Kwashiorkor, severe childhood malnutrition characterized by edema, is seen in the context of inadequate dietary intake and food insecurity, and resolves with therapeutic feeding (1). Historically, kwashiorkor was thought to result from dietary protein deficiency and hypoalbuminemia (2,3). However, clinical data do not support this notion because there is no evidence that children with kwashiorkor ingest any less protein on average than children with marasmus (4), edema resolves long before any change in albumin levels (5), and children with kwashiorkor can lose their edema on extremely low-protein diets (6). More recently, it has been proposed that kwashiorkor results from excessive oxidative stress (7), and there are a number of small case series that document that markers for oxidative stress are elevated in kwashiorkor (8,9) and that antioxidant status is compromised as well (10,11). However, this hypothesis has been challenged by a recent large prospective, randomized, double-blind, placebo-controlled trial of supplementation with vitamin E, n-acetyl-cysteine, riboflavin, and selenium, none of which prevented kwashiorkor in vulnerable children in Malawi (12). A recent case-control study from Malawi comparing food intakes in children with marasmus and kwashiorkor found that children with kwashiorkor consumed fewer eggs and tomatoes (13). However, these findings are limited by the retrospective study design and indirect method of dietary assessment.
Although it is clear that kwashiorkor is related to a poor diet, the salient determinants of that relationship remain an enigma. This study prospectively examined the relationship between diet and kwashiorkor in a population of vulnerable Malawian children and tested the hypotheses that children who develop kwashiorkor consume fewer eggs, tomatoes, small fish, and protein than those who do not.
PATIENTS AND METHODS
Kwashiorkor is common in Malawi; in a community survey of more than 25,000 children, 2% of all children ages 1 to 3 years were found to have edema (14). The Machinga district was found to have the highest prevalence of kwashiorkor in southern Malawi. The habitual diet in Machinga is monotonous and corn-based, and is supplemented with small fish. Most villagers are subsistence farmers who have difficulty growing crops in the sandy soil surrounding nearby Lake Chilwa. Approximately half of the villagers have access to a source of clean water. Food is prepared outdoors over open wood fires, and almost everyone in this area lives in mud huts with thatched roofs. Health care in these villages is provided mainly by traditional healers and health surveillance assistants, government employees with 1 year of health care training in first aid and simple health maintenance. The nearest health center was at least 40 km from the villages.
This study was conducted from January to March 2004 in 8 villages in the Machinga district of southern Malawi. The study was conducted in a population of children enrolled in a previously reported randomized double-blind, placebo-controlled trial of antioxidant supplementation to prevent kwashiorkor (12). All of the children residing in the villages ages 12 to 36 months of age without evidence of edema or severe chronic illness were eligible for the study. In families in which there were 2 or more eligible children, only the youngest child was enrolled because the foods consumed within the same family are likely to be the same. The study coincided with the rainy season, just before the annual harvest, when children are most likely to develop kwashiorkor. Written and oral informed consent was obtained from all of the children's caretakers before enrollment. The study was approved by the College of Medicine Research Ethics Committee of the University of Malawi and the Human Studies Committee of Washington University School of Medicine in St. Louis, MO.
This was a prospective, observational study in a population of children at risk for kwashiorkor to determine what foods and/or nutrients are associated with the development of the disease. Upon enrollment, the caretaker of the subject was questioned for demographic data. Each child was examined for edema, and his/her height, weight, and mid-upper arm circumference (MUAC) were measured. A food frequency questionnaire was completed by the child's caretaker only on enrollment. Caretakers and subjects returned for follow-up in their village every 2 weeks for 10 weeks. The presence of edema, body weight, MUAC, breast-feeding status and any history of fever, cough, or diarrhea in the preceding 2 weeks were recorded at every visit. Before enrollment, study investigators and senior project nurses were trained to assess edema in an inpatient nutritional unit. During the study edema was assessed by a study investigator by compressing the skin over both of the child's fourth metatarsal bones with a firm finger for 10 seconds and looking for evidence of pitting. All of the children who were found to have edema by an investigator were also checked independently by a senior project nurse. If the child was judged to have edema by both staff members, then the child was diagnosed with kwashiorkor and removed from the study. Depending on the clinical condition of the edematous child, she or he was brought to the nearest inpatient facility for standard treatment or offered home-based therapy with ready-to-use therapeutic food (15).
The primary outcome was the development of edema. The primary associations that were tested for were the consumption of eggs, fish, tomatoes, and protein. The secondary associations were all other foods as well as the prevalence of self-reported fever, cough, and diarrhea. The sample size was determined by the number needed to adequately power the trial of antioxidant supplementation, which was the primary reason that these children were being studied (12). It was estimated that 2% of the children would develop kwashiorkor and that the distribution of food intake would be similar to that reported in the retrospective study (13). Therefore, in the study population of approximately 1700 children, a difference in eggs, tomatoes, and small fish intake of 1 serving per week and a decrease in protein intake of 0.5 g/kg/d could be detected with 95% sensitivity and 80% power.
Food Frequency Questionnaire
Before the enrollment of participants, 53 foods were identified as constituents of the diet by mothers of children ages 1 to 3 years in these villages. These foods were identified during standardized focus group discussions designed to ascertain this information (16,17). Approximately 50% of the dietary energy is derived from corn; animal-derived foods constitute a small part of the diet. The food frequency questionnaire asked how often the child consumed each of the 53 foods during the previous 2 months. There were 9 possible food frequency answers for each food: 1, 2, or 3 times per day; 1, 2, or 3 times per week; or 0, 1, or 2 times per month.
Dietary Diversity Score
Dietary diversity was assessed using a standard 7-point score, which categorizes foods into the following groups: starchy staples, legumes, dairy, meat/fish/eggs, vitamin A–rich foods, other fruits and vegetables, and foods rich in fats (18). Each subject receives a score between 0 and 7, with 7 indicating the greatest dietary diversity. This scoring system has been used and validated in the developing world. Each of the 53 foods identified in this study were categorized into 1 of the 7 groups. The score for each food group was determined by adding servings per day of each food in the group. Therefore, the score for each group ranged from 0 to >20, with the number representing the estimated number of servings per day in that group. All group scores that were >1 were reduced to 1. The sum of all 7 food groups was the child's dietary diversity score.
The intakes of energy, protein, iron, zinc, thiamin, niacin, vitamin A, and vitamin C were estimated using the number of servings consumed determined by the food frequency questionnaire and data from previous dietary intake research. Previously, in the rural Machinga district among children ages 1 to 3 years, the average serving size for all 53 foods was quantified using an interactive 24-hour recall method (19–21). The nutrient composition of the foods was determined using standard techniques in a food analysis laboratory (22,23). To estimate the amount of nutrient consumed from each food daily, the number of servings consumed per day as reported on the food frequency questionnaire was multiplied by the average serving size and the amount of the nutrient in the food. The total estimated daily intake of a nutrient was determined by summing the amount consumed in each of the 53 foods. Because the children were enrolled in a trial of n-acetyl-cysteine, riboflavin, selenium, and vitamin E supplementation, intake of these nutrients was not assessed.
The demographic and anthropometric characteristics of the children with and without kwashiorkor were summarized and expressed as mean ± SD for continuous characteristics and number and percentage for dichotomous characteristics. The food frequency data were expressed as servings per month with the 25th and 75th percentile values. Comparisons were made using the Wilcoxon rank-sum test for continuous characteristics and by χ2 test for dichotomous characteristics. Simple statistical analyses for this study were performed with SPSS 13.0 for Windows (SPSS, Chicago, IL) and regression analyses were performed with SAS 9.1 (SAS, Cary, NC). Regression modeling was performed with a generalized linear mixed-regression model (GLIMMIX) that fits statistical models for data with correlations or nonconstant variability and when the response is not necessarily normally distributed (24,25).
