times compared to those with good dietary diversity, however it was not statistically significant. The factors that were statistically significant at a bivariable level of analysis were subjected to multivariable logistic regression. This is as shown in Table 3.

At multivariable analysis, the male child had 61.2% (AOR 1.61(1.03-2.53), P 0.04) increased risk for IDA compared to females and was significant.

Having a current episode of diarrhoea was associated with 1.71 odds for IDA (AOR 1.71(1.03-2.82), P 0.04) compared to those without diarrhoea.

Not consuming vegetables and eating fruits once in the 7 days before the study was associated with 2.47 times (AOR 2.47(1.35-4.52), P 0.00) and 1.97 times (AOR1.97(1.11-3.52) P 0.02) increased risk for IDA respectively compared to their counterparts’ consumed vegetables or fruits more than 5 times in 7 days preceding the study.

Additionally, poor feeding frequency was associated with 78.1% higher odds (AOR 1.78(1.14-2.77), P 0.01) for IDA compared to those having a good dietary frequency and was statistically significant as shown in Table 3.

Table 3: Bivariable and multivariable logistic regression analysis for associated factors

Variable	IDA, frequency n (%)		cOR (95% C.I)	P-value	AOR (95% C.I)	P-value
Variable	No (%)	Yes (%)	cOR (95% C.I)	P-value	AOR (95% C.I)	P-value
Age (months)
6-11	68(31.9)	45(29.8)	1.22(0.68-2.17)	0.51
12-17	88(41.3)	75(49.7)	1.57(0.92-2.68)	0.10
18-23	57(26.8)	31(20.5)	Ref
Sex
Female	108(50.7)	58(38.4)	Ref		Ref
Male	105(49.3)	93(61.6)	1.65(1.08-2.52)	0.02	1.61(1.03-2.53)	0.04
Gestation age (at birth)
Premature	15(7.0)	16(10.6)	Ref
Term	198(93.0)	135(89.4)	0.64(0.31-1.34)	0.23
Birth weight (kg)
<2.5	19(8.9)	19(12.6)	Ref
≥2.5	194(91.1)	132(87.4)	0.68(0.35-1.33)	0.26
Maternal age (years)
≤20	11(5.2)	3(2.0)	0.38(0.07-2.13)	0.27
21-30	138(64.8)	110(72.8)	1.12(0.35-3.61)	0.86
31-40	57(26.8)	33(21.9)	0.81(0.24-2.76)	0.74
>40	7(3.3)	5(3.3)	Ref
Maternal level of education
Primary	67(31.5)	44(29.1)	1.01(0.61-1.67)	0.98
Secondary	57(26.8)	49(32.5)	1.32(0.80-2.19)	0.28
Tertiary	89(41.8)	58(38.4)	Ref
Maternal occupation
House wife	42(19.7)	37(24.5)	1.36(0.76-2.47)	0.30
Formal employment	64(30.0)	37(24.5)	0.90(0.51-1.57)	0.70
Business	42(19.7)	35(23.2)	1.29(0.71-2.33)	0.40
