Cargando…
Factors predicting different times for brushing teeth during the day: multilevel analyses
BACKGROUND: The most effective and simple intervention for preventing oral disease is toothbrushing. However, there is substantial variation in the timing of brushing teeth during the day. We aimed to identify a comprehensive set of predictors of toothbrushing after lunch and after dinner and estima...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668384/ https://www.ncbi.nlm.nih.gov/pubmed/38001518 http://dx.doi.org/10.1186/s12903-023-03555-1 |
_version_ | 1785149118655496192 |
---|---|
author | Lee, Hwa-Young Kim, Nam-Hee Jeong, Jin-Young Shin, Sun-Jung Park, Hee-Jung Kawachi, Ichiro |
author_facet | Lee, Hwa-Young Kim, Nam-Hee Jeong, Jin-Young Shin, Sun-Jung Park, Hee-Jung Kawachi, Ichiro |
author_sort | Lee, Hwa-Young |
collection | PubMed |
description | BACKGROUND: The most effective and simple intervention for preventing oral disease is toothbrushing. However, there is substantial variation in the timing of brushing teeth during the day. We aimed to identify a comprehensive set of predictors of toothbrushing after lunch and after dinner and estimated contextual (i.e., geographic) variation in brushing behavior at different times of the day. METHODS: We constructed a conceptual framework for toothbrushing by reviewing health behavior models. The main data source was the 2017 Community Health Survey. We performed a four-level random intercept logistic regression to predict toothbrushing behavior. (individual, household, Gi/Gun/Gu, and Si/Do). RESULTS: Individuals under 30 years of age had higher likelihood of brushing after lunch, while brushing after dinner was higher among those aged 40–79 years. People engaged in service/sales, agriculture/fishing/labor/mechanics, as well as student/housewife/unemployed were 0.60, 0.41, and 0.49 times less likely to brush their teeth after lunch, respectively, compared to those working in the office, but the gap narrowed to 0.97, 0.96, 0.94 for brushing after dinner. We also found significant area-level variations in the timing of brushing. CONCLUSIONS: Different patterns in association with various factors at individual-, household- and Si/Gun/Gu-levels with toothbrushing after lunch versus toothbrushing after dinner suggests a need for tailored interventions to improve toothbrushing behavior depending on the time of day. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12903-023-03555-1. |
format | Online Article Text |
id | pubmed-10668384 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106683842023-11-24 Factors predicting different times for brushing teeth during the day: multilevel analyses Lee, Hwa-Young Kim, Nam-Hee Jeong, Jin-Young Shin, Sun-Jung Park, Hee-Jung Kawachi, Ichiro BMC Oral Health Research BACKGROUND: The most effective and simple intervention for preventing oral disease is toothbrushing. However, there is substantial variation in the timing of brushing teeth during the day. We aimed to identify a comprehensive set of predictors of toothbrushing after lunch and after dinner and estimated contextual (i.e., geographic) variation in brushing behavior at different times of the day. METHODS: We constructed a conceptual framework for toothbrushing by reviewing health behavior models. The main data source was the 2017 Community Health Survey. We performed a four-level random intercept logistic regression to predict toothbrushing behavior. (individual, household, Gi/Gun/Gu, and Si/Do). RESULTS: Individuals under 30 years of age had higher likelihood of brushing after lunch, while brushing after dinner was higher among those aged 40–79 years. People engaged in service/sales, agriculture/fishing/labor/mechanics, as well as student/housewife/unemployed were 0.60, 0.41, and 0.49 times less likely to brush their teeth after lunch, respectively, compared to those working in the office, but the gap narrowed to 0.97, 0.96, 0.94 for brushing after dinner. We also found significant area-level variations in the timing of brushing. CONCLUSIONS: Different patterns in association with various factors at individual-, household- and Si/Gun/Gu-levels with toothbrushing after lunch versus toothbrushing after dinner suggests a need for tailored interventions to improve toothbrushing behavior depending on the time of day. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12903-023-03555-1. BioMed Central 2023-11-24 /pmc/articles/PMC10668384/ /pubmed/38001518 http://dx.doi.org/10.1186/s12903-023-03555-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Lee, Hwa-Young Kim, Nam-Hee Jeong, Jin-Young Shin, Sun-Jung Park, Hee-Jung Kawachi, Ichiro Factors predicting different times for brushing teeth during the day: multilevel analyses |
title | Factors predicting different times for brushing teeth during the day: multilevel analyses |
title_full | Factors predicting different times for brushing teeth during the day: multilevel analyses |
title_fullStr | Factors predicting different times for brushing teeth during the day: multilevel analyses |
title_full_unstemmed | Factors predicting different times for brushing teeth during the day: multilevel analyses |
title_short | Factors predicting different times for brushing teeth during the day: multilevel analyses |
title_sort | factors predicting different times for brushing teeth during the day: multilevel analyses |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668384/ https://www.ncbi.nlm.nih.gov/pubmed/38001518 http://dx.doi.org/10.1186/s12903-023-03555-1 |
work_keys_str_mv | AT leehwayoung factorspredictingdifferenttimesforbrushingteethduringthedaymultilevelanalyses AT kimnamhee factorspredictingdifferenttimesforbrushingteethduringthedaymultilevelanalyses AT jeongjinyoung factorspredictingdifferenttimesforbrushingteethduringthedaymultilevelanalyses AT shinsunjung factorspredictingdifferenttimesforbrushingteethduringthedaymultilevelanalyses AT parkheejung factorspredictingdifferenttimesforbrushingteethduringthedaymultilevelanalyses AT kawachiichiro factorspredictingdifferenttimesforbrushingteethduringthedaymultilevelanalyses |