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close this bookMalnutrition and Infection - A review - Nutrition policy discussion paper No. 5 (UNSSCN, 1989, 144 p.)
close this folderMALNUTRITION AND INFECTION - by Andrew Tomkins and Fiona Watson1
View the document(introduction...)
View the document1. THE NUTRITION CYCLE
View the document2. THE INFECTION CYCLE
Open this folder and view contents3. INFECTION AND RISK OF MALNUTRITION
Open this folder and view contents4. MALNUTRITION AND RISK OF INFECTION
View the document5. LOW BIRTH WEIGHT AND RISK OF INFECTION
Open this folder and view contents6. CONCLUSIONS
Open this folder and view contents7. BIBLIOGRAPHY
View the document8. ALPHABETICAL LISTING OF REFERENCES IN BIBLIOGRAPHY
View the document9. NUTRITION AND INFECTION RE-EXAMINED: A RETROSPECTIVE COMMENT BY NEVIN S SCRIMSHAW

1. THE NUTRITION CYCLE


FIGURE 1

In Figure 1 a simplified model of the ‘Nutrition Cycle’ is shown. It emphasizes the complex nature of factors that affect nutritional status. Members of a household can only exist if they continue to eat, either by growing or earning money for food. Debilitating adult infections such as schistosomiasis, onchocerciasis, trypanosomiasis and malaria can prevent economically active household members from working and so providing food. The whole household may suffer as a result and marginally deficient members are especially vulnerable. It has recently been suggested that the spread of the AIDS virus throughout substantial areas of Africa could disrupt food production to the extent that widespread famine results (Kingman 1988). Furthermore it is important to recognise that food may not be equitably distributed nationally or between different family members and that individuals do not have identical rates of nutrient utilization.

The factors in Table 1 are all potentially important determinants of nutrition. It is not surprising therefore that studies of nutrition and infection performed in different social and economic environments sometimes give conflicting results.

TABLE 1

FACTORS AFFECTING THE NUTRITION CYCLE

Physical Fitness and Health

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Injury, illness, disability.

Employment Opportunities

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Economic/social status, market forces.

Agricultural Patterns

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Land, climate, availability of seeds, fertilisers, markets and transport, food prices.

Households

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Family size, number of dependents per food producer or wage earner, age distribution of the family.

Social

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Differential in food distribution within a family, beliefs about appropriate foods.

Problems in Research Design

Malnutrition

This term is used by many authors, few of whom define what they mean by it. We use the term to describe ‘nutritional inadequacy’ whether of protein, energy or micronutrients. A range of inadequacy states occur as the result of interaction of diet and nutritional requirement. This report focuses particularly on the ways that diet and requirements interact with infection.

Many children are underweight, short, or thin as a result of nutritional inadequacy which prevents growth to their genetic potential. Numerous factors contribute to small body size, and we use the term ‘poor growth’ rather than the term ‘protein energy malnutrition’ which focuses on two nutrients only. The nutritional inadequacies that cause ‘poor growth’ rather than thinness or shortness per se, may be responsible for higher rates of morbidity and mortality in children with poor growth. Thus we consider that low values for anthropometric indices are best considered as markers of a range of nutritional inadequacies rather than as direct biological causes of higher morbidity or mortality. We shall, however, use the term ‘protein energy malnutrition’ to describe children below 60% weight for age or with nutritional oedema to encompass the clinical syndromes of marasmus and kwashiorkor.

Cut-off points and confounding factors

An example, relating nutritional status to mortality risk from heart disease, illustrates some of the difficulties encountered when trying to relate the risk of infection to nutritional status. In most physiological measurements, such as blood pressure or haemoglobin concentration, it is o9o5 the norm to have a distribution with a median and various standard deviation scores above and below the median. These measurements may be used to predict the level of risk of a certain disease. Body mass index (BMI = weight/height2) for instance can be used to predict the likelihood of dying from a heart attack during the years after a simple anthropometric measurement. Two interesting aspects of this example emerge. Firstly, the relationship between nutrition and mortality is not linear. It is U shaped showing excess mortality at low levels and high levels of BMI. In theory it should therefore be possible to set cut-off points above and below which risk of mortality is increased. Between the points there should be little association between nutrition and risk of death. Secondly, the relationship is very different if cigarette smokers are analysed separately from non-smokers. Those who smoke have a higher risk of death from non-smokers with an identical BMI.

It has been frustrating to find that a number of different anthropometric, biochemical and clinical indices have been used to define nutritional status in the literature each with a variety of different cut-off points. The reason for selection of a specific cut-off point is rarely stated and all too frequently the analysis of association between nutrition and infections has been restricted to comparison of infection rates in those above and those below an arbitrarily defined cut-off rather than an examination of the level of nutrition at which risk of infections increase. The interaction between nutritional status and subsequent mortality (mostly from infection) reviewed later, shows different results in different communities. This implies that there is no single cut-off level which can be used universally to predict high risk individuals. For instance it is evident that there are considerable differences in the level of risk of mortality and infection between different populations of children of the same age and same weight and/or height. Presumably some of the co-existing biological variables, such as the presence of iron or vitamin A deficiency, or some of the social and economic variables, such as availability of health care or early treatment of infection, have quite marked influence on the outcome of an infection, independent of nutritional status. In the absence of a single cut-off point which is universally accepted as defining malnutrition, the definition used by the authors of the studies are reviewed is reported.

In the same way that the ‘confounding’ factor of smoking exerts an independent effect on mortality risk from heart disease, there are numerous confounding variables which affect the level of risk for morbidity and mortality associated with malnutrition. It is disappointing to find that these have rarely been taken into account in study designs. At the same time it is acknowledged that the complexity of confounding variables make it difficult to control for them all in a community based study.