To determine whether the development of kwashiorkor was associated with consumption of more or less of a specific food, each food was screened for a bivariate relationship using the Kruskal-Wallis test. All foods associated with the development of kwashiorkor at a level of P < 0.10 by this test were analyzed further using regression modeling. For each of the foods that were found to be significant at a level P < 0.10, a combined model using all of these foods, age, and sex was created. Foods found to be associated with kwashiorkor at a level of P < 0.01 in the combined model were considered associated with kwashiorkor. A significance level of P < 0.01 was chosen to identify associations because multiple comparisons were being made in the regression modeling.
To determine whether the development of kwashiorkor was associated with intake of more or less of a specific nutrient, a regression model using age, sex, and each nutrient was created. For each of the nutrients that were found to be significant at P < 0.10, a combined model using all of these nutrients was created. Nutrients found to be associated with kwashiorkor at a level of P < 0.01 in the combined model were considered associated with kwashiorkor. Dietary diversity scores were tabulated. The total dietary diversity score and the mean score in each of the 7 categories were compared using the Student t test.
A total of 1651 children were enrolled the study and 43 (2.6%) developed edema in the subsequent 10 weeks. Five children were ineligible for enrollment because they had edema at that time. Six children were lost to follow-up; it was reported that they had moved outside the study area. Two children who did not develop kwashiorkor died of an acute febrile illness. Of the 43 children who developed kwashiorkor, 42 were successfully treated with home-based therapy with ready-to-use therapeutic food. One child was hospitalized and subsequently died.
Children who developed kwashiorkor were younger and had more nutritional wasting and growth stunting than those who did not (Table 1). Of the children who developed kwashiorkor, 30 of 43 (70%) were still breast-feeding. No children were exclusively breast-fed. The 13 children with kwashiorkor who had stopped breast-feeding did so at 21 ± 6 months of age, compared with 23 ± 6 months of age for children who did not develop kwashiorkor (difference not significant). Children who developed kwashiorkor experienced more fever, cough, and diarrhea in the 28 days before diagnosis than those who did not (Table 2).
Regression modeling using demographic characteristics found that lower age was independently associated with the development of kwashiorkor. The F value for age was 13.02 (P < 0.001). Bivariate testing for the association of the development of kwashiorkor with consumption of more or less of any of the 53 foods yielded 7 associations that were likely to occur by chance <10% of the time. Consumption of less guava, cassava leaf, sweet potato leaf, small fish, goat meat, and corn bread was associated with the development of kwashiorkor (P < 0.10; Table 3). Consumption of more tomatoes was also associated with the development of kwashiorkor (P < 0.10; Table 3). Subsequent regression modeling using age, sex, and each of these 7 single foods showed that no food was associated with kwashiorkor at a level of P < 0.01. Post-hoc power calculations indicate that for foods consumed 3 or more times per month, it is unlikely that food consumption did not vary more than 50% between the children who developed kwashiorkor and those who did not (80% power). For foods consumed fewer than 3 times per month, the study had no power to conclude anything about the equivalence of the diet.
Regression modeling using age, sex, and the intake of single nutrients did not show a significant difference between affected and unaffected children (Table 4). Post-hoc power calculations of these nutrient comparisons show that nutrient consumption was unlikely to differ by more than 20% between children who developed kwashiorkor and those who did not. The protein-to-energy ratio of the diet, excluding breast milk, consumed by the children who developed kwashiorkor was 12.4% ± 2.4%, compared to 12.5% ± 1.9% for the children who did not develop kwashiorkor (difference not significant); a post-hoc power calculation of this comparison shows that children who developed kwashiorkor had less than a 1% chance (99% power) of having a protein-to-energy ratio 1.3% less than the children who did not develop kwashiorkor.
