Integrating Behavior Change Theory and Measures into Health-Based Cookstove Interventions: A Proposed Epidemiologic Research Agenda

Abstract

Nearly 3 billion people rely on solid fuel combustion to meet basic domestic energy needs (Rehfuess et al., 2006). Many households use traditional cookstoves to meet these energy needs, resulting in extremely high indoor air pollution concentrations. Household air pollution from biomass and coal combustion accounts for an estimated 3.9 million premature deaths per year, representing about 4.8% of the global disease burden (Smith et al., 2014). Improved, cleaner-burning stove designs have the potential to substantially reduce household air pollution exposures and improve health (Albalak et al., 2001; Bruce et al., 2004; Ezzati & Kammen, 2002; Smith, 2002). However, there are few randomized intervention trials, and previous stove intervention studies focused on health impacts have been plagued by low improved stove adoption and sustained use (Perez-Padilla et al., 2010; Romieu et al., 2009), severely limiting interpretations of these studies. Without addressing the ongoing social and behavioral process of adoption and stove use, the full benefits of stove dissemination programs cannot be realized or estimated (Pine et al., 2011; Rehfuess et al., 2014; Ruiz-Mercado et al., 2011; Troncoso et al., 2007). Several excellent reviews have compiled detailed descriptions of enablers and barriers to stove adoption across a wide variety of cultural and geographical scenarios (Lewis & Pattanayak, 2012; Rehfuess et al., 2014; Puzzolo et al., 2013). Furthermore, Puzzolo et al. (2013) have clearly outlined the complexity involved with promoting the use of improved fuels or stoves and the need to consider a broad range of factors, or constructs, influencing the likelihood of sustained adoption (i.e., fuel and technology characteristics; household and setting characteristics; knowledge and perceptions; financial, tax and subsidy aspects; market development; regulation, legislation, and standards; and programmatic and policy mechanisms). Keeping in mind that the behavior change process is dynamic, it is important to note that these enablers and barriers may interact at multiple levels (e.g., at the individual and community-level) as well as at various stages of change (e.g., intent to change behavior, initial behavior change, and/or sustained behavior change) (Rehfuess et al., 2014; Ruiz-Mercado et al., 2011). Given these recent contributions to the literature, this commentary is not meant to be a comprehensive review of behavior change theory, even within the cookstove research arena. Building upon this emerging body of work, the objective of this commentary is to propose that behavior change methods and theory also need to have a central role in epidemiologic intervention studies evaluating the health effects of cleaner-burning cookstoves – both in the promotion of behavioral change to maximize the health benefit and also in the accurate evaluation of the health impact of the intervention. Given the immense public health impact and the recent increase in efforts to fund large-scale dissemination programs of cleaner-burning cookstoves (Martin et al., 2011), the current research paradigms need to be challenged. It is clear that behavior change is a critical piece of the puzzle. Much of the focus has been placed on developing methods to achieve complete and sustained behavior change with respect to stove use, often with the goal of reaching a target guideline for pollutant concentrations (e.g., World Health Organization air quality guidelines). However, our current knowledge regarding the health benefits of cleaner-burning cookstove programs is severely limited, and the answers are inherently dependent on our ability to describe behavior. Exposure-response is a complex continuum with much uncertainty; we essentially ask the question, where do we expect people to land on the exposure-response curve after a new stove is introduced? In order to understand expected health benefits for a particular stove program we need to accurately predict reductions in exposure, which will vary depending on behaviors surrounding the use of the stove.