A conceptual model for studies on social determinants of health in Brazilian municipalities

Francisco Carlos Carvalho de Melo Rodolfo Ferreira Ribeiro da Costa Jansen Maia Del Corso About the authors

Abstract

The conceptual models of Social Determinants of Health (SDH) available in the literature, although useful for comprehending mechanisms that affect the results of the health system on the living conditions of the population, present limitations regarding their application in empirical studies and, consequently, in guiding public health policies. This occurs because the categories adopted by these models are not adequately represented by indicators of homogeneous variables subject to mathematical or statistical manipulations in a simple relation system. This study aims to help filling this gap by proposing an operationally applicable SDH conceptual model - reproducible as a mathematical or statistical model - to support studies and define strategies concerning public health. We resorted to the literature to review previously developed conceptual models, identifying a set of SDH and presenting recommendations and choice criteria. Then we located reliable data sources supplying indicators and variables listed in historic series and proposed an applicable conceptual model, which requires specific methods and tools for a systemic approach for operationalization.

Keywords:
Social Determinants of Health; SDH Conceptual Models; Systemic Approach

Introduction

Since 1991, conceptual models of social determinants of health (SDH) have been developed for comprehending mechanisms that affect the results of the health system on the living conditions of the population. These models report possible connections among SDH and locate strategic points for guiding policies. Although useful, they are often ill-suited to local contexts and the nuances of SDH and rarely offer policy-makers a clear direction for policy development (Exworthy, 2008EXWORTHY, M. Policy to tackle the social determinants of health: using conceptual models to understand the policy process. Health Policy and Planning, Londres, v. 23, p. 318-327, 2008.). This occurs because they are considered disparate variables, gathering biological, genetic, behavioral, political, cultural, and social factors within the same conceptual framework, with few indications on their practical operationalization.

As addressed by Evans and Stoddart (1994EVANS, R. G.; STODDART, G. L. Producing health, consuming health care. In: EVANS, R. G.; BAKER, M. L.; MARMOR, T. R. (Org.). Why are some people healthy and other no? The determinants of health of populations. Hawthorne: Aldine de Gruyer, 1994. p. 27-64., 2003EVANS, R. G.; STODDART G. L. Consuming research, producing policy? American Journal of Public Health, Oxford, v. 99, n. 3, p. 371-379, 2003.), conceptual models available in the literature have limitations that hamper their application in public health policies management. The authors do not suggest treating the categories of their model as if they could be adequately represented by a homogeneous variable or subject to mathematical or statistical manipulations, which would render inadequate combined and integral reproduction. For them, overcoming this limitation requires a systemic approach rather than a simple and linear system of relationships, or even a causal factor - as health depends on everything, all the time.

This study aims to help filling this gap by proposing an operationally applicable SDH conceptual model - reproducible as a mathematical or statistical model - to support studies and define strategies concerning public health. For that, we resorted to the literature for reviewing previously developed conceptual models, identifying a set of SDH and presenting recommendations and choice criteria. Then we located reliable data sources supplying indicators and variables listed in historic series and proposed an applicable conceptual model, which requires methods and tools specific for a systemic approach for operationalization.

Conceptual models of reference

By synthesizing conceptual models adopted by different studies on health disparities, Roux (2012ROUX, A. V. D. Conceptual approaches to the study of health disparities. Annual Review of Public Health, Palo Alto, v. 33, p. 41-58, 2012.) reports that their borders are fluid and that intermediate options are adopted, combining mutual elements among them. However, the author stresses fundamental characteristics that distinguish the conceptual approaches and their usefulness for studies in this field, grouping them into four sets: (1) genetic model; (2) fundamental cause model; (3) pathways model; and (4) interaction model - the role of gene-environment interaction. Our study highlights models with greater emphasis on the contexts of environment, society, economy, infrastructure, health services productions, and results regarding health conditions.

