| Literature DB >> 32166029 |
Ryan McGrath1, Nathaniel Johnson1, Lukus Klawitter1, Sean Mahoney1, Kara Trautman1, Caroline Carlson1, Ella Rockstad1, Kyle J Hackney1.
Abstract
Measures of handgrip strength can be used to conveniently assess overall muscle strength capacity. Although stand-alone measures of handgrip strength provide robust health information, the clinical meaningfulness to determine prevention and treatment options for weakness remains limited because the etiology of muscle weakness remains unclear. Moreover, clinical outcomes associated with handgrip strength are wide-ranging. Therefore, disentangling how handgrip strength is associated with health conditions that are metabolically or neurologically driven may improve our understanding of the factors linked to handgrip strength. The purpose of this topical review was to highlight and summarize evidence examining the associations of handgrip strength with certain health outcomes that are metabolically and neurologically driven. From this perusal of the literature, we posit that stand-alone handgrip strength be considered an umbrella assessment of the body systems that contribute to strength capacity, and a panoptic measurement of muscle strength that is representative of overall health status, not a specific health condition. Recommendations for future strength capacity-related research are also provided.Entities:
Keywords: Geriatric assessment; methods; muscle strength; muscle weakness; sarcopenia
Year: 2020 PMID: 32166029 PMCID: PMC7052448 DOI: 10.1177/2050312120910358
Source DB: PubMed Journal: SAGE Open Med ISSN: 2050-3121
Outline of reviewed studies for the associations between handgrip strength and chronic cardiometabolic health conditions.
| Article | Participants | Health condition | Key findings |
|---|---|---|---|
| Sayer et al.[ | 2677 men aged 59–73 years | Metabolic syndrome | Every standard deviation decrease of HGS was associated with a 0.05 standard deviation increase in fasting triglycerides (p = 0.006), 1.13 greater odds for high blood pressure (p = 0.004), 0.08 standard deviation unit increase in waist circumference (p < 0.001), 0.07 standard deviation unit increase in 2-h glucose (p = 0.001), and 0.05 standard deviation unit increase in homeostatic model assessment (p = 0.008). It was also found that lower HGS was associated with 1.18 greater odds (p < 0.001) for metabolic syndrome when using Adult Treatment Panel III guidelines and 1.11 greater odds (p = 0.03) for metabolic syndrome when utilizing International Diabetes Federation guidelines |
| Yi et al.[ | 2472 men and 2542 women aged ⩾ 20 years | Metabolic syndrome | Men (n = 2472) and women (n = 2542) in the strongest HGS quartile had 0.22 (p < 0.0001) and 0.16 decreased odds (p < 0.0001) for metabolic syndrome, respectively |
| Leong et al.[ | 142,861 adults aged 35–70 years | Cardiovascular disease mortality and myocardial infarction | Every 5-kg decrease in HGS was associated with a 1.17 higher hazard (p < 0.001) for cardiovascular disease mortality and 1.07 higher hazard (p = 0.002) for myocardial infarction |
| Celis-Morales et al.[ | 217,011 men and 260,063 women aged 40–69 years | Cardiovascular disease incidence, cardiovascular disease mortality | Every 5-kg lower HGS was associated with a 1.11 (p < 0.001) and 1.15 higher hazard (p < 0.001) for cardiovascular disease incidence, and a 1.22 (p < 0.001) and 1.19 higher hazard (p < 0.001) for cardiovascular disease mortality in men and women, respectively. Men who were weak had a 1.36 higher hazard (p < 0.001) for cardiovascular disease incidence and 1.84 higher hazard (p < 0.001) for cardiovascular disease mortality, while women who were weak had a 1.30 higher hazard (p < 0.001) for cardiovascular disease incidence and 1.44 higher hazard (p < 0.001) for cardiovascular mortality |
