Gepubliceerd in:

08-09-2022

Associations of somatic depressive symptoms with body mass index, systemic inflammation, and insulin resistance in primary care patients with depression

Auteurs: Aubrey L. Shell, Michelle K. Williams, Jay S. Patel, Elizabeth A. Vrany, Robert V. Considine, Anthony J. Acton, Jesse C. Stewart

Gepubliceerd in: Journal of Behavioral Medicine | Uitgave 6/2022

Abstract

The somatic depressive symptom cluster (including appetite and sleep disturbances) is more strongly associated with insulin resistance (a diabetes risk marker) than other depressive symptom clusters. Utilizing baseline data from 129 primary care patients with depression but no diabetes in the eIMPACT trial (M_age= 59 years, 78% female, 50% Black), we examined associations of somatic depressive symptoms with insulin resistance (HOMA-IR), body mass index (BMI), and high-sensitivity C-reactive protein (hsCRP). We tested BMI and hsCRP as mediators and race as a moderator of these relationships. Hyperphagia was positively associated HOMA-IR (β = 0.19, p = .048) and BMI (β = 0.30, p < .001); poor appetite was negatively associated with HOMA-IR (β = -0.24, p = .02); hypersomnia was positively associated with HOMA-IR (β = 0.28, p = .003), BMI (β = 0.26, p = .003), and hsCRP (β = 0.23, p = .01); and disturbed sleep was positively associated with hsCRP (β = 0.21, p = .04). BMI partially mediated hyperphagia and hypersomnia’s associations with HOMA-IR; hsCRP partially mediated the hypersomnia-HOMA-IR association; and race moderated the hyperphagia-HOMA-IR association (positive for White participants but null for Black participants). People with depression experiencing hyperphagia and/or hypersomnia may be a subgroup with greater insulin resistance; BMI and hsCRP are likely pathways in these relationships. This study highlights the importance of considering the direction of somatic depressive symptoms in the context of cardiometabolic disease risk.

vorige artikel Coping self-efficacy, perceived helpfulness of coping, and distress: a longitudinal investigation of breast and gynecologic cancer patients undergoing chemotherapy

volgende artikel Examining negative affect, sleep duration, and using food to cope as predictors of weight in midlife women

Abdullah, A., Peeters, A., de Courten, M., & Stoelwinder, J. (2010). The magnitude of association between overweight and obesity and the risk of diabetes: a meta-analysis of prospective cohort studies. Diabetes Research and Clinical Practice, 89(3), 309–319. https://doi.org/10.1016/j.diabres.2010.04.012CrossRefPubMed

American Diabetes Association. (2022). Classification and diagnosis of diabetes: standards of medical care in diabetes—2022. Diabetes Care, 45(Suppl 1), 17–38. https://doi.org/10.2337/dc22-S002CrossRef

Au, B., Smith, K. J., Gariépy, G., & Schmitz, N. (2014). C-reactive protein, depressive symptoms, and risk of diabetes: results from the English Longitudinal Study of Ageing (ELSA). Journal of Psychosomatic Research, 77(3), 180–186. https://doi.org/10.1016/j.jpsychores.2014.07.012CrossRefPubMed

Austin, A. W., Gordon, J. L., Lavoie, K. L., Arsenault, A., Dasgupta, K., & Bacon, S. L. (2014). Differential association of insulin resistance with cognitive and somatic symptoms of depression. Diabetic Medicine, 31(8), 994–1000. https://doi.org/10.1111/dme.12465CrossRefPubMed

Banks, S., & Dinges, D. F. (2007). Behavioral and physiological consequences of sleep restriction. Journal of Clinical Sleep Medicine, 03(05), 519–528. https://doi.org/10.5664/jcsm.26918CrossRef

Bellou, V., Belbasis, L., Tzoulaki, I., & Evangelou, E. (2018). Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses. PLoS One, 13(3), e0194127–e0194127. https://doi.org/10.1371/journal.pone.0194127CrossRefPubMedPubMedCentral

Bonora, E., Targher, G., Alberiche, M., Bonadonna, R. C., Saggiani, F., Zenere, M. B., & Muggeo, M. (2000). Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care, 23(1), 57–63. https://doi.org/10.2337/diacare.23.1.57CrossRefPubMed

Cappuccio, F. P., D’Elia, L., Strazzullo, P., & Miller, M. A. (2010). Quantity and quality of sleep and incidence of type 2 diabetes: a systematic review and meta-analysis. Diabetes Care, 33(2), 414–420. https://doi.org/10.2337/dc09-1124CrossRefPubMed

