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Original Articles
Intra-Oral Factors Influencing Halitosis in Young Women
Ho Sun Shon, Kyoung Ok Kim, Jae Kwan Jung, Eun Jong Cha, Su Ok Lee, Kyung Ah Kim
Osong Public Health Res Perspect. 2018;9(6):340-347.   Published online December 31, 2018
DOI: https://doi.org/10.24171/j.phrp.2018.9.6.08
  • 4,172 View
  • 36 Download
  • 3 Citations
AbstractAbstract PDF
Objectives

The aim of this research was to determine intra-oral factors that affect halitosis in young women.

Methods

This study was performed between March 2014 to May 2014, and included 35 women in their 20s with good oral health. Correlation and logistic regression analyses were performed to investigate the change in halitosis immediately, and 1 hour after scaling.

Results

In both oral gas (OG) and extraoral gas (EG) groups, halitosis was reduced after scaling compared to before scaling. The logistic regression analysis of oral state factors in OG showed that as oral fluid [odds ratio (OR) = 0.792, p = 0.045] and dental plaque (OR = 0.940, p = 0.016) decreased by 1 unit, the OR in the OG group decreased (> 50). In addition, as glucose levels in the oral cavity (OR = 1.245, p = 0.075) and tongue coating index (OR = 2.912, p = 0.064) increased by 1 unit, the OR in the OG group increased (> 50). Furthermore, in the EG group, as oral fluid (OR = 0.66, p = 0.01) and dental plaque (OR = 0.95, p = 0.04) decreased, the OR in the EG group decreased (> 50) significantly.

Conclusion

To control halitosis, it is necessary to increase oral fluid and decrease the amount of tongue plaque. Furthermore, maintaining a healthy oral environment, aided by regular scaling and removal of dental plaque, may significantly control halitosis.

Citations

Citations to this article as recorded by  
  • Role of Probiotics in Halitosis of Oral Origin: A Systematic Review and Meta-Analysis of Randomized Clinical Studies
    Nansi López-Valverde, Antonio López-Valverde, Bruno Macedo de Sousa, Cinthia Rodríguez, Ana Suárez, Juan Manuel Aragoneses
    Frontiers in Nutrition.2022;[Epub]     CrossRef
  • Prevalence and associated factors of self‐reported halitosis among institutionalized adolescents: Cross‐sectional study
    Francisco Wilker Mustafa Gomes Muniz, Laura Barreto Moreno, Taciane Menezes da Silviera, Cassiano Kuchenbecker Rösing, Paulo Roberto Grafitti Colussi
    International Journal of Dental Hygiene.2022;[Epub]     CrossRef
  • Microbiota in intra-oral halitosis – characteristics, effects of antibacterial mouth rinse treatment
    D. S. Vikina, I. N. Antonova, V. V. Tec, T. E. Lazareva
    Parodontologiya.2020; 25(1): 4.     CrossRef
Developing the High-Risk Drinking Scorecard Model in Korea
Jun-Tae Han, Il-Su Park, Suk-Bok Kang, Byeong-Gyu Seo
Osong Public Health Res Perspect. 2018;9(5):231-239.   Published online October 31, 2018
DOI: https://doi.org/10.24171/j.phrp.2018.9.5.04
  • 14,857 View
  • 99 Download
  • 2 Citations
AbstractAbstract PDF
Objectives

This study aimed to develop a high-risk drinking scorecard using cross-sectional data from the 2014 Korea Community Health Survey.

Methods

Data were collected from records for 149,592 subjects who had participated in the Korea Community Health Survey conducted from 2014. The scorecard model was developed using data mining, a scorecard and points to double the odds approach for weighted multiple logistic regression.

Results

This study found that there were many major influencing factors for high-risk drinkers which included gender, age, educational level, occupation, whether they received health check-ups, depressive symptoms, over-moderate physical activity, mental stress, smoking status, obese status, and regular breakfast. Men in their thirties to fifties had a high risk of being a drinker and the risks in office workers and sales workers were high. Those individuals who were current smokers had a higher risk of drinking. In the scorecard results, the highest score range was observed for gender, age, educational level, and smoking status, suggesting that these were the most important risk factors.

