Mendelian Randomization analysis of the causal effect of cigarette smoking on hospital costs

Padraig Dixon; Hannah Sallis; Marcus Munafo; George Davey Smith; Laura Howe

doi:10.1093/ntr/ntae089

Mendelian Randomization analysis of the causal effect of cigarette smoking on hospital costs

Nicotine Tob Res. 2024 Apr 17:ntae089. doi: 10.1093/ntr/ntae089. Online ahead of print.

Authors

Padraig Dixon^{1

2}, Hannah Sallis^{2

3}, Marcus Munafo^{2

3

4}, George Davey Smith^{2

4

5}, Laura Howe^{2

5}

Affiliations

¹ Nuffield Department of Primary Care Health Sciences, University of Oxford.
² MRC Integrative Epidemiology Unit, University of Bristol.
³ School of Psychological Science, University of Bristol.
⁴ NIHR Biomedical Research Centre, University of Bristol of Bristol.
⁵ Population Health Sciences, University of Bristol.

PMID: 38628153
DOI: 10.1093/ntr/ntae089

Abstract

Introduction: Knowledge of the impact of smoking on healthcare costs is important for establishing the external effects of smoking and for evaluating policies intended to modify this behavior. Conventional analysis of this association is difficult because of omitted variable bias, reverse causality, and measurement error.

Methods: We approached these challenges using a Mendelian Randomization study design; genetic variants associated with smoking behaviors were used in instrumental variables models with inpatient hospital costs (calculated from electronic health records) as the outcome. We undertook genome wide association studies to identify genetic variants associated with smoking initiation and a composite smoking index (reflecting cumulative health impacts of smoking) on up to 300,045 individuals (mean age: 57 years at baseline, range 39 to 72 years) in the UK Biobank. We followed individuals up for a mean of six years.

Results: Genetic liability to initiate smoking (ever versus never smoking) was estimated to increase mean per-patient annual inpatient hospital costs by £477 (95% confidence interval (CI): £187 to £766). A one-unit change in genetic liability to the composite smoking index (range: 0-4.0) increased inpatient hospital costs by £204 (95% CI: £105 to £303) per unit increase in this index. There was some evidence that the composite smoking index causal models violated the instrumental variable assumptions, and all Mendelian Randomization models were estimated with considerable uncertainty. Models conditioning on risk tolerance were not robust to weak instrument bias.

Conclusions: Our findings have implications for the potential cost-effectiveness of smoking interventions.

Implications: We report the first Mendelian Randomization analysis of the causal effect of smoking on healthcare costs. Using two distinct smoking phenotypes, we identified substantial impacts of smoking on inpatient hospital costs, although the causal models were associated with considerable uncertainty. These results could be used alongside other evidence on the impact of smoking to evaluate the cost-effectiveness of anti-smoking interventions and to understand the scale of externalities associated with this behaviour.

Keywords: Genetics; Mendelian Randomization; healthcare costs; smoking instrumental variables.