Peasant	65(30.5)	42(27.8)	Ref
Stunted*
No	149(70.0)	110(72.8)	Ref
Yes	64(30.0)	41(27.2)	1.09(0.82-1.44)	0.55
Wasted*
No	173(81.2)	120(79.5)	Ref
Yes	40(18.8)	31(20.5)	1.12(0.66-1.89)	0.68
HIV status
Negative	209(98.1)	143(94.7)	Ref
Positive	1(0.5)	3(2.0)	2.44(0.57-10.35)	0.23
Sero-exposed	3(1.4)	5(3.3)	4.39(0.45-42.57)	0.20
Pneumonia
No	171(80.3)	119(78.8)	Ref
Yes	42(19.7)	32(21.2)	1.10(0.65-1.83)	0.73
Current fever
No	138(64.8)	89(58.9)	Ref
Yes	75(35.2)	62(41.1)	1.28(0.84-1.97)	0.26
History of fever in last 2 weeks
No	108(50.7)	70(46.4)	Ref
Yes	105(49.3)	81(53.6)	1.19(0.78-1.81)	0.41
Current diarrhoea episode
No	169(79.3)	105(69.5)	Ref		Ref
Yes	44(20.7)	46(30.5)	1.68(1.04-2.72)	0.03	1.71(1.03-2.82)	0.04
Diarrhoea history in last 2 weeks
No	149(70.0)	114(75.5)	Ref
Yes	64(30.0)	37(24.5)	0.76(0.47-1.21)	0.24
Deworming in last 3 months
No	79(46.7)	59(48.8)	0.92(0.58-1.47)	0.74
Yes	90(53.3)	62(51.2)	Ref
Exclusive breastfeeding
≤6 months	194(91.1)	142(94.0)	0.65(0.28-1.47)	0.30
>6 months	19(8.9)	9(6.0)	Ref
Dietary diversity
Poor	135(63.4)	100(66.2)	1.08(0.83-1.40)	0.58
Good	78(36.6)	51(33.8)	Ref
Acceptable meal frequency
No	89(41.8)	84(55.6)	1.38(1.08-1.77)	0.01	1.78(1.14-2.77)	0.01
Yes	124(58.2)	67(44.4)	Ref		Ref
Dietary intake in the last 7 days
Meat
Never	71(33.3)	48(31.8)	0.68(0.21-2.22)	0.52
Once	61(28.6)	48(31.8)	0.79(0.24-2.60)	0.69
2-5 times	75(35.2)	49(32.5)	0.65(0.20-2.14)	0.48
>5 times	6(2.8)	6(4.0)	Ref
Fish
Never	132(62.0)	98(64.9)	2.04(0.63-6.60)	0.23
Once	45(21.1)	30(19.9)	1.83(0.53-6.30)	0.34
2-5 times	25(11.7)	19(12.6)	2.09(0.58-7.60)	0.26
>5 times	11(5.2)	4(2.6)	Ref
Vegetables
Never	40(18.8)	50(33.1)	2.50(1.44-4.35)	0.00	2.47(1.35-4.52)	0.00
Once	64(30.0)	44(29.1)	1.38(0.81-2.34)	0.24	1.41(0.80-2.47)	0.23
2-5 times	23(10.8)	14(9.3)	1.22(0.57-2.60)	0.61	1.15(0.52-2.55)	0.73
>5 times	86(40.4)	43(28.5)	Ref		Ref
Chicken
Never	170(79.8)	111(73.5)	3.92(0.47-32.99)	0.21
Once	24(11.3)	34(22.5)	8.50(0.96-75.23)	0.05
2-5 times	13(6.1)	5(3.3)	2.31(0.22-24.32)	0.49
>5 times	6(2.8)	1(0.7)	Ref
Fruits
Never	49(23.0)	37(24.5)	1.46(0.80-2.69)	0.22	1.10(0.57-2.14)	0.78
Once	75(35.2)	70(46.4)	1.81(1.05-3.11)	0.03	1.97(1.11-3.52)	0.02
2-5 times	29(13.6)	13(8.6)	0.87(0.40-1.90)	0.72	0.92(0.40-2.07)	0.83
>5 times	60(28.2)	31(20.5)	Ref		Ref