Conclusion

A credit risk scorecard system can be applied to quantify the scoring method, not only to help the medical service provider to understand the meaning, but also to help the general public to understand the danger of high-risk drinking more easily.

Citations

Citations to this article as recorded by  
  • A Study on ML-Based Sleep Score Model Using Lifelog Data
    Jiyong Kim, Minseo Park
    Applied Sciences.2023; 13(2): 1043.     CrossRef
  • A Simple-to-Use Score for Identifying Individuals at High Risk of Denosumab-Associated Hypocalcemia in Postmenopausal Osteoporosis: A Real-World Cohort Study
    Kyoung Jin Kim, Namki Hong, Seunghyun Lee, Miryung Kim, Yumie Rhee
    Calcified Tissue International.2020; 107(6): 567.     CrossRef
Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods
Payam Amini, Saman Maroufizadeh, Reza Omani Samani, Omid Hamidi, Mahdi Sepidarkish
Osong Public Health Res Perspect. 2017;8(3):195-200.   Published online June 30, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.3.06
  • 3,291 View
  • 30 Download
  • 8 Citations
AbstractAbstract PDF
Objectives

Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods.

Methods

This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6–21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used.

Results

The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB (p < 0.05).

Conclusion

Identifying and training mothers at risk as well as improving prenatal care may reduce the PTB rate. We also recommend that statisticians utilize the logistic regression model for the classification of risk groups for PTB.

Citations

Citations to this article as recorded by  
  • Associations Among Multimorbid Conditions in Hospitalized Middle-aged and Older Adults in China: Statistical Analysis of Medical Records
    Yan Zhang, Chao Chen, Lingfeng Huang, Gang Liu, Tingyu Lian, Mingjuan Yin, Zhiguang Zhao, Jian Xu, Ruoling Chen, Yingbin Fu, Dongmei Liang, Jinmei Zeng, Jindong Ni
    JMIR Public Health and Surveillance.2022; 8(11): e38182.     CrossRef
  • Iranian midwives’ awareness and performance of respectful maternity care during labor and childbirth
    Simin Haghdoost, Fatemeh Abdi, Azam Amirian
    European Journal of Midwifery.2021; 5(December): 1.     CrossRef
  • A diagnostic profile on the PartoSure test
    Safoura Rouholamin, Maryam Razavi, Mahroo Rezaeinejad, Mahdi Sepidarkish
    Expert Review of Molecular Diagnostics.2020; 20(12): 1163.     CrossRef
  • Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis
    Herdiantri Sufriyana, Atina Husnayain, Ya-Lin Chen, Chao-Yang Kuo, Onkar Singh, Tso-Yang Yeh, Yu-Wei Wu, Emily Chia-Yu Su
    JMIR Medical Informatics.2020; 8(11): e16503.     CrossRef
  • Analysis of Spontaneous Preterm Labor and Birth and Its Major Causes Using Artificial Neural Network
    Yun-Sook Kim
    Journal of Korean Medical Science.2019;[Epub]     CrossRef
  • A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
    Evangelia Christodoulou, Jie Ma, Gary S. Collins, Ewout W. Steyerberg, Jan Y. Verbakel, Ben Van Calster
    Journal of Clinical Epidemiology.2019; 110: 12.     CrossRef
  • Comparison of three data mining models for prediction of advanced schistosomiasis prognosis in the Hubei province
    Guo Li, Xiaorong Zhou, Jianbing Liu, Yuanqi Chen, Hengtao Zhang, Yanyan Chen, Jianhua Liu, Hongbo Jiang, Junjing Yang, Shaofa Nie, Michael French
    PLOS Neglected Tropical Diseases.2018; 12(2): e0006262.     CrossRef
  • Algorithm on age partitioning for estimation of reference intervals using clinical laboratory database exemplified with plasma creatinine
    Xiaoxia Peng, Yaqi Lv, Guoshuang Feng, Yaguang Peng, Qiliang Li, Wenqi Song, Xin Ni
    Clinical Chemistry and Laboratory Medicine (CCLM).2018; 56(9): 1514.     CrossRef
Articles
Study on the Correlation of Premises Condition Index and the Presence of Larvae of Aedes Species Mosquitoes in Human Dwellings of the Cuddalore District of Tamil Nadu, India
Parasuraman Basker, Radhakrishnan Ezhil
Osong Public Health Res Perspect. 2012;3(1):3-7.   Published online December 31, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.11.046
  • 1,908 View
  • 12 Download
  • 5 Citations
AbstractAbstract PDF
Conclusions It is concluded that this study helps in conducting rapid survey to identify the presence of Aedes larvae with a minimum number of staff for both inspection and treatment of Aedes larvae during the epidemic situation. Objectives To predict dwellings for the presence of Aedes larvae rapidly based on Premises Condition Index (PCI) factors, we studied the possible presence of Aedes species mosquitoes larvae among houses in the Chidambaram urban of Cuddalore District in Tamil Nadu, India based on the scores of variables in PCI, namely House, Yard and degree of shadow. Data of these variables were collected in September and October 2006 from 1813 houses in the Chidambaram urban area during the intensive vector control activities employed for the prevention and control of Chikungunya.
Methods
The association between presence of larvae and the variables of PCI was tested by Chi-square and Correlation. The predictability of the presence of Aedes larvae based on PCI factors was computed by logistic regression.
Results
The study shows 301 containers in 132 houses were found positive with Aedes species out of 1813 houses surveyed. It was further observed that the probability of presence of positive premises was four times higher in the premises with 75% shadow compared with premises with a 25% shadow. These findings showed a significant association (p < 0.001) with positive premises.

