Methodological
Viola Mathenia
Background: The results of cohort studies relating sodium (Na) intake to blood pressure-related cardiovascular disease (CVD) are inconsistent. To understand whether methodological issues account for the inconsistency, we reviewed the quality of these studies.
Methods and results: We reviewed cohort studies that examined the association between Na and CVD. We then identified methodological issues with greatest potential to alter the direction of association (reverse causality, systematic error in Na assessment), some potential to alter the direction of association (residual confounding, inadequate follow-up), and the potential to yield false null results (random error in Na assessment, insufficient power). We included 26 studies with 31 independent analyses. Of these, 13 found direct associations between Na and CVD, 8 found inverse associations, 2 found J-shaped associations, and 8 found null associations only. On average there were 3 to 4 methodological issues per study. Issues with greater potential to alter the direction of association were present in all but 1 of the 26 studies (systematic error, 22; reverse causality, 16). Issues with lesser potential to alter the direction of association were present in 18 studies, whereas those with potential to yield false null results were present in 23.
In the social sciences, methodological individualism is the principle that subjective individual motivation explains social phenomena, rather than class or group dynamics which are illusory or artificial and therefore cannot truly explain market or social phenomena. This concept was introduced as an assumption in the social sciences by Max Weber, and discussed in his book Economy and Society.[1]
Economist Mark Blaug has criticized over-reliance on methodological individualism in economics, saying that "it is helpful to note what methodological individualism strictly interpreted [...] would imply for economics. In effect, it would rule out all macroeconomic propositions that cannot be reduced to microeconomic ones [...] this amounts to saying goodbye to almost the whole of received macroeconomics. There must be something wrong with a methodological principle that has such devastating implications".[5]
The methodological framework is a robust process with guidelines and points to be examined, on a case-by-case basis, and in a sound and proportionate manner according to the specifics of each assistance measure. It ensures the identification risks and benefits, as well as provisions designed to prevent diversion or abuse of equipment.
The Standing Committee Meth@Mig provides a forum for discussing methodological approaches and tools in migration research and assessing the best options available for tackling manifold methodological challenges. The Standing Committee takes on a pluralist perspective as it addresses (1) issues relevant across a wide range of research methods in migration studies, such as obtaining informed consent in cross-cultural settings, gaining access to hard-to-reach populations, operationalising relevant concepts, and leveraging the potential of new communication technologies, as well as (2) issues relevant for specific research approaches (be they quantitative, qualitative, mixed-methods or experimental) as applied to the study of international migration in all its facets and dimensions.
Due to its transversal methodological profile, Meth@Mig is uniquely suited to cooperate with various other IMISCOE Standing Committees that are mainly defined by substantive research agendas. Such cooperation may, for instance, consist of jointly organised events or publications. The Standing Committee places special emphasis on sharing innovative procedures and on interconnecting researchers from different methodological schools as well as migration scholars and experts in research methodology.
This report gives a specific focus to describing the methodology underpinning the Gender Equality Index. It presents the different steps taken in the computation of the Gender Equality Index 2017 as well as the changes made to the methodological and measurement framework in the process of updating the Index.
Reliable and comparable analysis of risks to health is key for preventing disease and injury. Causal attribution of morbidity and mortality to risk factors has traditionally been conducted in the context of methodological traditions of individual risk factors, often in a limited number of settings, restricting comparability.
In this paper, we discuss the conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines. The issues include: comparing the burden of disease due to the observed exposure distribution in a population with the burden from a hypothetical distribution or series of distributions, rather than a single reference level such as non-exposed; considering the multiple stages in the causal network of interactions among risk factor(s) and disease outcome to allow making inferences about some combinations of risk factors for which epidemiological studies have not been conducted, including the joint effects of multiple risk factors; calculating the health loss due to risk factor(s) as a time-indexed "stream" of disease burden due to a time-indexed "stream" of exposure, including consideration of discounting; and the sources of uncertainty.
It is important to emphasize that risk assessment, as defined above, is distinct from intervention analysis, whose purpose is estimating the benefits of a given intervention or group of interventions in a specific population and time. Rather, risk assessment aims at mapping alternative population health scenarios with changes in distribution of exposure to risk factors over time, irrespective of whether exposure change is achievable using existing interventions. Therefore, while intervention analysis is a valuable input into cost-effectiveness studies, risk assessment contributes to assessing research and policy options for reducing disease burden by changing population exposure to risk factors. Summary measures of population health (SMPH) and their use in the burden of disease analysis are discussed elsewhere [21, 22]. The next three sections of this paper discuss the conceptual basis and methodological issues for the remaining three of the above points. We then discuss the sources and quantification of uncertainty.
Mathers et al. [23] described two traditions for causal attribution of health determinants, outcomes, or states: categorical attribution and counterfactual analysis. In categorical attribution, an event such as death is attributed to a single cause (such as a disease or risk factor) or group of causes according to a defined set of rules (hence 100% of the event is attributed to the single cause or group of causes). The International Classification of Disease system (ICD) attribution of causes of death [24] and attribution of some injuries to alcohol or occupational conditions are examples of categorical attribution. In counterfactual analysis, the contribution of one or a group of diseases, injuries, or risk factors to a summary measure of population health (SMPH) is estimated by comparing the current or future levels of the SMPH with the levels that would be expected under some alternative hypothetical scenario including the absence of or reduction in the disease(s) or risk factor(s) of interest. This hypothetical scenario is referred to as the counterfactual (see Maldonado and Greenland [25] for a discussion of conceptual and methodological issues in use of a counterfactuals).
We have described a framework for systematic quantification of the burden of disease due to risk factors which attempts to unify the growing interest in health risks in a number of health, physical, and social sciences. We have discussed the following attributes of the framework along with the corresponding methodological issues that arise in its application:
For more effective and affordable implementation of a prevention paradigm, policies, programs, and scientific research should acknowledge and take advantage of the interactive role of major risks to health, across and within causality layers. Despite methodological complexity and empirical difficulties, especially in estimating time-based multi-risk exposures, this framework provides a consistent basis for better information about the causes of disease and injury.
CJL Murray and AD Lopez developed the initial CRA framework and M Ezzati further methodological aspects in discussion with other authors. Majid Ezzati drafted the paper, with contributions from other authors.
In this talk, Todd Little, professor of Educational Psychology and Leadership at Texas Tech University, will present a number of critical methodological practices that are essential to address the challenging research questions surrounding systems of injustice. Advanced methodological tools provide unparalleled opportunities to answer research questions in such a way that policy and practice are properly served.
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