Association between the Prime Diet Quality Score and depressive symptoms in a Mediterranean population with metabolic syndrome. Cross-sectional and 2-year follow-up assessment from PREDIMED-PLUS study
The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori...
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Published in | British journal of nutrition Vol. 128; no. 6; pp. 1170 - 1179 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Cambridge, UK
Cambridge University Press
28.09.2022
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Subjects | |
Online Access | Get full text |
ISSN | 0007-1145 1475-2662 1475-2662 |
DOI | 10.1017/S0007114521004323 |
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Abstract | The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles (P
for trend = 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found (β (95 %) CI = −0·67 z-score (–1·17, −0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time. |
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AbstractList | The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles (
= 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found (
(95 %) CI = -0·67 z-score (-1·17, -0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time. The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles (Pfor trend = 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found (β (95 %) CI = -0·67 z-score (-1·17, -0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time.The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles (Pfor trend = 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found (β (95 %) CI = -0·67 z-score (-1·17, -0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time. The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles (Pfor trend = 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found (β (95 %) CI = −0·67 z-score (–1·17, −0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time. The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles ( P for trend = 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found ( β (95 %) CI = −0·67 z-score (–1·17, −0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time. The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles (P fₒᵣ ₜᵣₑₙd = 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found (β (95 %) CI = −0·67 z-score (–1·17, −0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time. The burden of depression is increasing worldwide, specifically in older adults. Unhealthy dietary patterns may partly explain this phenomenon. In the Spanish PREDIMED-Plus study, we explored (1) the cross-sectional association between the adherence to the Prime Diet Quality Score (PDQS), an a priori-defined high-quality food pattern, and the prevalence of depressive symptoms at baseline (cross-sectional analysis) and (2) the prospective association of baseline PDQS with changes in depressive symptomatology after 2 years of follow-up. After exclusions, we assessed 6612 participants in the cross-sectional analysis and 5523 participants in the prospective analysis. An energy-adjusted high-quality dietary score (PDQS) was assessed using a validated FFQ. The cross-sectional association between PDQS and the prevalence of depression or presence of depressive symptoms and the prospective changes in depressive symptoms were evaluated through multivariable regression models (logistic and linear models and mixed linear-effects models). PDQS was inversely associated with depressive status in the cross-sectional analysis. Participants in the highest quintile of PDQS (Q5) showed a significantly reduced odds of depression prevalence as compared to participants in the lowest quartile of PDQS (Q1) (OR (95 %) CI = 0·82 (0·68, 0·98))). The baseline prevalence of depression decreased across PDQS quintiles (P for trend = 0·015). A statistically significant association between PDQS and changes in depressive symptoms after 2-years follow-up was found (β (95 %) CI = −0·67 z-score (–1·17, −0·18). A higher PDQS was cross-sectionally related to a lower depressive status. Nevertheless, the null finding in our prospective analysis raises the possibility of reverse causality. Further prospective investigation is required to ascertain the association between PDQS and changes in depressive symptoms along time. |
Author | Estruch, Ramon Sorto-Sánchez, Carolina Vidal, Josep Buil-Cosiales, Pilar Toledo, Estefanía Konieczna, Jadwiga Daimiel Ruiz, Lidia Gea, Alfredo Tojal-Sierra, Lucas Muñoz-Perez, Miguel-Ángel Martín, Vicente García-Ríos, Antonio Coltell, Oscar Cárdenas, Jersy J. Gómez-Martínez, Carlos Zulet, María Angeles Serra-Majem, Lluis Santos-Lozano, José Manuel Alonso-Gómez, Ángel M. Matía Martín, Pilar Fernández-Aranda, Fernando Ros, Emilio Martín-Peláez, Sandra Castañer Niño, Olga Tur, Josep A. Hernández-Fleta, José Luis Gómez-Pérez, Ana María Corella Piquer, Maria Dolores Pintó Sala, Xavier Wärnberg, Julia Fernández-Barceló, Olga Martínez-González, Miguel Ángel Vioque Lopez, Jesús López-Miranda, José Abete, Itziar Lassale, Camille Cano-Ibáñez, Naomi Malcampo-Manrúbia, Mireia Bueno-Cavanillas, Aurora Bernabé-Casanova, Andrea Casas, Rosa Saiz, Carmen Salas-Salvadó, Jordi Martínez Hernandez, José Alfredo Lapetra, José Delgado-Rodríguez, Miguel Bernal-López, Maria Rosa Romaguera, Dora Becerra-Tomás, Nerea Sánchez-Villegas, Almudena |