Citations

Citations to this article as recorded by  
  • Source reduction with a purpose: Mosquito ecology and community perspectives offer insights for improving household mosquito management in coastal Kenya
    Jenna E. Forsyth, Francis M. Mutuku, Lydiah Kibe, Luti Mwashee, Joyce Bongo, Chika Egemba, Nicole M. Ardoin, A. Desiree LaBeaud, Roberto Barrera
    PLOS Neglected Tropical Diseases.2020; 14(5): e0008239.     CrossRef
  • Ability of the Premise Condition Index to Identify Premises with Adult and Immature Aedes Mosquitoes in Kampong Cham, Cambodia
    John Hustedt, Dyna Doum, Vanney Keo, Sokha Ly, BunLeng Sam, Vibol Chan, Sebastien Boyer, Marco Liverani, Neal Alexander, John Bradley, Didot Budi Prasetyo, Agus Rachmat, Sergio Lopes, Rithea Leang, Jeffrey Hii
    The American Journal of Tropical Medicine and Hyg.2020; 102(6): 1432.     CrossRef
  • Pitch and Flat Roof Factors’ Association with Spatiotemporal Patterns of Dengue Disease Analysed Using Pan-Sharpened Worldview 2 Imagery
    Fedri Rinawan, Ryutaro Tateishi, Ardini Raksanagara, Dwi Agustian, Bayan Alsaaideh, Yessika Natalia, Ahyani Raksanagara
    ISPRS International Journal of Geo-Information.2015; 4(4): 2586.     CrossRef
  • Study on Entomological Surveillance and its Significance during a Dengue Outbreak in the District of Tirunelveli in Tamil Nadu, India
    Parasuraman Basker, Pichai Kannan, Rajagopal Thirugnanasambandam Porkaipandian, Sivsankaran Saravanan, Subramaniam Sridharan, Mahaligam Kadhiresan
    Osong Public Health and Research Perspectives.2013; 4(3): 152.     CrossRef
  • The Risk ofAedes aegyptiBreeding and Premises Condition in South Mexico
    Pablo Manrique-Saide, Clive R Davies, Paul G Coleman, Azael Che-Mendoza, Felipe Dzul-Manzanilla, Mario Barrera-Pérez, Silvia Hernández-Betancourt, Guadalupe Ayora-Talavera, Miguel Pinkus-Rendón, Pierre Burciaga-Zúñiga, Gustavo Sánchez Tejeda, Juan I Arred
    Journal of the American Mosquito Control Associati.2013; 29(4): 337.     CrossRef

PHRP : Osong Public Health and Research Perspectives