Abstract
Muscle weakness, which is often determined with low handgrip strength (HGS), is associated with several adverse health conditions, however, the prevalence and trends of weakness in the United States is not well-understood. We sought to estimate the prevalence and trends of weakness in Americans aged at least 50-years. The total unweighted analytic sample included 22,895 Americans from the 2006-2016 waves of the Health and Retirement Study. HGS was measured with a handgrip dynamometer. Males with weakness were below at least one of the absolute or normalized (body mass, body mass index) cut-points: <35.5-kg, <0.45-kg/kg, <1.05-kg/kg/m2. The presence of any weakness in females was also identified as being below one of the absolute or normalized HGS cut-points: <20.0-kg, <0.34-kg/kg, or <0.79-kg/kg/m2. There was an increasing trend in the prevalence of any weakness over time (p<0.001). The prevalence of weakness was 45.1% (95% confidence interval (CI): 44.0-46.0) in the 2006-2008 waves, and 52.6% (CI: 51.5-53.7) in the 2014-2016 waves. Weakness prevalence was higher for older (≥65-years) Americans (64.2%; CI: 62.8-65.5) compared to middle-aged (50-64 years) Americans (42.2%; CI: 40.6-43.8) in the 2014-2016 waves. Moreover, the prevalence of weakness in the 2014-2016 waves was generally higher in females (54.5%; CI: 53.1-55.9) than males (50.4%; CI: 48.7-52.0). Differences existed in weakness prevalence across races and ethnicities. The findings from our investigation suggest that the prevalence of weakness is overall pronounced and increasing in Americans. Efforts for mitigating and better operationalizing weakness will elevate in importance as our older American population grows.
Keywords: Aging, Epidemiology, Hand Strength, Muscle Strength, Muscle Strength Dynamometer
INTRODUCTION
Although engaging in healthy lifestyle behaviors such as resistance training helps to improve and maintain muscle strength across the lifespan (8), declines in strength naturally occur during aging (26). Specifically, age-related strength losses are observed as early as 30-years, and declining strength potentiates during middle-age (13). Low muscle strength is associated with several adverse health outcomes such as chronic cardiometabolic morbidities, functional limitations, and early all-cause mortality (19,20). Moreover, strength deficits are part of decision algorithms for muscle-related conditions such as sarcopenia (4), and represent the onset of physical disablement (2). Therefore, it is not surprising that musculoskeletal conditions are among the greatest healthcare expenditures in the United States (5). The presence of such conditions may only grow, as approximately 21% of Americans will be aged at least 65-years by the year 2030 (27).
Rigorous and meticulous evaluations of muscle strength that require specialized equipment and high functional capacity (21) are challenging for older populations because the necessary physical attributes required to complete these assessments diminish during aging (9). Handgrip strength (HGS) is a long-standing, convenient, and reliable assessment of overall strength that is often collected in clinical, translational research, and epidemiological settings (19). Several normative-reference standards for absolute HGS in Americans allow strength capacity comparisons amongst peers, whereas multiple criterion-reference standards also exist for helping to categorize absolute HGS values by making comparisons to a pre-specified threshold (18). In these cases, persons with HGS below a given pre-specified standard are considered weak.
While absolute HGS cut-points for determining weakness require minimal data post-processing and are simple to interpret, body size influences HGS, and body size can be operationalized with body mass and body mass index (BMI) (18). HGS cut-points for determining weakness, which are inclusive of absolute HGS, HGS normalized to body mass, and HGS normalized to BMI, have recently been created (3,16). However, the number of persons categorized as weak with each of these cut-points is inconsistent, although being below either the absolute or normalized HGS cut-points suggests weakness is present (24). Examining how persons who are considered weak under one or more of the absolute or normalized HGS cut-points will provide information about how the presence of weakness with multiple operational definitions may alter weakness status. Further, surveilling the prevalence of weakness status beginning at middle-age could be especially important for observing trends in strength declines given age-related losses in strength exacerbate during this lifespan period if not maintained (13). Continued surveillance of weakness status may help to inform the efficacy of current interventions seeking to improve or maintain strength during aging, guide programming to increase strength capacity, and identify at-risk populations wherein weakness might be frequently observed. We sought to estimate the prevalence and trends of weakness in Americans aged at least 50-years.