*- based on WHO child growth standards.

Comparison of Mentzer index with RDW in the presence of microcytosis in the diagnosis of iron deficiency anaemia

The prevalence of IDA using Mentzer index was 45.3% compared to the 41.5% prevalence using RDW and Microcytosis. Further analysis found a Spearman correlation coefficient of 0.521 (p<0.0001), suggesting a strong positive significant correlation between the two tests. This is summarised in Table 4.

Table 4: A comparative table for Mentzer index versus RDW plus microcytosis in the diagnosis of iron deficiency anaemia among the study participants

Diagnostic test	Prevalence of IDA
Hb<11g/dl + RDW>14 + microcytosis	41.5%
Hb<11g/dl + Mentzer Index >13	45.3%

Spearman correlation coefficient		0.521
P-value		0.000

The overall prevalence of IDA among the study participants was 44.5%. three -quarters (75.1%) of the anaemic participants it was due to iron deficiency. This can be attributed to the methods used in the diagnosis of IDA. This study employed a combination of red cell distribution, width, and microcytosis (on complete blood count and peripheral film) to derive the diagnosis. RDW is a simple and widely available test in routine haematological tests that measures the degree of the RBC size heterogenicity(Kai et al., 2021). It equally can express the smallest variation in red cell size which is accompanied by early iron deficiency unlike the other red cell indices (MCV, Mean corpuscular haemoglobin (MCH) and Mean corpuscular haemoglobin concentration (MCHC))(Sultana et al., 2011). There’s usually an overlap between patients with microcytic hypochromic anaemia in regard to red cell indices. This was observed in a study in Dhaka Shishu hospital where there was no significant difference between IDA and thalassemia regarding MCV, MCH, and MCHC. A difference, however, was noted with RDW with statistically significance (P < 0.000)(Tayab et al., 2021). RDW is a very sensitive measure that changes earliest in the presence of iron deficiency anaemia even before microcytosis(Özdemir, 2015). Thus, it’s a sensitive measure in differentiating IDA from other causes of microcytic anaemia. (Özdemir, 2015; Sazawal S, Dhingra U, Dhingra P, 2014; WHO, 2001). The peripheral film was considered as an earlier way for microcytosis before CBC mean corpuscular volume changes are observed. This further gives an earlier diagnosis of microcytic anaemia(Cheesbrough, 2009; Simbauranga et al., 2015). It's thus a recommended test in the absence of iron studies for the diagnosis of IDA(Tayab et al., 2021). This could be one of the reasons why the study findings were lower than that observed in Lacor hospital, Uganda at 65.4%(Ocan et al., 2018) and in Tanzania at 76% among children 6-23 months (Msaki et al., 2022) where the diagnosis of IDA was based on peripheral film and Hb levels respectively.

On another hand, the prevalence was higher than 17.7% in Eastern Uganda (Nicole et al., 2020) and 21.1% in Entebbe (Muriuki, 2020). The higher prevalence is explained by the fact that the age category used in the current study is highly prone to IDA due to its rapid growth and accelerated nutrient demand(Malako et al., 2018). In addition, a wide age category was used compared to the Eastern Uganda study that enrolled children aged 11-23 months and both studies used iron studies for the diagnosis of IDA which is a more specific test compared to RDW plus microcytosis. Unfortunately, iron studies are costly and not readily available. The study findings also agree with other studies that IDA is the leading cause of anaemia among children (Özdemir, 2015; WHO, 2013). This anaemia burden is still ranked as a severe public health concern(WHO, 2015) and thus an area of great concern to the public.

The majority of the study participants with IDA had mild-moderate anaemia 135 (89.4%) with the commonest being moderately anaemic 78 (51.7%) and only 16(10.6%) had severe anaemia. This is because mild to moderate IDA is asymptomatic and therefore those affected do not seek health attention. This agrees with a study in Korea where the prevalence was 36.9% (N=491), 59.3% (N=789), and 3.8% (N=50) for mild, moderate, and severe anaemia respectively(Joo et al., 2016)

Male infants had more than 60% higher odds (AOR 1.61 (1.03-2.53), P 0.04) of having IDA compared to females. This could be explained by the fact that compared to girls, boys have a higher pre-and postnatal growth rate but with low iron storage states due to the observed larger intestinal iron loss, lower absorption, and more frequent infections .(Habib et al., 2016; Joo et al., 2016; Kuziga et al., 2017; Wieringa et al., 2007;Woldie et al., 2015) The study findings agree with a study in Finland where iron deficiency and IDA were more in boys compared to girls (19% vs. 9%)(Holmlund-suila et al., 2022). It also concurs with a study in western Kenya where male children had an increased risk for ID compared to females(Foote et al., 2013) and in Pakistan, being female was associated with reduced odds for IDA(Habib et al., 2016).

Children with current diarrhoea episodes were 1.7 times more likely to have IDA compared to those without diarrhoea. This is because diarrhoea interferes with iron absorption due to the short transit time of feeds and damage to the microvilli responsible for iron absorption(Woldie et al., 2015). The study findings agree with a study in Indonesia where current diarrhoea was 1.2 times more likely to be associated with IDA compared to those without diarrhoea (Semba et al., 2008). Additionally, this study concurs with a study in Nepal where one in every 3 children with acute diarrhoea had depleted iron stores and 31.0% of the anaemia observed among the study participants was due to iron deficiency(Chandyo et al., 2015). Whereas studies have shown that diarrhoea is associated with IDA due to reduced absorption, it is also possible that diarrhoea can occur as a result of IDA. This is because iron deficiency is associated with reduced immunity leading to recurrent infections including those of the gastrointestinal tract (Jonker et al., 2017).

