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Introduction <p>The prevalence of obesity among adults has increased significantly in recent decades, particularly in low-income neighbourhoods. To better understand this trend, we examined the underlying dynamics driving this rise in Dutch cities.</p> Method <p>Using Group Model Building (GMB) with thirteen scientific experts, we developed a&#xa0;system map illustrating the feedbackloops contributing to the increase in obesity. Based on a&#xa0;system analysis, we identified the key dynamics that have driven obesity in low-income neighbourhoods over the past 30&#xa0;years.</p> Results <p>The rise in obesity results from the interaction between four subsystems: the food environment, the physical activity environment, the socioeconomic environment, and the socio-political environment. Three core dynamics illustrate how these subsystems interact: 1)&#xa0;adverse socioeconomic conditions and an unhealthy food environment reinforce each other, 2)&#xa0;social distance between social groups and adverse socioeconomic conditions reinforce each other and 3)&#xa0;social distance between institutions and communities and the normalisation of unhealthy behaviours reinforce each other.</p> Discussion <p>The system map highlights the need for a&#xa0;broad, cross-sectoral approach that addresses the underlying causes of obesity, such as adverse socioeconomic conditions, unhealthy social norms, and distrust in government. As long as these structural drivers persist, isolated policy measures will have only limited impact. Effective policies must therefore focus on breaking the key dynamics that sustain the system.</p>

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Hoe maatschappelijke dynamieken leiden tot obesitas in lage-inkomenswijken en hoe deze doorbroken kunnen worden

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月16日

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  • Fleur ter Ellen,
  • Joost Oude Groeniger,
  • Karien Stronks,
  • Luc Hagenaars,
  • Karen Oude Hengel,
  • Frank van Lenthe

摘要

Introduction

The prevalence of obesity among adults has increased significantly in recent decades, particularly in low-income neighbourhoods. To better understand this trend, we examined the underlying dynamics driving this rise in Dutch cities.

Method

Using Group Model Building (GMB) with thirteen scientific experts, we developed a system map illustrating the feedbackloops contributing to the increase in obesity. Based on a system analysis, we identified the key dynamics that have driven obesity in low-income neighbourhoods over the past 30 years.

Results

The rise in obesity results from the interaction between four subsystems: the food environment, the physical activity environment, the socioeconomic environment, and the socio-political environment. Three core dynamics illustrate how these subsystems interact: 1) adverse socioeconomic conditions and an unhealthy food environment reinforce each other, 2) social distance between social groups and adverse socioeconomic conditions reinforce each other and 3) social distance between institutions and communities and the normalisation of unhealthy behaviours reinforce each other.

Discussion

The system map highlights the need for a broad, cross-sectoral approach that addresses the underlying causes of obesity, such as adverse socioeconomic conditions, unhealthy social norms, and distrust in government. As long as these structural drivers persist, isolated policy measures will have only limited impact. Effective policies must therefore focus on breaking the key dynamics that sustain the system.