METHODS: A total of 2084 community dwelling older adults from wave I and II were recruited through a multistage random sampling method. TUG was performed using the standard protocol and scores were then stratified based on with and without mild cognitive impairment (MCI), gender and in a 5-year age groups ranging from ages of 60's to 80's.
RESULTS: 529(16%) participants were identified to have MCI. Past history of falls and medical history of hypertension, heart disease, joint pain, hearing and vision problem, and urinary incontinence were found to have influenced TUG performance. Cognitive status as a mediator, predicted TUG performance even when both gender and age were controlled for (B 0.24, 95% CI (0.02-0.47), β 0.03, t 2.10, p = 0.36). Further descriptive analysis showed, participants with MCI, women and older in age took a longer time to complete TUG, as compared to men with MCI across all age groups with exceptions for some age groups.
CONCLUSION: These results suggested that MCI needs to be taken into consideration when testing older adults using TUG, besides age and gender factors. Data using fast speed TUG may be required among older adults with and without MCI for further understanding.
METHODS: A discovery cohort of Malaysian Chinese descent (NPC patients, n = 140; Healthy controls, n = 256) were genotyped using Illumina® HumanOmniExpress BeadChip. PennCNV and cnvPartition calling algorithms were applied for CNV calling. Taqman CNV assays and digital PCR were used to validate CNV calls and replicate candidate copy number variant region (CNVR) associations in a follow-up Malaysian Chinese (NPC cases, n = 465; and Healthy controls, n = 677) and Malay cohort (NPC cases, n = 114; Healthy controls, n = 124).
RESULTS: Six putative CNVRs overlapping GRM5, MICA/HCP5/HCG26, LILRB3/LILRA6, DPY19L2, RNase3/RNase2 and GOLPH3 genes were jointly identified by PennCNV and cnvPartition. CNVs overlapping GRM5 and MICA/HCP5/HCG26 were subjected to further validation by Taqman CNV assays and digital PCR. Combined analysis in Malaysian Chinese cohort revealed a strong association at CNVR on chromosome 11q14.3 (Pcombined = 1.54x10-5; odds ratio (OR) = 7.27; 95% CI = 2.96-17.88) overlapping GRM5 and a suggestive association at CNVR on chromosome 6p21.3 (Pcombined = 1.29x10-3; OR = 4.21; 95% CI = 1.75-10.11) overlapping MICA/HCP5/HCG26 genes.
CONCLUSION: Our results demonstrated the association of CNVs towards NPC susceptibility, implicating a possible role of CNVs in NPC development.
OBJECTIVE: To examine the associations of change in body mass index (BMI), waist circumference, and percent fat mass with change in intraocular pressure (IOP) in a large sample of Korean adults.
DESIGN, SETTING AND PARTICIPANTS: Cohort study of 274,064 young and middle age Korean adults with normal fundoscopic findings who attended annual or biennial health exams from January 1, 2002 to Feb 28, 2010 (577,981 screening visits).
EXPOSURES: BMI, waist circumference, and percent fat mass.
MAIN OUTCOME MEASURE(S): At each visit, IOP was measured in both eyes with automated noncontact tonometers.
RESULTS: In multivariable-adjusted models, the average increase in IOP (95% confidence intervals) over time per interquartile increase in BMI (1.26 kg/m2), waist circumference (6.20 cm), and percent fat mass (3.40%) were 0.18 mmHg (0.17 to 0.19), 0.27 mmHg (0.26 to 0.29), and 0.10 mmHg (0.09 to 0.11), respectively (all P < 0.001). The association was stronger in men compared to women (P < 0.001) and it was only slightly attenuated after including diabetes and hypertension as potential mediators in the model.
CONCLUSIONS AND RELEVANCE: Increases in adiposity were significantly associated with an increase in IOP in a large cohort of Korean adults attending health screening visits, an association that was stronger for central obesity. Further research is needed to understand better the underlying mechanisms of this association, and to establish the role of weight gain in increasing IOP and the risk of glaucoma and its complications.