Children with poor acceptable meal frequency were 1.8 times more likely to develop IDA compared to their counterparts that had an acceptable meal frequency. This is because poor meal frequency limits the iron provision from complementary feeds to cater for the accelerated iron demand for the fast-growing infant. Additionally, reduced meal frequency renders the child more dependent on breastmilk which isn't sufficient to supply the required nutrients including iron above 6 months of age(Abeshu et al., 2016; WHO, 2002). The study findings concur with a study in northern Uganda where lack of complementary feeding and insufficient complementary feeding increased the risk of IDA by four times and two times respectively(Ocan et al., 2018). Additionally, the study agrees with a study in Kenya where low diet intake was observed as a major cause of anaemia in children aged 6 months to 14 years(Ngesa & Mwambi, 2014).

Children who never ate vegetables in the 7 days before the study were 2.5 times more likely to have IDA, while Consuming Fruits once in the 7 days before the study increased the likelihood of developing IDA by more than 90% compared to those that consumed vegetables and fruits more than 5 times in the 7 days before the study respectively. This is because vegetables and fruits contain iron and vitamin C which play a crucial role in enhancing iron absorption from non-haem iron in the cereal-based diet which predominate the staple foods in the region (Chouraqui, 2022; Mantadakis et al., 2020). Plant sources are highly rich in iron, but iron is not readily bioavailable as only 5-15% is available for body absorption(Chouraqui, 2022). One of the reasons for the low uptake of vegetables among children is the misconception that it is not acceptable to feed children vegetables and not palatable to the children in face of more palatable foods (Riley et al., 2018). Another negative impact of vegetables is the high content of phytates and phenolic compounds which inhibit iron absorption in the gut. Thus, considering a particular food item may be misleading, but rather a complete meal philosophy is more inclusive, especially balancing between enhancement (ascorbic acid, heme, iron, and fermented foods) and inhibition(Chouraqui, 2022). This study's findings agree with a study in South Africa where consumption of "vegetables and fruits other than vitamin A-rich'' was associated with lower odds of being anaemic at both 24-hour recall and 3-day recall(Visser et al., 2020). Furthermore, it concurs with a study in Tanzania and Brazil where not consuming vegetables and consumption of fruits/fruits juice <2 portions/day increased the risk for IDA by two times (Ferreira et al., 2016).

Accordingly, WHO recommends special attention to foods that enhance iron absorption/ consumption of fruit and vegetables as a way to mitigate the burden of IDA among children the world over(WHO, 2001).

Worth noting in this study is that there was no association between meat consumption and IDA among the study participants thou it’s a known source of nutritional iron. This could be attributed to the fact that majority of the participants at least consumed meat once week 67.3%. Additionally, iron level could be contributed through the use of Bushera which is a key feed during complementary feeding as porridge(Muyanja et al., 2003). Bushera made out of millet is estimated to contain about 2-8mg/100g of bioavailable iron and it’s associated with a 13.2% increment in HB following regular consumption as porridge/meal for at least 21 days compared to other regular diets and a 54.7% increase in Serum ferritin levels(Anitha et al., 2021).

The study found a strong positive significant correlation between RDW in the presence of microcytosis and Mentzer index in the diagnosis of iron deficiency anaemia (spearman correlation coefficient 0.521, P value 0.000). This implies that both tests are very likely to give the same result when used independently. The study findings of a strong correlation between RDW and Mentzer index are supported by a meta-analysis comparing numerous red cell indices in differentiating IDA and beta thalassemia found a sensitivity of 1.0(0.5 -1.4) at 95% confidence interval, p-value false positive rate <0.001-0.5(-0.9 to -0.1) and a P value of < 0.001 using RDW as reference (Hoffmann et al., 2015). Additionally, a study comparing RDW and Mentzer index found a sensitivity of 94.2% and 99.4% and PPV of 98.8% and 97.7% for the diagnosis of IDA when compared with serum ferritin among primigravids in Pakistan(Zafar et al., 2019). During iron deficiency, smaller RBCs are produced by the bone marrow resulting in a smaller RBC count and low MCV thus a Mentzer index of >13(Tabassum et al., 2022). Therefore, RDW and Mentzer index can be used for early presumptive diagnosis of IDA and thus early initiation of treatment to avert the complications and long-term sequelae associated with IDA.

Limitations

The gold standard of serum ferritin for IDA was not used. However, the researcher diagnosed IDA based on RDW in the presence of microcytosis (low MCV and peripheral blood film smear).

IDA is highly prevalent among infants aged 6-23 months with at least four in 10 being affected. Screening for IDA should be recommended in male children with current diarrhoea, poor intake of fruits and vegetables, and poor meal frequency. The Mentzer index is an equally good alternative screening test for IDA.

