Carbon Footprint of Animal- and Plant-Based Protein Foods Consumption Among Adults in Saudi Arabia
サウジアラビア成人における動物性・植物性タンパク質食品消費の炭素足跡 (AI 翻訳)
Yasmine Tawfiq Alsalem, Hala Hazam Al-Otaibi
🤖 gxceed AI 要約
日本語
サウジアラビア成人1624人を対象に、動物性・植物性タンパク質食品の消費に伴う炭素足跡（CF）を定量化した。動物性タンパク質がCFの98.5%を占め、ラム肉と牛肉が最も高い排出原単位を示した。高摂取群はEAT-Lancet目標を大幅に超過。食生活の一部を植物性にシフトすることでVision 2030の排出削減に貢献できる。
English
This study quantified the carbon footprint (CF) of protein food consumption among 1624 Saudi adults. Animal-based proteins contributed 98.5% of total dietary CF, with lamb and beef having the highest emission intensities. High consumers exceeded EAT-Lancet red meat targets. A partial shift toward plant-based proteins could significantly reduce per capita emissions, aligning with Saudi Vision 2030.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本でも食の脱炭素化が議論される中、本論文はタンパク質源別の炭素足跡の定量化手法を示しており、日本の食料システムにおける排出削減政策や企業の製品カーボンフットプリント算定に応用可能。ただしサウジアラビア特有の食文化に基づく結果であるため、日本の状況にそのまま適用するには注意が必要。
In the global GX context
This study contributes empirical dietary carbon footprint data from the GCC region, supporting global food system transition strategies like the EAT-Lancet targets. It underscores the dominance of red meat in diet-related emissions and provides a methodology for national-level dietary CF assessment that can inform climate pledges and food policy.
👥 読者別の含意
🔬研究者:Provides a cross-sectional methodology for dietary CF estimation using LCA emission factors and identifies sociodemographic predictors.
🏢実務担当者:Useful for food companies and sustainability teams to understand carbon hotspots in protein supply chains and for designing low-carbon product portfolios.
🏛政策担当者:Supports evidence-based dietary guidelines and food system interventions to align with national climate targets (e.g., Saudi Vision 2030).
📄 Abstract（原文）
Background/Objectives: Animal-source protein consumption in Saudi Arabia has increased substantially over the last two decades, raising concerns regarding its environmental impact in a country with among the highest per capita carbon emissions globally. Despite growing interest in sustainable diets, empirical evidence on dietary carbon footprint (CF) in Gulf Cooperation Council countries remains limited. This study aimed to quantify the CF associated with the consumption of animal- and plant-based protein foods among Saudi adults and to identify sociodemographic and lifestyle predictors of dietary CF, with attention to sex differences. Methods: A cross-sectional study was conducted among 1624 Saudi adults (47.1% males; 52.9% females). A newly developed, expert-reviewed, and pilot-tested food frequency questionnaire covering 21 protein-containing food items (13 animal-based; 8 plant-based) was used to estimate daily intake. CF values were calculated using Life Cycle Assessment-derived greenhouse gas emission factors (kgCO2e/kg food) obtained from peer-reviewed sources. Sex-stratified multiple linear regression models and a pooled sex × animal-source protein food interaction model was used to identify independent predictors of daily CF. Results: Animal-source protein foods contributed 45,641.8 kgCO2e/week to cumulative CF—a 64-fold excess over plant-based sources (708.33 kgCO2e/week). Mean individual protein-food CF was 4.07 kgCO2e/day, of which 98.5% derived from animal sources. Lamb and beef carried the highest emission intensities; nuts the lowest. Animal-source intake was the strongest independent predictor of CF in both sexes, with a significantly stronger association in males than females. High consumers substantially exceeded EAT–Lancet red meat targets across all consumption strata. Conclusions: Red meat dominates protein-food-related GHG emissions among Saudi adults. Even a partial dietary shift toward plant-based proteins, embedded within a coordinated food-system transformation framework, could substantially reduce per capita emissions in alignment with Saudi Vision 2030 and One Health targets.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/nu18121856first seen 2026-06-23 05:46:47
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