Abstract
Non-communicable diseases, such as cardiovascular diseases (CVDs), diabetes and cancer account for more than half of the global disease burden, and 75% of related deaths occur in low- and middle-income countries (LMICs). Despite large regional variations in CVD incidence and prevalence, CVDs remain the leading causes of death worldwide. With urbanisation, developing nations are undergoing unprecedented labour-force transitions out of agriculture and into types of non-agricultural employment, mainly in the industry and service sectors. There are few studies on the effect of these transitions on CVDs and CVD risk factors in LMICs. We systematically searched MEDLINE, PubMed, EMBASE and the Cochrane Library from January 1950 to January 2017 to assess the association of engaging in agriculture compared to types of non-agricultural employment (e.g. services and manufacturing) with CVD incidence, prevalence and risk factors. Studies were included if they: included participants who engaged in agriculture and participants who did not engage in agriculture; measured atherosclerotic CVDs or their modifiable risk factors; and involved adults from LMICs. We assessed the quality of evidence in seven domains of each study. Prevalence ratios with 95% confidence intervals were calculated and compared in forest plots across studies. Study heterogeneity did not permit formal meta-analyses with pooled results. There was a lack of publications on the primary outcomes, atherosclerotic CVDs (n = 2). Limited evidence of varying consistency from 13 studies in five countries reported that compared with non-agricultural workers, mainly living in urban areas, rural agriculture workers had a lower prevalence of hypertension, overweight and obesity; and a higher prevalence of underweight and smoking. High quality evidence is lacking on the associations of engaging in and transitioning out of agriculture with atherosclerotic CVDs and their modifiable risk factors in LMICs. There is a need for interdisciplinary longitudinal studies to understand associations of types of employment and labour-force transitions with CVD burdens in LMICs.