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Prevalence and risk factors of anemia among children 6–59 months in India: A multilevel analysis

Published:March 03, 2020DOI:https://doi.org/10.1016/j.cegh.2020.02.015

      Abstract

      Background

      Early detection of anemia and subsequent measures to prevent anemia can help children grow healthily. There is considerable attention given to the impact of individual-level factors on Anaemia, but less is known about how community characteristics affect Anaemia among children. The present study was focused at estimating the prevalence and associated risk factors at individual and community level in India among children aged 6–59 months in India.

      Methods

      Descriptive statistics and the chi-square test were applied using fourth round of National Family Health Survey dataset. Later, to explore the association of child anemia and some potential risk factors regarding hierarchy (individual and community level) of data, a multilevel logistic regression model was conducted using STATA-SE 14 software.

      Results

      The results indicate that some aspects of the community influence the anemia risks of children. For instance, a 1% increase in the proportion of mother education in the community decreased the likelihood of anemia by 9% among children. Northeast region was the only region at lesser risk of anemia. Higher community level ethnic and religious homogeneity is associated with decreased odds of anemia among children. Children aged 12–35 months, girl child, children having diarrhoea, mothers of age group 15–24, high parity and low exposure to mass-media were the high risk individual factors of anemia among children.

      Conclusions

      Overall, the present study indicated the requirement to include community-level factors beyond the individual level factors by policymakers to eradicate the burden of anemia in the country and the high prevalence states.

      Keywords

      1. Background

      Childhood anemia is a major public health concern affecting both developed and developing countries. Worldwide 1.6 billion people suffer from anemia of which two-thirds are under preschool children.
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      According to the World Health Organization (WHO) criteria, the condition of anemia is said to be a severe public health problem if its prevalence is 40% or more. Also, according to the WHO Classification of countries by degree of public health significance of anemia, India comes under the severe category for both children and pregnant women.
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      There is substantial evidence that children in the age group of 6–59, who are living in the low-income household are at higher risk of anemia compared to those with higher income.
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      Inadequate access to food and poor sanitation are often correlated with low income and to some extent, explain the higher risk of anemia among these children.
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      • Gedefaw L.
      Nutritional iron deficiency anemia: magnitude and its predictors among school age children, southwest Ethiopia: a community based cross-sectional study.
      Parent's level of education constitutes a well-documented determinant of anemia in children because educated parents are more likely to have well-paid employment and also more likely to adopt healthier dietary behaviour.
      • Goswmai S.
      • Das K.K.
      Socio‐economic and demographic determinants of childhood anemia.
      The mother's level of education, in its turn, influences the practices related to the child's health care.
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      • Lee H.J.
      • Jang H.B.
      • et al.
      Effects of maternal education on diet, anemia, and iron deficiency in Korean school-aged children.
      The age of the child is another risk factor for anemia, and many studies have found to vary the causes of anemia with age.
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      • Moerschel S.K.
      Evaluation of anemia in children.
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      • Bizzarro M.J.
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      • Ehrenkranz R.A.
      Differential diagnosis and management of anemia in the newborn.
      In a study, have demonstrated that children between 6 and 24 months have a significantly higher prevalence of anemia (two times) when compared to children between 24 and 59 months.
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      • Lira P.I.C.
      • Batista-Filho M.
      Prevalence of anemia in children 6-59 months old in the state of Pernambuco, Brazil.
      Previous studies have demonstrated that the incidence of anaemia can vary between males and females.
      • Osorio M.M.
      Determinant factors of anemia in children.
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      • Queiroz S.S.
      Anemia em crianças menores de dois anos atendidas nas unidades basicas de saude no Estado de São Paulo, Brasil.
      However, most authors have shown that there is no difference in the prevalence of anemia or haemoglobin concentration regarding gender.
      • Osorio M.M.
      Determinant factors of anemia in children.
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      • Golding J.
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      ,
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      • Milman N.
      • Samuelson G.
      A longitudinal study of iron status in healthy Danish infants: effects of early iron status, growth velocity and dietary factors.
      Community level factors play an essential role in the risk of anemia. Previous studies have documented the higher risk of anemia in children of rural.
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      • Ngnie-Teta I.
      Risk Factors for Anemia in Preschool Children in SubSaharan Africa.
      ,
      • Osorio M.M.
      Determinant factors of anemia in children.
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      Modelling hierarchically clustered longitudinal survival processes with applications to childhood mortality and maternal health.
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      • Ngnie-Teta I.
      • Kuate-Defo B.
      • Receveur O.
      Multilevel modelling of sociodemographic predictors of various levels of anemia among women in Mali.
      The disease was found to be higher in lower Caste population in some parts of India.
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      • Kumari K.
      • Uppal M.
      Prevalence of anemia in Bazigar (ex-nomadic tribe) preschool children of Punjab.
      ,
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      • Gangadhar M.R.
      Prevalence of anemia in Jenukuruba primitive tribal children of Mysore district, Karnataka.
      Anemia has severe consequences on growth, development, and survival of a child; and the factors which influence the occurrence of anemia in a population are fundamental to the implementation of control measures. The findings of the study on the prevalence of anemia, and also its associated factors will help to set up preventive programs, updating of the treatment protocols, follow up and care of anemic children, formulation of policies, and also to create public awareness about child anemia in India.

