2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India

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originalfilename EPIDEMIOLOGICAL MODELLING OF PERIODONTAL DISEASE AND ITS ASSOCIATED FACTORS AMONG ADULTS IN SAIDAPET, CHENNAI, SOUTH INDIA (PHD_2023).pdf
person Selvaraj Sidoharthan
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spelling 15373 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15373 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 General Document Malaysia Library Staff (Top Management) Library Staff (Management) Library Staff (Support) Terengganu Faculty of Medicine English application/pdf 1.5 Server storage Scanned document Universiti Sultan Zainal Abidin UniSZA Private Access Universiti Sultan Zainal Abidin SAMBox 3.0.10; modified using iTextSharp™ 5.5.10 ©2000-2016 iText Group NV (AGPL-version) 263 EPIDEMIOLOGICAL MODELLING OF PERIODONTAL DISEASE AND ITS ASSOCIATED FACTORS AMONG ADULTS IN SAIDAPET, CHENNAI, SOUTH INDIA (PHD_2023).pdf 2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India 2023-08-11 00:00 Copyright©PWB2025 Dissertations, Academic Sila masukkan subject wajib Dissertations, Academic. Terima kasih... Periodontal diseases—Epidemiology—India Epidemiological studies in dentistry Selvaraj Sidoharthan Dental related conditions in India have become a major obstacle in present days. Periodontal disease affects majority of Indian adult population. The aim of our study was to evaluate the role of sociodemographic and habitual factors towards periodontal disease and assess oral health knowledge, attitude, and behavior among Chennai adults to develop an epidemiological model of periodontal disease. A cross-sectional study was carried out among adults residing in Chennai. Data collection was carried out in two phases in two locations (Velachery and Saidapet), during validation phase 225 participants were included for exploratory factor analysis and 260 participants included for confirmatory factor analysis by simple random sampling. On the other hand, for assessment phase 288 participants were selected by non-probability sampling method. Individuals who were above the age of 18 years and volunteering themselves were included. On the other hand, individuals who were mentally, physically, and legally incapacitated were excluded. Firstly, we carried out exploratory factor analysis, that resulted in 11 items in knowledge domain, eight items in the attitude domain, and eight items in the behavior domain depicting satisfactory factor loading. Furthermore, confirmatory factor analysis was carried out for the 27-item oral health knowledge, attitude, and behavior questionnaire. Periodontal examination was carried out based on WHO recommendations with coding 0(healthy gums),1(bleeding on probing),2 (presence of calculus during probing),3(presence of periodontal pocket depth between 3.5-5.55 mm),4(presence of periodontal pocket depth 6mm or more) using a CPI probe. Finally, assessment of periodontal disease predicting factors and oral health knowledge, attitude, and behavior was assessed using regression analysis by utilizing statistical software R version 3.6.1. Internal consistency reliability of oral health knowledge, attitude, and behavior values were 0.67, 0.87 and 0.68, respectively. The validated questionnaire had sufficient goodness-of-fit values and the measurement model exhibited ideal convergent and discriminant validity following model re-specification. Based on the study findings factors like age group 25 and 34 years (AOR = 2.25; 95% CI 1.14–4.55), 35–44 years (AOR = 1.80; 95% CI 0.89–3.64), ≥ 45 years old (AOR = 2.89; 95% CI 1.41–6.01), ethnicity (AOR = 2.71; 95% CI 1.25–5.81), smoking (AOR = 0.38; 95% CI 0.16–0.65), primary level education (AOR = 0.07; 95% CI 0.01–0.50) high school level education (AOR = 0.06; 95% CI 0.01–0.27), university level education (AOR = 0.08; 95% CI 0.01–0.36) and an individual’s oral health behavior (AOR = 0.09; 95% CI 0.03–0.25) were found to be associated with gum diseases. Factors like age, ethnicity, smoking and alcohol habits and oral health behavior of an individual were notable periodontal disease influencing factors. Our findings would assist in developing epidemiological model of periodontal disease which helps to provide a better insight on removing the inequalities of an individual to maintain a better oral health status and might fill the vacuum by giving proper idea to formulate evidence based oral health reinforcement programs. Epidemiological Modelling Adult Population Thesis
spellingShingle 2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India
state Terengganu
subject Dissertations, Academic
Periodontal diseases—Epidemiology—India
Epidemiological studies in dentistry
summary Dental related conditions in India have become a major obstacle in present days. Periodontal disease affects majority of Indian adult population. The aim of our study was to evaluate the role of sociodemographic and habitual factors towards periodontal disease and assess oral health knowledge, attitude, and behavior among Chennai adults to develop an epidemiological model of periodontal disease. A cross-sectional study was carried out among adults residing in Chennai. Data collection was carried out in two phases in two locations (Velachery and Saidapet), during validation phase 225 participants were included for exploratory factor analysis and 260 participants included for confirmatory factor analysis by simple random sampling. On the other hand, for assessment phase 288 participants were selected by non-probability sampling method. Individuals who were above the age of 18 years and volunteering themselves were included. On the other hand, individuals who were mentally, physically, and legally incapacitated were excluded. Firstly, we carried out exploratory factor analysis, that resulted in 11 items in knowledge domain, eight items in the attitude domain, and eight items in the behavior domain depicting satisfactory factor loading. Furthermore, confirmatory factor analysis was carried out for the 27-item oral health knowledge, attitude, and behavior questionnaire. Periodontal examination was carried out based on WHO recommendations with coding 0(healthy gums),1(bleeding on probing),2 (presence of calculus during probing),3(presence of periodontal pocket depth between 3.5-5.55 mm),4(presence of periodontal pocket depth 6mm or more) using a CPI probe. Finally, assessment of periodontal disease predicting factors and oral health knowledge, attitude, and behavior was assessed using regression analysis by utilizing statistical software R version 3.6.1. Internal consistency reliability of oral health knowledge, attitude, and behavior values were 0.67, 0.87 and 0.68, respectively. The validated questionnaire had sufficient goodness-of-fit values and the measurement model exhibited ideal convergent and discriminant validity following model re-specification. Based on the study findings factors like age group 25 and 34 years (AOR = 2.25; 95% CI 1.14–4.55), 35–44 years (AOR = 1.80; 95% CI 0.89–3.64), ≥ 45 years old (AOR = 2.89; 95% CI 1.41–6.01), ethnicity (AOR = 2.71; 95% CI 1.25–5.81), smoking (AOR = 0.38; 95% CI 0.16–0.65), primary level education (AOR = 0.07; 95% CI 0.01–0.50) high school level education (AOR = 0.06; 95% CI 0.01–0.27), university level education (AOR = 0.08; 95% CI 0.01–0.36) and an individual’s oral health behavior (AOR = 0.09; 95% CI 0.03–0.25) were found to be associated with gum diseases. Factors like age, ethnicity, smoking and alcohol habits and oral health behavior of an individual were notable periodontal disease influencing factors. Our findings would assist in developing epidemiological model of periodontal disease which helps to provide a better insight on removing the inequalities of an individual to maintain a better oral health status and might fill the vacuum by giving proper idea to formulate evidence based oral health reinforcement programs.
title 2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India
title_full 2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India
title_fullStr 2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India
title_full_unstemmed 2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India
title_short 2023_Epidemiological Modelling of Periodontal Disease and Its Associated Factors Among Adults in Saidapet, Chennai, South India
title_sort 2023_epidemiological modelling of periodontal disease and its associated factors among adults in saidapet, chennai, south india