Availability of data and materials

Data is available from the corresponding author upon request.

Funding

There was no funding for this study

Conflict of interest

The authors declare no conflict of interest regarding the publication of this research work

Acknowledgement

We acknowledge that this manuscript was shared as a preprint with research square accessible at the following link: https://www.researchsquare.com/article/rs-2742978/v1

Author’s contribution:

DK– conceptual framework, study design, methodology, manuscript body, text writing

WIE - study design, methodology, designed tables and figures

SM – methodology and data analysis

YAO – Conceptual framework, methodology, data analysis, and presentation

MN- Conceptual framework, methodology.

GN- Conceptual framework, Methodology, study design, result presentation.

All authors proofread the final manuscript.

Abeshu, M. A., Lelisa, A., & Geleta, B. (2016). Complementary Feeding : Review of Recommendations , Feeding Practices , and Adequacy of Homemade Complementary Food Preparations in Developing Countries – Lessons from ethiopia. Frontiers in Nutrition, 3(41), 1–9. https://doi.org/10.3389/fnut.2016.00041

Anitha, S., Kane-potaka, J., Botha, R., Givens, D. I., Liana, N., Sulaiman, B., Upadhyay, S., Vetriventhan, M., & Tsusaka, T. W. (2021). Millets Can Have a Major Impact on Improving Iron Status , Hemoglobin Level , and in Reducing Iron Deficiency Anemia – A Systematic Review and Meta-Analysis. Front. Nutr, 8(October), 1–14. https://doi.org/10.3389/fnut.2021.725529

Beatrice, E., Deborah, N., & Gina, K. (2019). Content of Iron and Vitamin A in Common Foods Given to Children 12–59 Months Old from North Western Tanzania and Central Uganda. Nutrients, 11(454), 1–11. https://doi.org/10.3390/nu11030484

Betsy, L., Elias, J., John, H., Eileen, M., & Abraham, W. W. (2000). Poorer Behavioral and Developmental Outcome More Than 10 Years After Treatment for Iron Deficiency in Infancy. Pediatrics, 105(4), 51-. https://doi.org/10.1542/peds.105.4.e51

Chandyo, R. K., Ulak, M., Adhikari, R. K., & Sommerfelt, H. (2015). Prevalence of Iron Deficiency and Anemia among Young Children with Acute Diarrhea in Bhaktapur, Nepal. Healthcare, 641(3), 593–606. https://doi.org/10.3390/healthcare3030593

Chaparro, C. M., & Suchdev, P. S. (2019). Anemia epidemiology, pathophysiology, and etiology in low- and middle-income countries. Ann N Y Acad Sci, 1450(1), 15–31. https://doi.org/10.1111/nyas.14092.Anemia

Cheesbrough, M. (2009). District Laboratory Practice in Tropical Countries Part 2 (2nd Edition). CAMBRIDGE UNIVERSITY PRESS.

Chouraqui, J. (2022). Dietary Approaches to Iron Deficiency Prevention in Childhood — A Critical Public Health Issue. Nutrients, 14(1604), 1–24.

Faraj, S. A., Ahmed, H. S., & Raghad, A. S. (2017). IRON DEFICIENCY ANEMIA IN CHILDREN “EXPERIENCE OF SINGLE CENTER.” INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH, 6(12), 235–236.

Ferreira, S., Katille, M., Bezerra, D. A., & Assunção, M. L. De. (2016). Prevalence of and factors associated with anemia in school children from Maceió , northeastern Brazil. BMC Public Health, 16(380), 1–12. https://doi.org/10.1186/s12889-016-3073-2

Foote, E. M., Sullivan, K. M., Ruth, L. J., Oremo, J., Sadumah, I., Williams, T. N., & Suchdev, P. S. (2013). Determinants of Anemia among Preschool Children in Rural, Western Kenya. Am. J. Trop. Med. Hyg, 88(4), 757–764. https://doi.org/10.4269/ajtmh.12-0560

Fufa, B., & Gutema, H. (2019). Nursing and Health Care Prevalence of Anemia and Associated Factors among Children. International Archives of International Archives Of, 5(129), 1–5. https://doi.org/10.23937/2469-5823/1510129

GAIN and UNICEF. (2019). COMPREHENSIVE NUTRIENT GAP ASSESSMENT (CONGA): findings for children 6–23 months in Uganda. (Issue December).