Author_xml | – sequence: 1 givenname: Naomi surname: Cano-Ibáñez fullname: Cano-Ibáñez, Naomi email: ncaiba@ugr.es organization: 1Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain – sequence: 2 givenname: Lluis surname: Serra-Majem fullname: Serra-Majem, Lluis organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 3 givenname: Sandra surname: Martín-Peláez fullname: Martín-Peláez, Sandra organization: 1Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain – sequence: 4 givenname: Miguel Ángel surname: Martínez-González fullname: Martínez-González, Miguel Ángel organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 5 givenname: Jordi orcidid: 0000-0003-2700-7459 surname: Salas-Salvadó fullname: Salas-Salvadó, Jordi organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 6 givenname: Maria Dolores surname: Corella Piquer fullname: Corella Piquer, Maria Dolores organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 7 givenname: Camille orcidid: 0000-0002-9340-2708 surname: Lassale fullname: Lassale, Camille organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 8 givenname: José Alfredo surname: Martínez Hernandez fullname: Martínez Hernandez, José Alfredo organization: 13Department of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, IdisNA, Pamplona, Spain – sequence: 9 givenname: Ángel M. surname: Alonso-Gómez fullname: Alonso-Gómez, Ángel M. organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 10 givenname: Julia surname: Wärnberg fullname: Wärnberg, Julia organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 11 givenname: Jesús surname: Vioque Lopez fullname: Vioque Lopez, Jesús organization: 2Centro de Investigación Biomédica en Red Epidemiología y Salud Pública (CIBERESP), Institute of Health Carlos III, Madrid, Spain – sequence: 12 givenname: Dora surname: Romaguera fullname: Romaguera, Dora organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 13 givenname: José surname: López-Miranda fullname: López-Miranda, José organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 14 givenname: Ramon surname: Estruch fullname: Estruch, Ramon organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 15 givenname: Ana María surname: Gómez-Pérez fullname: Gómez-Pérez, Ana María organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 16 givenname: José Manuel surname: Santos-Lozano fullname: Santos-Lozano, José Manuel organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 17 givenname: Fernando surname: Fernández-Aranda fullname: Fernández-Aranda, Fernando organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 18 givenname: Aurora surname: Bueno-Cavanillas fullname: Bueno-Cavanillas, Aurora organization: 1Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain – sequence: 19 givenname: Josep A. surname: Tur fullname: Tur, Josep A. organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 20 givenname: Vicente surname: Martín fullname: Martín, Vicente organization: 2Centro de Investigación Biomédica en Red Epidemiología y Salud Pública (CIBERESP), Institute of Health Carlos III, Madrid, Spain – sequence: 21 givenname: Xavier surname: Pintó Sala fullname: Pintó Sala, Xavier organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 22 givenname: Miguel surname: Delgado-Rodríguez fullname: Delgado-Rodríguez, Miguel organization: 2Centro de Investigación Biomédica en Red Epidemiología y Salud Pública (CIBERESP), Institute of Health Carlos III, Madrid, Spain – sequence: 23 givenname: Pilar surname: Matía Martín fullname: Matía Martín, Pilar organization: 28Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clínico San Carlos (IdISSC), Madrid, Spain – sequence: 24 givenname: Josep surname: Vidal fullname: Vidal, Josep organization: 29CIBER Diabetes y Enfermedades Metabólicas (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 25 givenname: Jersy J. surname: Cárdenas fullname: Cárdenas, Jersy J. organization: 31Department of Endocrinology and Nutrition, Hospital Fundación Jiménez-Díaz, Instituto de Investigaciones Biomédicas IISFJD, University Autónoma, Madrid, Spain – sequence: 26 givenname: Lidia surname: Daimiel Ruiz fullname: Daimiel Ruiz, Lidia organization: 14Nutritional Control of the Epigenome, Precision Nutrition and Obesity Program IMDEA Food, CEI UAM + CSIC, Madrid, Spain – sequence: 27 givenname: Emilio orcidid: 0000-0002-2573-1294 surname: Ros fullname: Ros, Emilio organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 28 givenname: Pilar surname: Buil-Cosiales fullname: Buil-Cosiales, Pilar organization: 2Centro de Investigación Biomédica en Red