BACKGROUND: It remains unknown whether short measures of depression perform as well as long measures in predicting adverse outcomes such as mortality. The present study aims to examine the predictive value of a single-item measure of depression for mortality. METHODS: A total of 14,185 participants of the GAZEL cohort completed the 20-item Center-for-Epidemiologic-Studies-Depression (CES-D) scale in 1996. One of these items (I felt depressed) was used as a single-item measure of depression. All-cause mortality data were available until 30 September 2009, a mean follow-up period of 12.7 years with a total of 650 deaths. RESULTS: In Cox regression model adjusted for baseline socio-demographic characteristics, a one-unit increase in the single-item score (range 0-3) was associated with a 25% higher risk of all-cause mortality (95% CI: 13-37%, P<0.001). Further adjustment for health-related behaviours and physical chronic diseases reduced this risk by 36% and 8%, respectively. After adjustment for all these variables, every one-unit increase in the single-item score predicted a 15% increased risk of death (95% CI: 5-27%, P<0.01). There is also an evidence of a dose-reponse relationship between reponse scores on the single-item measure of depression and mortality. CONCLUSION: This study shows that a single-item measure of depression is associated with an increased risk of death. Given its simplicity and ease of administration, a very simple single-item measure of depression might be useful for identifying middle-aged adults at risk for elevated depressive symptoms in large epidemiological studies and clinical settings.
BACKGROUND: It remains unknown whether short measures of depression perform as well as long measures in predicting adverse outcomes such as mortality. The present study aims to examine the predictive value of a single-item measure of depression for mortality. METHODS: A total of 14,185 participants of the GAZEL cohort completed the 20-item Center-for-Epidemiologic-Studies-Depression (CES-D) scale in 1996. One of these items (I felt depressed) was used as a single-item measure of depression. All-cause mortality data were available until 30 September 2009, a mean follow-up period of 12.7 years with a total of 650 deaths. RESULTS: In Cox regression model adjusted for baseline socio-demographic characteristics, a one-unit increase in the single-item score (range 0-3) was associated with a 25% higher risk of all-cause mortality (95% CI: 13-37%, P<0.001). Further adjustment for health-related behaviours and physical chronic diseases reduced this risk by 36% and 8%, respectively. After adjustment for all these variables, every one-unit increase in the single-item score predicted a 15% increased risk of death (95% CI: 5-27%, P<0.01). There is also an evidence of a dose-reponse relationship between reponse scores on the single-item measure of depression and mortality. CONCLUSION: This study shows that a single-item measure of depression is associated with an increased risk of death. Given its simplicity and ease of administration, a very simple single-item measure of depression might be useful for identifying middle-aged adults at risk for elevated depressive symptoms in large epidemiological studies and clinical settings.
Authors: Harriet L MacMillan; Christopher J S Patterson; C Nadine Wathen; John W Feightner; Paul Bessette; R Wayne Elford; Denice S Feig; Joanne Langley; Valerie A Palda; Christopher Patterson; Bruce A Reeder; Ruth Walton Journal: CMAJ Date: 2005-01-04 Impact factor: 8.262
Authors: M S Lachs; A R Feinstein; L M Cooney; M A Drickamer; R A Marottoli; F C Pannill; M E Tinetti Journal: Ann Intern Med Date: 1990-05-01 Impact factor: 25.391
Authors: Marine Azevedo Da Silva; Archana Singh-Manoux; Martin J Shipley; Jussi Vahtera; Eric J Brunner; Jane E Ferrie; Mika Kivimäki; Hermann Nabi Journal: J Sleep Res Date: 2013-07-31 Impact factor: 3.981
Authors: Ronald C Kessler; Maria Petukhova; Nancy A Sampson; Alan M Zaslavsky; Hans-Ullrich Wittchen Journal: Int J Methods Psychiatr Res Date: 2012-08-01 Impact factor: 4.035
Authors: Yu-Ping Su; Chin-Kuo Chang; Richard D Hayes; Gayan Perera; Matthew Broadbent; David To; Matthew Hotopf; Robert Stewart Journal: PLoS One Date: 2014-09-03 Impact factor: 3.240
Authors: Dillon T Browne; Aarti Kumar; Sofia Puente-Duran; Katholiki Georgiades; George Leckie; Jennifer Jenkins Journal: PLoS One Date: 2017-04-04 Impact factor: 3.240