Callahan, C. M., Unverzagt, F. W., Hui, S. L., Perkins, A. J., & Hendrie, H. C. (2002). Six-item screener to identify cognitive impairment among potential subjects for clinical research. Medical Care, 40(9), 771–781. https://doi.org/10.1097/00005650-200209000-00007CrossRefPubMed

Case, S. M., & Stewart, J. C. (2014). Race/ethnicity moderates the relationship between depressive symptom severity and C-reactive protein: 2005–2010 NHANES data. Brain Behavior and Immunity, 41, 101–108. https://doi.org/10.1016/j.bbi.2014.04.004CrossRefPubMed

Centers for Disease Control and Prevention (2017). National diabetes statistics report, 2017. Atlanta, GA: Centers for Disease Control and Prevention, U.S. Department of Health and Human Services. Retrieved from https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf

Centers for Disease Control and Prevention (2020). National diabetes statistics report, 2020. Atlanta, GA: Centers for Disease Control and Prevention, U.S. Department of Health and Human Services. Retrieved from https://www.cdc.gov/diabetes/pdfs/data/statistics/national-diabetes-statistics-report.pdf

Chait, A., & den Hartigh, L. J. (2020). Adipose tissue distribution, inflammation and its metabolic consequences, including diabetes and cardiovascular disease. Frontiers in Cardiovascular Medicine, 7(22), https://doi.org/10.3389/fcvm.2020.00022

Cizza, G., Ronsaville, D. S., Kleitz, H., Eskandari, F., Mistry, S., Torvik, S., & Martinez, P. E. (2012). Clinical subtypes of depression are associated with specific metabolic parameters and circadian endocrine profiles in women: the power study. PLoS One, 7(1), e28912. https://doi.org/10.1371/journal.pone.0028912CrossRefPubMedPubMedCentral

Czech, M. P. (2017). Insulin action and resistance in obesity and type 2 diabetes. Nature Medicine, 23(7), 804–814. https://doi.org/10.1038/nm.4350CrossRefPubMedPubMedCentral

Derogatis, L. R., Lipman, R. S., Rickels, K., Uhlenhuth, E. H., & Covi, L. (1974). The Hopkins Symptom Checklist (HSCL). A measure of primary symptom dimensions. Modern Problems of Pharmacopsychiatry, 7(0), 79–110. https://doi.org/10.1159/000395070CrossRefPubMed

Diabetes Prevention Program (DPP). (2002). description of lifestyle intervention. Diabetes Care, 25(12), 2165–2171. https://doi.org/10.2337/diacare.25.12.2165CrossRef

Domecq, J. P., Prutsky, G., Leppin, A., Sonbol, M. B., Altayar, O., Undavalli, C., & Mauck, K. F. (2015). Drugs commonly associated with weight change: a systematic review and meta-analysis. The Journal of Clinical Endocrinology & Metabolism, 100(2), 363–370. https://doi.org/10.1210/jc.2014-3421

Duncan, B. B., Schmidt, M. I., Pankow, J. S., Ballantyne, C. M., Couper, D., & Heiss, G. (2003). Low-grade systemic inflammation and the development of type 2 diabetes: The atherosclerosis risk in communities study. Pathophysiology : The Official Journal Of The International Society For Pathophysiology / Isp, 52(7), 1799–1805. https://doi.org/10.2337/diabetes.52.7.1799CrossRef

Fowler, M. J. (2011). Microvascular and Macrovascular Complications of Diabetes. Clinical Diabetes, 29(3), 116–122. https://doi.org/10.2337/diaclin.29.3.116CrossRef

Fried, E. I., von Stockert, S., Haslbeck, J. M. B., Lamers, F., Schoevers, R. A., & Penninx, B. W. J. H. (2019). Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates. Psychological Medicine, 50(16), 2682–2690. https://doi.org/10.1017/S0033291719002770CrossRefPubMed

Grandner, M. A., Buxton, O. M., Jackson, N., Sands-Lincoln, M., Pandey, A., & Jean-Louis, G. (2013). Extreme sleep durations and increased c-reactive protein: effects of sex and ethnoracial group. Sleep, 36(5), 769–779. https://doi.org/10.5665/sleep.2646CrossRefPubMedPubMedCentral

Grandner, M. A., Seixas, A., Shetty, S., & Shenoy, S. (2016). Sleep duration and diabetes risk: population trends and potential mechanisms. Current Diabetes Reports, 16(11), 106–106. https://doi.org/10.1007/s11892-016-0805-8CrossRefPubMedPubMedCentral