METHODS
Experimental Approach to the Problem
A secondary analysis of data from the 2006-2016 waves of the Health and Retirement Study (HRS) were performed for this study. The HRS utilizes a longitudinal-panel design whereby new cohorts of middle-aged persons are added every 6-years (7). Core interviews occur biennially and subjects are followed until death. Sampling weights are provided by the HRS for generating nationally-representative data. Detailed face-to-face interviews started in the HRS at the 2006 wave to assure that additional information beyond the core interviews, such as HGS, could be collected (7). The detailed interviews were conducted at alternating waves with a random half sample. As such, we merged these waves of the HRS to ensure that the random half samples completing HGS testing were examined uniformly. Additional details about the HRS are available elsewhere (29).
Subjects
The unweighted initial sample included 23,116 Americans aged at least 50-years with HGS measured from the 2006-2016 waves of the HRS. Subjects without information for age, sex, race and ethnicity, body mass, and BMI were excluded (n=221). The unweighted descriptive characteristics of the 22,895 total subjects are presented in Table 1. Overall, subjects were aged 64.4±10.5 years and were mostly female (56.9%). A new cohort of middle-aged subjects were added during the 2010-2012 merged waves (7), which may explain the unweighted sample size increase and age decrease. Written informed consent was provided by all subjects before entering the HRS and protocols were approved by the University’s Behavioral Sciences Committee Institutional Review Board.
Table 1.
Unweighted Descriptive Characteristics of the Subjects.
| Total Sample (n=22,895) |
2006-2008 Waves (n=13,572) |
2010-2012 Waves (n=15,904) |
2014-2016 Waves (n=14,965) |
|
|---|---|---|---|---|
| Age (years) | 64.4±10.5 | 68.5±9.9 | 66.3±10.7 | 66.9±10.6 |
| Age Group (n (%)) | ||||
| Middle-Aged Adult (n (%)) | 12,589 (55.0) | 4,866 (35.9) | 7,812 (49.1) | 7,211 (48.2) |
| Older Adult (n (%)) | 10,306 (45.0) | 8,706 (64.1) | 8,092 (50.9) | 7,754 (51.8) |
| Sex (n (%)) | ||||
| Male | 9,875 (43.1) | 5,708 (42.1) | 6,873 (43.2) | 6,387 (42.7) |
| Female | 13,020 (56.9) | 7,864 (57.9) | 9,031 (56.8) | 8,578 (57.3) |
| Race and Ethnicity (n (%)) | ||||
| Hispanic | 2,944 (12.8) | 1,147 (8.5) | 1,926 (12.1) | 2,103 (12.1) |
| Non-Hispanic Black | 4,370 (19.1) | 1,791 (13.2) | 3,021 (19.0) | 2,989 (20.0) |
| Non-Hispanic Other | 14,769 (64.5) | 288 (2.1) | 494 (3.1) | 9,266 (61.9) |
| Non-Hispanic White | 812 (3.6) | 10,346 (76.2) | 10,463 (65.8) | 607 (4.0) |
| BMI (kg/m2) | 28.7±6.1 | 28.1±5.8 | 28.7±6.1 | 29.0±6.3 |
| Body Mass (kg) | 81.7±19.6 | 79.6±18.7 | 81.5±19.5 | 82.0±19.9 |
Note: Results are presented as mean±standard deviation or frequency (percentage) as indicated. BMI=body mass index; kg=kilograms; m2=meters-squared.
Procedures
A Smedley spring-type handgrip dynamometer (Scandidact; Odder, Denmark) was used to measure HGS. Subjects reporting a surgery, swelling, inflammation, severe pain, or an injury in both hands in the past 6 months were not part of HGS testing. Trained interviewers fit the dynamometer to the hand size of each subject and provided instruction for the HGS protocols. Subjects were allowed a practice trial with their reported dominant hand. Beginning on the non-dominant hand, subjects stood and held the dynamometer with their arm at the side at 90-degrees and squeezed with maximal effort. Interviewers recorded each HGS trial wherein two measures were collected with each hand, alternating between hands. If a subject experienced difficulty grasping the dynamometer then they were allowed to perform HGS testing with their arm on a supporting object. Likewise, persons unable to stand could complete HGS testing seated. More details about HGS test protocols in the HRS are available elsewhere (6).
