Synergistic associations of visual and self-reported hearing acuity with low handgrip strength in older adults: a population-based cross-sectional study.

BACKGROUND: It is unclear whether visual and hearing acuity are independently or synergistically associated with muscle strength. We aimed to examine the associations of visual and self-reported hearing acuity with low handgrip strength and the additive interaction between visual and hearing acuity on low handgrip strength in people over 60 years. METHOD: Data of 3,075 individuals aged over 60 years from the 2017 and 2018 Korea National Health and Nutrition Examination Survey were used for this cross-sectional study. Low handgrip strength was defined based on the 20th percentile of the study population (< 30.4 kg for male and < 17.7 kg for female). Visual and self-reported hearing acuity were each divided into three categories: good, moderate, and impaired. Multiple logistic regression and relative excess risk due to interaction (RERI) were performed. RESULTS: Of the 3,075 participants, 993 (32.3 %) demonstrated low handgrip strength. Low handgrip strength was more prevalent in participants with moderate (adjusted odds ratio [AOR] = 1.54, 95 % confidence interval [CI] = 1.12-2.12) and impaired visual acuity (AOR = 2.00, 95 % CI = 1.34-2.96). Both moderate and impaired self-reported hearing acuity were significantly associated with low handgrip strength (moderate: AOR = 1.25, 95 % CI = 1.01-1.55; impaired: AOR = 1.66, 95 % CI = 1.15-2.38). The more severe the sensory function decline, the higher the association with muscle weakness. Moreover, combined sensory impairments were associated with deteriorating low handgrip strength (AOR = 8.38), with significantly strong additive interactions (RERI = 2.61, 95 % CI = 2.52-2.70). CONCLUSIONS: Awareness is needed regarding the risk of reduced muscle strength in individuals with moderate and impaired sensory function. Older people with sensory function decline in clinical settings may benefit from programs such as exercise prescription to prevent muscle weakness.

Associations of Handgrip Strength and Handgrip Strength Asymmetry With Depression in the Elderly in Korea: A Cross-sectional Study.

OBJECTIVES: Recent studies have suggested that assessing handgrip strength (HGS) asymmetry together with HGS may be helpful for evaluating problems in geriatric patients. This study aimed to identify whether HGS asymmetry, weakness, or both were associated with depression in Korean older adults. METHODS: This study included 4274 subjects from the sixth and seventh Korea National Health and Nutrition Examination Survey. Depression was measured using the Patient Health Questionnaire-9. The maximum HGS of the dominant hand was used as a representative value. HGS symmetry was categorized by the ratio of the HGS of the dominant hand to that of non-dominant hand. The odds ratio (OR) for depression was calculated according to the HGS and its symmetry. RESULTS: In total, 240 (12.5%) men and 534 (22.7%) women had depression. HGS or HGS asymmetry showed no statistically significant associations with depression in elderly men. Elevated odds of depression were observed in elderly women with low HGS (OR, 1.93; 95% confidence interval [CI], 1.33 to 2.81) or prominent HGS asymmetry (OR, 1.46; 95% CI, 1.02 to 2.08). There was a positive additive interaction between asymmetric HGS and weakness, as women with low and prominently asymmetric HGS showed higher odds of depression (OR, 3.77; 95% CI, 2.16 to 6.59) than women with high and symmetric HGS. CONCLUSIONS: Depression in elderly Korean women was associated with both low and asymmetric HGS. Our findings support the potential value of HGS asymmetry as an indicator of HGS.

Genome Gerrymandering: optimal division of the genome into regions with cancer type specific differences in mutation rates.

The activity of mutational processes differs across the genome, and is influenced by chromatin state and spatial genome organization. At the scale of one megabase-pair (Mb), regional mutation density correlate strongly with chromatin features and mutation density at this scale can be used to accurately identify cancer type. Here, we explore the relationship between genomic region and mutation rate by developing an information theory driven, dynamic programming algorithm for dividing the genome into regions with differing relative mutation rates between cancer types. Our algorithm improves mutual information when compared to the naive approach, effectively reducing the average number of mutations required to identify cancer type. Our approach provides an efficient method for associating regional mutation density with mutation labels, and has future applications in exploring the role of somatic mutations in a number of diseases.