Epidemiología y Salud Pública (CIBERESP), Institute of Health Carlos III, Madrid, Spain – sequence: 29 givenname: Nerea surname: Becerra-Tomás fullname: Becerra-Tomás, Nerea organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 30 givenname: Carmen surname: Saiz fullname: Saiz, Carmen organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 31 givenname: Miguel-Ángel surname: Muñoz-Perez fullname: Muñoz-Perez, Miguel-Ángel organization: 34Unitat de Suport a la Recerca en Atenció Primaria de Barcelona, IDIAP Jordi Gol, Primary Care Division, Institut Català de la Salut, Barcelona, Spain – sequence: 32 givenname: Itziar surname: Abete fullname: Abete, Itziar organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 33 givenname: Lucas surname: Tojal-Sierra fullname: Tojal-Sierra, Lucas organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 34 givenname: Olga surname: Fernández-Barceló fullname: Fernández-Barceló, Olga organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 35 givenname: Andrea surname: Bernabé-Casanova fullname: Bernabé-Casanova, Andrea organization: 35Centro de Salud Raval-Elche. Elche, Alicante, Spain – sequence: 36 givenname: Jadwiga surname: Konieczna fullname: Konieczna, Jadwiga organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 37 givenname: Antonio surname: García-Ríos fullname: García-Ríos, Antonio organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 38 givenname: Rosa surname: Casas fullname: Casas, Rosa organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 39 givenname: Maria Rosa surname: Bernal-López fullname: Bernal-López, Maria Rosa organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 40 givenname: José surname: Lapetra fullname: Lapetra, José organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 41 givenname: Estefanía surname: Toledo fullname: Toledo, Estefanía organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 42 givenname: Carlos orcidid: 0000-0002-3077-6702 surname: Gómez-Martínez fullname: Gómez-Martínez, Carlos organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 43 givenname: Oscar surname: Coltell fullname: Coltell, Oscar organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 44 givenname: Mireia surname: Malcampo-Manrúbia fullname: Malcampo-Manrúbia, Mireia organization: 12Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain – sequence: 45 givenname: María Angeles surname: Zulet fullname: Zulet, María Angeles organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 46 givenname: Carolina surname: Sorto-Sánchez fullname: Sorto-Sánchez, Carolina organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 47 givenname: Alfredo surname: Gea fullname: Gea, Alfredo organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain – sequence: 48 givenname: José Luis surname: Hernández-Fleta fullname: Hernández-Fleta, José Luis organization: 37Psychiatry Service, Hospital Dr. Negrín, Gran Canaria, Las Palmas de Gran Canaria, Spain – sequence: 49 givenname: Olga surname: Castañer Niño fullname: Castañer Niño, Olga organization: 12Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain – sequence: 50 givenname: Almudena surname: Sánchez-Villegas fullname: Sánchez-Villegas, Almudena organization: 4Consorcio CIBER, M.P. Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34713791$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1016/j.clnu.2019.08.021 10.1016/j.jad.2017.09.022 10.1016/j.appet.2010.01.014 10.1079/BJN2002778 10.1093/oxfordjournals.aje.a116966 10.1093/ije/22.3.512 10.1016/j.rpsm.2014.09.001 10.1016/j.psychres.2017.04.020 10.1016/j.jpsychires.2018.09.006 10.1007/s12603-012-0437-x 10.1017/S0029665116000045 10.1161/CIRCULATIONAHA.109.192644 10.4088/JCP.v67n1217 10.1371/journal.pone.0195103 10.1079/PHN200061 10.1097/00005768-200008000-00011 10.1016/j.jad.2014.11.030 10.1093/ije/dyy225 10.1016/j.pcd.2017.09.002 10.3945/ajcn.113.069880 10.1038/nrn2421 10.1016/S0140-6736(06)68770-9 10.1093/ajcn/nqx015 10.1016/j.ypmed.2017.03.016 10.1016/j.biopsych.2008.11.029 10.1016/j.jad.2019.11.160 10.1017/S0033291719001958 10.1159/000430229 10.1007/s00394-019-01982-x 10.1186/1471-244X-13-175 10.1111/psyg.12389 10.1249/MSS.0b013e31821ece12 10.1186/1741-7015-11-208 10.1177/2167702616645777 10.1097/00041433-200202000-00002 |
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SubjectTerms | Aged Cross-Sectional Studies Depression - epidemiology Diabetes Diet Diet, Mediterranean Dietary Surveys and Nutritional Epidemiology Follow-Up Studies Food Food quality Humans Lifestyles Mental depression Metabolic disorders Metabolic Syndrome Older people Population prospective studies Questionnaires Regression analysis Regression models Sleep Statistical analysis |
Title | Association between the Prime Diet Quality Score and depressive symptoms in a Mediterranean population with metabolic syndrome. Cross-sectional and 2-year follow-up assessment from PREDIMED-PLUS study |
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