Background: Gingivitis and periodontitis cause the inflammation of the soft tissue around the teeth and destroy the supporting structures of the teeth. This is highly prevalent during pregnancy and lactation. Objectives: The present study aimed to investigate the periodontal status in pregnant and lactating women in Ilam province, Iran in 2018 - 2019. Methods: This descriptive-analytical study was conducted on 100 pregnant and lactating women who were selected via cluster and stratified sampling. Data were collected using a demographic questionnaire and the community periodontal index of treatment needs (CPITN). Data analysis was performed in SPSS version 24 using independent t-test, chi-square, and one-way ANOVA at the significance level of 0.05. Results: The mean age of the pregnant and lactating women was 25.62 ± 5.52 and 29.08 ± 6.83 years, respectively. In total, 30% of the pregnant women had a healthy gingival, 18% had bleeding, 36% had a mass, and 16% had CPITN. As for the lactating women, 44% had a healthy gingival, 32% had bleeding, 20% had a mass, and 4% had an envelope. CPITN index II and III were significantly higher in the pregnant women compared to the lactating women. Among the pregnant women, there were 49 housewives and only one employee, while 50 of the lactating women were housewives. Conclusions: According to the results, the sample population had an unfavorable periodontal status, and the pregnant women needed more oral health education.

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Background: Sleep deprivation is a common problem among the elderly in the cardiac care unit (CCU). Objectives: The present study aimed to determine the effects of environmental modifications on sleep quality improvement in these people. Methods: The study population included 60 elderly patients whose sleep quality was assessed by the Pittsburgh Sleep Quality Index with even domains. The environmental factors that can disturb sleep quality were determined via a questionnaire, including 13 questions on a 5-point Likert scale. Descriptive and inferential statistical analyses were performed in SPSS 22 software via independent sample student t-test and chi-square. Results: After environmental modifications, the total sleep quality scores changed from 11.8 to 5.96, indicating sleep quality improvement. Before executing the environmental modifications, there were no significant correlations between sleep quality scores and demographic variables (sex, age, marital status, and economic status). However, after the modifications, there was a significant relationship between sleep quality and economic status (P = 0.024). Conclusions: Environmental factors can affect sleep quality in the elderly hospitalized in CCU. Therefore, it is possible to improve sleep quality in these individuals by modulating environmental conditions.