Survey of oral hygiene behaviour, knowledge and oral hygiene status among Hong Kong adults : a pilot study

Objectives: To study the correlation between oral health behaviour and knowledge with respect to the oral hygiene status of Hong Kong Chinese adults. Materials and methods: Subject selection was by convenience sampling. A total of four outreach visits were arranged in March 2015. The participants’ oral health behavior and knowledge were evaluated through a self-reported questionnaire, while existing oral conditions were recorded following clinical examination using Visible Plaque Index (VPI) and Gingival Bleeding Index (GBI). Data analysis was carried out using SPSS on results obtained from the questionnaire as well as clinical examination. Results: A total of 147 subjects participated in this research project, of which 72% (103/147) were female while 28% (44/147) were male. Male subjects had statistically significantly higher mean VPI scores compared to female subjects interproximally, buccally and lingually (t-test, p<0.05). Furthermore, there exists a statistically significant negative correlation between oral health knowledge score (mean = 9.3, SD = 3.1) and VPI score (Pearson correlation test, p=0.025). Subjects who agreed accumulation of plaque or bacteria as a contributing factor to caries and periodontal diseases are statistically significantly lower than subjects who disagreed this statement in terms of mean VPI scores (53% vs 63%, t-test, p<0.05). Conclusion: Participants with better oral health knowledge who also recognized accumulation of plaque or bacteria as one of the contributing factors to dental caries and periodontal disease had better oral hygiene levels in terms of VPI.published_or_final_versio

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries