Sociodemographic profile and social support for post-stroke depression in Kinshasa: A rehabilitation based cross-sectional study
Author(s)
Magloire Nkosi Mpembi*,
Samuel Mampunza ma Miezi,
André Peeters,
Marie-Pierre de Partz,
Sévérine Henrard,
Victoria Kubuta Massamba,
Roland Nengi Nsam,
Thierry Matonda ma Nzuzi,
Jean Macq,
Vincent Dubois,
Eric Constant
Affiliation(s)
Institut de Recherché Santé et Société, Université Catholique de Louvain (UCL), Brussels, Belgium. Centre Neuro PsychoPathologique, Université de Kinshasa (UNIKIN), Kinshasa, Congo. Cliniques Universitaires Saint Luc, Université Catholique de Louvain (UCL), Brussels, Belgium. Research Center in Epidemiology, Biostatistics and Clinical Trials, School of Public Health, Université Libre de Bruxelles, Brussels, Belgium.
Institut de Recherché Santé et Société, Université Catholique de Louvain (UCL), Brussels, Belgium. Centre Neuro PsychoPathologique, Université de Kinshasa (UNIKIN), Kinshasa, Congo. Cliniques Universitaires Saint Luc, Université Catholique de Louvain (UCL), Brussels, Belgium. Research Center in Epidemiology, Biostatistics and Clinical Trials, School of Public Health, Université Libre de Bruxelles, Brussels, Belgium.
ABSTRACT
The World Health Organization has highlighted the emergence of non-communicable chronic diseases, including stroke, in developing countries. As a cause of death, stroke ranks first in Africa. Stroke is the foremost cause of neuropsychiatric disease, including post-stroke depression (PSD) which is a very common disease. Surveys of this condition in Congolese pa tients are virtually non-existent. The objectives of this study were to assess the prevalence of PSD in Congolese patients and identify associated sociodemographic factors. Age, sex, address, province of origin, social and professional status, education, religion and consumption habits were chosen as indicators or parameters of interest to be examined in this study. The results of descriptive analyses are presented as frequencies for categorical variables and as mean ± standard deviation for quantitative variables. The association between different variables was assessed using tables of comparisons of proportions and the Chi-square test. Logistic regression was performed to predict the occurrence of PSD. There were more male than female patients. The mean age was 54.67 ± 12.51 years. Nearly 3 fourths of the patients were aged less than 65. The family was the primary source of social support. The majority was satisfied by the social support received from the family. Just over half the study patients (53.6%) had mild to severe depression as assessed by the PHQ9. Univariate analysis and logistic regression indicated a statistically significant association between low educational level and the occurrence of PSD. However, there was no relationship between age, sex or drinking habits and the onset of PSD. The majority of the subjects were satisfied by the social support from their families. Depression was common after stroke with the occurrence of 53.6%. These results highlight the need to investigate, diagnose and treat PSD, which is a risk factor for morbidity and mortality after stroke.
The World Health Organization has highlighted the emergence of non-communicable chronic diseases, including stroke, in developing countries. As a cause of death, stroke ranks first in Africa. Stroke is the foremost cause of neuropsychiatric disease, including post-stroke depression (PSD) which is a very common disease. Surveys of this condition in Congolese pa tients are virtually non-existent. The objectives of this study were to assess the prevalence of PSD in Congolese patients and identify associated sociodemographic factors. Age, sex, address, province of origin, social and professional status, education, religion and consumption habits were chosen as indicators or parameters of interest to be examined in this study. The results of descriptive analyses are presented as frequencies for categorical variables and as mean ± standard deviation for quantitative variables. The association between different variables was assessed using tables of comparisons of proportions and the Chi-square test. Logistic regression was performed to predict the occurrence of PSD. There were more male than female patients. The mean age was 54.67 ± 12.51 years. Nearly 3 fourths of the patients were aged less than 65. The family was the primary source of social support. The majority was satisfied by the social support received from the family. Just over half the study patients (53.6%) had mild to severe depression as assessed by the PHQ9. Univariate analysis and logistic regression indicated a statistically significant association between low educational level and the occurrence of PSD. However, there was no relationship between age, sex or drinking habits and the onset of PSD. The majority of the subjects were satisfied by the social support from their families. Depression was common after stroke with the occurrence of 53.6%. These results highlight the need to investigate, diagnose and treat PSD, which is a risk factor for morbidity and mortality after stroke.