Garg, S., Srivastava, A., Singh, S., Jaiswal, R., & Singh, Y. K. (2016). Role of Hematological Indices in the Screening of Β-Thalassemia Minor (Trait) and Iron Deficiency Anaemia. American Research Journal of Hematology, 1(1), 1–5.

Habib, M. A., Black, K., Soofi, S. B., & Hussain, I. (2016). Prevalence and Predictors of Iron Deficiency Anemia in Children under Five Years of Age in Pakistan, A Secondary Analysis of National Nutrition Survey Data 2011 – 2012. PloS One, 11(5), 1–13. https://doi.org/10.1371/journal.pone.0155051

Hernell, O., Fewtrell, M. S., Georgieff, M. K., Krebs, N. F., & Bo, L. (2015). Summary of Current Recommendations on Iron Provision and Monitoring of Iron Status for Breastfed and Formula-Fed Infants in Resource-Rich and Resource-Constrained Countries Olle. The Journal of Peadiarics, 167(4, suppl.1), S40–S46. https://doi.org/10.1016/j.jpeds.2015.07.020

Hoffmann, J. J. M. L., Urrechaga, E., & Aguirre, U. (2015). Discriminant indices for distinguishing thalassemia and iron deficiency in patients with microcytic anemia : a meta-analysis. Clin Chem Lab Med, 53(12), 1883–1894. https://doi.org/10.1515/cclm-2015-0179

Holmlund-suila, E. M., Hauta-alus, H. H., & Enlund-cerullo, M. (2022). Iron status in early childhood is modi fi ed by diet , sex and growth : Secondary analysis of a randomized controlled vitamin D trial. Clinical Nutrition, 41, 279–287. https://doi.org/10.1016/j.clnu.2021.12.013

Jennifer, A. R. (2020). Iron-Deficiency Anemia. In M. K. ROBERT, W. S. G. I. JOSEPH, J. B. NATHAN, S. S. SAMIR, R. C. TASKER, & K. M. WILSON (Eds.), Nelson Textbook of Pediatrics (21st ed., pp. 9920–9929). Elsever iInc.

Jonker, F. A. M., Poel, E., & Bates, I. (2017). Anaemia , iron deficiency and susceptibility to infection in children in sub-Saharan Africa , guideline dilemmas. British Journal of Haematology, 177(April), 878–883. https://doi.org/10.1111/bjh.14593

Joo, E. Y., Kim, K. Y., Kim, D. H., Lee, J., & Kim, S. K. (2016). Iron deficiency anemia in infants and toddlers. Blood Research, 51(4), 0–5.

Kai, Y., Ying, P., Bo, Y., Furong, Y., Jin, C., Juanjuan, F., Pingping, T., & Fasu, Z. (2021). Red blood cell distribution width - standard deviation but not red blood cell distribution width coefficient of variation as a potential index for the diagnosis of iron - deficiency anaemia in mid - pregnancy women. Open Life Sciences, 16, 1213–1218.

Krawiec, P., & Pac-Kozuchowska, E. (2020). Biomarkers and Hematological Indices in the Diagnosis of Iron Deficiency in Children with Inflammatory Bowel Disease. Nutrient, 12(1358), 1–9.

Kuziga, F., Adoke, Y., & Wanyenze, R. K. (2017). Prevalence and factors associated with anaemia among children aged 6 to 59 months in Namutumba district , Uganda : a cross- sectional study. BMC Pediatrics, 17(25), 1–9. https://doi.org/10.1186/s12887-017-0782-3

Malako, B. G., Teshome, M. S., & Belachew, T. (2018). Anemia and associated factors among children aged 6 – 23 months in Damot Sore. BMC Hematology, 18(14), 1–9.

Mantadakis, E., Chatzimichael, E., & Zikidou, P. (2020). Iron Deficiency Anemia in Children Residing in High and Low-Income Countries : Risk Factors , Prevention , Diagnosis and Therapy. Mediterranean Journal of Hematology and Infectious Diseases, 12(1), 1–12.

