
Abstract Extreme temperatures threaten agriculture and exacerbate global food insecurity, yet their direct impact on dietary choices remains poorly understood. We provide novel evidence of how short-term exposures to extreme temperatures affect macronutrient intake in China. We show that both hot and cold weather elevate high-fat diet risks. In particular, hot weather reduces carbohydrate and protein consumption but not fat intake, while cold weather increases all nutrient intake, particularly fats. Temperature-induced dietary changes are shaped primarily by physiological responses to thermal stress, whereas physical activities demonstrate little effect. Technologies that improve indoor thermal comfort (via fans, air conditioners, and heating systems) substantially mitigate high-fat diet risks. Socioeconomic disparities are evident, with rural and poor individuals more likely to adopt high-fat diets under hot or cold weather. Projections indicate that more extreme temperatures due to climate change may increase the prevalence of high-fat diets nationally, while substantial regional heterogeneity emerges, with declines in northeast China and increases in southern China. These results highlight a crucial but overlooked pathway linking climate change to dietary health inequality.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