Different studies analyzed and discussed the available models; yet, those that influenced this study proposal are the prevailing ones: Dahlgren and Whitehead (1991DAHLGREN, G.; WHITEHEAD, M. Policies and strategies to promote social equity in health. Estocolmo: Institute for Future Studies, 1991.), Evans and Stoddart (1994EVANS, R. G.; STODDART, G. L. Producing health, consuming health care. In: EVANS, R. G.; BAKER, M. L.; MARMOR, T. R. (Org.). Why are some people healthy and other no? The determinants of health of populations. Hawthorne: Aldine de Gruyer, 1994. p. 27-64.), Diderichsen, Evans and Whitehead (2001DIDERICHSEN, F.; EVANS, T.; WHITEHEAD, M. The social basis of disparities in health. In: EVANS, T.; WHITEHEAD, M. et al. (Org.). Challenging inequities in health: from ethics to action. Nova York: Oxford University Press, 2001. p. 13-23.), and Solar and Irwin (2007SOLAR, O.; IRWIN, A. A conceptual framework for action on the social determinants of health: discussion paper for the Commission on Social Determinants of Health DRAFT. Genebra: WHO, 2007. Disponível em: <Disponível em: https://bit.ly/34ok31R >. Acesso em: 14 ago. 2015.
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), as well as the Dimension Matrix for Evaluation of the Health System Performance, presented by Viacava et al. (2012VIACAVA, F. et al. PROADESS - Avaliação de Desempenho do Sistema de Saúde Brasileiro: indicadores para monitoramento: relatório final. Rio de Janeiro: Fundação Oswaldo Cruz, 2012.), whose key characteristics will be address below.

Dahlgren and Whitehead (1991DAHLGREN, G.; WHITEHEAD, M. Policies and strategies to promote social equity in health. Estocolmo: Institute for Future Studies, 1991.) developed a pioneering model, revised in 2007, whose conceptual structure should be deemed as an interdependent system to improve health and reduce health risks. They emphasize that health policies may target strategies at any of the four policy levels embodied in the model, without necessarily including all of them.

For Evans and Stoddart (1994EVANS, R. G.; STODDART, G. L. Producing health, consuming health care. In: EVANS, R. G.; BAKER, M. L.; MARMOR, T. R. (Org.). Why are some people healthy and other no? The determinants of health of populations. Hawthorne: Aldine de Gruyer, 1994. p. 27-64., 2003EVANS, R. G.; STODDART G. L. Consuming research, producing policy? American Journal of Public Health, Oxford, v. 99, n. 3, p. 371-379, 2003.), individual’s behavioral and biological responses to social and physical environments and genetic load influence how they perceive their health and functional capacity and reflect on their well-being - health policy goal. Thus, the conclusive proof of a health policy is not only disease absence, but also its ability to provide well-being (Viacava et al., 2012VIACAVA, F. et al. PROADESS - Avaliação de Desempenho do Sistema de Saúde Brasileiro: indicadores para monitoramento: relatório final. Rio de Janeiro: Fundação Oswaldo Cruz, 2012.).

According to Diderichsen, Evans and Whitehead (2001DIDERICHSEN, F.; EVANS, T.; WHITEHEAD, M. The social basis of disparities in health. In: EVANS, T.; WHITEHEAD, M. et al. (Org.). Challenging inequities in health: from ethics to action. Nova York: Oxford University Press, 2001. p. 13-23.), many individual risk factors presuppose (or are strongly associated with) the social position and broader social context - area of residence (urban or rural), work environment, or the social and economic policies in force. Social context and social position might as well play a key role in the “social consequences” of a disease or injury.

The model proposed by Diderichsen, Evans and Whitehead (2001DIDERICHSEN, F.; EVANS, T.; WHITEHEAD, M. The social basis of disparities in health. In: EVANS, T.; WHITEHEAD, M. et al. (Org.). Challenging inequities in health: from ethics to action. Nova York: Oxford University Press, 2001. p. 13-23.), influenced, with some support, the development of the Commission on Social Determinants of Health model (Solar; Irwin, 2007SOLAR, O.; IRWIN, A. A conceptual framework for action on the social determinants of health: discussion paper for the Commission on Social Determinants of Health DRAFT. Genebra: WHO, 2007. Disponível em: <Disponível em: https://bit.ly/34ok31R >. Acesso em: 14 ago. 2015.
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), which contemplates: political and socioeconomic contexts, structural determinants of health inequalities, and intermediate determinants of health. Such a model differs from others due to its attributed importance on the political and socioeconomic contexts. Solar and Irwin (2007SOLAR, O.; IRWIN, A. A conceptual framework for action on the social determinants of health: discussion paper for the Commission on Social Determinants of Health DRAFT. Genebra: WHO, 2007. Disponível em: <Disponível em: https://bit.ly/34ok31R >. Acesso em: 14 ago. 2015.
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) state that their model contemplates social variables that cannot be directly measured at the individual level. This model is particularly important for our study, as it reinforces the possibility of studying SDH at the social level rather than at the individual level - which is often applied.

