Arthritis, physical function, and disability among older Mexican Americans over 23 years of follow-up.

OBJECTIVE: Arthritis is a common chronic condition in the ageing population. Its impact on physical function varies according to sociodemographic and race/ethnic factors. The study objective was to examine the impact of arthritis on physical function and disability among non-disabled older Mexican Americans over time. DESIGN: A 23-year prospective cohort study of 2230 Mexican Americans aged 65 years and older from the Hispanic Established Population for the Epidemiologic Study of the Elderly (1993/94-2016). The independent variable was self-reported physician-diagnosed arthritis, and the outcomes included Activities of Daily Living (ADL), Instrumental Activities of Daily Living (IADL), mobility, Short Physical Performance Battery (SPPB), and handgrip strength. Covariates were sociodemographic, medical conditions, body mass index, depressive symptoms, and cognitive function. General linear mixed models were performed to estimate the change in SPPB and muscle strength. General Equation Estimation models estimated the odds ratios (OR) of becoming ADL- or IADL- or mobility - disabled as a function of arthritis. All variables were used as time-varying except for sex, education, and nativity. RESULTS: Overall, participants with arthritis had higher odds ratio (OR) of any ADL [OR = 1.35, 95% Confidence Interval (CI) = 1.09-1.68] and mobility (OR = 1.34, 95% CI = 1.18-1.52) disability over time than those without arthritis, after controlling for all covariates. Women, but not men, reporting arthritis had increased risk for ADL and mobility disability. The total SPPB score declined 0.18 points per year among those with arthritis than those without arthritis, after controlling for all covariates (p-value < .010). CONCLUSIONS: Our study demonstrates the independent effect of arthritis in increasing ADL and mobility disability and decreased physical function in older Mexican Americans over 23-years of follow-up.

Pain as a predictor of frailty over time among older Mexican Americans.

The objective of this study was to examine pain as a predictor of frailty over 18 years of follow-up among older Mexican Americans who were nonfrail at baseline. Data were from a prospective cohort study of 1545 community-dwelling Mexican Americans aged ≥67 years from the Hispanic Established Populations for the Epidemiological Study of the Elderly (1995/1996-2012/2013). Frailty was defined as meeting 2 or more of the following: unintentional weight loss of >10 pounds, weakness, self-reported exhaustion, and slowness. The independent predictor was self-reported pain. Covariates included age, sex, marital status, education, comorbid conditions, body mass index, Mini-Mental State Examination, depressive symptoms, and limitation in activities of daily livings. General equation estimation was performed to estimate the odds ratio of frailty as a function of pain. A total of 538 participants (34.8%) reported pain at baseline. The prevalence of frailty among those with pain ranged from 24.4% in wave 3 to 41% in wave 8. The odds ratio of becoming frail over time as a function of pain was 1.71; 95% confidence interval: 1.41 to 2.09 after controlling for all covariates. Older age, hip fracture, high depressive symptoms, and activities of daily living disability were also associated with higher odds of becoming frail over time. Female participants and those with higher levels of education and high Mini-Mental State Examination scores were less at risk. In conclusion, pain was a significantly predictor of frailty. Early assessment and better management of pain may prevent early onset of frailty in older Mexican Americans.

Validation of the Modified Frailty Phenotype Measure in Older Mexican Americans.

OBJECTIVES: Develop and validate a modified frailty phenotype measure for older Mexican Americans participating in the Hispanic Established Populations for the Epidemiological Study of the Elderly (H-EPESE) and related studies. DESIGN: Expert-based panel evaluation of content validity, cross-sectional analysis of construct validity, and longitudinal analysis of criterion validity for a modified version of the frailty phenotype measure. SETTING: Five southwestern states. PARTICIPANTS: A total of 1833 community-dwelling Mexican Americans aged 67 years or older. MEASUREMENTS: Frailty was assessed using the frailty phenotype measure (weight loss, weakness, exhaustion, slowness, and low physical activity) and a modified frailty phenotype measure (replacing "low physical activity" with "limitations in walking half a mile"). Each individual was classified as non-frail, pre-frail, or frail based on both frailty measures (original vs modified). Expert panel consensus was used to examine content validity. Spearman correlation, κ, weighted κ, and bootstrapping κ examined construct validity (n = 1833). Generalized linear mixed models, odds ratios, Cox proportional regression models, hazard ratios, and C statistics were used to analyze criterion validity (n = 1446) across four outcomes: hospitalization, physician visits, disability, and mortality from wave 3 (1998-99) through wave 8 (2012-13). RESULTS: The original and modified frailty phenotype measures had a strong correlation (r = .89; P < .000) and agreement (κ = .84; 95% confidence interval [CI] = .81-.86; weighted κ = .86; 95% CI = .84-.88; bootstrap κ = .84; 95% CI = .81-.86; bootstrap-weighted κ = .86; 95% CI = .84-.88 with 1000 bootstrapping samples). Four outcome models showed similar risk predictions for both frailty measures, with the exception of physician visits for frail participants. CONCLUSION: "Limitations in walking half a mile" can be used as a substitute criterion for "low physical activity" in assessing frailty. The modified frailty phenotype measure was comparable with the original frailty phenotype measure in H-EPESE participants over time. Our results indicate the modified frailty phenotype is a useful longitudinally frailty measure for community-dwelling older Mexican Americans. J Am Geriatr Soc 67:2393-2397, 2019.

Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial.

BACKGROUND: The Internet has potential as a medium for health behavior change programs, but no controlled studies have yet evaluated the impact of a fully automated physical activity intervention over several months with real-time objective feedback from a monitor. OBJECTIVE: The aim was to evaluate the impact of a physical activity program based on the Internet and mobile phone technology provided to individuals for 9 weeks. METHODS: A single-center, randomized, stratified controlled trial was conducted from September to December 2005 in Bedfordshire, United Kingdom, with 77 healthy adults whose mean age was 40.4 years (SD = 7.6) and mean body mass index was 26.3 (SD = 3.4). Participants were randomized to a test group that had access to an Internet and mobile phone-based physical activity program (n = 47) or to a control group (n = 30) that received no support. The test group received tailored solutions for perceived barriers, a schedule to plan weekly exercise sessions with mobile phone and email reminders, a message board to share their experiences with others, and feedback on their level of physical activity. Both groups were issued a wrist-worn accelerometer to monitor their level of physical activity; only the test group received real-time feedback via the Internet. The main outcome measures were accelerometer data and self-report of physical activity. RESULTS: At the end of the study period, the test group reported a significantly greater increase over baseline than did the control group for perceived control (P < .001) and intention/expectation to exercise (P < .001). Intent-to-treat analyses of both the accelerometer data (P = .02) and leisure time self-report data (P = .03) found a higher level of moderate physical activity in the test group. The average increase (over the control group) in accelerometer-measured moderate physical activity was 2 h 18 min per week. The test group also lost more percent body fat than the control group (test group: -2.18, SD = 0.59; control group: -0.17, SD = 0.81; P = .04). CONCLUSIONS: A fully automated Internet and mobile phone-based motivation and action support system can significantly increase and maintain the level of physical activity in healthy adults.

Protein structure prediction servers at University College London.

A number of state-of-the-art protein structure prediction servers have been developed by researchers working in the Bioinformatics Unit at University College London. The popular PSIPRED server allows users to perform secondary structure prediction, transmembrane topology prediction and protein fold recognition. More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction. These servers are available from our software home page at http://bioinf.cs.ucl.ac.uk/software.html.

Predicting metal-binding site residues in low-resolution structural models.

The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.