F1000ResearchF1000Research2046-1402F1000 Research LimitedLondon, UK10.12688/f1000research.121657.1Research ArticleArticlesDeterminants of under-five anaemia in the high prevalence regions of Ghana
[version 1; peer review: awaiting peer review]
AlhassanAbdul RaufConceptualizationData CurationFormal AnalysisFunding AcquisitionInvestigationMethodologyProject AdministrationResourcesSoftwareSupervisionValidationVisualizationWriting – Original Draft PreparationWriting – Review & Editinghttps://orcid.org/0000-0003-2252-2646a1YakubuMusahConceptualizationMethodologyResourcesSupervisionValidationWriting – Original Draft PreparationWriting – Review & Editing1
Department of Surgery, Tamale Teaching Hospital, Tamale, 00233, Ghanaalhassana84@yahoo.com
Introduction: Anaemia is a serious public health issue that mostly affects children and women throughout their lives, resulting in a high morbidity and mortality burden. It is the third most dominant cause of hospital admission among children under-five in Ghana and the fourth leading cause of under-five mortality in Ghana. This study aims to identify the determinants of under-five anaemia in the high prevalent regions of Ghana using the Ghana Malaria Indicator Survey (2019 GMIS).
Methods: An analytic cross-sectional study was conducted using data from the Ghana Malaria Indicator Survey (2019 GMIS). The data was analysed using SPSS version 20. The relationship between the dependent and independent variables was established using the chi-square test and binary logistic regression model. A p-value of 0.05 was used to determine the statistical significance of the study.
Results: There were 913 eligible under-five children for this study, with 50.2% males and 49.8% females. The prevalence of under-five anaemia recorded in this current study for the three northern regions was 68.0%. The region with dominant (72.9%) prevalence was the Upper East region. Children of lower age group were more likely to be diagnosed with anaemia (P < 0.05). Children with female household heads were 35% less likely to be diagnosed with anaemia (AOR=0.65, 95% C.I.= 0.421-0.995). Those who had mothers with higher educational attainment were 79% less likely to be diagnosed with anaemia (AOR=0.21, 95% C.I.=0.085–0.541). Finally, those with history of fever in the last weeks were 62% more likely (AOR=1.62, 95% C.I. = 1.155–2.282).
Conclusions: The high prevalence in the three northern regions of Ghana can be corrected with women empowerment through higher formal educational achievement and improved income status.
AnaemiaGhananorthernPredictorsRegionUnder-FiveThe author(s) declared that no grants were involved in supporting this work.Introduction
Anaemia is a serious public health issue that mostly affects children and women throughout their lives, resulting in a high morbidity and mortality burden.
1 Anaemia, which can be caused by several factors necessitating a combination of treatment options.
2 Over the world, more than 273 million school-age children suffer from anaemia, making them one of the most affected by anaemia population groups.
1,2
Anaemia is defined as a condition in which the human body has insufficient haematocrit, haemoglobin, or red cells.
3,4 Malaria and a lack of nutrients including iron, folate, vitamin B12, and other nutrients are the leading causes of childhood anaemia.
5 Intestinal worms, haemoglobinopathy, and sickle cell disease are all other causes of anaemia.
5 Anaemia affects mostly children under the age of five, as well as pregnant women.
5
Anaemia is linked to age, gender, ethnicity, lower maternal education, and a low household wealth index.
6–9 It has also been linked to malaria and infections.
6,9
In recent research, it has been suggested that increasing a parent’s level of education and household income lowers a child’s risk of anaemia.
3,4,10,11 Poverty, maternal anaemia, and malnutrition should be dealt with to reduce the mortality of children under the age of five.
12 In addition, an earlier study discovered that improving malaria and anaemia control during pregnancy reduces the child’s risk of suffering from anaemia conditions.
13 Moreover, a study in Malawi revealed that the mother’s levels of education, household wealth status, having fever, or stunted growth are all associated with anaemia among children under-five.
14
Again, a study in Senegal showed that enhancing the mother’s level of literacy and the intake of animal protein (meat, fish, and eggs) decreased the risk of anaemia among children under-five.