The authors adopted the terms suggested by Graham (2004GRAHAM, H. Social determinants and their unequal distribution: clarifying policy understandings. The Milbank Quarterly, Oxford, v. 82, n. 1, p. 101-124, 2004.) and declared that the expression “structural determinants” refers specifically to the components of people’s socioeconomic position. These structural determinants, combined with the main characteristics of the socioeconomic and political contexts, comprise the social determinants of health inequities (or inequalities), operating by a series of intermediate social factors, or SDH.

Intermediate factors arise from the underlying social stratification setting and determine disparities in exposure and vulnerability regarding compromising health conditions. The models resemble each other by stressing genetic and biological processes mediating the effects of social determinants on health. The main categories of intermediate determinants on health are: material and psychosocial circumstances, behavioral and/or biological factors, and the health system itself as a social determinant.

Viacava et al. (2012VIACAVA, F. et al. PROADESS - Avaliação de Desempenho do Sistema de Saúde Brasileiro: indicadores para monitoramento: relatório final. Rio de Janeiro: Fundação Oswaldo Cruz, 2012.) developed a method to evaluate the Brazilian health system, employing the Dimension Matrix for Evaluation of the Health System Performance, based on the proposal of the Canadian Institute for Health Information and supported by the theoretical model of health production developed by Evans and Stoddart (1994EVANS, R. G.; STODDART, G. L. Producing health, consuming health care. In: EVANS, R. G.; BAKER, M. L.; MARMOR, T. R. (Org.). Why are some people healthy and other no? The determinants of health of populations. Hawthorne: Aldine de Gruyer, 1994. p. 27-64.). The dimensions applied by the Canadian model are: non-medical determinants of health (social, biological, and behavioral), health conditions, health system performance, and characteristics of both the community and health system (Raphael, 2009RAPHAEL, D. Social determinants of health: Canadian perspectives. 2. ed. Toronto: Canadian Scholars’ Press Inc., 2009. Disponível em: <Disponível em: https://bit.ly/39QTELn >. Acesso em: 7 abr. 2015.
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; Mr. Wolfson; Alvarez, 2002WOLFSON, M.; ALVAREZ, R. Towards integrated and coherent health information systems for performance monitoring: the Canadian experience. Measuring up: improving health systems performance in OECD countries. Paris: OECD, 2002.). The matrix added to this set the health system structure - its financing and human and material resources.

These SDH conceptual models present similarities within their structure, which implies the possibility of combining them into a compound form (Graham, 2004GRAHAM, H. Social determinants and their unequal distribution: clarifying policy understandings. The Milbank Quarterly, Oxford, v. 82, n. 1, p. 101-124, 2004.). Yet, Graham (2004GRAHAM, H. Social determinants and their unequal distribution: clarifying policy understandings. The Milbank Quarterly, Oxford, v. 82, n. 1, p. 101-124, 2004.), Exworthy (2008EXWORTHY, M. Policy to tackle the social determinants of health: using conceptual models to understand the policy process. Health Policy and Planning, Londres, v. 23, p. 318-327, 2008.), and O’Campo (2012O’CAMPO, P. Are we producing the right kind of actionable evidence for the social determinants of health? Journal of Urban Health: Bulletin of the New York Academy of Medicine, Nova York, v. 89, n. 6, p. 881-893, 2012.) warn against using public policies to face SDH for several reasons, among which we highlight four:

  1. Each analyzed model presents an important contribution, but none can meet all requirements by itself. Yet, by combining elements of various models, we may reach a structure to spark the debate.

  2. All SDH models are useful conceptual devices for identifying causal pathways that lead to different impacts on health. Yet, SDH models rarely offer policy-makers a clear direction for developing policies.

  3. SDH call for concrete policies of different organizations and sectors. Intergovernmental and intersectoral partnerships are fundamental to formulate strategies to approach SDH, but evidence has shown that these partnerships are hampered by cultural, organizational, and financial issues.

  4. Identifying, monitoring, and analyzing epidemiological changes over time are key for the political decision-making process. However, routine data are usually unavailable, of poor quality, or collected during insufficient periods to help policy decision-making.

