BASIC RESEARCH DESIGN: Case-control clinical and questionnaire study in a cluster sample of 50 villages.
METHODS: A total of 3000 persons were screened for the presence of periodontitis using the CDC case definition in full mouth examination. Equal numbers of cases (604 persons with periodontitis) and controls (604 without periodontitis) were recruited and interviewed with a piloted questionnaire. Univariate and multivariate analysis estimated crude and adjusted odds ratios (aOR) respectively with 95% confidence limits.
RESULTS: Six factors were determined by multivariate analysis to predict periodontitis: education less than or equal to twelve years of schooling (aOR=2.51, 95% CI=1.18-5.34), alcohol consumption (aOR= 1.7, 95% CI=1.16-2.49), consuming a non-vegetarian diet (aOR=1.38, 95% CI=1.08-1.76), not drinking milk (aOR=1.7, 95% CI= 1.29-2.24), not using a toothbrush for cleaning of teeth (aOR=2.98, 95% CI =1.71-5.21) and not cleaning teeth at least once a day (aOR=2.13, 95% CI=1.58-2.87).
CONCLUSION: Risk factors for periodontitis in a rural Indian population were identified. Further studies should validate these findings and appropriate recommendations should be developed to decrease the prevalence and burden of periodontitis in this population.
BASIC RESEARCH DESIGN: Systematic review and meta-analysis of observational studies performed using the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines.
METHOD: PubMed and Scopus were searched for eligible articles published in English from inception till November 2018. The quality of studies was assessed by the Newcastle Ottawa Scale. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated for the risk of periodontitis associated with highest versus lowest/non-alcohol in a random effects meta-analysis model. Heterogeneity and sensitivity were investigated in meta regression analysis. A funnel plot was used to assess publication bias.
RESULTS: Twenty-nine observational studies were included. One study with two separate datasets was considered as two separate studies for analysis. Alcohol consumption was significantly associated with the presence of periodontitis (OR = 1.26, 95% CI= 1.11-1.41). Significant heterogeneity (I2=71%) was present in the overall analysis, primarily attributable to sampling cross-sectional studies (I2=76.6%). A funnel plot and Egger tests (p=0.0001) suggested the presence of publication bias.
CONCLUSION: Alcohol consumption was associated with increased occurrence of periodontitis and should be considered as a parameter in periodontal risk assessment. Publication bias should be explored in future studies.
METHODS: A cross-sectional study was conducted using consecutive sampling. Each participant went through screening using the PUFA index, orthopantomography assessment using PAI, and comprehensive clinical examination to derive pulpal and apical diagnoses. The outcomes were dichotomized. Reliability was estimated using the Cohen kappa coefficient. Sensitivity, specificity, and predictive values were calculated. The area under the receiver operating characteristic curve was compared using the chi-square test.
RESULTS: A total of 165 participants were examined, 98.2% of whom had a decayed, missing, or filled tooth index >0. Of 4115 teeth assessed, 16.2% (n = 666) were diagnosed with pulpal disease and 7.9% (n = 325) with periapical disease. Interexaminer reliability for the PUFA index and PAI was 0.87 and 0.80, respectively. Intraexaminer reliability was 0.83 and 0.76 for the PUFA index and 0.75 and 0.72 for PAI. For pulpal diagnosis, the sensitivity of the PUFA index and PAI was 67.6% and 41.7%, respectively; the specificity of the PUFA index and PAI was 99.8% and 99.2%, respectively. For apical diagnosis, the sensitivity of the PUFA index and PAI was 87.7% and 75.4%, respectively; the specificity of the PUFA index and PAI was 95.4% and 98.4%, respectively. The PUFA index is statistically more accurate than PAI for pulpal diagnosis and apical diagnosis (P < .05).
CONCLUSIONS: The PUFA index can be used in screening for pulpal and periapical diseases with some limitations.
METHODS: This is a cross-section study of a subsample of 594 participants from the original sample of 2322 Malaysian elderly respondents, who had experienced major life events. Information on socio-demographic, social network, social support, religiosity and depression were collected through an interviewer-administered questionnaire. A multiple linear regression analysis was used to determine the factors associated with depression among elderly who experienced major life events.
RESULTS: Overall prevalence of depression among subsample of Malaysian elderly facing major life events was 9.4%. The results showed that age (p≤0.01), income (p≤0.001) and social network (p≤0.05) were significant associated with depression. In other words, with increasing age, low income as well as small social network associated with high risk of developing depression among elderly who had experienced major life events CONCLUSION: Other than age and income, social network were also associated with depression among elderly respondents who had experienced major life events. Therefore, professionals who are working with elderly with major life events should seek ways to enhance elderly networking as one of the strategies to prevent depression.