15 In comparison, the study done by Tine
et al. in Senegal showed that malaria parasitaemia, sickle cell disorder, alpha-thalassemia, and stunted growth are markedly associated with anaemia among children less than 10 years.
16 Furthermore, in McCuskee
et al., studied factors such as age, type of residence, socioeconomic status, and maternal education were associated with anaemia in their study that reviewed 15 observational studies from nine Sub-Saharan African countries, including Ghana, Malawi and Senegal.
17
Anaemia has a negative social and economic impact on affected nations and most of the nations affected are low-income nations.
9,18 In Africa, 3.3% of children aged 6–59 months suffer from severe anaemia, which is twice the global average.
19 The Ghana Health Service has stated that anaemia is the third most dominant cause for hospital admission among under-five in Ghana and fourth leading cause of under-five mortality in Ghana.
20 In Ghana, the overall prevalence of anaemia among children under-five was 78.4%, with 7.8% having severe anaemia, 48.0% having moderate anaemia, and 22.6% having mild anaemia. The regions with the highest prevalence rates were the Upper East (88.9%) and the Upper West (88.1%). The northern region also had a high prevalence of 82%.
21 These results motivated this present study to identify determinants of under-five anaemia in the high prevalence regions of Ghana using a recent dataset from the Ghana Malaria Indicator Survey (2019 GMIS).
MethodsThe survey design and sampling
An analytic cross-sectional study was conducted using data from the Ghana Malaria Indicator Survey (2019 GMIS). The Ghana Statistical Service (GSS) carried out the 2019 Ghana Malaria Indicator Survey (2019 GMIS) in close partnership with the Ghana National Malaria Control Programme (NMCP) and the Ghana Health Service National Public Health and Reference Laboratory. The survey was funded in part by the United States Agency for International Development (USAID), the Global Fund to Fight AIDS, Tuberculosis, and Malaria, and the Ghanaian government. The DHS Program, a USAID-funded project that provides support and technical support in the implementation of population and health surveys in countries around the world, was where ICF provided technical assistance. The Noguchi Memorial Institute handled external laboratory quality control for Medical Research (NMIMR).
The sampling frame for the 2019 GMIS is the same as that used for the 2010 PHC, which was conducted in Ghana by GSS.
22 Ghana established six new regions in 2019, giving the country a total of 16 regions and 260 administrative districts; however, the new administrative boundaries were not available at the time of the survey design. The sampling frame for the 2019 GMIS is thus based on the ten regional boundaries defined by the 2010 PHC.
All women between the ages of 15 and 49 who were permanent residents of the chosen household or visitors who stayed the night before the survey were eligible to be interviewed. Children aged 6 to 59 months were tested for anaemia and malaria infection with the permission of their parents or guardians. This study focused on the Children’s recodes dataset, which included 913 eligible children from the three northern regions (Upper West, Upper East, and Northern region).
Data collection
The 2019 GMIS used four types of questionnaires: the household questionnaire, the woman’s questionnaire, the biomarker questionnaire, and the fieldworker questionnaire.
23 Data for the 2019 GMIS were collected using questionnaires programmed into the computer-assisted personal interviewing (CAPI) application. The women’s questionnaire was used to collect data from women aged 15 to 49. These women were questioned on subjects such as characteristics of their background (age, education, literacy, religion, and ethnicity), reproductive history for the last five years, fever prevalence, and treatment for children under the age of five years. The biomarker questionnaire was used to record the results of anaemia and malaria testing in children aged 6-59 months.
Anaemia testing
A finger or heel prick was used for testing using a single-use retractable, spring-loaded, sterile lancet. Finger or heel prick was used because of high concentration of blood vessels around those areas. A drop of blood was then collected from the site and placed in a microcuvette. On-site haemoglobin analysis was performed using a battery powered portable HemoCue 201+ analyser, which produced a result in less than one minute.
23 The results of the anaemia test were recorded in the biomarker questionnaire as well as on a brochure left in the home, which included information on the causes and the prevention of anaemia. Parents or guardians of children with haemoglobin levels less than 8 g/dl were recommended to take the child to a health care facility for follow-up care and were given a referral letter with the haemoglobin reading to show to the facility’s health worker.