      2. Methods

      The data on anemia status of children along with some significant biological, socioeconomic, demographic, ethnic and dietary pieces of evidence were gathered from the database of NFHS-IV (National Family Health survey, 2005-06, Govt. of India).
      International Institute for Population Sciences (IIPS) & ORC MACRO
      It is a nationally representative sample survey, provides information on population, nutrition and health. It covers each state and union territory of India. The study was conducted under the guidance of Ministry of Health and Family Welfare (MoHFW), Government of India and the International Institute for Population Sciences (IIPS) is a nodal agency for conducting the survey. The survey follows a stratified two-stage sampling process. The primary sampling unit (PSU) was the villages for rural areas, and Census Enumeration Blocks (CEBs) in urban areas and the household was the second stage sampling unit (SSU) for both rural and urban areas. The PSU was selected using the probability proportional to size (PPS) sampling and households were selected using the systematic sampling procedure. Four type of survey questionnaire (household, women, men and biomarker) were canvassed in the survey.

      3. Measurement of variables

      Outcome Variable: The anemia level among children was measured by the haemoglobin concentration level with the help of a portable HemoCue Hb 201+ analyser in the survey. The HemoCue has been found to give very accurate results, comparable to estimates from more sophisticated laboratory instruments.
      • Gehring H.
      • Hornberger C.
      • Dibbelt L.
      • et al.
      Accuracy of point-of-care-testing (POCT) for determining haemoglobin concentrations.
      ,
      • Gupta K.
      • Arnold F.
      • Kishor S.
      • Parasuraman S.
      Concern on prevalence of anemia in pregnant & lactating women in India.
      The anemia level among children was categorised as 1 if haemoglobin level less than 11.0 g/dl (anemic) and 0 otherwise.

      3.1 Explanatory variables

      Depending of the severity of diarrhoea, it could lead to mild, moderate, or severe anemia.
      • Janus J.
      • Moerschel S.K.
      Evaluation of anemia in children.
      Diarrheal illness is associated with loss of iron and decreased absorption of nutrients needed to maintain normal haemoglobin status.
      • Bizzarro M.J.
      • Colson E.
      • Ehrenkranz R.A.
      Differential diagnosis and management of anemia in the newborn.
      It is also likely that, as demonstrated for other nutrient deficiencies, diarrhoea shares common cause with anemia.
      • Osorio M.M.
      • Lira P.I.C.
      • Batista-Filho M.
      Prevalence of anemia in children 6-59 months old in the state of Pernambuco, Brazil.
      ,
      • Torres M.A.A.
      • Sato K.
      • Queiroz S.S.
      Anemia em crianças menores de dois anos atendidas nas unidades basicas de saude no Estado de São Paulo, Brasil.
      Bednet use is well documented as an effective anemia prevention strategy.
      • Verhoeff F.H.
      • Brabin B.J.
      • Chimsuku L.
      • Kazembe P.
      • Broadhead R.L.
      An analysis of the determinants of anemia in pregnant women in rural Malawi: a basis for action.
      ,
      • Emond A.M.
      • Hawkins N.
      • Pennock C.
      • Golding J.
      Haemoglobin and ferritin concentrations in infants at 8 months of age.
      • Michaelsen K.F.
      • Milman N.
      • Samuelson G.
      A longitudinal study of iron status in healthy Danish infants: effects of early iron status, growth velocity and dietary factors.
      • Kuate-Defo B.
      Modelling hierarchically clustered longitudinal survival processes with applications to childhood mortality and maternal health.
      • Ngnie-Teta I.
      • Kuate-Defo B.
      • Receveur O.
      Multilevel modelling of sociodemographic predictors of various levels of anemia among women in Mali.
      • Sidhu S.
      • Kumari K.
      • Uppal M.
      Prevalence of anemia in Bazigar (ex-nomadic tribe) preschool children of Punjab.
      • Jai Prabhakar S.C.
      • Gangadhar M.R.
      Prevalence of anemia in Jenukuruba primitive tribal children of Mysore district, Karnataka.
      International Institute for Population Sciences (IIPS) & ORC MACRO
      • Gehring H.
      • Hornberger C.
      • Dibbelt L.
      • et al.
      Accuracy of point-of-care-testing (POCT) for determining haemoglobin concentrations.
      A recent study in Mali estimated that 30% of anemia is due to malaria.
      • Gupta K.
      • Arnold F.
      • Kishor S.
      • Parasuraman S.
      Concern on prevalence of anemia in pregnant & lactating women in India.
      An exhaustive review of the impact of malaria control on the risk of anemia among children
      • Verhoeff F.H.
      • Brabin B.J.
      • Chimsuku L.
      • Kazembe P.
      • Broadhead R.L.
      An analysis of the determinants of anemia in pregnant women in rural Malawi: a basis for action.
      estimates the protective efficacy of bednet usage on severe anemia to be 60% (hemoglobin <8 g/dL).
      The study variables for the present study was selected based on the existing literature on anemia. The explanatory variables taken in the study are child age in months (6–11, 12–35, 36+), sex (boy, girl), type of birth (single, multiple), size of the child (very small, small, average/large). The presence of diarrhoea (no, yes) and fever (no, yes) within last two weeks from the date of interview was considered. The presence of diarrhoea and fever is associated with the loss of iron and decreased absorption of nutrients which can affect the anemia level.
      • Hassan K.
      • Sullivan K.M.
      • Yip R.
      • Woodruff B.A.
      Factors associated with anemia in refugee children.
      The other variables considered in the study are bed net (no, yes), full immunization (yes, no), age of mother (15–24, 25–34, 35–49), parity (first parity, 2–3 parity, 4 and above), currently working (no, yes), wealth index (richest, richer, middle, poorer, poorest), mass media (full exposure, partial exposure, no exposure), drinking water (unimproved, improved), latrine facility type (improved, unimproved), region (south, west, north east, east, central, north), place of residence (urban, rural), community education (low, high), Ethnic Fractionalization Index (totally homogenous, not homogenous), Religion Fractionalization Index (totally homogenous, not homogenous). The use of bed net is associated with incidence of malaria and bed net use is documented as an effective anemia prevention strategy.
      • Korenromp E.L.
      • Armstrong-Schellenberg J.R.
      • Williams B.G.
      • Nahlen B.L.
      • Snow R.W.
      Impact of malaria control on childhood anaemia in Africa–a quantitative review.
      ,
      • Marchant T.
      • Schellenberg J.A.
      • Edgar T.
      • et al.
      Socially marketed insecticide-treated nets improve malaria and anaemia in pregnancy in southern Tanzania.
      Community education variable was indicating the proportion of women aged 15–49 with secondary or higher education in the community is high or low. Ethnic Fractionalization Index and religion fractionalization index were used to show the ethnic and religious diversity in the community. The index was calculated as EFL = 1- Σi (proportion of ethno-linguistic group/religious group i in the population)2. The totally homogenous category shows there was no diversity and not homogenous category shows complete diversity.
      • Boco A.G.
      Individual and Community Level Effects on Child Mortality: An Analysis of 28 Demographic and Health Surveys in Sub-saharan Africa.
      The ethnic and religious diversity are found to be associated with a larger talent pool and this could improve the quality of health workers in a community, which, a priori, promotes positive health or health outcomes.
      • Platas M.R.

