Education plays a crucial role in the pathway from poverty to smoking: a Mendelian randomization study. (24th August 2022)

• Record Type: Journal Article
• Authors: Shi, Xiaoqiang; Yuan, Wenji; Cao, Qingyi; Cui, Wenyan
• Is Part Of: Addiction. Volume 118:Number 1(2023)
• Page Start: 128
• Page End: 139
• Publication Date: 2022-08-24
• Subjects: Causal effect -- drug abuse -- education -- income -- Mendelian randomization -- smoking; Alcoholism -- Periodicals; Drug addiction -- Periodicals; 616.86
• DOI: 10.1111/add.16019
• Languages: English
• ISSNs: 0965-2140

Abstract

Abstract: Background and Aims: Disproportionately high rates of smoking have been found in low‐income communities, but the causal direction and role of education in this relationship remains less well understood. Here, we used bidirectional Mendelian randomization (MR) to measure the causal relationships between smoking, income and education. Design: Two‐sample univariable and multivariable MR analyses were conducted to evaluate the total and direct effect of income and education on tobacco smoking. The effects of smoking on education and income were explored with reverse MR analysis. Setting: European ancestry. Participants: The most recent large‐scale genome‐wide association study (GWAS) summary data on educational attainment, household income and smoking ( n = 143 210–766 345). Measurements: Genetic variants for exposures including income, education and smoking. Findings: Both income and education had protective effects against smoking, especially for smoking initiation (education: β = −0.447, 95% CI = −0.508 to −0.387, P < 0.001; income: β = −0.290, 95% CI = −0.43 to −0.149, P < 0.001) and cessation (education: β = −0.364, 95% CI = −0.429 to −0.298, P < 0.001; income: β = −0.323, 95% CI = −0.448 to −0.197, P < 0.001). Here, higher scores in cessation indicated a lower likelihood of quitting according to the coding scheme. There was little evidence that income influenced smoking once education was controlled for, whereas education could significantly affect smoking behaviours independently of income ( P = 3.40 × 10 −10 –0.0272). The reverse MR results suggested that smoking may result in a loss of years of schooling (β = −0.190, 95% CI = −0.297 to −0.083, P < 0.001) and reduced earnings (β = −0.204, 95% CI = −0.347 to −0.060, P = 0.006). Conclusions: Education appears to play an important role in the relationship between income and smoking. There is a bidirectional association of smoking with socioeconomic status.