The highest recorded HGS value from the trials was included in the analyses. Biological sex-specific absolute and normalized HGS cut-points were used for determining weakness status (3,16). Males with HGS <35.5 kg, <0.45 kg/kg, or <1.05 kg/kg/m2, and females with HGS <20 kg, HGS <0.34 kg/kg, or <0.79 kg/kg/m2 were considered as weak. Given that weakness is determined by having HGS below any of the absolute or normalized HGS cut-points (24), we further examined weakness status by categorizing subjects as being below 1, 2, or 3 HGS cut-points.
Age, sex (male, female), race and ethnicity (Hispanic, non-Hispanic black, non-Hispanic white, non-Hispanic other (included American Indian, Alaskan Native, Asian, Native Hawaiian, Pacific Islander)) were self-reported. Persons aged 50-64 years were considered middle-aged, while subjects ≥65-years were classified as older adults.
Statistical Analysis
All analyses were performed with SAS 9.4 software (SAS Institute; Cary, NC). The analyses were informed by HRS analytic guidelines to account for the complex sampling design in the HRS for generating population-based prevalence estimates that were nationally-representative (23). Prevalence estimates for weakness were presented as a weighted percentage and 95% confidence interval (CI), and comparisons of CIs were completed as appropriate. The prevalence of weakness was presented as 1) having any weakness, and 2) being below 1, 2, or 3 HGS cut-points. These prevalence estimates were shown as overall, and stratified by age group, sex, and race and ethnicity for each combined HRS wave (2006-2008; 2010-2012; 2014-2016).
Individual multilevel logistic regression models for evaluating trends in any weakness were performed with the survey weights included for overall weakness, age group, sex, and race and ethnicity. Repeated measures of individual persons in multiple waves were modeled utilizing a random intercept for each participant to account for the longitudinal design of the HRS. For each model, the dichotomous response variable was any weakness. In the overall model, the only explanatory variable was time (i.e., wave). Another model adjusted for time, age group (reference: middle-aged), and the interaction between time and age group examined trends by age group. Moreover, a model adjusted for time, sex (reference: female), and a time-by-sex interaction analyzed trends by sex. In the final model, there were explanatory variables for time, race/ethnicity (reference group: non-Hispanic other) and the interaction. An alpha level of 0.05 was used for all analyses.
RESULTS
The overall prevalence of weakness is presented in Table 2. The prevalence of any weakness overall trended upward over time (p<0.001). There were 45.1% (CI: 44.0-46.0) of Americans with weakness at the 2006-2008 waves and 46.6% (CI: 45.6-47.5) for the 2010-2012 waves. Relative to the 2006-2008 and 2010-2012 waves, the prevalence of weakness significantly increased to 52.6% (CI: 51.5-53.7) at the 2014-2016 waves. A similar theme was observed when examining the prevalence of Americans considered weak with 1, 2, or 3 definitions, such that differences also existed for the prevalence of weakness using several definitions within and between waves. For example, in the 2014-2016 waves, there was a lower prevalence of Americans with 3 weakness definitions (15.3%; CI: 14.6-16.0) compared to persons with 1 (19.1%; CI: 18.2-19.9) or 2 definitions (18.2%; CI: 17.3-18.9).
Table 2.