      3.2 Statistical analysis

      In the present study, the prevalence of anemia by different background characteristics was measured and presented in the form of a percentage. The Chi-square test at 5% level of significance, performed for measuring the association between different predictor variables and anemia. The multilevel logistic regression analysis was applied for determining the risk factors of anemia among children in India.

      3.3 Multilevel logistic regression model

      The multilevel logistic regression model was used to analyse the determinants of anemia at three levels (fixed part model) – individual, community (PSU), and district. The random intercept model was used to measure the random effect or the clustering of participants at the community and district levels. Three models have been constructed for the analysis. The first model was an empty model that comprised of no exposure variables, and it focused on decomposing the total variance into the community (i.e. PSU) and the district components, which is useful to measure the extent of cluster variation in anemia. The second model adjusted for individual or child level variables, the third model adjusted for community-level variables while the fourth model was a full model and adjusted for both individual and community level variables simultaneously. Odds ratio, p-value, standard error (SE) and 95% confidence interval have been shown in the table of fixed effect model.
      The advantage of multilevel logistic regression (i.e. MLR) analysis is that it allowed us to partition the variations in the outcome variable, i.e. less than 7 g/dl – severe anemia; 7.0–9.9 g/dl – moderate anemia; 10.0–10.9 g/dl – mild anemia
      • Korenromp E.L.
      • Armstrong-Schellenberg J.R.
      • Williams B.G.
      • Nahlen B.L.
      • Snow R.W.
      Impact of malaria control on childhood anaemia in Africa–a quantitative review.
      estimated at the individual level, and the variation is further attributable to the differences among individuals, communities and district level. Multicollinearity was examined using variance inflation factor (VIF) prior to multivariate analysis,.
      The multilevel logistic model can be expressed as follows:
      logit(pijk)=log(pijk1pijk)=α+β'xijk+ujk+vk


      where, log(pijk1pijk) is the logit function, in which pijk is the probability of children, ‘i’ is the community ‘j’ is the district, ‘k’ being anemic. The ‘α’ is the constant, and μjk and υk are the area level residual explained at the community and the district level.
      The variance partition coefficient (i.e. VPC), which is useful to measure both cluster and individual level variance, is attributable to the community and the district level.
      The VPC is calculated using the following formula:
      VPCc=σc2+σd2σc2+σd2+π23


      VPCd=σd2σc2+σd2+π23


      where, σc2 is the community level variance and σd2 shows district-level variance. The variance for the standard logistic distribution is π233.29.
      Similarly, Median Odds Ratio (MOR) is useful to measure cluster level variance. It depends upon area level variance. The details are explained elsewhere.
      • Marchant T.
      • Schellenberg J.A.
      • Edgar T.
      • et al.
      Socially marketed insecticide-treated nets improve malaria and anaemia in pregnancy in southern Tanzania.
      The MOR can be expressed as:
      MOR=exp[(2VA)0.6745]


      exp(0.95VA)


      where VA is area level variance, and 0.6745 is the 75th centile of the cumulative distribution function of the normal distribution with mean 0 and variance 1.
      All the statistical estimations and analyses are carried out with the help of the following software STATA 13 and MLwiN 2.28 software. However, ArcGIS 10 was used for creating the maps.