Haffner, S. M. (2003). Insulin resistance, inflammation, and the prediabetic state. The American Journal of Cardiology, 92(4, Supplement 1), 18–26. https://doi.org/10.1016/S0002-9149(03)00612-X

Hasson, B. R., Apovian, C., & Istfan, N. (2015). Racial/Ethnic differences in insulin resistance and beta cell function: relationship to racial disparities in type 2 diabetes among African Americans versus Caucasians. Current obesity reports, 4(2), 241–249. https://doi.org/10.1007/s13679-015-0150-2CrossRefPubMed

Hayes, A. F. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York, NY, US: Guilford Press

Hickman, R. J., Khambaty, T., & Stewart, J. C. (2014). C-reactive protein is elevated in atypical but not nonatypical depression: data from the National Health and Nutrition Examination Survey (NHANES) 1999–2004. Journal of Behavioral Medicine, 37(4), 621–629. https://doi.org/10.1007/s10865-013-9510-0CrossRefPubMed

Hill-Briggs, F., Adler, N. E., Berkowitz, S. A., Chin, M. H., Gary-Webb, T. L., & Haire-Joshu, D. (2020). Social determinants of health and diabetes: a scientific review. Diabetes Care, 44(1), 258–279. https://doi.org/10.2337/dci20-0053CrossRefPubMedCentral

Hines, G., Kennedy, I., Holman, R., & Headington (2004). Oxford, United Kingdom.The Oxford Centre for Diabetes, Endocrinology and Metabolism

Hostalek, U., Gwilt, M., & Hildemann, S. (2015). Therapeutic use of metformin in prediabetes and diabetes prevention. Drugs, 75(10), 1071–1094. https://doi.org/10.1007/s40265-015-0416-8CrossRefPubMedPubMedCentral

Irwin, M. R. (2015). Why sleep is important for health: a psychoneuroimmunology perspective. Annual Review of Psychology, 66, 143–172. https://doi.org/10.1146/annurev-psych-010213-115205CrossRefPubMed

Irwin, M. R., Olmstead, R., & Carroll, J. E. (2016). Sleep disturbance, sleep duration, and inflammation: a systematic review and meta-analysis of cohort studies and experimental sleep deprivation. Biological Psychiatry, 80(1), 40–52. https://doi.org/10.1016/j.biopsych.2015.05.014CrossRefPubMed

Johnson, A. R., Milner, J. J., & Makowski, L. (2012). The inflammation highway: metabolism accelerates inflammatory traffic in obesity. Immunological Reviews, 249(1), 218–238. https://doi.org/10.1111/j.1600-065X.2012.01151.xCrossRefPubMedPubMedCentral

Jokela, M., Virtanen, M., Batty, G. D., & Kivimäki, M. (2016). Inflammation and specific symptoms of depression. JAMA Psychiatry, 73(1), 87–88. https://doi.org/10.1001/jamapsychiatry.2015.1977CrossRefPubMed

Kahn, S. E., Hull, R. L., & Utzschneider, K. M. (2006). Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature, 444, 840–846. https://doi.org/10.1038/nature05482CrossRefPubMed

Kan, C., Silva, N., Golden, S. H., Rajala, U., Timonen, M., Stahl, D., & Ismail, K. (2013). A systematic review and meta-analysis of the association between depression and insulin resistance. Diabetes Care, 36(2), 480. https://doi.org/10.2337/dc12-1442CrossRefPubMedPubMedCentral

Kappelmann, N., Arloth, J., Georgakis, M. K., Czamara, D., Rost, N., Ligthart, S., & Binder, E. B. (2021). Dissecting the association between inflammation, metabolic dysregulation, and specific depressive symptoms: a genetic correlation and 2-Sample mendelian randomization study. JAMA Psychiatry, 78(2), 161–170. https://doi.org/10.1001/jamapsychiatry.2020.3436CrossRefPubMed

Katon, W., Von Korff, M., Lin, E., Walker, E., Simon, G. E., Bush, T., & Russo, J. (1995). Collaborative management to achieve treatment guidelines: impact on depression in primary care. Journal Of The American Medical Association, 273(13), 1026–1031. https://doi.org/10.1001/jama.1995.03520370068039CrossRefPubMed

