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Sick and depressed? The causal impact of a diabetes diagnosis on depression

Gaggero, A.;, Joan Gil (), Jiménez-Rubio, D.; and Eugenio Zucchelli ()

Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York

Abstract: There is sparse evidence on the impact of health information on mental health as well as on the mechanisms governing this relationship. We estimate the causal impact of health information on mental health via the effect of a diabetes diagnosis on depression. We employ a fuzzy regression discontinuity design (RDD) exploiting the exogenous cut-off value in the diagnosis of type-2 diabetes provided by a biomarker (glycated haemoglobin) and information on diagnosed clinical depression drawn from rich administrative longitudinal data from Spain. We find that overall a type-2 diabetes diagnosis increases the probability of becoming depressed, however this effect appears to be driven mostly by women. Results also appear to differ by changes in lifestyle induced by the diabetes diagnosis: while women who did not lose weight are more likely to develop depression, men who did lose weight present a reduced probability of being depressed. Results are robust to alternative parametric and non-parametric specifications and placebo tests.

Keywords: diabetes; depression; fuzzy regression discontinuity design; administrative longitudinal data; lifestyle changes (search for similar items in EconPapers)
JEL-codes: C21 I10 I12 (search for similar items in EconPapers)
Date: 2022-06
New Economics Papers: this item is included in nep-dem and nep-hea
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