Overall Prevalence of Weakness.
| Weighted Frequency | Weighted Prevalence | 95% Confidence Interval | |
|---|---|---|---|
| 2006-2008 Waves | |||
| Any Weakness | 27,122,782 | 45.1 | 44.0, 46.0 |
| 1 Weakness Definition | 10,235,402 | 17.0 | 16.2, 17.7 |
| 2 Weakness Definitions | 9,391,082 | 15.6 | 14.9, 16.3 |
| 3 Weakness Definitions | 7,496,298 | 12.5 | 11.8, 13.0 |
| 2010-2012 Waves | |||
| Any Weakness | 34,708,167 | 46.6 | 45.6, 47.5 |
| 1 Weakness Definition | 12,984,933 | 17.4 | 16.6, 18.1 |
| 2 Weakness Definitions | 12,058,784 | 16.2 | 15.4, 16.8 |
| 3 Weakness Definitions | 9,664,450 | 13.0 | 12.3, 13.5 |
| 2014-2016 Waves | |||
| Any Weakness | 40,820,834 | 52.6 | 51.5, 53.7 |
| 1 Weakness Definition | 14,848,912 | 19.1 | 18.2, 19.9 |
| 2 Weakness Definitions | 14,088,374 | 18.2 | 17.3, 18.9 |
| 3 Weakness Definitions | 11,883,548 | 15.3 | 14.6, 16.0 |
The prevalence of weakness by age group is shown in Table 3. Those who were middle-aged had any weakness prevalence of 32.7% (CI: 31.2-34.3), 34.9% (CI: 33.5-36.2), and 42.2% (CI: 40.6-43.8) at the 2006-2008, 2010-2012, and 2014-2016 waves, respectively. The prevalence of any weakness in older Americans was 58.1% (CI: 46.9-59.2), 61.9% (CI: 60.4-63.1), and 64.2% (CI: 62.8-65.5). There was a greater prevalence of any weakness in older adults compared to middle-aged adults (p<0.001). However, our trends analysis also suggest that there were no statistically significant trends in any weakness for older adults, but a significant increase in any weakness was observed in middle-aged Americans (p<0.001).
Table 3.
Prevalence of Weakness by Age Group.
| Weighted Frequency | Weighted Prevalence | 95% Confidence Interval | |
|---|---|---|---|
| Middle-Aged | |||
| 2006-2008 Waves | |||
| Any Weakness | 10,146,358 | 32.7 | 31.2, 34.3 |
| 1 Weakness Definition | 4,837,100 | 15.6 | 14.4, 16.8 |
| 2 Weakness Definitions | 3,697,323 | 12.0 | 10.9, 12.9 |
| 3 Weakness Definitions | 1,611,935 | 5.2 | 4.5, 5.9 |
| 2010-2012 Waves | |||
| Any Weakness | 14,723,932 | 34.9 | 33.5, 36.2 |
| 1 Weakness Definition | 7,070,434 | 16.8 | 15.6, 17.8 |
| 2 Weakness Definitions | 5,391,360 | 12.8 | 11.8, 13.7 |
| 3 Weakness Definitions | 2,262,138 | 5.3 | 4.7, 5.9 |
| 2014-2016 Waves | |||
| Any Weakness | 17,245,485 | 42.2 | 40.6, 43.8 |
| 1 Weakness Definition | 8,082,346 | 19.8 | 18.5, 21.0 |
| 2 Weakness Definitions | 6,305,903 | 15.4 | 14.3, 16.5 |
| 3 Weakness Definitions | 2,857,236 | 7.0 | 6.2, 7.7 |
| Older | |||
| 2006-2008 Waves | |||
| Any Weakness | 16,976,424 | 58.1 | 46.9, 59.2 |
| 1 Weakness Definition | 5,398,302 | 18.5 | 17.5, 19.3 |
| 2 Weakness Definitions | 5,693,759 | 19.5 | 18.5, 20.4 |
| 3 Weakness Definitions | 5,884,363 | 20.1 | 19.2, 21.0 |
| 2010-2012 Waves | |||
| Any Weakness | 19,984,235 | 61.9 | 60.4, 63.1 |
| 1 Weakness Definition | 5,914,499 | 18.3 | 17.3, 19.3 |
| 2 Weakness Definitions | 6,667,424 | 20.7 | 19.6, 21.6 |