Ethical considerations
The Ghana Health Service Ethical Review Committee and the Institutional Review Board of ICF both approved the protocol for the 2019 GMIS. Participants were notified about the advantages and disadvantages of taking part in the survey. It was voluntary to take part in the survey. Before administering the household or women’s questionnaire, eligible respondents were asked to provide written informed consent. Informed consent was obtained from parents or guardians of the children before blood samples were collected for malaria and anaemia testing. All data and information gathered were kept strictly confidential. Before analysing the data, the names and identification numbers of the participants were deleted from the finished data sets and to safeguard the identity of the respondents, blood samples were labelled with barcodes. Meanwhile, the DHS program approved the use of the DHS dataset (Ghana using the Ghana Malaria Indicator Survey, 2019 GMIS) for this present study on Dec 27, 2021.
Data analysis
The data was analysed using SPSS version 20 (IBM Corp., 2011, NY, RRID:SCR_002865). The categorical variable results, which included sample characteristics, were presented in tables with frequencies and percentages. To determine the relationship between the dependent and independent variables, the chi-square test was used. A binary logistic regression model was used to identify the predictive determinants of under-five anaemia. In addition, the results were presented as exponentiated β coefficients or adjusted odds ratio (AOR) with confidence intervals (CI). A p-value of 0.05 was used to determine the statistical significance of the study.
ResultsStudy participants
There were 913 eligible under-five children eligible for this study, the majority (44.6%) were from the northern region, 29.6% from the upper west, and 25.8% from the upper east region (
Table 2). There was almost even distribution of the participants among the sex of the children, 50.2% for males and 49.8% for females. Most (95.5%) of the children were of single birth and not a twin. Fever was recorded among 32.6% of the children within two weeks before the survey. The age of the study participants was from six months to 59 months. The children were placed into five different groups based on their ages, there was almost an equal distribution among these groups apart from the 6–11 age group which contained 13.3% of those included (
Table 1).
Demographic characteristics of children.
Frequency
Percentage
Child current age (months)
6–11
121
13.3%
12–23
203
22.2%
24–35
200
21.9%
36–47
198
21.7%
48–59
191
20.9%
Sex of child
Male
458
50.2%
Female
455
49.8%
Child is twin
Single birth
872
95.5%
1st of multiple
20
2.2%
2nd of multiple
21
2.3%
Had fever in last two weeks
No
615
67.4%
Yes
298
32.6%
The range of maternal age was 15 to 49 years and most (22.8%) were within the age group of 30-44 years. Males headed the majority (85.9%) of households and the majority of them were within the age group of 31-40 years. By religious affiliation, most of the respondents (49.1%) were of the Islamic religion. The majority (76.3%) of the children were from rural communities. Tribal affiliation was dominated (75.8%) by the Mole-Dagbani tribe. Most (55.8%) of the mothers had no formal education and most of the mothers (65.8%) were of the poorest wealth index. At the time of the survey, only 7.8% of the mothers were pregnant. The majority (88.5%) of the children had health insurance (
Table 2).
Demographic characteristics of mother.
