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Am. J. Trop. Med. Hyg., 73(4), 2005, pp. 698-704
Copyright © 2005 by The American Society of Tropical Medicine and Hygiene

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MALARIA AND NUTRITIONAL STATUS AMONG PRE-SCHOOL CHILDREN: RESULTS FROM CROSS-SECTIONAL SURVEYS IN WESTERN KENYA

JENNIFER F. FRIEDMAN*, ARTHUR M. KWENA, LISA B. MIREL, SIMON K. KARIUKI, DIANNE J. TERLOUW, PENELOPE A. PHILLIPS-HOWARD, WILLIAM A. HAWLEY, BERNARD L. NAHLEN, YA PING SHI, AND FEIKO O. TER KUILE
Division of Parasitic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia; Centre for Vector Biology and Control Research, Kenya Medical Research Institute, Kisumu, Kenya; International Health Institute and Department of Pediatrics, Brown University, Providence, Rhode Island; Department of Medical Biochemistry, Faculty of Health Sciences, Moi University, Eldoret, Kenya; Department of Infectious Diseases, Tropical Medicine & AIDS, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Child and Reproductive Health Group, Liverpool School of Tropical Medicine, Liverpool, United Kingdom; Roll Back Malaria, World Health Organization, Geneva, Switzerland


ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Protein-energy malnutrition (PEM) affects millions of children in the developing world. The relationship between malaria and PEM is controversial. The goal of this study was to evaluate whether undernutrition is associated with increased or decreased malaria attributable morbidity. Three cross-sectional surveys were conducted using insecticide-treated bed nets (ITNs) among children aged 0–36 months living in an area with intense malaria transmission. Data were collected on nutritional status, recent history of clinical illness, socioeconomic status, current malaria infection status, and hemoglobin. In multivariate models, stunted children had more malaria parasitemia (odds ratio [OR] 1.98, P < 0.0001), high-density parasitemia (OR 1.84; P < 0.0001), clinical malaria (OR 1.77; P < 0.06), and severe malarial anemia (OR 2.65; P < 0.0001) than nonstunted children. The association was evident in children with mild-to-moderate (–3 < height-for-age Z-score [HAZ] < –2) and severe stunting (HAZ < –3). The cross-sectional nature of the study limits the interpretation of causality, but the data provide further observational support that the presence of undernutrition, in particular chronic undernutrition, places children at higher, not lower risk of malaria-related morbidity.


INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Protein-energy malnutrition (PEM) affects a large proportion of children under age 5 years in the developing world; approximately 32% are stunted (height-for-age Z-score < –2 standard deviations) and about 9% are wasted (weight-for-height Z-score < –2 standard deviations). The prevalence of PEM varies greatly among regions of the world. In sub-Saharan Africa, 35.2% of children are stunted and 9.6% are wasted.1

PEM has been related to poor cognitive2–4 and school performance5,6 in young children. Further, stunting in early childhood has been related to poor performance on cognitive tests in late childhood.7,8 In addition, there is strong evidence to suggest that PEM places children under age 5 years at increased risk for mortality.9 Approximately 56% of child deaths are attributable to malnutrition’s potentiating effects, and most of these are attributable to mild-to-moderate, as opposed to severe malnutrition.10 Thus, understanding modifiable risk factors for even mild-moderate PEM may inform interventions with great potential to reduce under five mortality.

The relationship between malaria and PEM is controversial. With respect to malaria’s contribution to undernutrition, randomized controlled insecticide-treated bed net (ITN) trials, chemoprophylaxis studies, and a prospective cohort study all suggest that malaria has a detrimental effect on nutritional status in children under 5 years.11–16 However, whether the presence of undernutrition places children at higher,17–19 lower,20–24 or no differential risk25 for malaria-related morbidity is less clear.26,27

PEM and malaria are common in sub-Saharan Africa, and understanding the relationship between PEM and malaria is of great public health importance. Relatively few studies have examined the association of malaria with PEM in areas with intense perennial malaria infection.28,29 This study was conducted in the context of a large randomized controlled trial of ITNs designed to assess the impact of ITNs on under-5-years morbidity and mortality in an area with a high degree of malaria-attributable morbidity.30 The focus of two previous analyses was to address the role of ITNs in mediating malaria and nutritional morbidity.11,12 Another previous publication addressed the prevalence of PEM by age in his study population.31