      4. Results and findings

      The Sample Distribution for respondent by their background characteristics is shown in Table 1. The sample entails a higher proportion of children in the age group of 12–35 and 36+ months. The percentage of boy children is higher than the girl children. The table shows most of the births are single births. A higher percentage of children born average to large size in the sample. Nearly ninety percentages of children did not have diarrhoea and fever within the last two weeks from the date of the interview. A higher percentage (57.6%) of the population use bed net. Full immunization is more prevalent in the study population. The women are mostly in the age group of 25–34 age group. Children mostly belong to second to third parity. A higher percentage of women are non-working. There is not much variation in the wealth index distribution within the sample. Mostly women have partial exposure to the mass media. A higher percentages use improved drinking water, however, use of unimproved latrine facility is higher in the sample. Central region consists of the higher percentage of the sample, although the lowest percentage of the sample is from the west region. More than seventy-five percentages of the sample are from the rural area. Community education is high in the sample. Also, it is evident, that the ethnic diversity is more prevalent, although religious diversity is not much prevalent in the sample.
      Table 1Percentage Distribution of sample.
      Background Variables%N
      Child Age (in months)
      6–1111.326657
      12–3543.7103054
      36+45.0106162
      Sex of child
      Boy52.1122810
      Girl47.9113063
      Type of Birth
      Single98.4231982
      Multiple1.73891
      Size of Child
      Very small3.17197
      Small9.221052
      Average and above87.7201703
      Diarrhoea
      No91.1204854
      Yes8.920047
      Fever
      No86.9195496
      Yes13.129405
      Bed Net
      No57.6135743
      Yes42.5100130
      Full Immunization
      Yes86.1120806
      No13.919469
      Age of Mother
      15–2431.073040
      25–3458.4137833
      35–4910.625000
      Parity
      First parity37.087278
      2-3 Parity46.7110084
      4+ above16.338511
      Currently Working
      No82.033745
      Yes18.07398
      Wealth Index
      Richest13.431542
      Richer16.639142
      Middle20.047047
      Poorer23.655631
      Poorest26.562511
      Mass Media
      Full Exposure7.016513
      Partial Exposure64.9153140
      No Exposure28.166220
      Drinking Water
      Improved83.7197322
      Unimproved16.338551
      Latrine facility Type
      Improved48.4114140
      Unimproved51.6121733
      Region
      South10.023544
      West7.116681
      North East14.433847
      East20.949290
      Central29.068288
      North18.844223
      Place of Residence
      Urban23.856077
      Rural76.2179796
      Community Education
      Low43.9103549
      High56.1132324
      Ethnic Fractionalization Index
      Totally Homogeneous24.658050
      Not Homogeneous75.4177823
      Religion Fractionalization Index
      Totally Homogeneous66.5156853
      Not Homogeneous33.579020
      Total100.0235873
      Map 1 shows the state wise prevalence of anemia among children of 6–59 months. The national prevalence of anemia is found to be 58.7%. The map shows union territories (UTs) having the highest prevalence of anemia among children in India. Among the UT's Dadra & Nagar Haveli has the highest prevalence (84.4) followed by Daman & Diu (74.4) and Chandigarh (72.2). After the UT's Haryana state having the highest (71.1) prevalence followed by Jharkhand (70.1), Madhya Pradesh (69.0), Bihar (63.5) and Uttar Pradesh (63.5). The lowest prevalence of anemia is observed in Mizoram state (19.6) followed by Manipur (24.0), Nagaland (26.6), Assam (35.9) and Kerala (36.0). With the pattern of distribution, we can observe northern states having the highest prevalence and lowest among the north-eastern states of India. The clustering of the disease was more in the Central region and some of the states of the Eastern and western region. In the South, the higher prevalence of anemia was observed in Telangana and Karnataka.
      Map 1
      Map 1Prevalence of anemia at the State-level in India among children aged 6–59 months.
      Map 2 shows the district wise prevalence of anemia among children of 6–59 months. The top five district of having highest prevalence of anemia among children are Leh (95.8), Lahul & Spiti (94.9), Kargil (87.6), Banswara (84.4), and Dadra & Nagar Haveli (84.4) whereas bottom five lowest prevalence district of anemia are Champhai (7.9), Aizawl (11.1), Mokokchung (13.0), Phek (13.2) and Longleng (14.9). Among the top five districts two districts Leh and Kargil comes in Jammu & Kashmir, Lahul & Spiti district comes in Himachal Pradesh and Banswara district comes in the Rajasthan state of India. Champhai and Aizawl districts come in Mizoram and Mokokchung, Phek and Longleng come in Nagaland state. We can see in the district of the northern state having the highest prevalence of anemia whereas districts in the north-east state having the lowest prevalence of anemia among children of 6–59 months.
      Map 2
      Map 2District wise Prevalence of anemia among children aged 6–59 months in India.