The dietary diversity scores of both groups were low and similar (Table 5). These children almost never consumed foods cooked in oil, dairy products, or legumes.
This prospective dietary study identified no foods or nutrients that were associated with the development of kwashiorkor in a population of 12- to 36-month-old rural Malawian children. There were no differences in dietary diversity between affected and unaffected children.
Children who developed kwashiorkor had lower weight-for-height and height-for-age z scores and lower MUAC measurements than those who did not. This indicates that these children were already suffering from undernutrition, which made them vulnerable to the development of kwashiorkor.
This study was conducted in a homogenous, rural population of people consuming a monotonous, habitual diet. The role of foods and nutrients with respect to the development of kwashiorkor in areas with more varied habitual diets or feeding practices may be different. One potential confounding factor that was not accounted for was HIV infection, which was not assessed. HIV infection predisposes children to develop severe malnutrition, although this more commonly manifests as marasmus than kwashiorkor (26). Among a population of underweight rural Malawian children in an adjoining district ages 1 to 4 years, 1% were infected with HIV (27). Therefore, if we assume that the prevalence of HIV infection was 0.5% among our population of healthy children, then approximately 8 HIV-infected children would have participated in our study. Although it is likely that a few of the children who developed kwashiorkor in this study were infected with HIV, this represents <20% of the 43 cases of kwashiorkor.
The estimations of nutrient intake were made assuming that the portion sizes were uniform among all of the subjects. Although portion sizes do vary from family to family, in this region of Malawi the methods of preparing and serving food do not (20). Food is cooked over an open fire, and families are likely to have only 2 to 3 different cooking/serving vessels, which are used at every meal. The size of the cooking vessel is the primary determinant of the amount of food prepared at a given meal. When less food is available for preparation, a typical caretaker is likely to serve fewer meals per day. During times of food insecurity, Malawian families reduce the number of meals consumed, rather than the size of the meal. The dietary intake data were collected only at the beginning of the 10-week observation period, and thus we can be less confident that these data accurately describe the child's diet at the end of this observation period. Although it is unlikely that the foods eaten at the end this observation period were different than those identified at the onset, it is possible that some families reduced the frequency of food intake. The prospective study design and the large number of subjects enrolled prohibited us from collecting food frequency information at several intervals during the study.
It is surprising that in this large prospective study, not a single food or nutrient was associated with the development of kwashiorkor, including eggs and tomatoes, which were identified in a previous retrospective study (13). This study was insufficiently powered to prove dietary equivalence, particularly for foods consumed infrequently, and further work is needed to test the hypothesis that there were indeed no differences between the diets of children who developed kwashiorkor and those who did not.
There was no difference in the estimated protein intake between children who developed kwashiorkor and those who did not, nor was there a difference in the protein-to-energy ratio of the food they consumed. This is consistent with Gopalan's findings in India (4) and does not support the notion that kwashiorkor is the result of dietary protein deficiency. However, the higher prevalence of growth stunting and wasting in this population is consistent with the hypothesis of a chronically low energy and protein intake because stunting and wasting are often associated with low protein and energy intakes, respectively (3).
Breast-feeding after the age of 1 year was not associated with the development of kwashiorkor in this study. Some experts have emphatically stated that kwashiorkor is never seen in the breast-fed child (28), and this bit of common wisdom is often repeated by clinicians in the developing world. However, data from case series of patients with kwashiorkor to support this statement are lacking. Our data suggest that prolonged breast-feeding does not change the risk of developing kwashiorkor.
Although children in this study who developed kwashiorkor were more likely to have had fever, cough, and diarrhea in the previous 28 days, approximately half the children who developed kwashiorkor reported none of these symptoms. These are the most common symptoms of acute infection, and in cases of clinically serious infections, they are likely to be reported by mothers. It has been previously noted that infection usually precedes the development of kwashiorkor in children requiring hospitalization, and acute infection is thought to precipitate its development in vulnerable children (29). Data regarding infections that are more chronic, such as subacute malaria, or occult infections, such as parasitic gastrointestinal infestations, were not collected in this study.
