Publications

Optimal health benefits from exercise are achieved by meeting both aerobic and muscle strengthening guidelines, however, most older adults (OAs) do not exercise and the majority of those who do only perform one type of exercise. A pragmatic solution to this problem may be emphasizing a single exercise strategy that maximizes health benefits. The loss of muscle mass and strength at an accelerated rate are hallmarks of aging that, without intervention, eventually lead to physical disability and loss of independence. Additionally, OAs are at risk of developing several chronic diseases. As such, participating in activities that can maintain or increase muscle mass and strength, as well as decrease chronic disease risk, is essential for healthy aging. Unfortunately, there is a widely held belief that adaptations to aerobic and resistance exercise are independent of each other, requiring the participation of both types of exercise to achieve optimal health. However, we argue that this assertion is incorrect, and we discuss crossover adaptations of both aerobic and resistance exercise. Aerobic exercise can increase muscle mass and strength, though not consistently and may be limited to exercise that overloads a particular muscle group, such as stationary bicycling. In contrast, resistance exercise is effective at maintaining muscle health with increasing age, and also has significant effects on cardiovascular disease (CVD) risk factors, type 2 diabetes (T2D), cancer, and mortality. We posit that resistance exercise is the most effective standalone exercise strategy for improving overall health in OAs and should be emphasized in future guidelines.

BACKGROUND: Measures of handgrip strength have not only emerged as a clinically viable screening tool for determining risk for morbidity, functional disability, and early mortality, but also for helping to identify cognitive deficits. However, the phenomena that links low handgrip strength with cognitive decline remains unclear. The role of the muscular and neural systems, and their adaptations to muscle strengthening activities over the life course, may provide important information for how age-related changes to muscle mass, strength, and neural capacity influence cognition. Moreover, disentangling how handgrip strength and cognitive function are associated may help to inform healthcare providers working with aging adults and guide targeted interventions aiming to preserve muscle and cognitive functioning. OBJECTIVE: To 1) highlight and summarize evidence examining the associations of handgrip strength and cognitive functioning, and 2) provide directions for future research in this area. METHODS: Articles from the PubMed database were searched from November 2018-May 2019. The search term algorithm, inclusion and exclusion criteria were pre-specified by investigators. RESULTS: Several cross-sectional and longitudinal studies have revealed that measures of handgrip strength were associated with cognitive declines regardless of age demographics and the presence of comorbidities. CONCLUSION: Handgrip strength can be used in clinical and epidemiological settings for helping to determine the onset and progression of cognitive impairment. Future research should continue to examine how handgrip strength and cognitive function are linked.

The purpose of this study was to quantify head motion between isometric erector spinae (ES) contraction strategies, paradigms, and intensities in the development of a neuroimaging protocol for the study of neural activity associated with trunk motor control in individuals with low back pain. Ten healthy participants completed two contraction strategies; (1) a supine upper spine (US) press and (2) a supine lower extremity (LE) press. Each contraction strategy was performed at electromyographic (EMG) contraction intensities of 30, 40, 50, and 60% of an individually determined maximum voluntary contraction (MVC) (+/-10% range for each respective intensity) with real-time, EMG biofeedback. A cyclic contraction paradigm was performed at 30% of MVC with US and LE contraction strategies. Inertial measurement units (IMUs) quantified head motion to determine the viability of each paradigm for neuroimaging. US vs LE hold contractions induced no differences in head motion. Hold contractions elicited significantly less head motion relative to cyclic contractions. Contraction intensity increased head motion in a linear fashion with 30% MVC having the least head motion and 60% the highest. The LE hold contraction strategy, below 50% MVC, was found to be the most viable trunk motor control neuroimaging paradigm.

OBJECTIVES: To compare a composite measure of physical function that comprises locomotor and non-locomotor tests (i.e., the Mobility Battery Assessment (MBA)) with traditional measures of mobility (4-m usual gait speed (UGS), six-minute walk (6MW) gait speed, and short physical performance battery (SPPB) score) for assessing lower extremity function and discriminating community dwelling older adults with and without mobility limitations. DESIGN: Cross-sectional, observational study. SETTING: Laboratory-based. PARTICIPANTS: 89 community-dwelling older adults (74.9+/-6.7). MEASUREMENTS: Using principal component analysis we derived an MBA score for 89 community-dwelling older adults, and quantified 4-m UGS, 6MW gait speed, and SPPB score. The MBA score was based on five lab-based tests. We also quantified self-reported lower extremity function/mobility using the Neuro-QOL Lower Extremity Function-Mobility instrument. Based on this data a continuous score was derived and subjects were classified as "mobility limited" or "non-mobility limited". Correlations between the mobility measures and the Neuro-QOL score were calculated, and ROC curves were constructed to determine the AUC for the mobility measures ability to predict mobility limitations. RESULTS: The MBA had the largest AUC (0.92) for discriminating mobility limitations and exhibited the strongest correlation (0.73) with the Neuro-QOL Lower Extremity Function-Mobility Scale. The worst performing predictors were the 4-meter UGS and stair climb power both with an AUC of 0.8 for discriminating mobility limitations, and a low correlation with Neuro-QOL Lower Extremity Function Scale of 0.39 and 0.46, respectively. CONCLUSION: The MBA score moderately improves the magnitude of correlation and discrimination of mobility limitation in older adults than singular, standard tests of mobility.

