Unequal harvests: AI-assisted evidence map of trends and gaps in global farmer health research along SDG 3 priorities

Introduction Ensuring the health of agricultural workers, the world’s largest labour force, is key for sustainable food production and progress towards the Sustainable Development Goals (SDGs). Methods We conducted an artificial intelligence (AI)-assisted evidence map of research records on global farmer health published from 2015 to 2024.

We searched bibliographic databases and screened titles/abstracts using SWIFT-Active Screener, a collaborative review platform that uses machine-learning prioritisation to rank records for human review. We retrieved 32 006 records.

After manually screening 8533 records and stopping when the tool estimated ≥94% recall of relevant records, we included 1684 studies. We mapped research output by health topic category (non-communicable diseases (NCDs), communicable diseases, injuries and mental health) country income groups and alignment with SDG 3 targets.

Results Despite 98% of the agricultural workforce living in low- and middle-income countries (LMICs), 52% of studies originate from high-income countries (HICs). Research focuses on NCDs (29%) and injuries (26%), with LMICs focusing on pesticide poisoning and HIC on accidents.