These days, as a result of the epidemiological transition clinical practitioners and epidemiologists are confronting, unfortunately, a growing issue: chronic non-communicable diseases (CNCDs). These conditions - which include cardiovascular disease, some cancers, chronic respiratory disease and type 2 diabetes - explain around 60% of all deaths worldwide as well as accounting for 44% of premature deaths worldwide and having a huge negative economic impact (Daar et al., 2007). However, an important portion of CNCDs are preventable. Therefore, coordinated actions to deal with these conditions are necessary to avert the negative effects.
An important part of these concerted efforts must be conducted by clinical practitioners and epidemiologists. These professionals play a significative role in health promotion. Clinical practitioners have the chance, in most cases, dealing with individuals and epidemiologists have the opportunity taking population-based decisions in order to find and develop cost-effective strategies of health promotion.
A key concept regarding the role in health promotion for both clinical practitioners and epidemiologists is Capacity Building. This concept is defined as "the development of knowledge, skills, commitment, structures, systems and leadership to enable effective health promotion" (Smith, Tang, & Nutbeam, 2006). These actions are reflected at three different levels: the advancement of knowledge and skills among practitioners; the expansion of support and infrastructure for health promotion in organizations, and; the development of cohesiveness and partnership for health in communities (Smith, et al., 2006).
Often clinical practitioners must deal with patients with chronic disease in clinical settings. However, decisions are frequently based on palliative measures with the aim of reduce or cover a symptom and not taking into account the cause. As a result, there is no influence on the surrounding environment with the intention of reducing more similar cases. Therefore, clinical practitioners in an intersectoral action must create or promote healthy strategies to revert the situation at individual and population levels. Such efforts in general require a change in the society (Hemenway, 2010). However, clinical practitioners have the real experience with patients, and they can understand from other perspective the reality of their patients. For that reason the first step must be done by clinical practitioners due to they have the advantage to design, apply and promote realistic initiatives for requirements of the community. In this idea is possible to apply the concept of Community empowerment (WHO, 2009). This action could bring social and political change in favour of the community building from the individual to groups.
On the other hand, epidemiologists can provide evidence to create initiatives as well as re-evaluate ongoing initiatives in order to orientate and distribute efforts and resources for effective measures. Although benefactors are often perceived as unknown participants (Hemenway, 2010), because an important part of the population has almost no idea what epidemiologists do, these professionals are the link with the aim of transform statistics into real actions. In conclusion, epidemiologists are an important connection between facts, available evidence, practitioners, policies and implementation.
Clinical practitioners and epidemiologists must conduct coordinated strategies; however there is debate where the efforts must be orientated. For this reason after 25 years of the publication of the Geoffrey Rose's article (1985), Sick individuals and sick populations, continues to spark debate, discussion and analysis among health professionals. This situation is as a consequence of there is another context due to new available evidence and new challenges at Public Health level affecting in part the interesting Rose's theory (Doyle, Furey, & Flowers, 2006).
Decision taking: Dealing with individuals and populations
Geoffrey Rose (1985) stated different points to explain the advantages and disadvantages of individual and population-based approaches. Also, Rose's paper showed that individual and population approaches to improving health are fundamentally different and achieve different aims (Doyle, et al., 2006). From the point of view of modification of causes, Rose used examples of blood pressure and cholesterol to show that a small leftward shifting of the distribution curve of a single risk factor in a complete population could have a greater effect on morbidity and mortality than a large decrease in risk in the high-risk individuals (Manuel et al., 2006; Walls, McNeil, & Peeters, 2009).
The analysis of the effectiveness of health promotion interventions at individual and population levels can be addressed taking into account two important factors: quality of the evidence of causality; nature of the disease and its relationship with the nature of the intervention and the environmental context.
Quality of the evidence of causality
Rose (1985) in order to shift the curve suggested that to find determinants of prevalence and incidence, it is necessary to consider characteristics of populations, not characteristics of individuals. However, there are some detractors of this argument. For example, James McCormick (2001) stated that "good evidence of causal relationship must come from the study of individuals". This is probably a point for controversy due to the advances in genetic research during the last decades. Thus, this is still a call to action for clinical practitioners and, specifically, epidemiologists in their roles towards health promotion, because in their positions they can generate valid information to enhance and help this change in the rates.
However, in spite of the new available evidence regarding association and causality of diseases, it is necessary to improve systems of characterisation of the population using multi-component risk profiles or algorithms, which enable more precise estimation and identification of factors (Manuel, et al., 2006; McLaren, McIntyre, & Kirkpatrick, 2010). Therefore a better characterisation of the profile of the population and individuals enables effective decisions for epidemiologists and clinical practitioners.