| 3 Weakness Definitions | 7,402,312 | 22.9 | 21.9, 23.9 |
| 2014-2016 Waves | |||
| Any Weakness | 23,575,349 | 64.2 | 62.8, 65.5 |
| 1 Weakness Definition | 6,766,566 | 18.4 | 17.3, 19.4 |
| 2 Weakness Definitions | 7,782,471 | 21.2 | 20.1, 22.2 |
| 3 Weakness Definitions | 9,026,312 | 24.6 | 23.4, 25.6 |
Table 4 displays the prevalence of weakness by sex. The prevalence of any weakness in females was 47.3% (CI: 46.0-48.6) at the 2006-2008 waves, 48.4% (CI: 47.0-49.6) at the 2010-2012 wave, and 54.5% (CI: 53.1-55.9) at the 2014-2016 waves. The prevalence of any weakness in males was 42.4% (CI: 40.8-43.9) at the 2006-2008 waves, 44.6% (CI: 43.1-46.0) at the 2010-2012 waves, and 50.4% (CI: 48.7-52.0) at the 2014-2016 waves. There was a statistically significant increasing trend for any weakness in females (p<0.001), but not males. Table 5 presents prevalence of weakness by race and ethnicity. In the 2014-2016 waves, the prevalence of any weakness in Hispanics, non-Hispanic blacks, and non-Hispanic whites was 58.2% (CI: 55.0-61.3), 59.6% (CI: 57.1-62.0), and 51.4% (CI: 50.0-52.6), respectively. However, the prevalence of any weakness did not change over time for all races and ethnicities. Table 6 presents the results for the any weakness trends analyses.
Table 4.
Prevalence of Weakness by Sex.
| Weighted Frequency | Weighted Prevalence | 95% Confidence Interval | |
|---|---|---|---|
| Females | |||
| 2006-2008 Waves | |||
| Any Weakness | 15,459,229 | 47.3 | 46.0, 48.6 |
| 1 Weakness Definition | 4,473,381 | 13.7 | 12.8, 14.5 |
| 2 Weakness Definitions | 6,143,464 | 18.8 | 17.7, 19.8 |
| 3 Weakness Definitions | 4,842,384 | 14.8 | 13.9, 15.6 |
| 2010-2012 Waves | |||
| Any Weakness | 19,249,136 | 48.4 | 47.0, 49.6 |
| 1 Weakness Definition | 5,490,715 | 13.8 | 12.8, 14.7 |
| 2 Weakness Definitions | 7,743,451 | 19.5 | 18.4, 20.4 |
| 3 Weakness Definitions | 6,014,970 | 15.1 | 14.2, 15.9 |
| 2014-2016 Waves | |||
| Any Weakness | 22,636,923 | 54.5 | 53.1, 55.9 |
| 1 Weakness Definition | 6,422,908 | 15.5 | 14.4, 16.5 |
| 2 Weakness Definitions | 8,966,254 | 21.6 | 20.4, 22.7 |
| 3 Weakness Definitions | 7,247,761 | 17.5 | 16.5, 18.4 |
| Males | |||
| 2006-2008 Waves | |||
| Any Weakness | 11,663,553 | 42.4 | 40.8, 43.9 |
| 1 Weakness Definition | 5,762,021 | 21.0 | 19.6, 22.2 |
| 2 Weakness Definitions | 3,247,618 | 11.8 | 10.8, 12.7 |
| 3 Weakness Definitions | 2,653,914 | 9.6 | 8.8, 10.4 |
| 2010-2012 Waves | |||
| Any Weakness | 15,459,031 | 44.6 | 43.1, 46.0 |
| 1 Weakness Definition | 7,494,218 | 21.6 | 20.3, 22.8 |
| 2 Weakness Definitions | 4,315,333 | 12.5 | 11.5, 13.3 |
| 3 Weakness Definitions | 3,649,480 | 10.5 | 9.7, 11.3 |
| 2014-2016 Waves | |||
| Any Weakness | 18,183,911 | 50.4 | 48.7, 52.0 |
| 1 Weakness Definition | 8,426,004 | 23.4 | 21.9, 24.7 |
| 2 Weakness Definitions | 5,122,120 | 14.2 | 13.1, 15.2 |
| 3 Weakness Definitions | 4,635,787 | 12.8 | 11.9, 13.8 |
Table 5.