OBJECTIVES: Quantifying the association between muscle weakness and mortality with carefully matched cohorts will help to better establish the impact of weakness on premature death. We used a matched cohort analysis in a national sample of older Americans to determine if those who were weak had a higher risk for mortality compared with control groups with incrementally higher strength capacities. DESIGN: Longitudinal panel. SETTING: Detailed interviews that included physical measures were conducted in person, whereas core interviews were often performed over the telephone. PARTICIPANTS: Data from 19,729 Americans aged at least 50 years from the 2006-2014 waves of the Health and Retirement Study were analyzed. MEASURES: A handgrip dynamometer was used to assess handgrip strength (HGS) in each participant. Men with HGS 26 kg were considered weak, >/=26 kg were considered not weak, and >/=32 kg were considered strong. Women with HGS 16 kg were classified as weak, >/=16 kg were classified as not-weak, and >/=20 kg were classified as strong. The National Death Index and postmortem interviews determined the date of death. The greedy matching algorithm was used to match cohorts. RESULTS: Of the 1077 weak and not-weak matched pairs, 401 weak (37.2%) and 296 not-weak (27.4%) older Americans died over an average 4.4 +/- 2.5-year follow-up. There were 392 weak (37.0%) and 243 strong (22.9%) persons who died over a mean 4.5 +/- 2.5-year follow-up from the 1057 weak and strong matched pairs. Those in the weak cohort had a 1.40 [95% confidence interval (CI) 1.19, 1.64] and 1.54 (CI 1.30, 1.83) higher hazard for mortality relative to persons in the not-weak and strong control cohorts, respectively. CONCLUSIONS AND IMPLICATIONS: Our findings may indicate a causal association between muscle weakness and mortality in older Americans. Health care providers should include measures of HGS as part of routine health assessments and discuss the health risks of muscle weakness with their patients.

OBJECTIVES: Factors that are responsible for age-related neurologic deterioration of noncognitive and cognitive processes may have a shared cause. We sought to examine the temporal, directional associations of handgrip strength and cognitive function in a national sample of aging Americans. DESIGN: Longitudinal panel. SETTING: Enhanced interviews that included physical, biological, and psychosocial measures were completed in person. Core interviews were often conducted over the telephone. PARTICIPANTS: The analytic sample included 14,775 Americans aged at least 50 years who participated in at least 2 waves of the 2006-2016 waves of the Health and Retirement Study. MEASURES: Handgrip strength was measured with a hand-held dynamometer. Participants were considered cognitively intact, mildly impaired, or severely impaired according to the Telephone Interview of Cognitive Status questionnaire. Separate lagged general estimating equations analyzed the directional associations of handgrip strength and cognitive function. RESULTS: The overall time to follow-up was 2.1 +/- 0.4 years. Every 5 kg higher handgrip strength was associated with 0.97 [95% confidence interval (CI) 0.93, 0.99] lower odds for both future cognitive impairment and worse cognitive impairment. Those who were not weak had 0.54 (CI 0.43, 0.69) lower odds for future cognitive impairment and 0.57 (CI 0.46, 0.72) lower odds for future worse cognitive impairment. Conversely, any (beta = -1.09; CI -1.54, -0.64), mild (beta = -0.85; CI -1.34, -0.36), and severe cognitive impairment (beta = -2.34; CI -3.25, -1.42) predicted decreased handgrip strength. Further, the presence of any, mild, and severe cognitive impairment was associated with 1.82 (CI 1.48, 2.24), 1.65 (CI 1.31, 2.08), and 2.53 (CI 1.74, 3.67) greater odds for future weakness, respectively. CONCLUSIONS/IMPLICATIONS: Strength capacity and cognitive function may parallel each other, whereby losses of functioning in 1 factor may forecast losses of functioning in the other. Handgrip strength could be used for assessing cognitive status in aging Americans and strength capacity should be monitored in those with cognitive impairment.