Here we report further analyses addressing the relationship between both chronic and acute undernutrition and malaria among children aged 0–35 months protected by ITNs. Unlike some studies conducted among severely malnourished children in refugee camps, which suggested a protective effect on malaria, our data show that malaria and undernutrition are related such that undernourished children experienced more, not less, malaria and malaria-associated morbidity. Mild-to-moderate undernutrition does not seem to have a protective effect on malaria.


MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study area and population. The study area and population have been described in detail elsewhere.32 Briefly, these surveys were carried out in the context of a large ITN trial on the shores of Lake Victoria in Nyanza Province, western Kenya. Three cross-sectional surveys were conducted to determine the impact of ITNs on all-cause morbidity among preschool children, as described elsewhere.11,31 The first two surveys were carried out in February–March (Survey 1) and November–December 1998 (Survey 2), 14 and 22 months, respectively, after the introduction of ITNs. The final cross-sectional survey (Survey 3) was conducted in June–July 1999, approximately 4 months after ITNs were distributed to the control group.31 Each household was randomized to Survey 1, 2, or 3, such that one household and their occupants could only contribute once. This report uses data only from children who had received ITNs and no direct comparison is made between ITN and control groups as this has been presented elsewhere.12,31 Thus, the current analysis includes children living in villages randomized to ITNs in Surveys 1 and 2 (30 villages), plus children randomized initially to ITN or control (60 villages) in Survey 3.

There are two rainy seasons: the long rains take place from March to May and the short rains from October to December. Malaria is holoendemic and transmission occurs throughout the year. The number of infective bites ranges between 60 and 300 per person per year.33 Based on the HIV prevalence in the study area, approximately 7.2% of newborns are expected to be infected with HIV.30 Under-5 child mortality in the study area assessed prior to the ITN trial 1992–1996 was 210 of 1,000.30

ITN study design. As described elsewhere,30 permethrin-treated bed nets (Siam Dutch, Bangkok, Thailand), were distributed for use by January 1997, covering all sleeping spaces, in the villages randomized to the intervention group. The adherence rate (persons observed to be sleeping under ITNs) among children under 5 years was 66%.34

Procedures and data collection. Household characteristics. A structured questionnaire was used for each household to record indicators of socioeconomic status (SES) and educational status of the caretaker and head of household, as described elsewhere.35 Education level of the primary caregiver and head of household were combined to provide an education index.

Demographic and clinical data. The ages of the children were transcribed from census records and vaccination cards (if available) or verbal report from the caregiver. The year and month of birth could be determined for all children. For those children with an unknown day of birth, the 15th day of the month was used.

Anthropometric measurements were recorded, and a finger-prick blood sample (400 µL) was taken for determination of the hemoglobin (Hb) concentration and the presence of malaria parasites. Each child was examined by the clinical officer. History of illnesses in the preceding 2 weeks was recorded. Specifically, caretakers were asked if the child had diarrhea, an upper respiratory tract infection, vomiting, eating soil (pica), decreased appetite, weight loss, pallor, or malaria. They were also asked if their child received treatment for any of these, and if so, from where. Children who were ill were managed as described elsewhere.11

Laboratory methods. A full blood count, including repeat hemoglobin concentration, was determined the same afternoon using a Coulter Counter. Blood slides were examined for the presence of malaria parasites. The total number of asexual parasites and gametocytes was determined per 500 white blood cells and are expressed as the number per microliter, assuming a total white blood cell count of 8,000/µL. A stool sample was also examined using the Kato Katz method to detect the presence of geohelminths and Schistosoma mansoni. Samples were stored at 4°C and processed within 24 hours after collection.

