Network structure of perinatal depressive symptoms in latinas: Relationship to stress and reproductive biomarkers

Research in Nursing and Health

Volumn 40, Issue 3, 2017, Pages 218-228

  Santos, Hudson ^a   Fried, Eiko I ^b   Asafu Adjei, Josephine ^a   Jeanne Ruiz, R ^c  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

^c TEXAS A AND M HEALTH SCIENCE CENTER   (United States)

Author keywords

Biomarkers; Depressive symptoms; Latinas; Network analysis; Perinatal depression

Indexed keywords

BIOLOGICAL MARKER;

ADULT; BLOOD; CROSS-SECTIONAL STUDY; DEPRESSION; ETHNOLOGY; FEMALE; HISPANIC; HUMAN; MENTAL STRESS; NURSING RESEARCH; PERINATAL CARE; PREGNANCY; PSYCHOLOGY; SECOND TRIMESTER PREGNANCY; SYMPTOM ASSESSMENT;

ADULT; BIOMARKERS; CROSS-SECTIONAL STUDIES; DEPRESSION; FEMALE; HISPANIC AMERICANS; HUMANS; NURSING RESEARCH; PERINATAL CARE; PREGNANCY; PREGNANCY TRIMESTER, SECOND; STRESS, PSYCHOLOGICAL; SYMPTOM ASSESSMENT;

EID: 85013392443     PISSN: 01606891     EISSN: 1098240X     Source Type: Journal    
DOI: 10.1002/nur.21784     Document Type: Article

References (65)

1. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders. (5 ed.). Washington, DC: American Psychiatric Association.
2. Barrat, A., Barthelemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences of the USA, 101, 3747-3752. doi: 10.1073/pnas.0400087101
3. Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Beck Depression Inventory: Second edition manual. San Antonio, TX: The Psychological Corporation.
4. Beck, C. T. (2002). Postpartum depression: A metasynthesis. Qualitative Health Research, 12, 453-472. doi: 10.1177/104973202129120016
5. Bernstein, I. H., Rush, A. J., Yonkers, K., Carmody, T. J., Woo, A., McConnell, K., & Trivedi, M. H. (2008). Symptom features of postpartum depression: Are they distinct? Depression and Anxiety, 25, 20-26. doi: 10.1002/da.20276
6. Bloch, M., Daly, R. C., & Rubinow, D. R. (2003). Endocrine factors in the etiology of postpartum depression. Comprehensive Psychiatry, 44, 234-246. doi: 10.1016/S0010-440X(03)00034-8
7. Borsboom, D. (2008). Psychometric perspectives on diagnostic systems. Journal of Clinical Psychology, 64, 1089-1108. doi: 10.100 2/jclp.20503
8. Borsboom, D., & Cramer, A. O. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91-121. doi: 10.1146/annurevclinpsy-050212-185608
9. Boschloo, L., van Borkulo, C. D., Borsboom, D., & Schoevers, R. A. (2016). A prospective study on how symptoms in a network predict the onset of depression. Psychotherapy and Psychosomatics, 85, 183-184. doi: 10.1159/000442001
10. Brandes, U. (2001). A faster algorithm for betweenness centrality. The Journal of Mathematical Sociology, 25, 163-177. doi: 10.10 80/0022250X 2001.9990249
11. Castro, A. R. T., Anderman, P. C., Glover, V., O’Connor, T. G., Ehlert, U., & Kammerer, M. (2016). Associated symptoms of depression: Patterns of change during pregnancy. Archives of Women’s Mental Health. Advance online publication. doi: 10.1007/s00737-016-0685-6 [Epub ahead of print].
12. Corwin, E. J., Pajer, K., Paul, S., Lowe, N., Weber, M., & McCarthy, D. O. (2015). Bidirectional psychoneuroimmune interactions in the early postpartum period influence risk of postpartum depression. Brain, Behavior, and Immunity, 49, 86-93. doi: 10.1016/j. bbi.2015.04.012
13. Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mottus, R., Waldorp, L. J., & Cramer, A. O. J. (2015). State of the aRt personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality, 54, 13-29. doi: http://dx.doi.org/10.1016/j.jrp.2014.07.003
14. Cramer, A. O. J., van Borkulo, C. D., Giltay, E. J., van der Maas, H. L. J., Kendler, K. S., Scheffer, M., & Borsboom, D. (2016). Major depression as a complex dynamic system. PLOS ONE, 11, e0167490. doi: 10.1371/journal.pone.0167490
15. Ennis, S. R., Rios-Vargas, M., & Albert, N. (2011). The Hispanic population: 2010. Washington, DC: Economics and Statistics Administration.
16. Epskamp, S (2016). Network psychometrics (unpublished dissertation). Amsterdam: University of Amsterdam.
17. Epskamp, S., & Fried, E. I. (2016). A primer on estimating regularized psychological networks. Arxiv Preprint (ID 1607.01367), 1-14. Retrieved from http://arxiv.org/abs/1607.01367
18. Epskamp, S., Cramer, A., Waldorp, L., Schmittmann, V., & Borsboom, D. (2012). Qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48, 1-18. doi: 10.18637/jss.v048.i04
19. Epskamp, S., Borsboom, D., & Fried, E. (2016). Estimating psychological networks and their stability: A tutorial paper. Arxiv Preprint (ID 1604.08045), 1-34. Retrieved from https://arxiv.org/abs/1604.08462
20. Epskamp, S., Rhemtulla, M., & Borsboom, D. (2016). Generalized network psychometrics: Combining network and latent variable models. Psychometrika. Retrieved from http://arxiv.org/abs/1605.09288
21. Figueiredo, F. P., Parada, A. P., Araujo, L. F., Silva, W. A., & Del-Ben, C. M. (2015). The influence of genetic factors on peripartum depression: A systematic review. Journal of Affective Disorders, 172, 265-273. doi: 10.1016/j.jad.2014.10.016
22. Freeman, L. C. (1978). Centrality in social networks: Conceptual clarification. Social Networks, 1, 215-239. doi: https://doi.org/10.1016/0378-8733(78)90021-7
23. Fried, E. I. (2015). Problematic assumptions have slowed down depression research: Why symptoms, not syndromes are the way forward. Frontiers in Psychology, 6, 309. doi: 10.3389/fpsyg.2 015.00309
24. Fried, E. I., & Cramer, A. O. J. (2016). Moving forward: Challenges and directions for psychopathological network theory and methodology. OSF Preprint, 1-53. Retrieved from https://osf.io/bnekp. doi: 10.17605/OSF.IO/BNEKP
