Corroborative findings from many different kinds of nutritional studies can and should be used to gather sufficient evidence that nutrition is related to a disease8. For the purpose of this discussion, nutritional studies examining the relationships between past, present and future dietary or nutrient intake exposures to health outcomes related to TB, HIV/AIDS, will be grouped into either observational or intervention studies. The observational or descriptive studies includes ecological, cross-sectional, case-control and cohort studies and the intervention studies, include all experimental studies in which the scientist controls the system by making measured interventions in humans, animals, tissues or cells and compares the outcomes of these interventions to reference, control or placebo situations8.
Observational or descriptive studies
The descriptive nutritional epidemiology of TB, HIV/AIDS will include data on the relationships between dietary exposures and incidence, mortality and risk. The different types of descriptive or observational studies that could provide data to be evaluated for policy decisions are as follows:
Ecological or correlation studies
In these studies, population or group indices of dietary intake or nutritional status (exposure) are related to population or group indices of health status (outcome). The unit of analysis is not an individual but a group defined by time (e.g. calendar year, birth cohort), geography (e.g. country, province or city), or sociodemographic characteristics (e.g.
ethnicity, religion or socioeconomic status)8. An example could be plotting the intake of a specific food, nutrient or marker of nutritional status (such as body mass index) against the incidence or severity (mortality) of TB, HIV or AIDS for each country in Africa.
Ecological studies are helpful when within-group (country or region) variation in exposure as small compared to between-group variation. Ecological studies are ideal to explore newly proposed hypotheses, serving as a basis to develop follow-up studies.
They are useful for monitoring national trends in health indicators and the wider environmental (social, cultural and economic) factors that influence health.
The limitations or disadvantages of ecological studies are that they only show associations between exposures and outcomes on group level (never on an individual level). They do not prove causal links. In fact, observed relationships or associations between a dietary exposure and health outcome may be with a different, diet- associated confounding factor (such as a lack of hygienic environment or lack of care).
Furthermore, a lack of an association between an aspect of diet and disease may disguise an actual relationship because of possible varying genetic predispositions in different populations9.
Cross-sectional studies
Cross-sectional studies measure exposures and outcomes in the present, and at the same time in individuals. These individuals are sampled from the population in such a way as to reflect the population characteristics for both exposure and outcome. If information on other population characteristics are collected (such as age, gender, income, education, etc.), the effects of these factors on the exposure-outcome relationship can also be assessed.
Some characteristics to note of cross-sectional studies to ensure that their results are reliable and usable8 are selection bias, information bias, sample size and power. If the source population and sampling frame are not clearly described in the methods, the results may not reflect the source population and may not be generalisable. If a particular sector of the source population is excluded (e.g. individuals too ill to participate), the prevalence estimate and reported associations may be misleading. The sample size must be adequate to provide a reliable estimate of the population prevalence. Sample size must, therefore, be calculated with available formulas and should be reported as part of the methods. There must be sufficient information reported in the methods to evaluate if the exposure, outcome and other variables were measured with the required level of accuracy to answer the question. Therefore, validation and standardisation of methods employed must be reported.
The main disadvantage of cross-sectional studies is that the exposures are not measured before the onset of the outcome: it is therefore not possible to disentangle cause from effect. It could be for example that the illness (HIV infection) changes dietary patterns and nutrient intakes. A measured relationship between dietary patterns and HIV infection will therefore not necessarily reflect any causal relationship between malnutrition and risk of infection.
Case-control (case-referent) studies
In these studies, patients with a disease are compared to controls without the disease. These studies recruit subjects or participants on the basis of their outcome status and then explore past exposure measures. Case-control studies are especially efficient where the outcome is rare and all available cases can be recruited from the population of interest. If the cases are self-selected, for example from people attending clinics, there may be selection bias because some patients, for various reasons, may not attend clinics. Therefore, the paper must report recruitment procedures clearly to be of use in gathering evidence. Controls should be recruited at random from the same population as the cases. After random selection, controls could be matched to cases on certain characteristics (e.g. age, gender, etc.) that are known to influence outcome but of themselves are of no direct interest in the study. Because case-control studies usually rely on past exposure, information bias is possible, especially when past dietary intakes are related to present outcomes. It is therefore important when reviewing these studies to assess if past exposure is reported with the same accuracy and precision in cases and controls. The impact of exposure on outcome in case- control nutritional studies is usually expressed as an odds ratio. Participants are ranked and intake grouped into quartiles or thirds of the distribution (e.g. high, medium and low) and risk of outcome assessed according to this distribution. The absolute intake is therefore not necessary. Provided that the ranking of intake is consistent between cases and controls, the estimate of risk will reflect the underlying risk of exposure on outcome8.
Case-control studies are suitable to study rare outcomes. They are restricted to assessing one outcome (or at the most subsets of related outcomes) but may be able to assess many different exposures. The biggest problem and disadvantage of case-control studies is the potential of information bias in past exposure dietary recalls8.
Cohort (prospective) studies
Cohort studies measure exposure in the present and outcome is assessed at some point in the future. A cohort study can therefore be used to draw causal inferences about the effect of the exposure on outcome because the exposure is measured before the outcome is known. In evaluating cohort studies, it should be noted that the sample is not always selected to represent the distribution within the whole population – it may be weighted to maximise the heterogeneity of exposure, or it might be selected to minimize loss to follow-up. These factors may be considered to be of more importance than representativeness of the sample. The sample size is important: it should be large enough and subjects should be followed up over a sufficient length of time to have sufficient disease endpoints to calculate an estimate of the risk of disease.
The biggest disadvantage or concern of cohort studies is loss to follow-up, particularly when this may be differential by level of exposure. Therefore, when reviewing and evaluating cohort studies, one must ensure that the authors have described the drop-out rate and the reasons for loss of follow-up. It is possible that those who were lost to follow-up differed in important ways to those who were not lost. Other disadvantages of cohort studies are that they are often large, take many years to conduct and are expensive.
The biggest advantage of cohort studies is that they provide strong evidence for a causal relationship between exposures and outcomes, because it is unlikely that the measure of exposure is biased, being measured before the outcome is known.
Intervention (experimental, biological) studies
These are studies where the researcher controls or manipulates the exposure. They include human clinical trials (therapeutic, secondary or tertiary prevention), field trials (primary prevention) or field intervention studies. The best known clinical trial design, often used to examine effects of pharmaceutical agents, is the double-blind, placebo-controlled, cross-over, randomised clinical trial. This design is also used to examine effects of dietary interventions in healthy subjects or patients. Intervention studies include experimental studies using animal models or biological material.
Human intervention trials provide the most robust test of a causal hypothesis. Human intervention trials are most often conducted at the individual level, but are sometimes conducted at population level. Experimental studies in animal models or other biological material are necessary to provide information on underlying biological mechanisms that could explain relationships between exposure and outcome in humans. It is not always possible, safe nor ethical to test some dietary interventions in humans, especially if the exposure is suspected of causing or increasing risk, or aggravating a disease. There are some general principles that are relevant to all types of intervention studies. Table II gives a checklist based on these principles that should be followed when reviewing intervention studies.
Gray and Gray10 matched the different types of studies to the types of questions or actions in health (dietetic) practice as follows:
Cross-sectional study – diagnosis;
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Randomised controlled trials – treatment;
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Cohort study – prognosis;
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Cohort study and case-control study – etiology or harm.
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This is a rather simplified model (as will be seen in the next chapter), but it does indicate the type of studies needed for evidence to formulate diagnostic and treatment guidelines, to assess etiology and prognosis and whether an intervention may be harmful.