Do Climate Change Policies Promote or Conflict with Subjective Wellbeing: A Case Study of Suzhou, China

Int J Environ Res Public Health. 2016 Mar 21;13(3):344. doi: 10.3390/ijerph13030344.

Abstract

As public expectations for health rise, health measurements broaden from a focus on death, disease, and disability to wellbeing. However, wellbeing hasn't been incorporated into the framework of climate change policy decision-making in Chinese cities. Based on survey data (n = 763) from Suzhou, this study used Generalized Estimation Equation approach to model external conditions associated with wellbeing. Then, semi-quantitative analyses were conducted to provide a first indication to whether local climate change policies promote or conflict with wellbeing through altering these conditions. Our findings suggested: (i) Socio-demographic (age, job satisfaction, health), psychosocial (satisfaction with social life, ontological security/resilience) and environmental conditions (distance to busy road, noise annoyance and range hoods in the kitchen) were significantly associated with wellbeing; (ii) None of existing climate change strategies in Suzhou conflict with wellbeing. Three mitigation policies (promotion of tertiary and high-tech industry, increased renewable energy in buildings, and restrictions on car use) and one adaption policy (increasing resilience) brought positive co-benefits for wellbeing, through the availability of high-satisfied jobs, reduced dependence on range hoods, noise reduction, and valuing citizens, respectively. This study also provided implications for other similar Chinese cities that potential consequences of climate change interventions for wellbeing should be considered.

Keywords: Chinese city; climate change; co-benefits; policy implications; wellbeing.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • China
  • Cities
  • Climate Change*
  • Environment Design*
  • Female
  • Health Surveys / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Public Health / statistics & numerical data*
  • Public Policy*
  • Surveys and Questionnaires
  • Urban Health*
  • Young Adult