Definitions. Anemia and moderately severe anemia were defined as Hb concentrations below < 11.0 mg/dL and < 7.0 mg/dL, respectively. Malaria was defined as any asexual parasitemia detected on a thick or thin blood smear. High density parasitemia was defined as malaria parasitemia (any species) above an age-dependent threshold density as defined by Bloland and others: (0–5 months, 1,500/mm3; 6–11 months, 6,000/mm3; and 12–35 months, 7,000/mm3).36 Clinical malaria was defined as high density parasitemia with fever. Severe malarial anemia was defined as Hb < 7.0 mg/dL in the presence of any asexual malaria parasitemia. Height-for-age (HAZ), weight-for-height (WHZ), and weight-for-age (WAZ) Z-scores were calculated from Center for Disease Control (National Center for Health Statistics)/World Health Organization (1977/1985) reference values37 using EpiInfo 2000 software (version 2000, Atlanta, GA). Children were classified as stunted or wasted if the HAZ or WHZ was < –2, respectively. They were classified as having severe stunting or wasting if the HAZ or WHZ was < –3, respectively.

Data management and statistical methods. Data forms collected in the field were checked, coded, and entered using Clarion software. Data were cleaned using range and internal consistency checks. Overall descriptive statistics are reported in Table 1Go. Bivariate analyses were conducted to identify variables for consideration in multivariate models (data not shown). Covariates evaluated included demographic variables (age, gender, socioeconomic status), recent clinical history of illnesses such as diarrhea, vomiting, loss of appetite, fever, and clinical covariates from the day of evaluation including fever (temperature ≥ 37.5°C), presence of malaria as defined above, and presence of anemia of varying severity as described above. Variables that were significant at a level of P < 0.10 were considered for inclusion in multivariate models. A stepwise selection procedure within Statistical Analysis System (SAS version 8.02, SAS Institute, Cary, NC) was used to select covariates for the final multivariate models. Based on the covariates selected, the standard errors were adjusted for clustering at the village level, using a compound symmetry correlation structure, in SAS Proc Mixed. To account for any misspecification of the covariance structure, the empirical option was used. Age categories were included in each model. Cross-sectional survey number was also included in each model as a covariate to control for seasonal differences and possible methodological differences between surveys (difference in instruments used and staff). Missing values for covariates were assumed to be missing at random. The parameter estimates and standard errors from the HAZ and WHZ multivariate models are reported in Tables 2Go and 3Go. For Figures 1Go and 2Go, odds ratios were calculated using Proc GenMod, a procedure within SAS, and were adjusted for clustering at the village level.


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TABLE 1
Characteristics of study sample
 

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TABLE 2
Multivariate linear regression model predicting height-for-age Z-score*
 

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TABLE 3
Multivariate linear regression model predicting weight-for-height Z-score*
 


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  		    FIGURE 1. Prevalence of malaria-specific outcomes by stunted status. A, Prevalence of any malaria parasitemia. B, Prevalence of high density parasitemia. C, Prevalence of clinical malaria. D, Prevalence of severe malarial anemia. Odds ratios adjusted for clustering by village.

 


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  		    FIGURE 2. Prevalence of malaria-specific outcomes by wasted status A, Prevalence of any malaria parasitemia. B, Prevalence of high-density parasitemia. C, Prevalence of clinical malaria. D, Prevalence of severe malarial anemia. Odds ratios adjusted for clustering by village.

 
Ethical clearance and informed consent. The ITN project was approved by the institutional review boards of the Kenya Medical Research Institute (KEMRI), Nairobi, Kenya, and the Centers for Disease Control and Prevention (CDC), Atlanta, Georgia. Written informed consent was obtained from caretakers for each individual participant.


RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
A total of 1862 children in the ITN group were included at the following measurement times: 501 in February–March of 1998 (Survey 1), 477 in November–December 1998 (Survey 2), and 884 in June–July 1999 (Survey 3).

The overall health and nutritional status of the children was poor (Table 1Go). The mean height-for-age Z-score (HAZ) and weight-for-height Z-scores (WHZ) were –1.12 and –0.31, respectively, with 25% stunted and 5.6% wasted. Despite ITN use, 83.8% of caregivers reported seeking traditional or conventional medications for their child in the previous 2 weeks. Caregivers also reported a high cumulative history of diarrhea requiring treatment in the previous 2 weeks (53.6%), pica (22.0%), and loss of appetite (56.3%). Results from the physical examination and laboratory data supported the overall degree of morbidity with a high prevalence of documented fever (7.5%), anemia (70.9%), moderately severe anemia (8.3%), and clinical malaria (3.1%).