25. Fried, E. I., & Nesse, R. M. (2015a). Depression is not a consistent syndrome: An investigation of unique symptom patterns in the STARD study. Journal of Affective Disorders, 172, 96-102. doi: 10.1016/j.jad.2014.10.010
26. Fried, E. I., & Nesse, R. M. (2015b). Depression sum-scores don’t add up: Why analyzing specific depression symptoms is essential. BMC Medicine, 13, 72. doi: 10.1186/s12916-015-0325-4
27. Fried, E. I., van Borkulo, C. D., Cramer, A. O. J., Lynn, B., Schoevers, R. A., & Borsboom, D (2016). Mental disorders as networks of problems: A review of recent insights. Social Psychiatry and Psychiatric Epidemiology. Advance online publication. doi: 10.1007/s00127-016-1319-z
28. Friedman, J., Hastie, T., & Tibshirani, R. (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9, 432-441. doi: 10.1093/biostatistics/kxm045
29. Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21, 1129-1164. doi: 10.1002/spe.4380211102
30. Gavin, N. I., Gaynes, B. N., Lohr, K. N., Meltzer-Brody, S., Gartlehner, G., & Swinson, T. (2005). Perinatal depression: A systematic review of prevalence and incidence. Obstetrics and Gynecology, 106(5 Pt 1), 1071-1083. doi: 10.1097/01.AOG 0000183597.31630.db
31. Halbreich, U., & Karkun, S. (2006). Cross-cultural and social diversity of prevalence of postpartum depression and depressive symptoms. Journal of Affective Disorders, 91, 97-111. doi: 10.1016/j.jad.2005.12.051
32. Haslbeck, J. M. B., & Waldorp, L. J. (2016). How well do network models predict future observations? On the importance of predictability in network models. Arxiv Preprint (ID 1610.09108), 1-13. Retrieved from https://arxiv.org/abs/1610.09108
33. Henly, S. J. (2013). Use progress in psychometrics to advance nursing science: Revisiting factor analysis. Nursing Research, 62, 147-148. doi: 10.1097/NNR.0b013e318294b509
34. Henly, S. J. (2015). The symptom science model: Challenges in dissemination across the investigative sequence. Nursing Research, 64, 329-330. doi: 10.1097/NNR. 0000000000000119
35. Jokela, M., Virtanen, M., Batty, G. D., & Kivimaki, M. (2016). Inflammation and specific symptoms of depression. JAMA Psychiatry, 73, 1-6. doi: 10.1001/jamapsychiatry.2015.1977
36. Kuo, W. H., Wilson, T. E., Holman, S., Fuentes-Afflick, E., O’Sullivan, M. J., & Minkoff, H. (2004). Depressive symptoms in the immediate postpartum period among Hispanic women in three U.S. cities. Journal of Immigrant and Minority Health, 6, 145-153. doi: 10.1023/B:JOIH 0000045252.10412.fa
37. Lara-Cinisomo, S., Wisner, K. L., & Meltzer-Brody, S. (2015). Advances in science and biomedical research on postpartum depression do not include meaningful numbers of Latinas. Journal of Immigrant and Minority Health, 17, 1593. doi: 10.1007/s10903-015-0205-1
38. Lara-Cinisomo, S., Girdler, S. S., Grewen, K., & Meltzer-Brody, S. (2016). A biopsychosocial conceptual framework of postpartum depression risk in immigrant and U.S.-born Latina mothers in the United States. Women’s Health Issues, 26, 336-343. doi: 10.10 16/j.whi.2016.02.006
39. Lee, K. A., Meek, P., & Grady, P. A. (2014). Advancing symptom science: Nurse researchers lead the way. Nursing Outlook, 62, 301-302. doi: 10.1016/j.outlook.2014.05.010
40. Lucero, N. B., Beckstrand, R. L., Callister, L. C., & Sanchez Birkhead, A. C (2012). Prevalence of postpartum depression among Hispanic immigrant women. Journal of American Association of Nurse Practitioners, 24, 726-734. doi: 10.1111/j.1745-7599.20 12.00744.x
41. Muthen, B. O. (1989). Factor structure in groups selected on observed scores. British Journal of Mathematical and Statistical Psychology, 42, 81-90. doi: 10.1111/j. 2044-8317. 1989. tb01116.x
42. Newman, M. E. J. (2004). Analysis of weighted networks. Physical Review E, 70, 056131.
43. O’Hara, M. W., & McCabe, J. E. (2013). Postpartum depression: Current status and future directions. Annual Review of Clinical Psychology, 9, 379-407. doi: 10.1146/annurev-clinpsy-050212-185612
44. O’Hara, M. W., Rehm, L. P., & Campbell, S. B. (1982). Predicting depressive symptomatology: Cognitive-behavioral models and postpartum depression. Journal of Abnormal Psychology, 91, 457-461.
45. Olbert, C. M., Gala, G. J., & Tupler, L. A. (2014). Quantifying heterogeneity attributable to polythetic diagnostic criteria: Theoretical framework and empirical application. Journal of Abnormal Psychology, 123, 452-462. doi: 10.1037/a0036068
46. Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32, 245-251. doi: https://doi.org/10.1016/j.socnet.2010.03.006
47. Pe, M. L., Kircanski, K., Thompson, R. J., Bringmann, L. F., Tuerlinckx, F., Mestdagh, M., Gotlib, I. H. (2015). Emotion-network density in major depressive disorder. Clinical Psychological Science, 3, 292-300. doi: 10.1177/2167702614540645
48. Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385-401. doi: 10.1177/014662167700 100306
49. Redeker, N. S., Anderson, R., Bakken, S., Corwin, E., Docherty, S., Dorsey, S. G., & Grady, P. (2015). Advancing symptom science through use of common data elements. Journal of Nursing Scholarship, 47, 379-388. doi: 10.1111/jnu.12155
50. Ruiz, R. J., Dolbier, C. L., & Fleschler, R. (2006). The relationships among acculturation, biobehavioral risk, stress, corticotropinreleasing hormone, and poor birth outcomes in Hispanic women. Ethnicity and Disease, 16, 926-932.
51. Ruiz, R. J., Marti, C. N., Pickler, R., Murphey, C., Wommack, J., & Brown, C. E. (2012). Acculturation, depressive symptoms, estriol, progesterone, and preterm birth in Hispanic women. Archives of Women’s Mental Health, 15, 57-67. doi: 10.1007/s00737-012-0258-2
52. Ruiz, R. J., Stowe, R. P., Brown, A., & Wommack, J. (2012). Acculturation and biobehavioral profiles in pregnant women of Hispanic origin: Generational differences. Advances in Nursing Science, 35, E1-E10. doi: 10.1097/ANS.0b013e3182626199
53. Ruiz, R. J., Dwivedi, A. K., Mallawaarachichi, I., Balcazar, H. G., Stowe, R. P., Ayers, K. S., & Pickler, R. (2015). Psychological, cultural and neuroendocrine profiles of risk for preterm birth. BMC Pregnancy and Childbirth, 15, 204. doi: 10.1186/s12884-015-0640-y
54. Ruiz, R. J., Gennaro, S., O’Connor, C., Dwivedi, A., Gibeau, A., Keshinover, T., & Welsh, T. (2016). CRH as a predictor of preterm birth in minority women. Biological Research for Nursing, 18, 316-321. doi: 10.1177/1099800415611248
55. Santos, H., Tan, X., & Salomon, R. (2016). Heterogeneity in perinatal depression: How far have we come? A systematic review. Archives of Women’s Mental Health. Advance online publication. doi: 10.1007/s00737-016-0691-8
56. Schiller, C. E., Meltzer-Brody, S., & Rubinow, D. R. (2015). The role of reproductive hormones in postpartum depression. CNS Spectrums, 20, 48-59. doi: 10.1017/S1092852914000480
57. Schmittmann, V. D., Cramer, A. O. J., Waldorp, L. J., Epskamp, S., Kievit, R. A., & Borsboom, D. (2013). Deconstructing the construct: A network perspective on psychological phenomena. New Ideas in Psychology, 31, 43-53. doi: 10.1016/j.newideapsych.20 11.02.007
58. Seth, S., Lewis, A. J., & Galbally, M. (2016). Perinatal maternal depression and cortisol function in pregnancy and the postpartum period: A systematic literature review. BMC Pregnancy and Childbirth, 16, 124. http://doi.org/10.1186/s12884-016-0915-y
59. Stein, A., Pearson, R. M., Goodman, S. H., Rapa, E., Rahman, A., McCallum, M., Pariante, C. M. (2014). Effects of perinatal mental disorders on the fetus and child. Lancet, 384, 1800-1819. doi: 10.1016/S0140-6736(14)61277-0
60. Treadway, M. T., & Leonard, C. V. (2016). Isolating biomarkers for symptomatic states: Considering symptom-substrate chronometry. Molecular Psychiatry, 21, 1180-1187. doi: 10.1038/mp.2016.83 Epub 2016 May 31.
61. Tsigos, C., & Chrousos, G. P. (2002). Hypothalamic-pituitary-adrenal axis, neuroendocrine factors and stress. Journal of Psychosomatic Research, 53, 865-871. doi: 10.1016/S0022-3999(02) 00429-4
62. van Borkulo, C. (2016). Network Comparison Test. Retrieved from https://github.com/cvborkulo/NetworkComparisonTest
63. Wigman, J. T., van Os, J., Borsboom, D., Wardenaar, K. J., Epskamp, S., Klippel, A. MERGE. (2015). Exploring the underlying structure of mental disorders: Cross-diagnostic differences and similarities from a network perspective using both a topdown and a bottom-up approach. Psychological Medicine, 45, 2375-2387. doi: 10.1017/S0033291715000331
64. Wisner, K. L., Moses-Kolko, E. L., & Sit, D. K. (2010). Postpartum depression: A disorder in search of a definition. Archives of Women’s Mental Health, 13, 37-40. doi: 10.1007/s00737-009-0119-9
65. Yim, I. S., Tanner Stapleton, L. R., Guardino, C. M., Hahn-Holbrook, J., & Dunkel Schetter, C (2015). Biological and psychosocial predictors of postpartum depression: systematic review and call for integration. Annual Review of Clinical Psychology, 11, 99-137. doi: 10.1146/annurev-clinpsy-101414-020426