| Farmer et al.[ | 452,931 adults | Cardiovascular disease events | Low HGS was associated with cardiovascular disease events (hazard ratios ranged from 1.05 to 1.09) |
| McGrath et al.[ | 17,431 adults aged ⩾ 50 years | Chronic heart failure | Those who were weak had a 1.35 higher hazard (p < 0.05) for developing chronic heart failure compared to persons who were not weak |
| McGrath et al.[ | 801 men and 1102 women aged ⩾ 65 years | Diabetes | Men and women who were considered weak had a 1.05 (p < 0.001) and 1.38 higher hazard (p < 0.001) for incident diabetes, respectively |
| Karvonen-Gutierrez et al.[ | 424 adults aged 46.4 ± 2.8 years | Diabetes | Every 0.1 higher body weight normalized HGS was associated with a 0.81 lower hazard (p = 0.006) for incident diabetes |
| Li et al.[ | 1632 men aged ⩾ 35 years | Diabetes | Every 5-kg higher HGS was associated with 0.87 decreased odds for incident diabetes |
| Hamasaki et al.[ | 1282 adults aged 63.8 ± 13.9 years with diabetes | Cardiovascular disease events and hospitalization | Every 1-kg increase in HGS at baseline was associated with 0.89 decreased odds (p = 0.025) for cardiovascular disease events and 0.96 decreased odds (p < 0.001) for hospitalization |
| Celis-Morales et al.[ | 347,130 adults aged 55.9 ± 8.1 years | Cardiovascular disease incidence, cardiovascular disease mortality, all-cause mortality | Persons with diabetes who also had low HGS were at greater risk for adverse health outcomes such as cardiovascular disease incidence (hazard ratio: 1.98; p < 0.05), cardiovascular disease mortality (hazard ratio: 2.88; p < 0.05), and all-cause mortality (hazard ratio: 2.05; p < 0.05) compared to those with higher HGS |
HGS: handgrip strength.
Contents included in this table may have only captured findings from studies that were relevant for our review.
Outline of reviewed studies for the associations between handgrip strength and neural health conditions.
| Article | Participants | Health condition | Key findings |
|---|---|---|---|
| Jang and Kim[ | 1366 men and 1616 women aged ⩾ 65 years | Cognitive impairment | Men and women in the highest HGS quartile had 0.38 (p < 0.001) and 0.51 decreased odds (p < 0.001) for mild cognitive impairment compared to those in the lowest HGS quartile, respectively |
| Vancampfort et al.[ | 32,715 adults aged 62.0 ± 15.6 years | Cognitive impairment | Weakness was associated with 1.41 greater odds (p < 0.05) for mild cognitive impairment |
| McGrath et al.[ | 13,828 adults aged ⩾ 50 years | Cognitive impairment | Every 5-kg lower HGS was associated with 1.10 greater odds (p < 0.05) for any cognitive impairment, 1.18 greater odds (p < 0.05) for severe cognitive impairment, and 1.10 greater odds (p < 0.05) for poorer cognitive functioning |
| Buchman et al.[ | 887 older adults | Alzheimer’s disease | Each 1-pound decrease in baseline HGS was associated with a 1.5% increased risk (p < 0.05) for Alzheimer’s disease |
| Alfaro-Acha et al.[ | 2160 adults aged 71.9 ± 5.9 years | Cognitive impairment | A significant time-by-HGS quartile interaction existed for cognitive impairment (Q1: β = −0.18 ± 0.06, p < 0.0001; Q2: β = −0.21 ± 0.06, p < 0.001; Q3: β = −0.09 ± 0.05, p > 0.05; Q4 = reference) |
| Ogawa et al.[ | 352 older adults | Alzheimer’s disease | In women, Alzheimer’s disease advanced from “early Alzheimer’s disease” (HGS: 17.4 ± 3.7 kg; p < 0.01) to “mild Alzheimer’s disease” (HGS: 16.9 ± 3.7 kg; p < 0.0001) to “moderate Alzheimer’s disease” (HGS: 15.8 ± 3.8 kg; p < 0.0001) relative to women with normal cognition (HGS: 20.1 ± 3.3 kg) |
| Roberts et al.[ | 79 adults | Parkinson’s diseases | HGS was correlated with Unified Parkinson Disease Rating Scale scores (r = −0.36; p = 0.006) and Hoehn–Yahr scores (r = −0.37; p = 0.005) |
HGS: handgrip strength; Q: quartile.
Contents included in this table may have only captured findings from studies that were relevant for our review.