Prevalence of Weakness by Race and Ethnicity.
| Weighted Frequency | Weighted Prevalence | 95% Confidence Interval | |
|---|---|---|---|
| Hispanic | |||
| 2006-2008 Waves | |||
| Any Weakness | 2,135,582 | 51.1 | 47.5, 54.7 |
| 1 Weakness Definition | 615,014 | 14.7 | 12.1, 17.3 |
| 2 Weakness Definitions | 767,339 | 18.4 | 15.7, 21.0 |
| 3 Weakness Definitions | 753,229 | 18.0 | 15.4, 20.6 |
| 2010-2012 Waves | |||
| Any Weakness | 3,098,499 | 53.9 | 50.5, 57.1 |
| 1 Weakness Definition | 895,304 | 15.6 | 13.0, 18.1 |
| 2 Weakness Definitions | 1,121,399 | 19.5 | 16.8, 22.1 |
| 3 Weakness Definitions | 1,081,796 | 18.8 | 16.4, 21.1 |
| 2014-2016 Waves | |||
| Any Weakness | 4,016,627 | 58.2 | 55.0, 61.3 |
| 1 Weakness Definition | 1,126,955 | 16.3 | 13.9, 18.7 |
| 2 Weakness Definitions | 1,367,210 | 19.8 | 17.3, 22.2 |
| 3 Weakness Definitions | 1,522,462 | 22.1 | 19.5, 24.6 |
| Non-Hispanic Black | |||
| 2006-2008 Waves | |||
| Any Weakness | 2,593,052 | 49.5 | 46.7, 52.3 |
| 1 Weakness Definition | 903,834 | 17.3 | 15.1, 19.3 |
| 2 Weakness Definitions | 1,054,166 | 20.1 | 17.9, 22.3 |
| 3 Weakness Definitions | 635,052 | 12.1 | 10.3, 13.9 |
| 2010-2012 Waves | |||
| Any Weakness | 3,861,525 | 53.7 | 51.3, 56.0 |
| 1 Weakness Definition | 1,474,008 | 20.5 | 18.4, 22.5 |
| 2 Weakness Definitions | 1,588,886 | 22.1 | 20.0, 24.1 |
| 3 Weakness Definitions | 798,631 | 11.1 | 9.6, 12.5 |
| 2014-2016 Waves | |||
| Any Weakness | 4,573,293 | 59.6 | 57.1, 62.0 |
| 1 Weakness Definition | 1,674,067 | 21.8 | 19.7, 23.8 |
| 2 Weakness Definitions | 1,799,404 | 23.5 | 21.2, 25.5 |
| 3 Weakness Definitions | 1,099,822 | 14.3 | 12.6, 16.0 |
| Non-Hispanic Other | |||
| 2006-2008 Waves | |||
| Any Weakness | 576,695 | 38.7 | 32.0, 45.3 |
| 1 Weakness Definition | 237,067 | 15.9 | 10.7, 21.0 |
| 2 Weakness Definitions | 207,790 | 13.9 | 9.2, 18.6 |
| 3 Weakness Definitions | 131,838 | 8.9 | 5.6, 12.0 |
| 2010-2012 Waves | |||
| Any Weakness | 1,201,613 | 47.4 | 41.8, 53.0 |
| 1 Weakness Definition | 476,536 | 18.8 | 14.2, 23.3 |
| 2 Weakness Definitions | 431,236 | 17.0 | 12.8, 21.1 |
| 3 Weakness Definitions | 293,841 | 11.6 | 8.3, 14.8 |
| 2014-2016 Waves | |||
| Any Weakness | 1,696,192 | 48.0 | 42.5, 53.4 |
| 1 Weakness Definition | 760,756 | 21.5 | 17.1, 25.9 |
| 2 Weakness Definitions | 555,229 | 15.7 | 12.1, 19.2 |
| 3 Weakness Definitions | 380,207 | 10.8 | 7.9, 13.6 |
| Non-Hispanic White | |||
| 2006-2008 Waves | |||
| Any Weakness | 21,817,453 | 44.3 | 43.1, 45.4 |
| 1 Weakness Definition | 8,479,487 | 17.2 | 16.3, 18.0 |
| 2 Weakness Definitions | 7,361,787 | 15.0 | 14.1, 15.7 |
| 3 Weakness Definitions | 5,976,179 | 12.1 | 11.4, 12.7 |
| 2010-2012 Waves | |||
| Any Weakness | 26,546,530 | 45.0 | 43.8, 46.1 |
| 1 Weakness Definition | 10,139,085 | 17.2 | 16.3, 18.0 |
| 2 Weakness Definitions | 8,917,263 | 15.1 | 14.3, 15.8 |
| 3 Weakness Definitions | 7,490,182 | 12.7 | 12.0, 13.3 |
| 2014-2016 Waves | |||
| Any Weakness | 30,534,722 | 51.4 | 50.0, 52.6 |
| 1 Weakness Definition | 11,287,134 | 19.0 | 17.9, 19.9 |
| 2 Weakness Definitions | 10,366,531 | 17.4 | 16.5, 18.3 |
| 3 Weakness Definitions | 8,881,057 | 15.0 | 14.1, 15.7 |
Table 6.