Any model entails a broad and diversified interpretation of the health needs of the population. To elaborate a proposal, we must consider the validity of the theoretical-conceptual assumptions of the presented models and the warnings arising from them, as well as the purpose of applying them in a practical way, focusing on the social rather than on the individual level, so that relations can be interpreted by mathematical or statistical models.

Social determinants of health: types and choice criteria

Each conceptual model applies a broad set of SDH to explain and relate factors that promote health. The first challenge is identifying which determinants can be considered to develop a conceptual model. The next is designating which SDH will compose the model. This process must consider the theory and the availability of reliable data, especially if the focus is the operational or empirical application of the model. Webster and Lipp (2009WEBSTER, P.; LIPP, A. The evolution of the WHO city health profiles: a content review. Health Promotion International, Londres, v. 24, p. 56-63, 2009.) and Raphael (2009RAPHAEL, D. Social determinants of health: Canadian perspectives. 2. ed. Toronto: Canadian Scholars’ Press Inc., 2009. Disponível em: <Disponível em: https://bit.ly/39QTELn >. Acesso em: 7 abr. 2015.
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) suggest applying objective and subjective variables and indicators; Chart 1 synthetically shows their wide variety.

A broad and diverse set of determinants, containing direct and indirect factors, may affect the health condition of the population. Whereas some SDH can be easily quantifiable, others cannot. Some refer to individual issues while others refer to social characteristics as a whole. Chart 1 shows a variety of SDH, which indicates that selecting them for a systematized model requires attention.

For selecting SDH, we must follow consistent criteria, appropriate to the model. Chart 2 - built on the contributions of Fulop et al. (2001FULOP, N. et al. (Org.). Studying the organization and delivery of health services, research methods. Londres: Routledge Publishers, 2001.), Exworthy (2008EXWORTHY, M. Policy to tackle the social determinants of health: using conceptual models to understand the policy process. Health Policy and Planning, Londres, v. 23, p. 318-327, 2008.), Raphael (2009RAPHAEL, D. Social determinants of health: Canadian perspectives. 2. ed. Toronto: Canadian Scholars’ Press Inc., 2009. Disponível em: <Disponível em: https://bit.ly/39QTELn >. Acesso em: 7 abr. 2015.
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) and Craig, Thomas and Monroe (2015CRAIG, W.; THOMAS, L. C.; MONROE, J. A. M. The value of the “system” in public health services and systems research. American Journal of Public Health, Oxford, v. 105, n. 2, p. 147-149, 2015.) - synthesizes the key recommendations for selecting a set of SDH to develop a conceptual model.

Chart 1
Types of social determinants of health

Chart 2
Synthesis of recommendations for selecting SDH

Chart 2 depicts recommendations focused on the need to define management level and/or geographical approach, which establishes the scope of the chosen determinants. Acting upon social determinants - since it requires concrete policies of different organizations and sectors - entails an alignment with strategy - which involves different governmental structures, organizations, and public and private sectors - to ensure coherence with the lay public’s understanding of the factors influencing health and well-being. Finally, the selected SDH should allow us to explore and systemically interpret both the relations among them and health system interactions with other systems.

The nature/type of study must guide the choice for a management level and/or geographical approach. Mills (2012MILLS, A. Health policy and systems research: defining the terrain; identifying the methods. Health Policy and Planning, Londres, v. 27, p. 1-7, 2012.) exemplifies that political and historical analyses often focus on the meso and macro levels, whereas epidemiology and psychology focus on meso and micro. Our study is mainly focused on the meso level: we understand municipality as an analysis unit that limits the inclusion of subsystems interacting with the health system. Meso level comprises the local health system, involving broader economic and social structures that require concrete policies aligned with government structures. The next challenge posed for selecting SDH is developing a conceptual model in which these indicators or variables will be arranged and related.

Conceptual model for studies on SDH

Our proposed conceptual model has no intention of replacing existing models. However, it suggests an objective form of interpreting the probable scope and interrelationships among SDH in a more simplified, observable and applicable manner. It was influenced by the previously presented models, particularly by the model proposed by Solar and Irwin (2007SOLAR, O.; IRWIN, A. A conceptual framework for action on the social determinants of health: discussion paper for the Commission on Social Determinants of Health DRAFT. Genebra: WHO, 2007. Disponível em: <Disponível em: https://bit.ly/34ok31R >. Acesso em: 14 ago. 2015.
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), and selected SDH variables based on the recommendations depicted in Chart 2.