BACKGROUND: Discovering how certain health factors contribute to functional declines may help to promote successful aging. AIMS: To determine the independent and joint associations of handgrip strength (HGS) and cognitive function with instrumental activities of daily living (IADL) and activities of daily living (ADL) disability decline in aging Americans. METHODS: Data from 18,391 adults aged 50 years and over who participated in at least one wave of the 2006-2014 waves of the Health and Retirement Study were analyzed. A hand-held dynamometer assessed HGS and cognitive functioning was examined with a modified version of the Telephone Interview of Cognitive Status. IADL and ADL abilities were self-reported. Participants were stratified into four distinct groups based on their HGS and cognitive function status. Separate covariate-adjusted multilevel models were conducted for the analyses. RESULTS: Participants who were weak, had a cognitive impairment, and had both weakness and a cognitive impairment had 1.70 (95% confidence interval (CI) 1.57-1.84), 1.97 (CI 1.74-2.23), and 3.13 (CI 2.73-3.59) greater odds for IADL disability decline, respectively, and 2.26 (CI 2.03-2.51), 1.26 (CI 1.05-1.51), and 4.48 (CI 3.72-5.39) greater odds for ADL disability decline, respectively. DISCUSSION: HGS and cognitive functioning were independently and jointly associated with IADL and ADL disability declines. Individuals with both weakness and cognitive impairment demonstrated substantially higher odds for functional decline than those with either risk factor alone. CONCLUSIONS: Including measures of both HGS and cognitive functioning in routine geriatric assessments may help to identify those at greatest risk for declining functional capacity.

BACKGROUND: Gender and ethnicity are factors which influence strength, and hand dominance could be a critical component of handgrip strength (HGS) testing. Providing such HGS percentiles across the lifespan may help to identify weakness-related health concerns. We sought to generate growth charts and curves for HGS by gender and ethnicity in a nationally-representative sample of Americans aged 6-80 years. METHODS: Data from 13,617 participants in the 2011-2012 and 2013-2014 waves of the National Health and Nutrition Examination Survey were analyzed. HGS was measured with a handgrip dynamometer. Age, gender, ethnicity, and hand dominance were self-reported. Body Mass Index (BMI) was calculated from height and body mass. Measures of absolute HGS and HGS normalized to BMI were separately included in parametric quantile regression analyses for determining the 10th-90th percentiles across ages by gender and ethnicity. Similar models were also conducted by hand dominance. RESULTS: Differences in absolute HGS and HGS normalized to BMI quantiles across ages existed for each ethnicity regardless of gender. In men, absolute HGS generally increased until about 25 years of age, began to decline around age 30 years, and regressed into older adulthood. In women, absolute HGS appeared to rise starting at age 6 years, peaked between 20 and 30 years of age, but was maintained into mid-life before declining in older adulthood. Similar results were found for HGS normalized to BMI. CONCLUSIONS: Our findings provide percentile charts for HGS capacity that could be utilized for comparing individual measures of HGS to those from a United States population-representative sample.

BACKGROUND/OBJECTIVES: Examining handgrip strength (HGS) asymmetry and weakness together may extend the predictive capacity of HGS for capturing possible health problems such as cognitive impairment. The purpose of this study was to determine the associations of HGS asymmetry and weakness on lower cognitive functioning in a national sample of aging Americans. DESIGN: Longitudinal panel. SETTING: Participant residences. PARTICIPANTS: The analytic sample included 17,163 Americans aged 65.0 years (standard deviation = 10.1 years) who participated in the 2006 to 2016 waves of the Health and Retirement Study (HRS). MEASUREMENTS: A handgrip dynamometer was used to measure HGS; weakness was defined as HGS below 26 kg (men) or below 16 kg (women). Persons with HGS above 10% stronger on either hand were considered as having any HGS asymmetry. Those with HGS that was more than 10% stronger on their dominant or nondominant hand were considered as having dominant or nondominant HGS asymmetry, respectively. The Telephone Interview of Cognitive Status determined lower cognitive functioning (/=65 years). Covariate-adjusted linear mixed-effects models analyzed the associations of each HGS asymmetry and weakness group on lower cognitive functioning. RESULTS: Relative to those with symmetric HGS and no weakness, each HGS asymmetry and weakness group had greater odds for lower cognitive functioning: 1.15 (95% confidence interval [CI] = 1.03-1.27) for any HGS asymmetry alone, 1.64 (95% CI = 1.21-2.23) for weakness alone, and 1.95 (95% CI = 1.51-2.53) for any HGS asymmetry and weakness. Each HGS asymmetry dominance and weakness group also had greater odds for lower cognitive functioning: 1.12 (95% CI = 1.01-1.25) for asymmetric dominant HGS alone, 1.27 (95% CI = 1.05-1.53) for asymmetric nondominant HGS alone, 1.64 (95% CI = 1.21-2.23) for weakness alone, 1.89 (95% CI = 1.39-2.57) for weakness and asymmetric dominant HGS, and 2.10 (95% CI = 1.37-3.20) for weakness and asymmetric nondominant HGS. CONCLUSION: The presence of both HGS asymmetry and weakness may predict accelerated declines in cognitive functioning.