Frequency
Percentage
Age in 5-year groups
15–19
32
3.5%
20–24
158
17.3%
25–29
226
24.8%
30–34
208
22.8%
35–39
168
18.4%
40–44
88
9.6%
45–49
33
3.6%
Household head age
Less than or equal to 30 years
160
17.5%
31–40 years
249
27.3%
41–50 years
240
26.3%
51–60 years
117
12.8%
Greater than or equal to 61 years
147
16.1%
Sex of household head
Male
784
85.9%
Female
129
14.1%
Religion
Christianity
394
43.2%
Islam
448
49.1%
Traditional
33
3.6%
No religion
38
4.2%
Type of place of residence
Urban
216
23.7%
Rural
697
76.3%
Region
Northern
407
44.6%
Upper East
236
25.8%
Upper West
270
29.6%
Ethnicity
Akan
9
1.0%
Ga/Dangme
1
0.1%
Ewe
2
0.2%
Guan
35
3.8%
Mole-Dagbani
692
75.8%
Grusi
52
5.7%
Gurma
76
8.3%
Mande
8
0.9%
Other
38
4.2%
Highest educational level
No education
509
55.8%
Primary
175
19.2%
Secondary
197
21.6%
Higher
32
3.5%
Currently pregnant
No or unsure
842
92.2%
Yes
71
7.8%
Wealth index combined
Poorest
601
65.8%
Poorer
151
16.5%
Middle
92
10.1%
Richer
43
4.7%
Richest
26
2.8%
Registered by health insurance
No
105
11.5%
Yes
808
88.5%
Prevalence of anaemia
The prevalence of anaemia recorded in this current study for the three northern regions was 68.0%. In terms of levels, 2.7% were severe, 38.4% moderate, and 26.8% mild (
Table 3). The region with the highest (72.9%) prevalence was the upper east region, followed by 68.6% for the northern region, and then 63.0% for the upper west region (
X2=5.791, p=0.055). Prevalence was higher (69.9%) among those in rural communities than those in urban communities (62.0%) (
X2=4.652, p=0.031). A higher prevalence of anaemia was associated with children within the lower age groups, especially among those within the age group of 12-23 months (
X2=75.316, p≤0.001). Additionally, a higher maternal age group was associated with lower prevalence of anaemia in their children except those within the age group of 45-49 years who recorded the highest (75.8%) prevalence of anaemia in their children (
X2=14.830, p=0.022). The majority (76.5%) of those with a history of fever within two weeks before the survey had anaemia (χ
2=14.667, p≤0.001). More (69.3%) children of male headed households’ had anaemia compared to 60.5% for those with female household heads (
X2=3.939, p=0.047). A lower prevalence was associated with those with mothers of higher education attainment and the richest wealth index (p<0.05) (
Tables 4 &
5).
Prevalence of under-five anaemia.
Frequency
Percentage
Overall prevalence
Not anaemic
292
32.0%
Anaemic
621
68.0%
Anaemia level
Severe
25
2.7%
Moderate
351
38.4%
Mild
245
26.8%
Not anaemic
292
32.0%
Chi-square analysis for child factors associated with under-five anaemia.
Not anaemic
anaemic
Child current age (months)
6–11
28
23.1%
93
76.9%
X2
75.316
12–23
36
17.7%
167
82.3%
P-value
≤0.001
24–35
51
25.5%
149
74.5%
36–47
72
36.4%
126
63.6%
48–59
105
55.0%
86
45.0%
Sex of child
Male
138
30.1%
320
69.9%
X2
1.448
Female
154
33.8%
301
66.2%
P-value
.229
Child is twin
Single birth
281
32.2%
591
67.8%
X2
1.722
1st of multiple
7
35.0%
13
65.0%
P-value
.423
2nd of multiple
4
19.0%
17
81.0%
Had fever in last two weeks
No
222
36.1%
393
63.9%
X2
14.667
Yes
70
23.5%
228
76.5%
P-value
≤0.001
Chi-square analysis for maternal or community factors associated with under-five anaemia.