Multivariate models assessed the adjusted relationship between demographic and clinical covariates and HAZ, an indicator of achieved linear growth reflecting the long-term cumulative effects of health and nutritional intake. Age, cross-sectional survey, severe anemia, high-density parasitemia, and socioeconomic status were significantly related to HAZ (Table 2Go).

The adjusted relationship between WHZ, an indicator of acute nutritional status, and demographic and clinical covariates were also evaluated. Age, cross-sectional survey, a history of diarrhea in the past 2 weeks, hemoglobin < 7 mg/dL, recent treatment of malaria with traditional or conventional medication, and the combined level of education for the head of household and primary caretaker were significantly related to WHZ (Table 3Go).

In addition, we evaluated the relationship between the presence of stunting and wasting and risk for malaria-specific outcomes. We found that being stunted was associated with significantly increased odds for concurrent malaria, high-density parasitemia, and severe malarial anemia. (Figure 1Go) The presence of wasting increased the risk for only severe malarial anemia (Figure 2Go). Similar results were found when assessed for severe stunting and severe wasting (data not shown).


DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Millions of children worldwide suffer from undernutrition, and the causes are multifactorial. This is one of the first studies to examine the relationship between nutritional status and demographic and clinical risk factors in an area with intense, perennial malaria transmission and a high degree of malaria attributable morbidity.36

There is evidence to support the fact that malaria is causally related to decreased nutritional status. Randomized controlled insecticide treated bed net trials11,12,38 and chemoprophylaxis studies39,40 support the thesis that malaria infection is detrimental to the nutritional status of young children.

What is often debated, however, is whether undernutrition places children at increased or decreased risk for malaria infection.17,18,20,41 In this study, malaria outcomes were consistently related to decreased nutritional status, particularly HAZ. The cross-sectional design of the study limits the causal inferences that can be made; the observed association may be due to the cumulative detrimental effects of malaria on nutritional status. Alternatively, this may reflect an increased risk of malaria infection among stunted children.17,18 Verhoef and others found that, although the presence of stunting was not related to increased prevalence of malaria infection, it was associated with increased severity of anemia among children who were infected.17 In a longitudinal study in The Gambia, stunting at the start of a transmission season was associated with increased incidence of malaria.18 In addition, the World Health Organization’s Comparative Risk Assessment project found that children who were moderately to severely underweight had an increased, but not statistically significant risk of a clinical malaria attack, as compared with those who were better nourished.27,42 One longitudinal study with contradictory findings found that stunted children had a lower incidence of clinical malaria episodes than nonstunted children.24 It should be noted that the age range of this study differed from ours and the others cited, extending to 10 years of age. Three other prospective studies found no relationship between baseline nutritional status and subsequent incidence of malaria.15,41 The contradictions apparent in these studies may be related to severity of PEM, definitions of clinical malaria, or genetic differences in the cytokine profile of responses to malaria, particularly proinflammatory responses. Most reviews of this subject, however, conclude that chronic under-nutrition likely increases the risk for malaria morbidity and mortality.27,42 In this study, malaria outcomes were consistently related to low height-for-age Z-scores, an indicator of achieved height and long-term nutritional status.

We cannot exclude, however, that these acute episodes of malaria reflect a longer term increased susceptibility to malaria and possibly other infections in a selected group of children who became stunted as a result. This may represent an increased host susceptibility to malaria based on known variability in host immunologic responses to infection. Some of the relationships between infectious diseases such as diarrhea and malaria and undernutrition may be confounded by HIV status. No data were available with respect to HIV status in this study. HIV-infected adults and pregnant women are at increased risk of clinical malaria and high-density parasitemia,43,44 and HIV is a known cause of growth faltering among children in the developing world.45