Its proposed set of SDH does not represent routine data at individual level and is aligned with active parts of government policies at municipal level. The SDH address information regarding: population; economy, public investment, and municipal management efficiency; environmental conditions; infrastructure; health conditions; health coverage; and health services production, provided by mortality indicators. Information on these matters are available in official electronic databases, with open access, arranged in time series, and with reasonable level of security and reliability. Namely:

  • The Industry Federation of the State of Rio de Janeiro (Firjan);

  • Brazilian Institute of Geography and Statistics (IBGE);

  • Ministry of Health/National Registry of Health Establishments (MS/CNES);

  • Ministry of Health/Department of Informatics of the Brazilian National Health System (MS/DataSUS);

  • Ministry of Health/Primary Health Care Information System (MS/Siab);

  • Ministry of Health/Outpatient Information Systems (MS/SIA);

  • Ministry of Health/Hospital Information System (MS/SIH);

  • Ministry of Health/Mortality Information System (MS/SIM);

  • Ministry of Health/System on Public Health Budgets (MS/Siops);

  • Ministry of Labor/General Register of Employed and Unemployed (MTb/Caged);

  • Organization of Ibero-American States for Education, Science and Culture (Violence Map);

  • Brazilian National Treasury/Secretariat Finance (STN/Finbra).

Such electronic systems hold data at national, state, and municipal levels. They enabled us to identify and select 41 indicators or variables (Chart 3) that were grouped into seven dimensions based on the literature. We may increase the amount of useful data by using the electronic systems mentioned or by identifying other reliable sources. Then they must be reduced and grouped, using, for example, exploratory factor analysis to ease its operationalization by other mathematical or statistical resources.

However, the consulted databases impose some limitations regarding time-series availability and missing or inconsistent data - especially for small municipalities; for example, in Siab - for some important information that could have been considered by our proposed model.

Chart 3
SDH indicators and variables, available in official database

The elements shown in Chart 3 may be associated and analyzed in a systemic way - which is the approach proposed by WHO for studies on health systems. According to WHO, a health system consists of all organizations, people, and actions whose primary intent is to promote, restore, or maintain health. This includes efforts to influence SDH, as well as more direct health-improving activities (Pourbohloul; Kieny, 2011POURBOHLOUL, B.; KIENY, M. P. Complex systems analysis: towards holistic approaches to health systems planning and policy. Bulletin of the World Health Organization, Genebra, v. 89, n. 4, p. 242, 2011.; WHO, 2007WHO - WORLD HEALTH ORGANIZATION. Everybody’s business: strengthening health systems to improve health outcomes - WHO’s framework for action. Genebra, 2007.). Thus, systemic thinking tends to increase the perceived quality of the system constituting elements; or to increase the perception of the whole, its parts, and interactions within and between levels.

In this approach, an organization and its environment (context) are deemed as interrelated and interdependent parts that form a complex whole, rather than separate entities. Structures, interaction patterns, events, and organizational dynamics are factored as components of larger structures, which helps to anticipate (and not simply react to) certain occasions, and to better prepare for emerging challenges (Atun, 2012ATUN, R. Health systems, systems thinking and innovation. Health Policy Plan, Oxford, v. 27, p. iv4-iv8, 2012.; Peters, 2014PETERS, D. H. The application of systems thinking in health: why use systems thinking? Health Research Policy and Systems, Londres, p. 12-51, 2014.). It is thriving to adopt the systemic approach as theoretical focus for studies on health, which, according to Craig, Thomas and Monroe (2015CRAIG, W.; THOMAS, L. C.; MONROE, J. A. M. The value of the “system” in public health services and systems research. American Journal of Public Health, Oxford, v. 105, n. 2, p. 147-149, 2015.), may include:

  1. the governmental public health (federal, state, tribal, and local and territorial agencies that function as a governmental entity for public health).

  2. the public health system or partnerships that contribute for public health.

  3. other systems and structural components comprised by public health infrastructure (i.e. information systems, work force).

  4. systems science employed in exploring and understanding causal ties, complex dynamics, and interactions.

