Effects of Social Support, Sleep Quality, and Oral Health Impact Profile on Depression among Pregnant Women

Han, Se Young; Han, Yang Keum

Abstract

This study examined 191 pregnant women before delivery in an obstetrics and gynecology clinic in North Gyeongsang Province from May to September 2016 by using a questionnaire after obtaining informed consent for voluntary participation in the study. The study was performed to investigate the association of depression with sociodemographic characteristics, pregnancy-related characteristics, social support, sleep quality and Oral Health Impact Profile (OHIP) in pregnant women. The prevalence of depression among the pregnant women was 25.1% in the healthy group and 74.9% in the depression group. The depression level was significantly higher in women in the depression group who were unsatisfied with their marriage life, had no occupation, had lower social support, had poor sleep quality and had higher OHIP scores. The results of the logistic regression analysis indicated that, the risk ratio for more severe depression was significantly higher in the group with no experience of miscarriage and induced childbirth than in the group with childbirth experience. Conversely, the risk ratio for more severe depression was significantly lower in the group with high social support than in the group with low social support. Depression in the respondents significantly positively correlated with sleep quality and OHIP score but significantly negatively correlated with social support. The multiple regression analysis revealed that the depression level was significantly higher by 22.3% among pregnant women with lower marital satisfaction, no childbirth experience, lower social support and higher OHIP scores. In summary, depression was related to marital satisfaction, childbirth experience, social support, and OHIP score, among others, in pregnant women in this study. Therefore, further investigation is warranted to construct programs and measures that will help build positive thinking by designing and verifying a three-dimensional study model by taking into consideration various variables to reduce the incidence of depression in pregnant women.