Anemia and recent (2 weeks) treatment of acute malaria were also related to WHZ, a measure of acute undernutrition. It is possible that the relationship between anemia and acute undernutrition represents the expected colinearity between decreased macro- and micronutrient intake, rather than a causal relationship. Anemia is also likely to be marker for current or recent malaria illness, and acutely decreased nutritional status due to that illness. Interestingly, we did not find a relationship between WHZ and current malarial illness as depicted in Figure 2Go. This may be due to a lag in weight loss after an acute illness. It is possible that if WHZ were measured 1–2 weeks after malarial illness, the effect on WHZ would have been apparent. A longitudinal study, with clinical data collected at monthly intervals, conducted in The Gambia among children aged 6–36 months demonstrated that current malaria infection was related to decreased weight gain after the acute episode of malaria.46 The acute weight loss observed with malarial infection may be related to symptoms such as diarrhea and abdominal pain and anorexia,47 which may lead to malabsorption of nutrients and decreased intake, respectively. Parasitemia may also have a detrimental effect on nutritional status acutely through host elaboration of proinflammatory cytokines, which occurs even in mild malarial illness.48–50 These cytokines, particularly TNF-alpha, cause cachexia, characterized by decreased appetite and lean body wasting.51

Both PEM and malaria have enormous impact on the quality of life and likelihood of survival in this vulnerable age group in endemic Africa. Understanding the direct and indirect consequences of PEM on malaria and vice versa in areas of the world where significant comorbidity occurs is crucial, as findings may help guide the choice of public health interventions in settings of limited resources. Low height-for-age Z-scores in this age group were strongly associated with current malaria infection. The study design limits the interpretation of cause and effect; however, regardless of causality, these findings support previous observations that stunted children are more likely to have malaria infection and illness than nonstunted children and do not support the hypothesis that malnourished children are partially protected form malaria and malaria morbidity.

Received March 4, 2005. Accepted for publication June 2, 2005.

Acknowledgments: We express our gratitude to the children and caregivers who participated in the study and the many people that assisted with this project. The authors thank John Paul Clark, Neen Alrutz, and Mary Ettling for their continued interest and support. We also thank the Director of the Kenya Medical Research Institute for his permission to publish this work.

Financial support: The ITN project was funded by the United States Agency for International Development. Feiko O. Ter Kuile was supported, in part, by a grant from the Netherlands Foundation for the Advancement of Tropical Research (WOTRO) (The Hague, The Netherlands). Jennifer F. Friedman was supported by a United States Fulbright award and K23AI52125 from the National Institute of Allergy and Infectious Diseases.

* Address correspondence to Jennifer F. Friedman, M.D., M.P.H., International Health Institute and Department of Pediatrics, Brown University, Box G-B495, Providence, RI 02912. E-mail: Jennifer_ Friedman{at}Brown.edu. Back

Authors’ addresses: Jennifer F. Friedman, International Health Institute and Department of Pediatrics, Brown University, Box G-B495, Providence, RI 02912, E-mail: Jennifer_Friedman{at}Brown.edu. Arthur M. Kwena, Moi University, Department of Medical Biochemistry, Faculty of Health Sciences, Eldoret, Kenya. Lisa B. Mirel, National Center for Health Statistics, Division of Health and Nutrition Examination Suveys, Centers for Disease Control and Prevention, 3311 Toledo Road, MS P08, Hyattsville, MD 20782. Simon K. Kariuki, Kenya Medical Research Institute, Center for Vector Biology and Control Research, P.O. Box 1578, Kisumu-40100, Kenya. Dianne J. Terlou and Feiko O. ter Kuile, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK. Penelope A. Phillips-Howard, William A. Hawley, and Ya Ping Shi, National Center for ID, Division of Parasitic Diseases, Centers for Disease Control and Prevention, Mail Stop F-22, 4770 Buford Highway, Atlanta, GA 30341. Bernard L. Nahlen, World Health Organization, Roll Back Malaria, Avenue Appia 20, 1211, Beneva 27, Switzerland.

Reprint requests: Jennifer F. Friedman, M.D., M.P.H., International Health Institute and Department of Pediatrics, Brown University, Box G-B495, Providence, RI 02912. E-mail: Jennifer_Friedman@ Brown.edu.


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 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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