Department of Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK; Leverhulme Centre for Integrative Research on Agriculture and Health (LCIRAH), 36 Gordon Square, London WC1H 0PD, UK.
Department of Population Health, London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK; Leverhulme Centre for Integrative Research on Agriculture and Health (LCIRAH), 36 Gordon Square, London WC1H 0PD, UK.
Sci Total Environ. 2018 Dec 1;643:1411-1418. doi: 10.1016/j.scitotenv.2018.06.258. Epub 2018 Jul 4.
Agriculture is a major contributor to India's environmental footprint, particularly through greenhouse gas (GHG) emissions from livestock and fresh water used for irrigation. These impacts are likely to increase in future as agriculture attempts to keep pace with India's growing population and changing dietary preferences. Within India there is considerable dietary variation, and this study therefore aimed to quantify the GHG emissions and water usage associated with distinct dietary patterns. Five distinct diets were identified from the Indian Migration Study - a large adult population sample in India - using finite mixture modelling. These were defined as: Rice & low diversity, Rice & fruit, Wheat & pulses, Wheat, rice & oils, Rice & meat. The GHG emissions of each dietary pattern were quantified based on a Life Cycle Assessment (LCA) approach, and water use was quantified using Water Footprint (WF) data. Mixed-effects regression models quantified differences in the environmental impacts of the dietary patterns. There was substantial variability between diets: the rice-based patterns had higher associated GHG emissions and green WFs, but the wheat-based patterns had higher blue WFs. Regression modelling showed that the Rice & meat pattern had the highest environmental impacts overall, with 0.77 (95% CI 0.64-0.89) kg COe/capita/day (31%) higher emissions, 536 (95% CI 449-623) L/capita/day (24%) higher green WF and 109 (95% CI 85.9-133) L/capita/day (19%) higher blue WF than the reference Rice & low diversity pattern. Diets in India are likely to become more diverse with rising incomes, moving away from patterns such as the Rice & low diversity diet. Patterns such as the Rice & meat diet may become more common, and the environmental consequences of such changes could be substantial given the size of India's population. As global environmental stress increases, agricultural and nutrition policies must recognise the environmental impacts of potential future dietary changes.
农业是印度环境足迹的主要贡献者,特别是通过牲畜产生的温室气体(GHG)排放和灌溉用水。随着农业试图跟上印度不断增长的人口和不断变化的饮食偏好,这些影响未来可能会增加。在印度,饮食存在很大差异,因此本研究旨在量化与不同饮食模式相关的温室气体排放和用水量。使用有限混合建模从印度移民研究中确定了五种不同的饮食模式-印度的一个大型成人人口样本。这些被定义为:大米和低多样性,大米和水果,小麦和豆类,小麦,大米和油,大米和肉。根据生命周期评估(LCA)方法量化了每种饮食模式的温室气体排放量,并使用水足迹(WF)数据量化了用水量。混合效应回归模型量化了饮食模式对环境影响的差异。饮食之间存在很大差异:基于大米的模式与更高的相关温室气体排放和绿色 WF 相关,但基于小麦的模式具有更高的蓝色 WF。回归模型表明,大米和肉类模式的环境影响总体上最高,排放量比参考的大米和低多样性模式高出 0.77(95%CI 0.64-0.89)kg COe/ capita/天(31%),绿色 WF 高出 536(95%CI 449-623)L/ capita/天(24%),蓝色 WF 高出 109(95%CI 85.9-133)L/ capita/天(19%)。随着收入的增加,印度的饮食可能会变得更加多样化,远离大米和低多样性等模式。大米和肉类等模式可能会变得更加普遍,考虑到印度庞大的人口规模,这种变化可能会带来巨大的环境后果。随着全球环境压力的增加,农业和营养政策必须认识到潜在未来饮食变化的环境影响。