In the last decade, initiatives of research involving epidemiologists and clinical practitioners have been resulting in more evidence of high-quality level. For example, the INTERHEART case-control study was conducted in 52 countries providing important information in different risk factors and concluding that nine risk factors predict nine out of ten myocardial infarctions (Yusuf et al., 2004). Within the risk factors was included the genetic factor. This factor reveals significant information about the individual variability in front of modification and adaptations of the environment in a population-based context. As a response to that evidence was conducted another sub-study analysing specifically the genetic variants associated with myocardial infarction risk factors, the INTERHEART genetics study (Anand et al., 2009). In this study were identified thirteen single-nucleotide polymorphisms with Myocardial infarction. However, both studies have limitations associated with the methodology of case-control studies. For this reason, in the last 5 years a multi-professional and multi-centric team has been working on the Prospective Urban Rural Epidemiology (PURE) study (Teo, Chow, Vaz, Rangarajan, & Yusuf, 2009). This information will provide better quality of data in order to establish association and causality at individual and population levels in a specific environmental context.
These global initiatives are providing better tools among clinical practitioners and epidemiologists to reduce chronic non-communicable diseases. Also, it will be possible to use effective algorithms of decision according to the nature of the disease and the burden of the disease. Therefore, the role of these professionals in health promotion will be enhanced by setting up evidence for policy formulation and decision making.
Nature of the disease, the nature of the intervention and environment
Diseases have, generally, multi-factorial, multidirectional and multidimensional causes. Also, the absence o presence of disease in individuals and population depends on environmental influences, such as economic conditions (Germov, 2005). Therefore, diseases have different behaviour and distribution within populations and individuals. However, Rose supported his theory in a normal distribution and shape (Harper, 2009),but not all risk factors and CNCDs have such condition. For example, the obesity distribution and is far more right skewed than 30 years ago (Flegal & Troiano, 2000; Harper, 2009).
This situation is important to take into account when clinical practitioners and epidemiologists are planning a health promotion intervention. In this case, decisions to implement a population or individual intervention depend on the distribution of risk, the shape of the exposure-risk curve and the cost-effectiveness of the intervention (Harper, 2009). In addition, these factors must be situated into an environmental context, where factors such as adherence, education of the population and socioeconomic status could affect final results. For example, in the USA a smoking-cessation campaign showed to be less effective among less-educated populations compared with those who have already more education (Niederdeppe, Fiore, Baker, & Smith, 2008). Therefore, population based campaign must be assessed in these aspects to avoid inequality in the intervention and results.
In order to assess part of the advantages of individual (cost-effectiveness and benefit: risk ratio favourable) and population approaches (radical, large potential for population), some researchers had simulated situations evaluating different strategies and even including new strategies such as "High baseline risk strategy (HBR) - treating people with an increased risk of disease". Manuel et al. (2006) evaluated these strategies using the New Zealand cardiovascular disease prevention guidelines. According to Manuel's analysis the modern strategy of treating people at high baseline risk (using Framingham risk algorithm), is potentially more effective than population and individual approach (see table 1).
From: Manuel, D. G., Lim, J., Tanuseputro, P., Anderson, G. M., Alter, D. A., Laupacis, A., et al. (2006). Revisiting Rose: strategies for reducing coronary heart disease. BMJ, 332(7542), 659-662.
In the model, the HBR risk approach includes 12.9% of the population, while the population intervention a 100% and the individual approach an 11.1%. However, the number of deaths avoided for HBR approach is 290 per 100.000 individuals, comparing with 125 and 42 per 100.000 individuals for population and individual approaches, respectively.
On the other hand, analysis of data related to obesity have been showing that population based interventions are more effective than individual strategies (Brownell et al., 2009; Walls, et al., 2009), supporting Rose's ideas. However, effective strategies in obesity must address population and environment, promoting new policies for environmental adaptation (Kahn, Robertson, Smith, & Eddy, 2008).
Therefore, reasonable evidence-based interventions in health promotion must include both a population health strategy and a high baseline risk strategy (modern approach). The positive results of these interventions will enhance one of the disadvantages of population approach regarding motivation in patients and specialists. The most important point, it will improve the motivation among the professionals called to promote new strategies, clinical practitioners and epidemiologists, among others.
Conclusion
Effectiveness evidence Population approaches frequently yielded small benefit to individuals.
