Displaying all 5 publications

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  1. Razak IA, Jaafar N
    J Ir Dent Assoc, 1988;34(3):95-7.
    PMID: 3271816
    Matched MeSH terms: Dental Care/statistics & numerical data*
  2. Razak IA, Ali MM
    Gerodontics, 1988 Oct;4(5):265-7.
    PMID: 3271724
    Matched MeSH terms: Dental Care/statistics & numerical data*
  3. Yusof ZY, Netuveli G, Ramli AS, Sheiham A
    Oral Health Prev Dent, 2006;4(3):165-71.
    PMID: 16961024
    OBJECTIVES: To assess whether or not opportunistic oral cancer screening by dentists to detect pre-malignant or early cancer lesions is feasible. The objective was to analyse the patterns of dental attendance of a national representative sample over a period of 10 years to ascertain whether individuals at high-risk of oral cancer would be accessible for opportunistic oral cancer screening.

    METHODS: Secondary analysis of data extracted from the British Household Panel Survey, a national longitudinal survey (n=5547). Analysis to ascertain whether patterns of attendance for dental check-ups for a period of 10 years (1991-2001) were associated with risk factors for oral cancer such as age, sex, education, social class, smoking status and smoking intensity.

    RESULTS: Males, aged over 40 years, less educated manual workers and smokers were significantly less likely to attend for dental check-ups compared with females and younger, higher educated, higher socio-economic class non-smokers (p < 0.05). Throughout the 10-year period, young people, more than older people, had progressively lower odds ratios of attending. Those with more education used dental services more. Heavy smokers were infrequent attendees.

    CONCLUSIONS: This study suggests that opportunistic oral cancer screening by dentists is not feasible to include high-risk groups as they are not regular attendees over 10 years. Those who would be screened would be the low-risk groups. However, dentists should continue screening all patients as oral precancers are also found in regular attendees. More should be done to encourage the high-risk groups to visit their dentists.

    Matched MeSH terms: Dental Care/statistics & numerical data*
  4. Al-Alimi A, Halboub E, Al-Sharabi AK, Taiyeb-Ali T, Jaafar N, Al-Hebshi NN
    Int J Dent Hyg, 2018 Nov;16(4):503-511.
    PMID: 29963753 DOI: 10.1111/idh.12352
    OBJECTIVES: The relative importance of risk factors of periodontitis varies from one population to another. In this study, we sought to identify independent risk factors of periodontitis in a Yemeni population.

    METHODS: One hundred and fifty periodontitis cases and 150 healthy controls, all Yemeni adults 30-60 years old, were recruited. Sociodemographic data and history of oral hygiene practices and oral habits were obtained. Plaque index (PI) was measured on index teeth. Periodontal health status was assessed using Community Periodontal Index (CPI) and Clinical Attachment Loss (CAL) according to WHO. Periodontitis was defined as having one or more sextants with a CPI score ≥ 3. Multiple logistic regression modelling was employed to identify distal, intermediate and proximal determinants of periodontitis, while ordinal regression was used to identify those of CAL scores.

    RESULTS: In logistic regression, PI score was associated with the highest odds of periodontitis (OR = 82.9) followed by cigarette smoking (OR = 12.8), water pipe smoking (OR = 10.2), male gender (OR = 3.4) and age (OR = 1.19); on the other hand, regular visits to the dentist (OR = 0.05), higher level of education (OR = 0.37) and daily dental flossing (OR = 0.95) were associated with lower odds. Somewhat similar associations were seen for CAL scores (ordinal regression); however, qat chewing was identified as an additional determinant (OR = 4.69).

    CONCLUSION: Water pipe smoking is identified as a risk factor of periodontitis in this cohort in addition to globally known risk factors. Adjusted effect of qat chewing is limited to CAL scores, suggestive of association with recession.

    Matched MeSH terms: Dental Care/statistics & numerical data
  5. Masood M, Newton T, Bakri NN, Khalid T, Masood Y
    J Dent, 2017 Jan;56:78-83.
    PMID: 27825838 DOI: 10.1016/j.jdent.2016.11.002
    OBJECTIVES: To identify the determinants of OHRQoL among older people in the United Kingdom.

    METHODS: A subset of elderly (≥65year) participants from the UK Adult Dental Health Survey 2009 data was used. OHRQoL was assessed by means of the OHIP-14 additive score. The number of missing teeth; presence of active caries, dental pain, root caries, tooth wear, periodontal pockets>4mm, loss of attachment>9mm; having PUFA>0 (presence of severely decayed teeth with visible pulpal involvement, ulceration caused by dislocated tooth fragments, fistula and abscess); and wearing a denture were used as predictor variables. Age, gender, marital status, education level, occupation and presence of any long standing illness were used as control variables. Multivariate zero-inflated Poisson regression analysis was performed using R-project statistical software.

    RESULTS: A total of 1277 elderly participants were included. The weighted mean(SE) OHIP-14 score of these participants was 2.95 (0.17). Having active caries (IRR=1.37, CI=1.25;1.50), PUFA>0 (IRR=1.17, CI=1.05;1.31), dental pain (IRR=1.34, CI=1.20;1.50), and wearing dentures (IRR=1.30, CI=1.17;1.44), were significantly positively associated with OHIP-14 score. Having periodontal pockets>4mm, at least one bleeding site, and anterior tooth wear were not significantly associated with the OHIP-14 score.

    CONCLUSION: Whereas previous research has suggested a moderate relationship between oral disease and quality of life in this large scale survey of older adults, the presence of active caries and the presence of one or more of the PUFA indicators are associated with impaired oral health related quality of life in older adults, but not indicators of periodontal status. The implication of this is that whilst focussing on prevention of disease, there is an ongoing need for oral health screening and treatment in this group.

    Matched MeSH terms: Dental Care/statistics & numerical data
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