Not anemic
anemic
Age in 5-year groups
15–19
9
28.1%
23
71.9%
X2
14.830
20–24
39
24.7%
119
75.3%
P-value
.022
25–29
62
27.4%
164
72.6%
30–34
82
39.4%
126
60.6%
35–39
63
37.5%
105
62.5%
40–44
29
33.0%
59
67.0%
45–49
8
24.2%
25
75.8%
Household head age
≤30 years
45
28.1%
115
71.9%
X2
5.117
31–40 years
77
30.9%
172
69.1%
P-value
.275
41–50 years
83
34.6%
157
65.4%
51–60 years
32
27.4%
85
72.6%
≥61 years
55
37.4%
92
62.6%
Sex of household head
Male
241
30.7%
543
69.3%
X2
3.939
Female
51
39.5%
78
60.5%
P-value
.047
Religion
Christianity
134
34.0%
260
66.0%
Chi-square
2.141
Islam
136
30.4%
312
69.6%
P-value
.544
Traditional
12
36.4%
21
63.6%
No religion
10
26.3%
28
73.7%
Type of place of residence
Urban
82
38.0%
134
62.0%
X2
4.652
Rural
210
30.1%
487
69.9%
P-value
.031
Region
Northern
128
31.4%
279
68.6%
X2
5.791
Upper East
64
27.1%
172
72.9%
P-value
.055
Upper West
100
37.0%
170
63.0%
Ethnicity
Akan
3
33.3%
6
66.7%
Ga/Dangme
1
100.0%
0
0.0%
X2
3.815
Ewe
1
50.0%
1
50.0%
P-value
.873
Guan
13
37.1%
22
62.9%
Mole-Dagbani
220
31.8%
472
68.2%
Grusi
18
34.6%
34
65.4%
Gurma
23
30.3%
53
69.7%
Mande
3
37.5%
5
62.5%
Other
10
26.3%
28
73.7%
Highest educational level
No education
161
31.6%
348
68.4%
X2
18.370
Primary
48
27.4%
127
72.6%
P-value
≤0.001
Secondary
62
31.5%
135
68.5%
Higher
21
65.6%
11
34.4%
Currently pregnant
No or unsure
270
32.1%
572
67.9%
X2
.035
Yes
22
31.0%
49
69.0%
P-value
.851
Wealth index combined
Poorest
182
30.3%
419
69.7%
Poorer
44
29.1%
107
70.9%
X2
14.060
Middle
32
34.8%
60
65.2%
P-value
0.007
Richer
18
41.9%
25
58.1%
Richest
16
61.5%
10
38.5%
Registered by health insurance
No
31
29.5%
74
70.5%
X2
.330
Yes
261
32.3%
547
67.7%
P-value
.566
Predictors of anaemia
Those with significant association (p<0.25) on chi-square analysis were further modelled using binary logistics regression to identify predictor factors of anaemia. The age of the child could be used to predicted anaemia, children in the age group 36–59 months were 53% less likely to have anaemia compared to those within the age group of 6–11 months (p<0.05) (AOR=0.47, 95%, C.I.=0.273-0.819). Children of female household heads were 35% less likely to have anaemia compared to those with male household heads (AOR=0.65, 95% C.I.=0.421–0.995). Those with mother of higher educational attainment were 79% less likely to have anaemia when compared to those with no educational attainment (AOR=0.21, 95% C.I.=0.085–0.541). Finally, those with history of fever within the last two weeks prior to the survey were 62% more likely to have anaemia compared to those without a recent (two weeks) history of fever (AOR=1.62, 95%, C.I.=1.155–2.282) (
Table 6).
Binary logistic regression for predictor factors of under-five anaemia.
β
P - value
AOR
95% C.I. for AOR
Lower
Upper
Child current age (months)
6–11
Reference
12-–23
.350
.242
1.419
.790
2.551
24–35
-.260
.367
.771
.439
1.356
36–47
-.749
.008
.473
.273
.819
48–59
-1.537
≤0.001
.215
.124
.373
Sex of child
Male
Reference
Female
-.216
.165
.806
.594
1.093
Had fever in last two weeks
No
Reference
Yes
.485
.005
1.624
1.155
2.282
Maternal age in 5-year groups
15–19
Reference
20–24
.420
.368
1.521
.611
3.791
25–29
.544
.235
1.724
.701
4.235
30–34
-.019
.968
.982
.398
2.419
35–39
.098
.834
1.103
.440
2.765
40–44
.324
.523
1.382
.512
3.730
45–49
.755
.217
2.128
.642
7.054
Sex of household head
Male
Reference
Female
-.435
.047
.647
.421
.995
Type of place of residence
Urban
Reference
Rural
.154
.574
1.167
.682
1.995
Region
Northern
Reference
Upper East
.248
.229
1.282
.856
1.921
Upper West
-.279
.129
.756
.527
1.085
Highest educational level
No education
Reference
Primary
.041
.853
1.042
.675
1.609
Secondary
-.338
.129
.713
.461
1.104
Higher
-1.543
≤0.001
.214
.085
.541
Wealth index combined
Poorest
Reference
Poorer
.156
.489
1.169
.752
1.816
Middle
.149
.671
1.161
.582
2.316
Richer
.141
.762
1.152
.460
2.881
Richest
-.527
.340
.590
.200
1.741
Constant
1.043
.047
2.837
Discussion
Anaemia was found in 78.4 % of children under the age of five in Ghana, with 7.8% having severe anaemia, 48.0% having moderate anaemia, and 22.6% having mild anaemia.