To our knowledge, this study is the first prospective, comprehensive, population-based dietary survey in children at risk for kwashiorkor that has been reported in the literature. Although it is certainly not without limitations, the methodological strengths of the prospective design and 2-week follow-up provide the strongest evidence exploring the relationship between dietary intake and kwashiorkor. Although we can conclude that a monotonous corn-based diet with consumption of modest amounts of animal products certainly puts rural Malawian children at high risk for the development of kwashiorkor, with a 2.6% incidence during a 10-week period, unfortunately no particular foods or nutrients were identified as exacerbating that risk. The observation that edema resolved in 42 of 43 children with home-based therapy with an energy- and protein-dense diet suggests that such a dietary supplement may be useful as a preventive strategy.
This study surveyed all foods consumed by the children and estimated the consumption of some nutrients. It is possible that nutrients that were not considered in this study could be associated with the development of kwashiorkor. For example, refined corn flour, an important and ubiquitous staple in the Malawian diet, is particularly low in potassium, and whole-body potassium status has been noted to be compromised in kwashiorkor (30,31). In experimental animal models of kwashiorkor, the ratio of dietary sodium to potassium was found to be a determinant of edema (32). In addition, environmental contaminants such as aflatoxin have been geographically associated with the development of kwashiorkor (33). Investigation of the role of dietary potassium and aflatoxin may yield important insights about kwashiorkor. Kwashiorkor afflicts several million children worldwide, and the case fatality rate is estimated to be 10% to 50% (26); to develop effective preventive strategies, the enigmatic etiology of kwashiorkor must be further elucidated.
The authors thank the Doris Duke Clinical Research Fellows Program for their support, and the work of clinical staff members Rosemary Godwa, Chrissie Khoriyo, and Ramsey Makumba.
1. Williams CD. Kwashiorkor: a nutritional disease of children associated with a maize diet. Lancet 1935; 2:1151–1152.
2. Waterlow JC. Kwashiorkor revisited: the pathogenesis of oedema in kwashiorkor and its significance. Trans R Soc Trop Med Hyg 1984; 5:436–441.
3. Golden MHN. The development of concepts of malnutrition. J Nutr 2002; 132:2117S–2122S.
4. Gopalan C. Kwashiorkor and marasmus: evolution and distinguishing features. In: McCance RA, Widowson EM, editors. Calorie Deficiencies and Protein Deficiencies. London: Churchill; 1968. pp. 49–58.
5. Golden MHN, Golden BE, Jackson AA. Albumin and nutritional oedema. Lancet 1980; 1:114–116.
6. Golden MHN. Protein deficiency, energy deficiency and oedema of malnutrition. Lancet 1982; 1:1261–1265.
7. Golden MHN, Ramdath D. Free radicals in the pathogenesis of kwashiorkor. Proc Nutr Soc 1987; 46:53–68.
8. Manary MJ, Leeuwenburgh C, Heinecke JW. Increased oxidative stress in kwashiorkor. J Pediatr 2000; 137:421–424.
9. Lenhartz H, Ndasi R, Anninos A, et al. The clinical manifestation of the kwashiorkor syndrome is related to increased lipid peroxidation. J Pediatr 1998; 132:879–881.
10. Becker K, Leichsenring M, Gana L, et al. Glutathione and associated antioxidant systems in protein energy malnutrition: results of a study in Nigeria. Free Radic Biol Med 1995; 18:257–263.
11. Sive AA, Subotzky EF, Malan J, et al. Red blood cell antioxidant enzyme concentrations in kwashiorkor and marasmus. Ann Trop Paediatr 1993; 13:33–38.
12. Ciliberto H, Ciliberto M, Briend A, et al. Antioxidant supplementation for the prevention of kwashiorkor in Malawian children: randomised, double blind, placebo controlled trial. BMJ 2005; 330:1109–1112.