Khambaty, T., Stewart, J. C., Muldoon, M. F., & Kamarck, T. W. (2014). Depressive symptom clusters as predictors of 6-Year increases in insulin resistance: data from the Pittsburgh Healthy Heart Project. Psychosomatic Medicine, 76(5), 363–369. https://doi.org/10.1097/PSY.0000000000000063CrossRefPubMedPubMedCentral

Knol, M. J., Twisk, J. W. R., Beekman, A. T. F., Heine, R. J., Snoek, F. J., & Pouwer, F. (2006). Depression as a risk factor for the onset of type 2 diabetes mellitus. A meta-analysis. Diabetologia, 49(5), 837. https://doi.org/10.1007/s00125-006-0159-xCrossRefPubMed

Konttinen, H., Van Strien, T., Männistö, S., Jousilahti, P., & Haukkala, A. (2019). Depression, emotional eating and long-term weight changes: a population-based prospective study. International Journal of Behavioral Nutrition and Physical Activity, 16(1), 1–11. https://doi.org/10.1186/s12966-019-0791-8CrossRef

Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. https://doi.org/10.1046/j.1525-1497.2001.016009606.xCrossRefPubMedPubMedCentral

Kroenke, K., & Spitzer, R. L. (2002). The PHQ-9: A new depression diagnostic and severity measure. Psychiatric Annals, 32(9), 509–515. https://doi.org/10.3928/0048-5713-20020901-06CrossRef

Lamers, F., Milaneschi, Y., de Jonge, P., Giltay, E. J., & Penninx, B. W. (2017). J. H. Metabolic and inflammatory markers: associations with individual depressive symptoms.Psychological Medicine, 48(7),1102–1110. https://doi.org/10.1017/S0033291717002483

Lasserre, A. M., Glaus, J., Vandeleur, C. L., Marques-Vidal, P., Vaucher, J., Bastardot, F., & Preisig, M. (2014). Depression with atypical features and increase in obesity, body mass index, waist circumference, and fat mass: a prospective, population-based study. JAMA Psychiatry, 71(8), 880–888. https://doi.org/10.1001/jamapsychiatry.2014.411CrossRefPubMed

Lasserre, A. M., Strippoli, M. F., Glaus, J., Gholam-Rezaee, M., Vandeleur, C. L., Castelao, E., & Preisig, M. (2017). Prospective associations of depression subtypes with cardio-metabolic risk factors in the general population. Molecular Psychiatry, 22(7), 1026–1034. https://doi.org/10.1038/mp.2016.178CrossRefPubMed

Lee, P. W., Schulberg, H. C., Raue, P. J., & Kroenke, K. (2007). Concordance between the PHQ-9 and the HSCL-20 in depressed primary care patients. Journal of Affective Disorders, 99(1–3), 139–145. https://doi.org/10.1016/j.jad.2006.09.002CrossRefPubMed

Levis, B., Sun, Y., He, C., Wu, Y., Krishnan, A., Bhandari, P. M., Neupane, D., Imran, M., Brehaut, E., Negeri, Z., Fischer, F. H., Benedetti, A., Thombs, B. D., Che, L., Levis, A., Riehm, K., Saadat, N., Azar, M., Rice, D., & Zhang, Y. (2020). Accuracy of the PHQ-2 alone and in combination with the PHQ-9 for screening to detect major depression: systematic review and meta-analysis. Journal Of The American Medical Association, 323(22), 2290–2300. https://doi.org/10.1001/jama.2020.6504CrossRefPubMed

Li, Z. Y., Wang, P., & Miao, C. Y. (2011). Adipokines in inflammation, insulin resistance and cardiovascular disease. Clinical and Experimental Pharmacology and Physiology, 38(12), 888–896. https://doi.org/10.1111/j.1440-1681.2011.05602.xCrossRefPubMed

Luc, K., Schramm-Luc, A., Guzik, T. J., & Mikolajczyk, T. P. (2019). Oxidative stress and inflammatory markers in prediabetes and diabetes. Journal of Physiological Pharmacology, 70(6), https://doi.org/10.26402/jpp.2019.6.01

Luppino, F. S., de Wit, L. M., Bouvy, P. F., et al. (2010). Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies. Archives of General Psychiatry, 67(3), 220–229. https://doi.org/10.1001/archgenpsychiatry.2010.2CrossRefPubMed

Mac Giollabhui, N., Ng, T. H., Ellman, L. M., & Alloy, L. B. (2020). The longitudinal associations of inflammatory biomarkers and depression revisited: systematic review, meta-analysis, and meta-regression. Molecular Psychiatry. https://doi.org/10.1038/s41380-020-00867-4CrossRefPubMedPubMedCentral