Mccarthy, E. K., Kiely, M. E., Hannon, G., Ahearne, C., Kenny, L. C., Hourihane, J. O. B., Irvine, A. D., & Murray, D. M. (2017). Microcytosis is associated with low cognitive outcomes in healthy 2-year-olds in a high-resource setting. British Journal of Nutrition, 118, 360–367. https://doi.org/10.1017/S0007114517001945

Menon, M. P., & Yoon, S. S. (2015). Prevalence and Factors Associated with Anemia among Children under 5 Years of Age — Uganda , 2009. Am. J. Trop. Med. Hyg, 93(3), 521–526. https://doi.org/10.4269/ajtmh.15-0102

Msaki, R. V., Lyimo, E., Masumo, R. M., Mwana, E., Katana, D., Julius, N., Munuo, A., Leyna, G., Issaka, A., Dhami, M. V., & Agho, K. E. (2022). Predictors of iron deficiency anaemia among children aged 6 – 59 months in Tanzania : Evidence from the 2015 – 16 TDHS-MIS cross- sectional household survey. PLOS Glob Public Health, 2(11), 1–28. https://doi.org/10.1371/journal.pgph.0001258

Mukesh, C., Deepak, S., & Dhanraj, S. S. D. D. (2015). Significance of Red Cell Distribution Width in the Diagnosis of Iron Deficiency Anemia : An Observational Study from India. Journal of Pediatrics and Neonatal Care, 2(6), 00102. https://doi.org/10.15406/jpnc.2015.02.00102

Muriuki, J. M. (2020). The way we measure iron deficiency in children needs to change. Here’s why https://theconversation.com/amp/the-way-we-measure-iron-deficiency-in... 1–6.

Muriuki, J. M., Mentzer, A. J., Webb, E. L., Morovat, A., Kimita, W., Ndungu, F. M., Macharia, A. W., Crane, R. J., Berkley, J. A., Lule, S. A., Cutland, C., Sirima, S. B., Diarra, A., Tiono, A. B., Bejon, P., Madhi, S. A., Hill, A. V. S., Prentice, A. M., Suchdev, P. S., … Williams, T. N. (2020). Estimating the burden of iron deficiency among African children. BMC Medicine, 18(31), 1–14.

Muyanja, C., Kikafunda, J., Narvhus, J., Helgetun, K., & Langsrud, T. (2003). PRODUCTION METHODS AND COMPOSITION OF BUSHERA : A Ugandan Traditional Fermented Cereal Beverage. African Journal of Food, Agriculture, Nutrition and Development, 3(1), 1–14.

Ngesa, O., & Mwambi, H. (2014). Prevalence and risk factors of anaemia among children aged between 6 months and 14 years in Kenya. PloS One, 9(11), 1–10.

Nicole, D. F., Laird, J. R., Sarah, N., Abdelrahman, L., Siti, H., Martin, A., Rhona, B., D.Whitehead, J. R., Carine, M., & Maria, E. J. (2020). An Integrated Infant and Young Child Feeding and Micronutrient Powder Intervention Does Not Affect Anemia , Iron Status , or Vitamin A Status among Children Aged 12 – 23 Months in Eastern Uganda. J Nutr, 00, 1–7.

Ocan, A., Oyet, C., Webbo, F., Wambi, B., & Taremwa, I. M. (2018). Prevalence , morphological characterization , and associated factors of anemia among children below 5 years of age attending St . Mary ’ s Hospital. Journal of Blood Medicine, 9, 195–201.

Özdemir, N. (2015). Iron deficiency anemia from diagnosis to treatment in children. Türk Ped Arş, 50, 11–19. https://doi.org/10.5152/tpa.2015.2337

Purnamasidhi, C. A. W., Suega, K., & Bakta, I. M. (2019). Role of Red Cell Distribution Width ( RDW ) in the diagnosis of iron deficiency anemia. Indonesia Journal of Biomedical Science, 13(1), 12–15. https://doi.org/10.15562/ijbs.v13i1.160

Riley, L. K., Rupert, J., & Boucher, O. (2018). Nutrition in Toddlers. Am Fam Physician, 98(4), 227–233.

Sarah, B., Sheikh, K., & Shah, T. (2018). Red Cell Distribution Width is Early Marker for Detection of Iron Deficiency Anemia during Pregnancy. J Liaquat Uni Med Health Sci., 17(03), 165–169. https://doi.org/10.22442/jlumhs.181730571

Sazawal S, Dhingra U, Dhingra P, et al. (2014). Efficiency of red cell distribution width in identification of children aged 1-3 years with iron deficiency anemia against traditional hematological markers. BMC Pediatrics, 14, 8.

Sazawal, S., Dhingra, U., Dhingra, P., Dutta, A., Shabir, H., Menon, V. P., & Black, R. E. (2014). Efficiency of red cell distribution width in identification of children aged 1-3 years with iron deficiency anemia against traditional hematological markers. BMC Pediatrics, 14(8), 2–7.

