Beverage Consumption Patterns and Oral Health Outcomes: Do Milk and Water Confer Protective Benefits against Sugary- or Acidic-Beverage Consumption?
Bibliographic record
Abstract
Background: \nDiseases affecting the oral cavity are the most prevalent chronic conditions in the world, and affect all ages, sexes, and nationalities. Diet is a strong predictor of oral health, and beverage consumption may affect oral health outcomes; however, there has been relatively little research on the association between the balance of beverages in the diet and oral health outcomes. \n \nMethods: \nThe current study used data from the Canadian Health Measures Survey (CHMS) to determine the impact of the type and frequency of beverage consumption on oral health, as well as the interaction between beverages. The first round of data collection for the CHMS took place between March 1, 2007 and March 31, 2009, and involved 5604 Canadians between the ages of 6 and 79 from across Canada. The sample targeted individuals in privately occupied dwellings, and is representative of 97% of the Canadian population. The CHMS consisted of two components: a household questionnaire to collect sociodemographic information, health history, and information on personal habits, and a clinical examination to collect anthropometric measures, blood and urine samples, and oral health measures. For our current analysis, age was restricted to age 12-30 inclusive, with 16 participants removed for missing responses giving a final sample size of 1534. \nThe current analysis examined a number of different types of beverages, including water, milk, regular soft drinks, diet soft drinks, fruit juices, fruit-flavoured drinks, vegetable juices, sport drinks, and alcohol; and four oral health outcomes: dental decay, periodontal health, self-rated oral health (SROH), and a general oral health index (OHX). Descriptive tests and Poisson and Ordinal Regression were used to determine whether an association existed between the variables of interest, and if so, the magnitude of this association. Four models, each consisting of three sub-models, were fitted in order to address the hypotheses and research questions. Due to the complex sampling nature of the CHMS, survey weights were used as outlined by Statistics Canada, and clustering and bootstrapped analyses were carried out in order to account for the complex nature of the data. \n \nResults: \n\tA number of the beverage variables, as well as other covariates, were associated with oral health outcomes. Soft drink consumption was associated with all of the oral health outcomes in the main effects models with increased soft drink consumption having a detrimental effect on oral health. Fruit-flavoured beverage consumption was significant with a negative impact in the dental decay main effects model, and water consumption was significant for the SROH main effects model, having a positive effect on SROH as the frequency of water consumption increased. Milk was significant and beneficial in all index models, and the milk and sugary- or acidic-beverage interaction variables were significant in all index models except for the sugary index model for dental decay. A number of the covariates were also found to be significant: age was associated with all dental decay, periodontal health and OHX models with higher age being associated with poorer oral health, sex was significant in the dental decay models as well as the index models for SROH with females having better oral health, income and frequency of dental care were significant in all of the SROH models (higher income and more frequent visits to health care professionals being associated with better SROH), frequency of flossing was associated with all of the dental decay models in a detrimental way, and fibre consumption was significant in the dental decay models as well as the index models for periodontal health and OHX and had a positive impact on oral health. All other beverage variables and covariates were not significant in any model. \n \nDiscussion: \n\tConsumption of some beverages, specifically regular soft drinks, fruit-flavoured beverages, water and milk, had a small but significant effect on oral health outcomes. It was also found that milk consumption is protective over sugary or acidic beverage interaction, but the interaction between water and sugary and acidic beverages does not seem to be significant. The small magnitude of association suggests oral health outcomes are highly multi-factorial in etiology and oral health status is the result of an accumulation of life exposures. Further investigations would benefit from the inclusion of information regarding access to fluoridated water, as well as longitudinal studies. Overall, the current findings contribute evidence on the importance of minimizing consumption of regular soft drinks and fruit-flavoured beverages, and replacing these drinks with those with more beneficial oral health effects such as milk and water.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".