      4.1 Prevalence of anemia by background characteristics among children aged 6–59 months

      The bivariate association between anemia status of children aged 6–59 months and predictors are shown in Table 2. The overall prevalence of anemia was 59% in India among 6–59 months in children. The prevalence of anemia among children aged 6–59 months was 69% for children under 6–11 months, 48% of children were anemic of aged 36+ months. Hence, as the age of children increases the prevalence of anemia among children decreased. Sex of the children, full immunization and currently working status was the only explanatory variable that had an insignificant association with anemia among children aged 6–59 months. The prevalence of anemia was higher among multiple births (63%) compared to mothers who give single birth with 59% respectively. Anemia is more prevalent among children born very small at the time of birth compared to children in size small and average/large. In the present study, Diarrhoea and fever have shown a significant association with anemia. In addition, not using bed nets shows association with anemia. The higher the age of the mother, the lower is the prevalence of anemia among children. High parity children are more anemic. The wealth index shows a significant association with anemia status among children aged between 6 and 59 months. It indicates that children from the poorest (65%) families followed by poorer (60%) were more exposed to anemia compared to children from richest (52%) families. Mothers having no exposure to media have a higher prevalence of anemic children compared to the mothers have partial or full exposure to media, with findings showing a significant association. The source of drinking water and latrine facility had a significant association with anemia status among children aged between 6 and 59 months in India. The proportion of anemia status was also high for children who didn't use improved water. Children, who used improved latrine facility, had a lower prevalence of anemia (55%) than children who did not use improved latrine facility (62.1%). In India, the prevalence of anemia varied from one region to another, shows significant association among children aged between 6 and 59 months. The highest proportion of anemia status was observed in the central region (63%) followed by North (61%), East (60%), West (57%), South (54%) and the lowest percentage that was recorded in Northeast region (37%). Accordingly, nearly 60% of anemic children resided in rural areas with relatively lesser percentages (56%) resided in urban areas. The prevalence of anemia is higher where community education is low and vice versa. It is important to note that ethnic and religion fractionalization index, have observed to be significantly associated with the prevalence of anemia in the bivariate analysis. The higher levels of community ethnic and religious concentration decrease the prevalence of anemia among children.
      Table 2Prevalence of Anemia among children 6–59 Months with Chi-Square Results.
      Background VariablesPrevalence of AnemiaN
      Child AgeP = 0.000
      6–1168.622012
      12–3566.593059
      36+48.694424
      SexP = 0.693
      Boy58.5109087
      Girl58.8100408
      Type of BirthP = 0.000
      Single58.6206651
      Multiple62.62844
      Size of ChildP = 0.000
      Very Small63.55787
      Small61.018434
      Average and above58.3180652
      DiarrhoeaP = 0.000
      No58.0190639
      Yes65.018856
      FeverP = 0.000
      No58.2181934
      Yes61.627561
      Bed NetP = 0.000
      No59.9120388
      Yes56.789107
      Full ImmunizationP = 0.466
      Yes56.8114819
      No60.017361
      Age of MotherP = 0.000
      15–2461.864163
      25–3457.3123372
      35–4956.121960
      ParityP = 0.000
      First parity55.676761
      2-3_Parity59.598782
      4+_above64.033952
      Currently WorkingP = 0.807
      No58.329926
      Yes58.36584
      Wealth IndexP = 0.000
      Richest51.928147
      Richer54.535001
      Middle59.141853
      Poorer59.949361
      Poorest64.155133
      Mass MediaP = 0.000
      Full Exposure53.314656
      Partial Exposure57.2136448
      No Exposure63.758391
      Drinking WaterP = 0.000
      Improved58.6175779
      Unimproved59.033716
      Latrine facility TypeP = 0.000
      Improved54.9101638
      Unimproved62.1107857
      RegionP = 0.000
      South54.420547
      West56.814659
      Northeast36.929312
      East59.544365
      Central62.960873
      North61.339739
      Place of ResidenceP = 0.000
      Urban56.149826
      Rural59.6159669
      Community EducationP = 0.000
      Low64.391449
      High54.6118046
      Ethnic Fractionalization IndexP = 0.000
      Totally Homogeneous56.451490
      Not Homogeneous59.2158005
      Religion Fractionalization IndexP = 0.000
      Totally Homogeneous58.5139781
      Not Homogeneous58.969714
      Total58.7209495