Focusing on the system is of paramount importance for improving health systems performance (Mays; Scutchfield, 2015MAYS, G. P.; SCUTCHFIELD, F. D. The value of the “system” in public health services and systems research (editorials). American Journal of Public Health, Oxford, v. 105, n. 2, p. S147-S149, 2015.). Previous studies by Luke and Stamatakis (2012LUKE, D. A.; STAMATAKIS, K. A. Systems science methods in public health: dynamics, networks, and agents. Annual Review of Public Health, Palo Alto, v. 33, p. 357-376, 2012.) and Willis et al. (2012WILLIS, C. D. et al. System tools for system change. BMJ Quality & Safety, Londres, v. 21, p. 250-262, 2012.) identified proper theories, methods, and tools for studying systems. (2012). Peters (2014PETERS, D. H. The application of systems thinking in health: why use systems thinking? Health Research Policy and Systems, Londres, p. 12-51, 2014.) synthesized a set of resources applicable to studies in the field of health system, depending on their characteristics. Figure 1 shows a conceptual model for analyzing health systems in medium-sized Brazilian municipalities; this model demands a systemic approach based on appropriate metrics.

Figure 1
Conceptual model for analyzing health systems in Brazilian municipalities

The conceptual model is described below. It recommends applying appropriate methods and tools for the systemic approach, in which the relations among elements would cover all indicators at the same time. We decided to reinforce the importance of each dimension by citing previous studies that applied conventional metrics.

Column I: formed by three dimensions (economic and socio-demographic, environmental, and fiscal) concerning demographic profile, income and employability, environmental indicators associated with basic sanitation, and governance - expressed by indicators of municipalities’ fiscal management, a health system element (Savigny; Adam, 2009SAVIGNY, D.; ADAM, T. (Org.). Aplicación del pensamiento sistémico al fortalecimiento de los sistemas de salud. Alianza para la investigación en políticas y sistemas de salud. Genebra: OMS, 2009.).

Studies on sanitation - Teixeira and Guilhermino (2006TEIXEIRA, J. C.; GUILHERMINO, R. L. Análise da associação entre saneamento e saúde nos estados brasileiros, empregando dados secundários do banco de dados indicadores e dados básicos para a saúde 2003 - IDB 2003. Engenharia Sanitária e Ambiental, Rio de Janeiro, v. 11, n. 3, p. 277-282, 2006.), Sousa and Leite Filho (2008SOUSA, T. R. V.; LEITE FILHO, P. A. M. Análise por dados em painel do status de saúde no Nordeste brasileiro. Revista de Saúde Pública, São Paulo, v. 42, n. 5, p. 796-804, 2008.), Ferrari and Bertolozzi (2012FERRARI, R. A. P.; BERTOLOZZI, M. R. Mortalidade pós-neonatal no território brasileiro: uma revisão da literatura. Revista da Escola de Enfermagem da USP, São Paulo, v. 46, n. 5, p. 1207-1214, 2012.) and Rasella (2013RASELLA, D. Impacto do Programa Água para Todos (PAT): sobre a morbi-mortalidade por diarreia em crianças do estado da Bahia, Brasil. Cadernos de Saúde Pública, Rio de Janeiro, v. 29, n. 1, p. 40-50, 2013.) - reported negative and statistically significant associations between basic sanitation (access to piped water, sanitary sewage, and waste collection) and infant mortality.

Column II: formed by two dimensions (social investment and urban infrastructure); their indicators present municipal expenditures in public policies as a proxy for the importance attributed to them by municipal administration. The financing of health systems is also an element of the health system (Savigny; Adam, 2009SAVIGNY, D.; ADAM, T. (Org.). Aplicación del pensamiento sistémico al fortalecimiento de los sistemas de salud. Alianza para la investigación en políticas y sistemas de salud. Genebra: OMS, 2009.). Other functions and activities of service provision and interventions in areas of public policy development engage with health policies development and results. Overall, public expenditure growth is expected to be significantly and negatively related to mortality (Ará et al. 2005ARÁ, O. A. et al. Health system outcomes and determinants amenable to public health in industrialized countries: a pooled, cross-sectional time series analysis. BMC Public Health, Utrecht, v. 5, n. 8, p. 1-10, 2005.; Andrade, 2010. Teixeira; Fortunato, 2014; Kim; Saada, 2013KIM, D.; SAADA, A. The social determinants of infant mortality and birth outcomes in Western developed nations: a cross-country systematic review. International Journal of Environmental Research and Public Health, Basel, v. 10, n. 6, p. 2296-2335, 2013.) or to expenditure, inequality, and infant mortality - as reported by Bradley et al. (2011BRADLEY, E. H. et al. Health and social services expenditures: associations with health outcomes. BMJ Quality Safety, Hoboken, v. 20, n. 10, p. 826-831, 2011.) and Ramalho et al. (2013RAMALHO, W. M. et al. As desigualdades na mortalidade infantil entre municípios no Brasil de acordo com o Índice de Desenvolvimento Familiar, 2006-2008. Revista Panamericana de Salud Pública, Washington, v. 33, n. 3, p. 205-212, 2013.). Investing in internal control has acquired increasing importance in the Brazilian public management scope, either by national legislation requirement or by the acknowledgment of its relevance for successfully implementing public policies.