Outline of reviewed studies for the associations between handgrip strength and functional health conditions.
| Article | Participants | Health condition | Key findings |
|---|---|---|---|
| Gopinath et al.[ | 947 adults aged ⩾ 65 years | IALD disability | Every 10-kg increase in HGS was associated with 0.61 decreased odds (p < 0.05) for IADL disability |
| Germain et al.[ | 10,149 adults aged 71.8 ± 7.7 years | IADL disability | Those in the middle and high HGS tertile had 0.61 (p < 0.05) and 0.47 lower odds (p < 0.05) for an IADL disability compared to individuals in the lowest HGS tertile, respectively |
| McGrath et al.[ | 672 adults aged 81.7 ± 4.1 years | IADL disability | Every 10-kg increase in HGS at baseline was associated with 0.95 decreased odds (p < 0.05) for losses in IADLs |
| McGrath et al.[ | 15,336 adults aged ⩾ 50 years | IADL disability | Every 5-kg decrease in HGS was associated with 1.11 greater odds for an impairment in using a map, 1.07 greater odds for an impairment in preparing hot meals, 1.09 greater odds for an impairment in taking medications, 1.06 greater odds for an impairment in managing money, 1.05 greater odds for an impairment in using a telephone, and 1.10 greater odds for an impairment in shopping for groceries (all p < 0.05) |
| Al Snih et al.[ | 1050 older men and 1443 older women | BADL disability | Men and women in the lowest HGS quartiles had a 1.90 and 2.28 higher hazard (p < 0.05) for any BADL limitation |
| McGrath et al.[ | 2270 older adults aged ⩾ 65 years | BADL disability | Those who were considered weak had a 1.25 higher hazard (p < 0.0001) for incident BADL disability compared to persons who were not weak and did not have diabetes |
| Zhang et al.[ | 6127 adults aged ⩾ 45 years | BADL disability | Those who were considered weak had 2.26 greater odds (p < 0.001) for BADL disability compared to those who were not weak |
| McGrath et al.[ | 17,747 adults aged ⩾ 50 years | BADL disability | Every 5-kg decrease in HGS was associated with a 1.20 higher hazard for an eating limitation, 1.14 higher hazard for a walking limitation, 1.14 higher hazard for a bathing limitation, 1.09 higher hazard for a dressing limitation, 1.08 higher hazard for a transferring limitation, and 1.06 higher hazard for a toileting limitation (p < 0.05 for all) |
BADLs: basic activities of daily living; HGS: handgrip strength; IADLs: instrumental activities of daily living.
Contents included in this table may have only captured findings from studies that were relevant for our review.
Outline of reviewed studies for the associations between handgrip strength and dynamic functional assessments.
| Article | Participants | Assessment | Key findings |
|---|---|---|---|
| Alonso et al.[ | 110 women aged 67.4 ± 5.9 | Timed-up-and-go | HGS on the dominant (r = −0.20; p = 0.03) and non-dominant hand (r = −0.20; p = 0.03) is correlated with the timed-up-and-go test |
| Martin-Ponce et al.[ | 310 adults aged ⩾ 60 years | 6-min walk | Those who were in the lower HGS category walked a shorter distance (84.3 ± 12.0 m) on the 6-min walk test than those in the higher HGS category (178.0 ± 14.0 m; p < 0.001) |
| Zhang et al.[ | 106 adults aged 62.0 ± 10.0 years | 6-min walk | HGS was correlated with 6-min walk test distance (r = 0.221; p = 0.029) and also predicted 6-min walk distance (β = 3.162; p < 0.001) |
| Harris-Love et al.[ | 30 adults aged 62.5 ± 9.2 years | Gait speed | HGS is correlated with gait speed (r = 0.42; p = 0.021) |
| Arvandi et al.[ | 808 adults aged ⩾ 65 years | Fall history | Every 1-kg increase in HGS was associated with 0.97 decreased odds (p = 0.26) for falls |
| Stevens et al.[ | 349 men and 280 women aged 63–73 years | Short physical performance battery | Every 1-kg increase in HGS was associated with a 0.07-s decrease in the timed-up-and-go test, 0.02-s decrease in 3-m walk time, and 1% decrease in chair rises time for men (all p < 0.001). Every 1-kg increase in HGS was associated with a 0.13-s decrease in the timed-up-and-go test, 0.03-s decrease in 3-m walking time, and 1% decrease in chair rises time for women (all p < 0.001) |
HGS: handgrip strength.
Contents included in this table may have only captured findings from studies that were relevant for our review.
Figure 1.Conceptual model for identifying third factors for paralleling associations between muscle strength capacity and morbidities that are metabolically or neural driven.
Figure 2.Conceptual model for evaluating how strength capacity and health could be influenced through the muscular and nervous systems by different categories of mediating factors.