Determining the factors associated with oral health‐related quality of life in Chinese elders: Findings from the fourth national survey

Zhi, Qinghui; Si, Yan; Wang, Xing; Tai, Baojun; Dong, Haiyang; Wang, Bo; Zheng, Shu Guo; Liu, Xue Nan; Rong, Wen Sheng; Wang, Wei Jian; Wang, Chun Xiao; Xiong, Feng; Lin, Huancai

doi:10.1111/cdoe.12674

Cited by 9 publications

(9 citation statements)

References 33 publications

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“…For example, findings from a cross-sectional study in Hong Kong demonstrated lower household income, divided into income groups, was significantly associated with higher score in the OHIP-14, therefore representing worse OHRQoL [ 17 ]. Similarly, results from the 4th National Oral Health Survey among over 4000 Chinese adults showed that participants with higher household income per capita had better OHRQoL [ 18 ]. The negative impact of low household income on a person’s OHRQoL has also been reported among adolescents [ 12 , 19 ].…”

Section: Discussionmentioning

confidence: 99%

Does Oral Health-Related Quality of Life Differ by Income Group? Findings from a Nationally Representative Survey

Hajek

König

Kretzler

et al. 2022

IJERPH

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Objectives: Clarify the association between income group and oral health-related quality of life. Methods: Data were used from a nationally representative online survey with n = 3075 individuals. It was conducted in late Summer 2021. The established Oral Health Impact Profile (OHIP-G5) was used to measure oral health-related quality of life. The income group (household net income) was used as key independent variable. It was adjusted for several covariates. Full-information maximum likelihood was used to address missing values. Results: Individuals in the lowest income decile had a lower oral health-related quality of life (Cohen’s d = −0.34) compared to individuals in the second to ninth income deciles. Individuals in the highest income decile had a higher oral health-related quality of life (Cohen’s d = 0.20) compared to individuals in the second to ninth income deciles. Consequently, there was a medium difference (Cohen’s d = 0.53) between individuals in the lowest income decile and individuals in the highest income decile. Additionally, multiple linear regressions showed significant differences between individuals in the lowest income decile and individuals in the second to ninth income deciles (β = 0.72, p < 0.01). In contrast, only marginal significant differences were identified between individuals in the second to ninth income deciles and individuals in the highest income decile (β = −0.28, p < 0.10). Conclusions: The current study particularly stressed the association between low income and low oral health-related quality of life in the general adult population. Increasing oral health-related quality of life in individuals with low income is a major issue which should be targeted.

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Section: Discussionmentioning

confidence: 99%

Does Oral Health-Related Quality of Life Differ by Income Group? Findings from a Nationally Representative Survey

Hajek

König

Kretzler

et al. 2022

IJERPH

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“…8,26 Caries risk assessment is a fundamental measure in the screening of people with a high risk of caries to facilitate prevention. 27 There are two main types of CRA, namely, reasoning-based programs (CAT and CAMBRA) and algorithm-driven programs Dental caries is a multifactorial disease and CRA tools usually include multiple risk factors and protective factors in a prediction system. In the current study, children's dietary habits (e.g., consumption of cookies and cakes) and oral hygiene (e.g., frequency of tooth brushing) were validated as significant predictive factors, which was consistent with many previous investigations.…”

Section: Discussionmentioning

confidence: 99%

“…Caries risk assessment is a fundamental measure in the screening of people with a high risk of caries to facilitate prevention. 27 There are two main types of CRA, namely, reasoning-based programs (CAT and CAMBRA) and algorithm-driven programs (Cariogram and NUS-CRA). 16 However, no CRA model can accurately predict whether an individual will develop caries at a certain time.…”

Section: Discussionmentioning

confidence: 99%

Nomogram prediction of caries risk among schoolchildren age 7 years based on a cohort study in Shanghai

et al. 2021

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Objective Caries risk assessment tools are essential for identifying and providing treatment for individuals at high risk of developing caries. We aimed to develop a nomogram for the assessment and evaluation of caries risk among Chinese children. Methods We enrolled schoolchildren age 7 years from a primary school in Shanghai. Baseline information of participants was collected using a questionnaire completed by children’s caregivers. A nomogram of a novel prediction scoring model was established based on predictors detected in univariate and multivariate analyses. Predictive accuracy and discriminative ability of the nomogram were calculated using the concordance index (C index). The bootstrap method (1000 samples) was used to decrease overfitting. The net benefit of the model was validated using decision curve analysis. Results Overall, 406 children with complete information and two completed dental examinations were included in the final analysis. The nomogram based on logistic regression model coefficients demonstrated a C index of 0.766 (95% confidence interval: 0.761–0.771) for caries risk. The net benefit of the decision curve analysis was 38.6% at 55% threshold probability. Conclusion This nomogram model, derived using dietary habits, oral hygiene status, and caries experience, showed promising predictive ability to assess the caries risk among Chinese children.

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“…Studies indicate that lower OHRQoL in older adults is associated with increased age, sex, socioeconomic disadvantage, anxiety or depression, negative self-rated general health, poor oral health, lack of dentures, dry mouth, poor chewing and swallowing function, and irregular dental visits [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. Poor nutritional status has also a deleterious effect on OHRQoL [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Increased Oral Dryness and Negative Oral Health-Related Quality of Life in Older People with Overweight or Obesity

2022

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This cross-sectional study was to evaluate the association between the oral health-related quality of life (OHRQoL) of older Thai people with obesity and oral health indicators. General and oral conditions were assessed. Oral dryness was determined using the Xerostomia Inventory-11 (XI-11) and clinical oral dryness score (CODS). OHRQoL was evaluated by the oral health impact profile (OHIP-14). Participants were aged 60–86 years; 73 (59.3%) were overweight or obese, and 50 (40.7%) were normal weight. Older patients with obesity had almost four times the rate of hypertension (OR = 3.59; 95%CI:1.34–9.60; p = 0.002), more missing teeth (p = 0.025), and higher CODS (p = 0.014) than those without obesity. The total XI-11 scores were positively associated with the total CODS, after adjusting for BMI (r = 0.267, p = 0.003). Those with obesity had almost three times the tendency for a negative OHRQoL compared with the non-obese (OR = 2.73; 95%CI:1.12–6.71; p = 0.04). After adjusting for all related factors, the chances of predicting an OHIP-14 score of four based on obesity and total XI-11 score were 4.42 (95%CI:1.57–12.47; p = 0.005) and 1.11 (95%CI:1.02–1.20; p = 0.013), respectively. Obesity had an increasingly undesirable negative impact on the OHRQoL of older Thai people and was influenced by BMI and oral dryness.

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Determining the factors associated with oral health‐related quality of life in Chinese elders: Findings from the fourth national survey

Cited by 9 publications

References 33 publications

Does Oral Health-Related Quality of Life Differ by Income Group? Findings from a Nationally Representative Survey

Does Oral Health-Related Quality of Life Differ by Income Group? Findings from a Nationally Representative Survey

Nomogram prediction of caries risk among schoolchildren age 7 years based on a cohort study in Shanghai

Increased Oral Dryness and Negative Oral Health-Related Quality of Life in Older People with Overweight or Obesity

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