21 The regions with the highest prevalence rates were the Upper East (88.9 %) and the Upper West (88.1%). The northern region also had a high prevalence of 82%.
21 In this present study, the prevalence of anaemia in the three northern regions was 68.0%, and the region with the highest prevalence was the upper east region (72.9%), followed by the northern region (68.6%) and then the upper west region (63.0%). In addition, in this study, the prevalence of anaemia was found to be higher among those in rural communities than those in urban communities, this is similar to the study report of Ewusie,
et al.21 There is a strong relationship between poverty and anaemia, and the three northern are the poorest regions in Ghana, especially among the rural communities.
22 Poverty, maternal anaemia, and malnutrition are issues that need to be addressed to help reduce the mortality of children under the age of five.
12
Again, further analysis of an earlier study points to the fact that maternal empowerment in terms of higher educational attainment can be the solution for improving the anaemia status of children in Ghana and the world.
25 According to current studies, increasing a parent’s level of education and household income lowers a child’s risk of anaemia.
3,4,10,11 The results of these earlier studies are confirmed in this present study, lower prevalence was associated with those with higher education attainment and the highest wealth index. Children that had mothers with higher educational attainment were 79% less likely to have anaemia when compared to those with no educational attainment. In addition, it was more common for children with males as their households’ heads to have anaemia compared to those with females as their household heads. Children of female household heads were 35% less likely to have anaemia compared to those with male household heads. Higher educational attainment is associated with a better income status,
23 and poverty is also associated with malnutrition, hence these issues, needing to be handled to reduce the morbidities and mortality associated with children under-five.
12
Finally, those children with their age three years and above were 53% less likely to have anaemia compared to those aged less than one year. This means that nearly every single child in this region between the ages of 6-11 months is 47% likely to be anaemic. This result confirms an earlier national study, which reported a higher prevalence among those less than two years of age.
21 Anaemia in children under the age of two years may be caused by a high prevalence of maternal micronutrient deficiency, as children born to malnourished mothers have low iron, zinc, vitamin A and B12, and folate stores.
24,25 Moreover in rural Ghana nutrient-rich diets such as beef, eggs, and other haeme-containing foods are only introduced to children after weaning, usually after 18-24 months.
26 In addition, younger children are more susceptible to infections and diseases that impair iron absorption.
27 This present study confirmed the negative impact fever has on under-five anaemia, the majority of those with history of fever within two weeks prior to the survey had anaemia. Those with history of fever within two weeks before the survey were 62% more likely to have anaemia compared to those without a recent history of fever. In addition, this was the same case of earlier studies in Malawi and Ghana among children under the age of five.
14,21
The current study has limitations, such as the fact that the Ghana Malaria Indicator Survey (2019 GMIS) is a cross-sectional study, which requires caution in interpreting this study findings, due to possibility of recall bias. The study’s strength, however, is that GMIS datasets are typically nationally representative and use the same data collection procedure; thus, the study’s findings are generalisable to the three northern regions of Ghana studied.
Conclusions
High prevalence of anaemia in these regions is linked to child age, gender of the household head, lower maternal education, and a low household wealth index. The high prevalence in these regions could be corrected with women empowerment through higher formal educational achievement and improved income status.
Data availability
Data used in this study are from the Children’s recodes dataset of the Ghana Malaria Indicator Survey (2019 GMIS). available from:
https://dhsprogram.com/data/dataset_admin/login_main.cfm. Access to the dataset requires registration and is granted only for legitimate research purposes. A guide for how to apply for dataset access is available at:
https://dhsprogram.com/data/Access-Instructions.cfm.
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