Column III: formed by two dimensions (infrastructure and health services provision), directly associated with facilities and equipment and the results in the provision of health services, as expressed by Savigny and Adam (2009SAVIGNY, D.; ADAM, T. (Org.). Aplicación del pensamiento sistémico al fortalecimiento de los sistemas de salud. Alianza para la investigación en políticas y sistemas de salud. Genebra: OMS, 2009.). The infrastructure of health services is expressed in the availability of health facilities and primary and specialized medical centers, as well as hospital beds associated or not with the Brazilian National Health System (SUS).

Health services provision may be very broad. However, some indicators may not be available in reliable sources with time series arrangement. Public health care growth is often expected to negatively impact mortality rates. Researchers such as Cavalini and Leon (2008CAVALINI, L. T.; LEON, A. C. M. P. Morbidade e mortalidade nos municípios brasileiros: um estudo multinível da associação entre indicadores socioeconômicos e de saúde. International Journal of Epidemiology, Oxford, v. 37, n. 4, p. 775-783, 2008.) and Lansky et al. (2014LANSKY, S. et al. Pesquisa Nascer no Brasil: perfil da mortalidade neonatal e avaliação da assistência à gestante e ao recém-nascido. Caderno de Saúde Pública, Rio de Janeiro, v. 30, supl., p. S192-S207, 2014.) developed studies on the Family Health Strategy, the main health care program in Brazil.

The proposed model contemplates private health care. Overall, the increase in private health expenditures is expected to reduce public health expenditure; likewise, the increase in health insurance coverage is associated with reduced mortality indicators. There is a wide literature dedicated to private health care, such as Leite (2009LEITE, F. Taxas de mortalidade entre beneficiários de planos de saúde e a população brasileira em 2004 e 2005: o que mudou? São Paulo: IESS, 2009.), Nishijima, Cyrillo and Biasoto Junior (2010NISHIJIMA, M.; CYRILLO, D. C.; BIASOTO JUNIOR, G. Análise econômica da interação entre a infraestrutura da saúde pública e privada no Brasil. Economia e Sociedade, Campinas, v. 19, n. 3, p. 589-611, 2010.), Blanchette and Tolley (2001BLANCHETTE, C.; TOLLEY, E. Public and private sector involvement in health-care systems: a comparison of OECD countries. [S.l.], 2001. Disponível em: <Disponível em: https://bit.ly/2xaahEk >. Acesso em: 4 abr. 2020.
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), Inoue, Rodrigues and Afonso (2015INOUE, J. T.; RODRIGUES, C. G.; AFONSO, L. E. Avaliação das informações de óbitos de beneficiários de planos de saúde no Brasil de 2004 a 2009. In: ENCONTRO NACIONAL DE ESTUDOS POPULACIONAIS, 18., Águas de Lindóia, 2015. Anais… Águas Claras: Abep, 2015. Disponível em: <Disponível em: https://bit.ly/2XlOuUO >. Acesso em: 16 out. 2015.
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), Mou (2013MOU, H. The political economy of the public-private mix in heath expenditure: an empirical review of thirteen OECD countries. Health Policy, Londres, v. 113, n. 3, p. 270-283, 2013.) and Leal (2014LEAL, R. M. O mercado de saúde suplementar no Brasil: regulação e resultados econômicos dos planos privados de saúde. 296 f. 2014. Tese (Doutorado em Políticas Públicas) - Instituto de Economia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, 2014. Disponível em: <Disponível em: https://bit.ly/2RlfiRt >. Acesso em: 10 jul. 2016.
https://bit.ly/2RlfiRt...
).