      4.2 Association of anemia with different risk factors at different levels: results of the multilevel analysis

      4.2.1 Fixed effect model

      This study used multilevel modelling analysis on anemia using DHS dataset, and the results showed in Table 3 that there was a significant variation of anemia across clusters in India. The model 1 is a null model. Model 2 shows that children aged 12–35 months were (OR = 1.13; 95% CI: 0.99–1.28) significantly more likely to have anemia as compared to 6–11 months children. The likelihood of being anemic for girl child was 1.07 times in model 2 and 1.06 in model 3 higher (07% more likely) than boy child with significant results. Anemia was also found to be more likely among children of small size (OR = 1.34 and 1.11) in model 2 and model 3 with 1.24 and 1.05 times more likely among children of average/large size in model 2 and model 3, though the results were significant only in model 2. In model 2, another variable significantly associated with childhood anemia was diarrhoea and use of bed net. Children suffered from diarrhoea were 22% more likely to have anemia while the use of bed net decreased the likelihood of anemia by 16%. After including all the variables in model 3, children suffered from diarrhoea was 17% more likely to be anemic, but the use of bed net became insignificant in model 3. Mother's age was strongly associated with the prevalence of anemia. The risk of anemia among children was 0.84 and 0.82 less likely in age group 25–34 and 35–49 years age group compared to 15–24 years age group. The findings were significant.
      Table 3Results for multilevel analysis of the prevalence of childhood Anemia, India 2015-16.
      Background VariablesModel 1Model 2Model 3
      Empty ModelSECIOddsSEP ValueCIOddsSEP ValueCI
      Child Age
      6-11®
      12–351.130.070.0610.99–1.281.010.070.9370.88–1.15
      36+0.480.030.0000.42–0.540.420.030.0000.37–0.48
      Sex
      Boy®
      Girl1.070.030.0171.01–1.141.060.030.0401.00–1.13
      Type of Birth
      Single®
      Multiple1.180.160.2200.90–1.541.160.160.2680.89–1.52
      Size of Child
      Very Small®
      Small1.340.120.0011.13–1.581.110.110.2490.93–1.34
      Average and above1.240.090.0021.08–1.421.050.080.5750.89–1.22
      Diarrhoea
      No®
      Yes1.220.070.0001.09–1.371.170.070.0061.05–1.31
      Fever
      No®
      Yes0.990.050.8970.91–1.090.980.050.6140.89–1.07
      Bed Net
      No®
      Yes0.840.030.0000.78–0.910.950.040.1970.88–1.03
      Full Immunization
      Yes®
      No1.090.060.1030.98–1.211.070.060.1920.97–1.19
      Age of Mother
      15-24®
      25–340.840.030.0000.78–0.910.870.030.0000.81–0.94
      35–490.820.050.0020.73–0.930.900.060.0850.79–1.02
      Parity
      First parity®
      2-3 parity1.170.040.0001.09–1.251.110.040.0031.04–1.19
      4+ above1.270.070.0001.14–1.411.140.070.0261.01–1.27
      Currently Working
      No®
      Yes1.030.040.4840.95–1.121.010.040.8420.93–1.09
      Mass Media
      Full Exposure®
      Partial Exposure1.360.070.0001.22–1.521.180.070.0041.06–1.32
      No Exposure1.730.110.0001.53–1.971.270.090.0011.10–1.46
      Wealth Index
      Richest®
      Richer1.150.060.0101.03–1.27
      Middle1.310.070.0001.17–1.46
      Poorer1.420.090.0001.25–1.61
      Poorest1.660.130.0001.43–1.93
      Drinking Water
      Improved®
      Unimproved0.970.050.4550.88–1.06
      Latrine facility Type
      Improved®
      Unimproved1.080.050.0621.00–1.18
      Region
      South®
      West1.430.160.0011.15–1.79
      Northeast0.470.050.0000.38–0.58
      East1.100.110.3550.90–1.34
      Central1.490.140.0001.24–1.78
      North1.810.170.0001.51–2.17
      Place of Residence
      Urban®
      Rural0.970.040.5280.89–1.06
      Community Education
      Low®
      High0.910.040.0160.84–0.98
      Ethnic Fractionalization Index
      Totally Homogeneous®
      Not Homogeneous1.080.050.0930.99–1.17
      Religion Fractionalization Index
      Totally Homogeneous®
      Not Homogeneous1.070.040.0960.99–1.15
      Note: ® Reference category, significance level: * (p < 0.10), ** (p < 0.05), *** (p < 0.01), CI: Confidence Interval, SE: Standard Error.
      The odds of Mother's parity of 2–3 and above 4 were significantly associated with anemia. In model 2, 17% of parity 2–3 and 27% of parity 4 and above were more likely to have anemic children than mother with first parity, while in model 3, it was 11% (2–3 parity) and 14% (4+ parity) respectively. No and partial media exposure are significantly more likely to associate as compared to full media exposure in both model 2 and model 3. The less exposure to mass media among mothers increased the likelihood of anemia among children.
      In model 3, household and community variables are taken in the analysis. In India, children living in households with medium and poor living standards had a higher risk of anemia than children living in households with high living standards. The odds of anemia is higher among household used unimproved latrine facility. The odds of having anemic children is less in the northeast region (OR = 0.47) with significant association compared to the south region. The Northern region is highly likely to experience anemia among children compared to the Southern region. Community education was significantly associated with anemia in India (OR = 0.91; 95%CI = 0.84–0.98). The clusters level of ethnic fractionalization was 0.91 times less likely while religion fractionalization was 1.08 times more likely to have anemic children compared to non-anemic children, showing a significant association. The lower level of community ethnic and religious concentration are significantly increased the likelihood of anemia among children.

      4.2.2 Random intercept model

      Table 4 shows the results of the random intercept model, which explored the variation in the prevalence of anemia at the district and community (PSU) levels in India. The empty model (null model) showed that childhood anemia was not random across the communities and districts. The variance partition coefficient (VPC) for the empty model at the district and community levels contributed 12% and 20% respectively to the total variation in the prevalence of anemia. The results revealed that the variation in the prevalence of anemia was attributable to the community-level factors. The full model, after having been adjusted for the individual and community-level variables, shows that the variation in childhood anemia across the districts (8.5%) and communities (16.8%) was decreasing but was, nevertheless, statistically significant for communities as well as districts. A high value of VPC would reflect a high clustering of anemia prevalence within communities plus a high neighbourhood effect on individual risk of anemia. The remaining percentage of variability is due to the variation in the respondents/households and other unknown factors. Thus, there remains some regional level variance unaccounted for in the model. Similarly, the median odds ratio (MOR) confirmed the geographical variation in the prevalence of anemia in India. The MOR for anemia was 2.37 at the community level and 1.95 at the district level in the empty model, indicating that the prevalence of anemia was higher at the community level. After the model was adjusted for all the factors, the variation in anemia decreased to a MOR of 2.17 at the community level and to a MOR of 1.73 at the district level. This shows that after the model having been adjusted for all the factors, the effect was still statistically significant in the full model.
      Table 4Results for Random Intercept model for the prevalence of childhood Anemia at cluster level by multilevel logistic regression, India, 2015-16.
      Random Effect PartModel 1SE95% CIModel 2SE95% CIModel 3SE95% CI
      Variance (SE)
      Dist.0.4970.0290.44–0.550.490.040.42–0.560.340.030.28–0.39
      PSU0.3260.0080.31–0.340.330.030.27–0.390.330.030.26–0.39
      VPC(%)
      Level 3 (Dist.)12.111.98.5
      Level 2 (PSU)20.019.916.8
      Median odds Ratio (MOR)
      MORDist1.951.941.73
      MORPSU2.372.362.17
      Note: CI: Confidence Interval, SE: Standard Error, VPC: Variance Partition Coefficient.