Results for the Any Weakness Trends Analyses.
| Estimate | 95% Confidence Interval |
p-value | |
|---|---|---|---|
| Model | |||
| Intercept | −0.71 | −0.82, −0.59 | <0.001 |
| Wave | 0.08 | 0.07, 0.09 | <0.001 |
| Age Group | |||
| Intercept | −1.60 | −1.80, −1.40 | <0.001 |
| Wave | 0.12 | 0.10, 0.13 | <0.001 |
| Older | 1.01 | 0.76, 1.26 | <0.001 |
| Wave*Older | −0.01 | −0.03, 0.02 | 0.66 |
| Sex | |||
| Intercept | −0.66 | −0.82, −0.50 | <0.001 |
| Wave | 0.08 | 0.06, 0.09 | <0.001 |
| Male | −0.11 | −0.35, 0.13 | 0.38 |
| Wave*Male | 0.01 | −0.02, 0.02 | 0.90 |
| Race and Ethnicity | |||
| Intercept | −0.60 | −1.30, 0.13 | 0.10 |
| Wave | 0.05 | −0.01, 0.12 | 0.11 |
| Hispanic | 0.15 | −0.67, 0.97 | 0.71 |
| Non-Hispanic White | −0.16 | −0.90, 0.58 | 0.67 |
| Non-Hispanic Black | 0.03 | −0.76, 0.81 | 0.95 |
| Wave*Hispanic | 0.01 | −0.06, 0.09 | 0.72 |
| Wave*Non-Hispanic White | 0.03 | −0.04, 0.10 | 0.37 |
| Wave*Non-Hispanic Black | 0.02 | −0.05, 0.09 | 0.58 |
DISCUSSION
The findings of this investigation revealed that the prevalence of weakness is pronounced and increasing in Americans aged at least 50-years. Specifically, approximately 45% of Americans were considered as having any weakness in the 2006-2008 waves, and approximately 47% of Americans were weak under the same criteria for the 2010-2012 waves. The prevalence of persons considered weak elevated to about 53% in the 2014-2016 wave. The proportion of Americans considered weak with 2-3 cut-point definitions generally decreased. Although weakness exists in middle-aged Americans, a higher proportion of weakness was observed in the older American demographic. There was an increasing trend in any weakness for females but not males. While the prevalence of weakness differed across race and ethnicity, the highest prevalence was generally observed in Americans identifying as Hispanic or non-Hispanic black. Our findings suggest that many Americans aged at least 50-years are living with weakness, thereby increasing their risk for adverse health outcomes. Regular screening for weakness with handgrip dynamometry may help to identify persons considered weak so that referrals to muscle strengthening and nutritional interventions can be conducted.