Cite this paper
Mpembi, M. , Miezi, S. , Peeters, A. , de Partz, M. , Henrard, S. , Massamba, V. , Nsam, R. , Nzuzi, T. , Macq, J. , Dubois, V. and Constant, E. (2013) Sociodemographic profile and social support for post-stroke depression in Kinshasa: A rehabilitation based cross-sectional study. Open Journal of Epidemiology, 3, 111-117. doi: 10.4236/ojepi.2013.3318.
Mpembi, M. , Miezi, S. , Peeters, A. , de Partz, M. , Henrard, S. , Massamba, V. , Nsam, R. , Nzuzi, T. , Macq, J. , Dubois, V. and Constant, E. (2013) Sociodemographic profile and social support for post-stroke depression in Kinshasa: A rehabilitation based cross-sectional study. Open Journal of Epidemiology, 3, 111-117. doi: 10.4236/ojepi.2013.3318.
References
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[1] Heller, R.F., Langhorne, P. and James, E. (2000) Improving the Stroke Outcome: the Benefits of Increasing Availability of Technology. Bull World Health Organ, 78, 1338-1343. [2] Sagui, E. (2007) Les accidents vasculaires cérébraux en Afrique subsaharienne. Médecine Tropicale, 67, 596-600. [3] Mckay, J. and Mensa, G.A. (2004) The Atlas of heart disease and stroke. WHO-CDC, Geneva. [4] Grosjean, M. and Courbin C. (2003) Points essentiels du guideline sur la prise en charge des patients souffrant d’ accident vasculaire cérébral. Louvain Médical, 122, 575-581. [5] Longo-Mbenza, B., Tonduangu, K., Muyeno, K., Phanzu, M., Kebolo Baku, A., Muvova, D., Lelo, T., Odio, W., Lukoki, L., Bikangi Nkiabungu, F., Kilembe, M., Tshiamala, P., Katalay, L., Mwema, M and Muyembe, T. (2000) Predictors of stroke-associated mortality in Africans. Revue d’Epidémiologie et de Santé Publique, 48, 31-39. [6] Schmid, A.A., Kroenke, K., Hendrie, H.C., Bakas, T., Sutherland, J.M. and Williams, L.S. (2011) Post-stroke depression and treatment effects on functional outcomes. Neurology, 11, 1000-1005. doi:10.1212/WNL.0b013e318210435e [7] Lenzi, G.L., Altieri, M. and Maestrini, I. (2008) Post-stroke depression. Revue Neurologique, 164, 837-840. doi:10.1016/j.neurol.2008.07.010 [8] Gabaldón, L., Fuentes, B., Frank-García, A. and Díez-Tejedor, E. (2007) Post-stroke depression: Importance of its Detection and treatment. Cerebrovascular Diseases, 24, 181-188. doi:10.1159/000107394 [9] Carballeira, Y., Dumont, P., Borgacci, S., Rentsch, D., de Tonnac, N., Archinard, M. and Andreoli, A. (2007) Criterion validity of the French version of Patient Health Questionnaire (PHQ) in a hospital department of internal medicine. Psychology and Psychotherapy, 80, 69-77. doi:10.1348/147608306X103641 [10] Sutcliffe, L.M. and Lincoln, N.B. (1998) The assessment of depression in aphasic stroke patients: The development of the stroke aphasic depression questionnaire. Clinical Rehabilitation, 12, 506-513. doi:10.1191/026921598672167702 [11] Thorvaldsen, P., Kuulasma, K., Rajakanga, A.M., Rastenyte, D., Sarti, C. and Wilhelmsen, L. (1997) Stroke trends in WHO MONICA project. Stroke, 28, 5-6. doi:10.1161/01.str.28.3.500 [12] Petrea, R.E., Beiser, A.S., Seshadri, S., Kelly-Hayes, M., Kase, C.S. and Wolf, P.A. (2009) Stroke in women: Gender differences in stroke incidence and post stroke disability in the Framingham Heart Study. Stroke, 40, 1032-1037. doi:10.1161/strokeaha.108.542894 [13] Wyller, T.B. (1999) Stroke and gender. Journal of Gender-Specific Medicine, 2, 41-45. [14] Modena, M.G., Bonetti, L., Coppi, F., Bursi, F. and Rossi, R. (2002) Prognostic role of reversible endothelial dysfunction in hypertensive postmenopausal women. Journal of the American College of Cardiology, 40, 505-510. doi:10.1016/S0735-1097(02)01976-9 [15] Nguyen, D.H., Paule, P., Pham, N.S., Michel, R., Vu Dien, B. and Fourcade, L. (2007) Etude des facteurs de risque cardiovasculaire associés à l’athérosclérose de l’aorte thoracique dépistée par échocardiographie transoesophagienne au Viêt-Nam. Médecine Tropicale, 67, 573-578. [16] Roof, R.L. and Hall, E.D. (2000) Gender differences in acute CNS trauma and stroke: Neuroprotective effects of estrogen and progesterone. Journal of Neurotrauma, 17, 367-388. doi:10.1089/neu.2000.17.367 [17] Sibon, I., Lasalle-Lagadec, S., Renou, P. and Swendsen, J. (2012) Evolution of depression symptoms following stroke: A prospective study using computerized ambulatory monitoring. Cerebrovascular Diseases, 33, 280-285. doi:10.1159/000334663 [18] Carota, A. and Paoluci, S. (2007) Depression after stroke. In: Godefroy, O. and Bogousslavsky, J., Eds., The Behavioral and Cognitive Neurology of Stroke, Cambridge University Press, Cambridge, 548-570. doi:10.1017/CBO9780511544880.030 [19] Camus, V. and Schmitt, L. (2000) Manifestations psychiatriques des affections cérébrovasculaires: Approche clinique et thérapeutique. Encyclopédie MédicoChirurgicale Psychiatrie. [20] Herrmann, N., Black, S.E., Lawrence, J., Szekely, C. and Szalai, J.P. (1998) The sunnybrook stroke study: A prospective study of depressive symptoms and functional outcome. Stroke, 29, 618-624. doi:10.1161/01.STR.29.3.618 [21] Paolucci, S., Antonucci, G., Pratesi, L., Traballesi, M., Grasso, M.G. and Lubich, S. (1999) Post-stroke depression and its role in rehabilitation of inpatients. Archives of Physical Medicine and Rehabilitation, 80, 985-990. doi:10.1016/S0003-9993(99)90048-5 [22] Eriksson, M., Asplund, K., Glader, E.L., Norrving, B., Stegmayr, B., Terént, A., Asberg, K.H. and Wester, P.O. (2004) Riks-stroke collaboration self-reported depression and use of antidepressant after stroke: A national survey. Stroke, 35, 936-941. doi:10.1161/01.STR.0000121643.86762.9a [23] Oladiji, J.O., Akinbo, S.R.A., Aina, O.F. and Aiyejunsule, C.B. (2009) Risk factor of post-stroke depression among stroke survivors in Lagos, Nigeria. African Journal of Psychiatry, 12, 47-51. [24] Carod-Art, F.J., Coral, F.L., Trizotto, D.F. and Moreira, C.M. (2009) Post-stroke depression: Prevalence and determinants in Brazilian stroke depression. Cerebrovascular Diseases, 28, 157-165. doi:10.1159/000226114 [25] Chatterjee, K., Fall, S. and Barer, D. (2010) Mood after stroke: A case control study of biochemical, neuro-imaging and socio-economic risk factors for major depression in stroke survivors. BMC Neurology, 10, 125. doi:10.1186/1471-2377-10-125 [26] Lincoln, N.B. and Flannaghan, T. (2003) Cognitive behavioral psychotherapy for depression following stroke: A randomized controlled trial. Stroke, 34, 111-115. doi:10.1161/01.STR.0000044167.44670.55 [27] Kotila, M., Numminen, H., Waltimo, O. and Kaste, M. 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