The infrastructure of public and private health services in Brazil focuses on hospital-level care; primary care is contemplated by public assistance programs and health insurance coverage. Studies on this matter often report a negative and statistically significant association between health services infrastructure and mortality rates. However, this is not always the case. Hospital beds are poorly geographically distributed, medical supplies are concentrated by the private sector (health plans and insurance), and higher mortality rates are believed to occur in public beds, according to Santos (2009SANTOS, I. S. O mix público-privado no sistema de saúde brasileiro: elementos para a regulação da cobertura duplicada. 186 f. Tese (Doutorado em Saúde Pública) - Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz, Rio de Janeiro, 2009. Disponível em: <Disponível em: https://bit.ly/3e6EeWs >. Acesso em: 1 nov. 2015.
https://bit.ly/3e6EeWs...
), Santos and Amarante (2010SANTOS, N. R.; AMARANTE, P. D. C. (Org.). Gestão pública e relação público-privado na saúde. Rio de Janeiro: Cebes, 2010. Disponível em: <Disponível em: https://bit.ly/39O0MrX >. Acesso em: 1 nov. 2015.
https://bit.ly/39O0MrX...
) and Machado (2014MACHADO, J. P. O arranjo público-privado no Brasil e a qualidade da assistência hospitalar em São Paulo e no Rio Grande do Sul. 2014. Tese (Doutorado em Saúde Pública) - Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz, Rio de Janeiro, 2014.).

Column IV: formed by the mortality dimension, which indicates the quality of health services and, above all, population’s health conditions. Ará et al. (2005ARÁ, O. A. et al. Health system outcomes and determinants amenable to public health in industrialized countries: a pooled, cross-sectional time series analysis. BMC Public Health, Utrecht, v. 5, n. 8, p. 1-10, 2005.), Leite (2009LEITE, F. Taxas de mortalidade entre beneficiários de planos de saúde e a população brasileira em 2004 e 2005: o que mudou? São Paulo: IESS, 2009.), Soares & Menezes (2010SOARES, E. S.; MENEZES, G. M. S. Fatores associados à mortalidade neonatal precoce: análise de situação no nível local. Epidemiologia e Serviços de Saúde, Brasília, DF, v. 19, n. 1, p. 51-60, 2010.) and Allanson & Petrie (2013ALLANSON, P.; PETRIE, D. Longitudinal methods to investigate the role of health determinants in the dynamics of income-related health inequality. Journal of Health Economics, Londres, v. 32, p. 922-937, 2013.) consider mortality rate as an indicator of life and health conditions and a reflection of populations’ health. Infant mortality rates are important indicators that play a key role in life expectancy at birth and have been historically used to assess populations’ life and health conditions.

Final considerations

The literature presents useful conceptual models for understanding the relations and functioning of health systems, possible connections between different types of SDH, as well as indicating strategic points for guiding policies. However, these models impose limitations regarding joint manipulation of categories, such as mathematical or statistical variables, hindering their application to public health policies.

Our study proposes a SDH conceptual model operationally applicable to support studies and management practices on public health. We resorted to conceptual models available in the literature to propose a model in which SDH variables or indicators could be systematized and better interpreted by quantitative methods. We collected data on the environment, society, economy, structure, public and private sector of health services, and on how they affect population’s health. Our proposed model applied indicators or variables available in official databases with a time series arrangement, applicable to different types of metrics.

The resulting model comprises an active part of government policy, focusing on the Brazilian public health system and socioeconomic structures at municipal level. The model is operationalizable and reflexible, enabling adaptations according to data reliability. Our conceptual model proposed has no intention of replacing existing models. However, it offers a viable alternative application, as understanding its relation system may help formulate public health strategies.

Genetic and Biological aspects presented unreliable and insufficient data, so we excluded these elements from the model. We also did not consider qualitative data. These characteristics indicate limitations in the model proposed and suggest the possibility for further studies to explore.

The characteristics of all conceptual reference models, including the one proposed in our study, elicit the need for applying appropriate theories, methods, and tools for the systemic approach. We recommend this conceptual model to be tested by artificial intelligence resources, such as Bayesian networks, neural networks, or other compatible resource. The integral reproduction of the system of relationships among SDH may offer contextualized information to define health management strategies at municipal level.

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Publication Dates

  • Publication in this collection
    17 July 2020
  • Date of issue
    2020

History

  • Received
    21 Nov 2018
  • Accepted
    03 Mar 2020
Faculdade de Saúde Pública, Universidade de São Paulo. Associação Paulista de Saúde Pública. SP - Brazil
E-mail: saudesoc@usp.br