Different HGS thresholds exist for determining weakness, and we utilized the summation of the presence of weakness with three different absolute and normalized HGS cut-points in Americans. Weakness, as determined with HGS, signifies the initial stages of the disabling process (2). Poor physical performance is similarly determined with slow gait speed, and functional disability, such as difficulty or an inability in completing basic self-care tasks, typically occurs successively when weakness initially is present (2). Batsis et al. (1) likewise used absolute and BMI normalized weakness cut-points with 2006-2008 HRS data and found rates of functional limitations were greater in persons with weakness regardless of cut-point. However, Patel et al. (24) used the same weakness cut-points as in our investigation with HRS as a partial data source and suggested the prevalence of weakness in older Americans is contingent on the weakness cut-point utilized. Accordingly, using different cut-points for defining weakness, regardless of absolute or normalized, may influence the sensitivity and specificity of the next stages of disablement (24). Further, cut-points normalized to body mass or BMI may not best capture how body dimension factors into HGS measurements. Adjusting HGS to height-squared could be optimal for normalizing HGS to a body dimension (22), but cut-points for HGS normalized to height-squared do not yet exist, yet need creation. Therefore, it is possible that persons considered weak under multiple cut-points, such as the absolute and normalized cut-points used in our study, are truly weak. Using only a single absolute or normalized HGS cut-point could lead to weakness misclassification. However, more research about the sensitivity and specificity of disablement and other age-related outcomes with an ordinal weakness cut-point definition approach is warranted.
Given that muscle strength decreases with age starting around middle adulthood onwards (26), it is not surprising that we found the prevalence of weakness was higher in older compared to middle-aged Americans. When examining weakness status by gender, we found an upward trend in weakness for females. Moreover, we generally observed a higher prevalence of weakness in Hispanic and non-Hispanic black Americans. These stratified findings align with other investigations evaluating weakness prevalence with different data sources and cut-points (15,24). Despite increased participation in resistance training in the United States (12), other factors that influence strength such as dietary protein and Vitamin D intake, could be inadequate in community-dwelling older adults (10,11). While early intervention for persons screened as weak is key for deflecting a downward functional trajectory (14), multidisciplinary interventions that are inclusive of physical activity, nutrition, and other relevant health domains remain critical for strength elevation and preservation.
Some limitations of this study should be noted. The HRS does not specify certain races and ethnicities such as non-Hispanic Asian. When normalizing HGS to body mass or BMI, caution should be acknowledged for persons with underweight and severe obese status because such body dimension characteristics may skew how HGS is normalized (17). The HRS alternates waves for their detailed face-to-face interviews, which included HGS measurements, thereby explaining why we combined relevant alternating waves. Being under at least one of the HGS cut-points we used suggests weakness is present (24), but it remains unknown how being below more than one of the weakness definitions used in our investigation influences weakness status and subsequent disablement.
Our investigation found that up to 53% of Americans aged at least 50-years were weak. The overall prevalence of any weakness increased from 2006-2016. Sub-group analyses for age, sex, and race and ethnicity revealed differential findings for weakness. Physical activity participation (e.g., resistance training) and a healthy diet remain crucial for preventing, treating, and changing weakness status. Continuing to surveil the trends in weakness status, at individual and population-based levels, may help to inform the effectiveness of current interventions aiming to improve strength during aging, guide programming related to strength capacity, and reveal populations that should be targeted for weakness interventions. Such surveillance may help the rapidly growing older American demographic live longer and with more independence.
PRACTICAL APPLICATIONS
Given that the United States will be experiencing a large increase in the older adult population demographic (27) and age-related health conditions, the demand for exercise professionals that are qualified to work with older persons will similarly grow. Handgrip dynamometers could be useful tools for feasibly assessing strength capacity in relevant aging populations. Guidelines for appropriate physical activity participation to improve strength in older adults, including resistance training, should be strongly encouraged for preventing and treating weakness (8,25). Nutritional counseling is also advised as nutrient intake may influence health and responses to interventions. Repeated measures of HGS could be used for monitoring progress (28), but changes of functional abilities may inform how strength assessments are conducted.
ACKNOWLEDGEMENTS
Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R15AG072348 (PI is RM). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The results of the present study do not constitute endorsement of the product by the authors or the NSCA. The authors report no conflicts of interest.
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