Framework for participatory quantitative health impact assessment in low- and middle-income countries

Thondoo, Meelan; de Vries, Daniel H.; Rojas Rueda, David, 1979-; Ramkalam, Yashila D.; Verlinghieri, Ersilia; Gupta, Joyeeta; Nieuwenhuijsen, Mark J.

doi:http://dx.doi.org/10.3390/ijerph17207688

Framework for participatory quantitative health impact assessment in low- and middle-income countries

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Thondoo M, De Vries DH, Rojas-Rueda D, Ramkalam YD, Verlinghieri E, Gupta J, et al. Framework for participatory quantitative health impact assessment in low - and middle-income countries. Int J Environ Res Public Health. 2020 Oct 21; 17(20): 7688. DOI: 10.3390/ijerph17207688

Abstract

Background: Conducting health impact assessments (HIAs) is a growing practice in various organizations and countries, yet scholarly interest in HIAs has primarily focused on the synergies between exposure and health outcomes. This limits our understanding of what factors influence HIAs and the uptake of their outcomes. This paper presents a framework for conducting participatory quantitative HIA (PQHIA) in low- and middle-income countries (LMICs), including integrating the outcomes back into society after an HIA is conducted. The study responds to the question: what are the different components of a participatory quantitative model that can influence HIA implementation in LMICs?. Methods: To build the framework, we used a case study from a PQHIA fieldwork model developed in Port Louis (Mauritius). To explore thinking on the participatory components of the framework, we extract and analyze data from ethnographic material including fieldnotes, interviews, focus group discussions and feedback exercises with 14 stakeholders from the same case study. We confirm the validity of the ethnographic data using five quality criteria: credibility, transferability, dependability, confirmability, and authenticity. We build the PQHIA framework connecting the main HIA steps with factors influencing HIAs. Results: The final framework depicts the five standard HIA stages and summarizes participatory activities and outcomes. It also reflects key factors influencing PQHIA practice and uptake of HIA outcomes: costs for participation, HIA knowledge and interest of stakeholders, social responsibility of policymakers, existing policies, data availability, citizen participation, multi-level stakeholder engagement and multisectoral coordination. The framework suggests that factors necessary to complete a participatory HIA are the same needed to re-integrate HIA results back into the society. There are three different areas that can act as facilitators to PQHIAs: good governance, evidence-based policy making, and access to resources. Conclusions: The framework has several implications for research and practice. It underlines the importance of applying participatory approaches critically while providing a blueprint for methods to engage local stakeholders. Participatory approaches in quantitative HIAs are complex and demand a nuanced understanding of the context. Therefore, the political and cultural contexts in which HIA is conducted will define how the framework is applied. Finally, the framework underlines that participation in HIA does not need to be expensive or time consuming for the assessor or the participant. Yet, participatory quantitative models need to be contextually developed and integrated if they are to provide health benefits and be beneficial for the participants. This integration can be facilitated by investing in opportunities that fuel good governance and evidence-based policy making.