      5. Discussion

      Detection of risk factors is fundamental for planning and implementation of programs to eradicate childhood anemia, especially in those groups where prevalence is very high. Childhood anemia is found to be a major public health challenge in India with a high prevalence of nearly sixty percentages. Several studies have recorded the higher prevalence of anemia including India and in other countries.
      • Boco A.G.
      Individual and Community Level Effects on Child Mortality: An Analysis of 28 Demographic and Health Surveys in Sub-saharan Africa.
      • Platas M.R.
      • Bhise M.D.
      • Patra S.
      Prevalence and correlates of hypertension in Maharashtra, India: a multilevel analysis.
      The study confirmed prevalence estimates differed by some key variables associated with anemia, as well as regional variation. These regional differences could be due to inadequate dietary intake; access to health care centres; and infectious disease risk.
      • Ngnie-Teta I.
      • Receveur O.
      • Kuate-Defo B.
      Risk factors for moderate to severe anemia among children in Benin and Mali: insights from a multilevel analysis.
      This study reveals that the prevalence of anemia amongst young was higher than in the overall population. The result showed as the age increases the risk of anemia among children decreases. This could likely be due to the higher incidences of maternal micronutrient deficits as well as low concentrations of iron in breast milk due to anemia in mothers, insufficient to meet the daily requirements of iron for the children. The likelihood of anemia is significantly higher among children less than two years old compared to those aged 2–5 years may be due to the iron intake which improves with age in the form varied diet including haemoglobin rich foods. Literature have reported a similar trend that the risk of having anemia prevalence decreases with age.
      • Osorio M.M.
      • Lira P.I.C.
      • Batista-Filho M.
      Prevalence of anemia in children 6-59 months old in the state of Pernambuco, Brazil.
      ,
      ,
      • Nguyen P.H.
      • Nguyen K.C.
      • Le M.B.
      • et al.
      Risk factors for anemia in Vietnam.
      ,
      • Soh P.
      • Ferguson E.L.
      • McKenzie J.E.
      • Homs M.Y.V.
      • Gibson R.S.
      Iron deficiency and risk factors for lower iron stores in 6–24-month-old New Zealanders.
      The prevalence of anemia showed a homogeneous distribution according to sex (58.5% boy and 58.8% girl). However, few studies have found a higher prevalence of anemia in boys than in girls.
      • Balarajan Y.S.
      • Fawzi W.W.
      • Subramanian S.V.
      Changing patterns of social inequalities in anaemia among women in India: cross-sectional study using nationally representative data.
      ,
      • Ejigu B.A.
      • Wencheko E.
      • Berhane K.
      Spatial pattern and determinants of anaemia in Ethiopia.
      The likelihood of children being anemic, residing in poorest households appeared to increase the risk of childhood anemia when compared with other wealth index individuals. The finding is consistent with previous studies
      • Bhise M.D.
      • Patra S.
      Prevalence and correlates of hypertension in Maharashtra, India: a multilevel analysis.
      ,
      • Magalhaes R.J.S.
      • Clements A.C.
      Mapping the risk of anaemia in preschool-age children: the contribution of malnutrition, malaria, and helminth infections in West Africa.
      ,
      • Ngesa O.
      • Mwambi H.
      Prevalence and risk factors of anaemia among children aged between 6 months and 14 years in Kenya.
      and plausibly reflecting better household nutritional status.
      • Semedo R.M.
      • Santos M.M.
      • Baião M.R.
      • Luiz R.R.
      • da Veiga G.V.
      Prevalence of anaemia and associated factors among children below five years of age in Cape Verde, West Africa.
      In addition, even after controlling for drinking water and sanitation facilities, Diarrhoea shows significant association with anemia.
      • Ughasoro M.D.
      • Emodi I.J.
      • Okafor H.U.
      • Ibe B.C.
      Prevalence and risk factors of anaemia in paediatric patients in South-East Nigeria.
      Diarrhoeal illness is prone among children of lower socio-economic status. It is associated with a deficiency in iron content and decreased absorption of other micronutrients deficiencies which is needed to maintain normal haemoglobin status.
      • Hassan K.
      • Sullivan K.M.
      • Yip R.
      • Woodruff B.A.
      Factors associated with anemia in refugee children.
      ,
      • Muniz P.T.
      • Castro TG de
      • Araújo TS de
      • et al.
      Child health and nutrition in the Western Brazilian Amazon: population-based surveys in two counties in Acre State.
      • Singh R.K.
      • Patra S.
      Extent of anaemia among preschool children in EAG States, India: a challenge to policy makers.
      • Singh M.B.
      • Fotedar R.
      • Lakshminarayana J.
      • Anand P.K.
      Studies on the nutritional status of children aged 0–5 years in a drought-affected desert area of western Rajasthan, India.
      • Desai M.R.
      • Terlouw D.J.
      • Kwena A.M.
      • et al.
      Factors associated with hemoglobin concentrations in pre-school children in Western Kenya: cross-sectional studies.
      In contrast with our findings, conclusions from other studies also indicate that women with low educational level were more likely to be anemic children, shows a significant association between education and anemia.
      • Fotso J.-C.
      • Kuate-Defo B.
      Socioeconomic inequalities in early childhood malnutrition and morbidity: modification of the household-level effects by the community SES.
      • Woldie H.
      • Kebede Y.
      • Tariku A.
      Factors associated with anemia among children aged 6–23 months attending growth monitoring at Tsitsika Health Center, Wag-Himra Zone, Northeast Ethiopia.
      • Osório M.M.
      • Lira P.I.
      • Batista-Filho M.
      • Ashworth A.
      Prevalence of anemia in children 6-59 months old in the state of Pernambuco, Brazil.
      However, the current study didn't consider the prevalence of anemia among children of anemic mothers as mothers and children can share common socioeconomic status, home environment, and dietary conditions which may reflect the common nutritional status of the household.
      • Oliveira M.A.A.
      • Osorio M.M.
      • Raposo M.C.F.
      Socioeconomic and dietary risk factors for anemia in children aged 6 to 59 months.
      ,
      • Woldie H.
      • Kebede Y.
      • Tariku A.
      Factors associated with anemia among children aged 6–23 months attending growth monitoring at Tsitsika Health Center, Wag-Himra Zone, Northeast Ethiopia.
      ,
      • Osório M.M.
      • Lira P.I.
      • Batista-Filho M.
      • Ashworth A.
      Prevalence of anemia in children 6-59 months old in the state of Pernambuco, Brazil.