13. Sullivan J, Ndekha M, Maker D, et al. The quality of the diet in Malawian children with kwashiorkor and marasmus. Matern Child Nutr 2006; 2:114–122.
14. Courtright P, Canner J. The distribution of kwashiorkor in the southern region of Malawi. Ann Trop Paediatr 1995; 15:221–226.
15. Ciliberto MA, Sandige H, Ndekha MJ, et al. A comparison of home-based therapy with ready-to-use therapeutic food with standard therapy in the treatment of malnourished Malawian children: a controlled, clinical effectiveness trial. Am J Clin Nutr 2005; 81:864–870.
16. Parsons M, Greenwood J. A guide to the use of focus groups in health care research: part 1. Contemp Nurs 2000; 9:169–180.
17. Mansell I, Bennett G, Northway R, et al. The learning curve: the advantages and disadvantages in the use of focus groups as a method of data collection. Nurs Res 2004; 11:79–88.
18. Arimond M, Ruel MT. Dietary diversity is associated with child nutritional status: evidence from 11 demographic and health surveys. J Nutr 2004; 134:2579–2585.
19. Ferguson EL, Gadowsky SI, Huddle M, et al. An interactive 24-h recall technique for assessing the adequacy of trace mineral intakes of rural Malawian women; its advantage and limitations. Eur J Clin Nutr 1995; 49:565–578.
20. Hotz C, Gibson RS. Complimentary feeding practices and dietary intakes from complimentary foods amongst weanlings in rural Malawi. Eur J Clin Nutr 2001; 55:841–849.
21. Ferguson EL. A Comparison of the Seasonal Food Consumption Patterns and Zinc Status of Preschool Children Living in Rural Areas of Southern Malawi and Southern Ghana [doctoral dissertation]. Guelph, Ontario, Canada: University of Guelph; 1992.
22. Ferguson EL, Gibson RS, Thompson LU, et al. Phytate, zinc and calcium contents of 30 East African foods and their calculated phytate:zinc, Ca:phytate and [Ca][phytate]/[Zn] molar ratios. J Food Comp Anal 1988; 1:316–325.
23. Bunch S, Murphy SP. User's Guide to the Operation of the World Food Dietary Assessment System, version 2.0. Berkeley, CA: University of California Office of Technology Licensing; 1997.
25. Littell RC, Milliken GA, Stroup WW, et al. SAS System for Mixed Models. Cary, NC: SAS; 1996.
26. Brewster DR, Manary MJ, Graham SM. Case management of kwashiorkor: and intervention project at seven nutrition rehabilitation centers in Malawi. Eur J Clin Nutr 1997; 51:139–147.
27. Maleta K, Kuittinen J, Duggan MB, et al. Supplementary feeding of underweight, stunted Malawian children with a ready-to-use food. J Pediatr Gastroenterol Nutr 2004; 38:152–158.
28. Jelliffe DB, Jelliffe EF. Causation of kwashiorkor: toward a multifactorial consensus. Pediatrics 1992; 90:110–113.
29. Whitehead RG. Infection and the development of kwashiorkor and marasmus in Africa. Am J Clin Nutr 1977; 30:1281–1284.
30. Michaelsen KM, Clausen T. Inadequate supplies of potassium and magnesium in relief food-implications and countermeasures. Lancet 1987; 1:1421–1423.
31. Alleyne GAO. Studies on total body potassium in malnourished infants: factors affecting potassium repletion. Br J Nutr 1970; 24:205–212.
32. McGuire EA, Young VR. Nutritional edema in a rat model of protein deficiency: significance of the dietary potassium and sodium content. J Nutr 1986; 116:1209–1224.
33. Hendrickse RG, Coulter JB, Lamplugh SM, et al. Aflatoxins and kwashiorkor: a study in Sudanese children. Br Med J Clin Res Ed 1982; 285:843–846.
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