Majd, M., Saunders, E. F. H., & Engeland, C. G. (2020). Inflammation and the dimensions of depression: a review. Frontiers in Neuroendocrinology, 56, 100800. https://doi.org/10.1016/j.yfrne.2019.100800CrossRefPubMed

Manea, L., Gilbody, S., & McMillan, D. (2012). Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis. Canadian Medical Association Journal, 184(3), E191–196. https://doi.org/10.1503/cmaj.110829CrossRefPubMedPubMedCentral

Mezuk, B., Eaton, W. W., Albrecht, S., & Golden, S. H. (2008). Depression and type 2 diabetes over the lifespan: a meta-analysis. Diabetes Care, 31(12), 2383–2390. https://doi.org/10.2337/dc08-0985CrossRefPubMedPubMedCentral

Milaneschi, Y., Simmons, W. K., van Rossum, E. F. C., & Penninx, B. W. (2019). Depression and obesity: evidence of shared biological mechanisms. Molecular Psychiatry, 24(1), 18–33. https://doi.org/10.1038/s41380-018-0017-5CrossRefPubMed

National Heart Lung and Blood Institute & National Institute of Diabetes and Digestive and Kidney Diseases. (1998). Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. National Heart, Lung, and Blood Institute

National Institute of Diabetes and Digestive and Kidney Diseases (2018). Insulin resistance & prediabetes. Retrieved from https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/prediabetes-insulin-resistance

Nelson, D. E., Holtzman, D., Bolen, J., Stanwyck, C. A., & Mack, K. A. (2001). Reliability and validity of measures from the Behavioral Risk Factor Surveillance System (BRFSS). Sozial- Und Praventivmedizin, 46(Suppl 1), S3–42PubMed

O’Connor, M., Butcher, I., Hansen, C. H., Kleiboer, A., Murray, G., Sharma, N., & Sharpe, M. (2010). Measuring improvement in depression in cancer patients: a 50% drop on the self-rated SCL-20 compared with a diagnostic interview. General Hospital Psychiatry, 32(3), 334–336. https://doi.org/10.1016/j.genhosppsych.2010.01.001CrossRefPubMed

Paans, N., Bot, M., Brouwer, I. A., Visser, M., Roca, M., Kohls, E., Watkins, E., & Penninx, B. (2018). The association between depression and eating styles in four European countries: The MooDFOOD prevention study. Journal of psychosomatic research, 108, 85–92. https://doi.org/10.1016/j.jpsychores.2018.03.003CrossRefPubMed

Paige, E., Korda, R., Kemp-Casey, A., Rodgers, B., Dobbins, T., & Banks, E. (2015). A record linkage study of antidepressant medication use and weight change in Australian adults. Australian & New Zealand Journal of Psychiatry, 49(11), 1029–1039. https://doi.org/10.1177/0004867415607365CrossRef

Pearson, T. A., Mensah, G. A., Alexander, R. W., Anderson, J. L., Cannon, R. O., Criqui, M., & Vinicor, F. (2003). Markers of inflammation and cardiovascular disease. Circulation, 107(3), 499–511. https://doi.org/10.1161/01.CIR.0000052939.59093.45CrossRefPubMed

Polanka, B. M., Vrany, E. A., Patel, J., & Stewart, J. C. (2017). Depressive disorder subtypes as predictors of incident obesity in US adults: moderation by race/ethnicity. Americal Journal of Epidemiology, 185(9), 734–742. https://doi.org/10.1093/aje/kwx030CrossRef

Price, J. L., Bruce, M. A., & Adinoff, B. (2021). Addressing structural racism in psychiatry with steps to improve psychophysiologic research. JAMA Psychiatry. https://doi.org/10.1001/jamapsychiatry.2021.2663CrossRefPubMedPubMedCentral

Rahe, C., Baune, B. T., Unrath, M., Arolt, V., Wellmann, J., Wersching, H., & Berger, K. (2015). Associations between depression subtypes, depression severity and diet quality: cross-sectional findings from the BiDirect Study. Bmc Psychiatry, 15(1), 38CrossRefPubMedPubMedCentral

Raison, C. L., Capuron, L., & Miller, A. H. (2006). Cytokines sing the blues: inflammation and the pathogenesis of depression. Trends in Immunology, 27(1), 24–31. https://doi.org/10.1016/j.it.2005.11.006CrossRefPubMed