      6. Conclusion

      In summary, our study demonstrates that the prevalence of anemia is more prevalent among children aged 6–59 months in India was a severe public health problem. Our findings provide several insights into the population. Children aged 12–35 months, girl child, children having diarrhoea, mothers in the age group of 15–24, high parity children and low exposure to mass media among mother were high risk individual factors of anemia among children. The study showed low community education as a major determinant of anemia among children. It is also found that low community ethnic and religious concentration increased the chances of anemia among children. The socioeconomic status of the family and iron diet deficiency and other essential nutrients are of great importance in the development of anemia. Thus, the government should pay more attention to significant factors like wealth index, availability of pure drinking water and sanitation facilities as these are the most influential factors that should be enhanced anyway. Spatial variability of state and district of anemia prevalence are the sole findings of this paper.
      • Lover A.A.
      • Hartman M.
      • Chia K.S.
      • Heymann D.L.
      Demographic and spatial predictors of anemia in women of reproductive age in Timor-Leste: implications for health program prioritization.
      Hence, the government should give special attention to households having children of aged 6–59 months living in these high anemic prevalence regions. The government should also focus on providing information to new mothers on adequate nutrition for their young babies. Special emphasis on addressing iron and other micronutrient deficiencies, should be a prime focus to reduce childhood anemia under public health policy and intervention programmes. This research, based on recent Indian DHS will undoubtedly contribute to a greater comprehension of the determinants of anemia at the individual, and community levels.

      6.1 Limitations of the study

      There are a few limitations to this study. First, this analysis used cross-sectional surveys, it was not possible to follow Haemoglobin levels in an individual. Thus, our study fails to determine any causal relation-ships and direction of causality between socioeconomic status and anemia which may be bidirectional. However, the surveys are nationally representative and it uses consistent methodologies in the assessment and classification of anemia across time, the estimates of anemia prevalence is likely to represent a population-based estimates. Secondly, relationships between children's dietary iron intake and supplementation were not possible due to the absence of data in the DHS surveys as it is well documented in few kinds of literature that iron-deficiency anemia contributes to approximately half of the total anemia population.
      • Grantham-McGregor S.
      • Ani C.
      Iron-deficiency anemia: reexamining the nature and magnitude of the public health problem.
      • Oppenheimer S.J.
      Iron-deficiency anemia: reexamining the nature and magnitude of the public health problem.
      • Asobayire F.S.
      • Adou P.
      • Davidsson L.
      • Cook J.D.
      • Hurrell R.F.
      Prevalence of iron deficiency with and without concurrent anemia in population groups with high prevalences of malaria and other infections: a study in Cote d'Ivoire.

      6.2 Policy implications

      Over time, there has been an increasing trend seen among anemic women of reproductive age. Anemia remains a major public health problem in the country, thus have a number of implications for both policy makers and health professionals. Among all other developing countries, India was the first country to establish a national anemia programme in 1970 named as Nutritional Anemia Prophylaxis Programme which was constituted by the Ministry of Health and Family Welfare. It aimed to target specific populations who are at high risk of anemia, namely pregnant women, lactating women and preschool children between 1 and 5 years of age.
      • Kapur D.
      • Agarwal K.N.
      • Agarwal D.K.
      Nutritional anemia and its control.
      Later, anemia prevention and control came into existence in health strategies and programmes. An ambitious time-bound goal set out in 11th Five Year Plan to reducing anemia among girls and by women 50% by 2012.
      • Five Year Plans
      Planning Commission.
      However, due to variations in states, this goal is unlikely to be reached. Improved capacity to translate policies relating to health and nutrition may in part explain the performance in responding to anemia in this population. Enhancing the usage of the present approach reaction to anemia prevention and control, together with addressing knowledge gaps behind these expanding patterns, will enhance our capacity to address the multifactorial aetiology of anemia within the Indian population.

      Availability of data and materials

      The datasets generated and/or analyzed during the current study are available in the DHS Program repository, http://dhsprogram.com/data/available-datasets. cfm.

      Ethics approval and consent to participate

      Informed consent was obtained at the beginning of each interview and the authors sought permission from the DHS program for the use of the data.

      Authors’ contributions

      MD contributed to the conceptualization and design of the study. MD, MB, LP acquired the data, conducted the analysis and interpreted the results. MD and LP drafted the article. MD, HC, PD revised the draft critically for important intellectual content. All authors reviewed and approved the final version of the manuscript.

      Funding

      We have not received any funding or received grant from any funding agencies for this study.

      Declaration of competing interest

      The authors declare that they have no competing interests.

      Acknowledgments

      The authors are thankful to the Demographic Health Survey (DHS), for providing the NFHS-4 data upon request. Data can be obtained after free registration on the site www.dhsprogram.com and by submitting the data request form. The data set is accessible to anyone and is not allowed to use for commercial purposes.

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