Semba, R. D., Pee, S. De, Ricks, M. O., Sari, M., & Bloem, M. W. (2008). Diarrhea and fever as risk factors for anemia among children under age five living in urban slum areas of Indonesia. International Journal of Infectious Diseases, 12, 62–70. https://doi.org/10.1016/j.ijid.2007.04.011

Simbauranga, R. H., Kamugisha, E., Hokororo, A., Kidenya, B. R., & Makani, J. (2015). Prevalence and factors associated with severe anaemia amongst under-five children hospitalized at Bugando Medical. BMC Hematology, 15(13), 1–9. https://doi.org/10.1186/s12878-015-0033-5

SriLestari, S. A., Ini, P., Erial, B., & Rahadiyanto, K. Y. (2014). Mentzer index as a screening tool for iron deficiency anemia in 6-12-year-old children. Paediatrica Indonesiana, 54(5), 294–298.

Sultana, G., Haque, S., Sultana, T., Rahman, Q., & Ann, A. (2011). Role of red cell distribution width (RDW ) in the detection of iron deficiency anaemia in pregnancy within the first 20 weeks of gestation. Bangladesh Med Res Counc Bull, 37, 102–105.

Tabassum, S., Khakwani, M., Fayyaz, A., & Taj, N. (2022). Role of Mentzer index for differentiating iron deficiency anemia and beta thalassemia trait in pregnant women. Pak J Med Sci, 38(4), 878–882.

Tayab, A., Hoq, A., & Begum, M. (2021). Cut off Value of Red Cell Distribution Width ( RDW ) in Screening and Diagnosis of Iron Deficiency Anemia and E Thalassemia Trait. DS (Child) H J, 37(1), 51–58.

UBOS. (2016). Uganda Demographic and Health Survey 2016.

Visser, M., Zyl, T. Van, Hanekom, S. M., Baumgartner, J., Hoeven, M. Van Der, Taljaard-krugell, C., Smuts, C. M., & Faber, M. (2020). Associations of dietary diversity with anaemia and iron status among 5- to 12-year-old schoolchildren in South Africa. Public Health Nutrition, 24(9), 2554–2562. https://doi.org/10.1017/S1368980020000543

Wang, M. (2016). Iron Deficiency and Other Types of Anemia in Infants and Children. Am Fam Physician, 93(4), 270–278.

WHO. (2001). Iron Deficiency Anaemia Assessment, Prevention and Control A guide for programme managers.

WHO. (2002). Complementary feeding: report of the global consultation, and summary of guiding principles for complementary feeding of the breastfed child.

WHO. (2011). Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity.Vitamin and Mineral Nutrition Information System.

WHO. (2013). Essential Nutrition Actions: improving maternal, newborn, infant and young child health and nutrition.

WHO. (2015). The Global Prevalence of Anaemia in 2011.

Wieringa, F. T., Berger, J., Dijkhuizen, M. A., Hidayat, A., Ninh, N. X., Utomo, B., Wasantwisut, E., & Winichagoon, P. (2007). Sex differences in prevalence of anaemia and iron deficiency in infancy in a large multi-country trial in South-East Asia. British Journal of Nutrition, 98(5), 1070–1076. https://doi.org/10.1017/S0007114507756945

Woldie, H., Kebede, Y., & Tariku, A. (2015). Factors Associated with Anemia among Children Aged 6 – 23 Months Attending Growth Monitoring at Tsitsika Health Center , Wag-Himra Zone , Northeast Ethiopia. Journal of Nutrition and Metabolism Volume, 2015, 9.

Zafar, M., Tabassum, A., Cheema, Q. A., & Mazhar, S. B. (2019). Role of Red Cell Distribution Width and Mentzer Index in Differentiating Iron Deficiency Anemia from Anemia Due to β Thalassemia Trait. Journal of South Asian Federation of Obstetrics and Gynaecology, 11(5), 297–300.

The authors declare no competing interests.

Download PDF

Version 2

posted

You are reading this latest preprint version

Prevalence and factors associated with Iron deficiency anaemia among children aged 6-23 months in southwestern Uganda.

Status:

Version 2

Abstract

Figures

Introduction

Methods And Materials

Results

Discussion

Conclusion And Recommendation

Declarations

References

Additional Declarations

Status:

Version 2