Rudvik, A., & Mansson, M. (2018). Evaluation of surrogate measures of insulin sensitivity – correlation with gold standard is not enough. BMC Medical Research Methodology, 18, 64. https://doi.org/10.1186/s12874-018-0521-yCrossRefPubMedPubMedCentral

Schweiger, U., Greggersen, W., Rudolf, S., Pusch, M., Menzel, T., Winn, S., & Peters, A. (2008). Disturbed glucose disposal in patients with major depression; application of the glucose clamp technique. Psychosomatic Medicine, 70(2), 170–176. https://doi.org/10.1097/PSY.0b013e318164231dCrossRefPubMed

Serretti, A., Mandelli, L., & Laura, M. (2010). Antidepressants and body weight: a comprehensive review and meta-analysis. Journal of Clinical Psychiatry, 71(10), 1259–1272. https://doi.org/10.4088/JCP.09r05346bluCrossRefPubMed

Shell, A. L., Jackson, R. A., Patel, J. S., Hirsh, A. T., Cyders, M. A., & Stewart, J. C. (2021). Associations of somatic depressive symptoms with food attentional bias and eating behaviors. Appetite, 167, 105593. https://doi.org/10.1016/j.appet.2021.105593CrossRefPubMed

Simmons, W. K., Burrows, K., Avery, J. A., Kerr, K. L., Taylor, A., Bodurka, J., & Drevets, W. C (2020). Appetite changes reveal depression subgroups with distinct endocrine, metabolic, and immune states. Molecular Psychiatry, 25(7), 1457–1468. https://doi.org/10.1038/s41380-018-0093-6CrossRefPubMed

Unützer, J., Katon, W., Callahan, C. M., Williams, J., John, W., Hunkeler, E., & Harpole, L.,… Investigators, f. t. I. (2002). Collaborative care management of late-life depression in the primary care setting. A randomized controlled trial.JAMA, 288(22),2836–2845. https://doi.org/10.1001/jama.288.22.2836

van Strien, T., Winkens, L., Toft, M. B., Pedersen, S., Brouwer, I., Visser, M., & Lähteenmäki, L. (2016). The mediation effect of emotional eating between depression and body mass index in the two European countries Denmark and Spain. Appetite, 105, 500–508. https://doi.org/10.1016/j.appet.2016.06.025CrossRefPubMed

Vrany, E. A., Berntson, J. M., Khambaty, T., & Stewart, J. C. (2016). Depressive symptoms clusters and insulin resistance: race/ethnicity as a moderator in 2005–2010 NHANES data. Annals of Behavioral Medicine, 50(1), 1–11. https://doi.org/10.1007/s12160-015-9725-0CrossRefPubMed

Walker, E. A., Katon, W. J., Russo, J., Von Korff, M., Lin, E., Simon, G., & Unützer, J. (2000). Predictors of outcome in a primary care depression trial. Journal of General Internal Medicine, 15(12), 859–867. https://doi.org/10.1046/j.1525-1497.2000.91142.xCrossRefPubMedPubMedCentral

Wallace, T. M., Levy, J. C., & Matthews, D. R. (2004). Use and abuse of HOMA modeling. Diabetes Care, 27(6), 1487–1495. https://doi.org/10.2337/diacare.27.6.1487CrossRefPubMed

Titel: Associations of somatic depressive symptoms with body mass index, systemic inflammation, and insulin resistance in primary care patients with depression
Auteurs: Aubrey L. Shell
Michelle K. Williams
Jay S. Patel
Elizabeth A. Vrany
Robert V. Considine
Anthony J. Acton
Jesse C. Stewart
Publicatiedatum: 08-09-2022
Uitgeverij: Springer US
Gepubliceerd in: Journal of Behavioral Medicine / Uitgave 6/2022
Print ISSN: 0160-7715
Elektronisch ISSN: 1573-3521
DOI: https://doi.org/10.1007/s10865-022-00356-9

Andere artikelen Uitgave 6/2022

Correlates of HIV Testing across the lifespan – adolescence through later adulthood – among sexual minority men in the US who are not on PrEP

Brief Report

Social–contextual factors interact with masculinity to influence college men’s HPV vaccination intentions: The role of descriptive norms, prototypes, and physician gender

Examining negative affect, sleep duration, and using food to cope as predictors of weight in midlife women

Crossing lines does not equal intersectionality

Letter to Editor

Racial/ethnic variations in inflammatory markers: exploring the role of sleep duration and sleep efficiency

Intersectionality does not equal intersectional stigma: reply to Lett (2022)

Letter to Editor