Abstract
The most common modeling approaches to understanding incidence, prevalence and control of chronic diseases in populations, such as statistical regression models, are limited when it comes to dealing with the complexity of those problems. Those complex adaptive systems have characteristics such as emerging properties, self-organization and feedbacks, which structure the system stability and resistance to changes. Recently, system science approaches have been proposed to deal with the range, complexity, and multifactor nature of those public health problems. In this paper we applied a multilevel systemic approach to create an integrated, coherent, and increasingly precise conceptual framework, capable of aggregating different partial or specialized studies, based on the challenges of the Longitudinal Study of Adult Health – ELSA-Brasil. The failure to control blood pressure found in several of the study's subjects was discussed, based on the proposed model, analyzing different loops, time lags, and feedback that influence this outcome in a population with high educational level, with reasonably good health services access. We were able to identify the internal circularities and cycles that generate the system’s resistance to change. We believe that this study can contribute to propose some new possibilities of the research agenda and to the discussion of integrated actions in the field of public health.
Highlights
The second half of the 1990s witnessed a debate between critics and defenders of Modern Epidemiology [1]
CDVs and Diabetes: A Study Based on Qualitative Systemic Approach
This paper presents a systemic model for CVD&Diabetes in the context of the ELSA-Brasil project, employing an original “soft” approach, whose theoretical foundations can be found in [42,43,44,45]
Summary
The second half of the 1990s witnessed a debate between critics and defenders of Modern Epidemiology [1]. The “examples or comments” may include needs or opportunities for future research (including literature searches, additional data collection, methods etc.), bibliographic references, examples (for greater clarity), and, whenever they are not obvious, the semantic connections that may exist between the relationship that is being described and others, as a check on the model’s consistency This column is dedicated basically to clarifying the model. The individual's active influence on the Body System's blood pressure (BP) occurs predominantly through the relationship R104, which comes from the Active Life subsystem, where the specific actual healthcare or health damaging actions can take place, including taking medication, plus lifestyle.
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