Comparison of grip strength measurements for predicting all-cause mortality among adult aged 20+ years: NHANES 2011-2014

Comparison of grip strength measurements for predicting all-cause mortality among adult aged 20+ years: NHANES 2011-2014 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Comparison of grip strength measurements for predicting all-cause mortality among adult aged 20+ years: NHANES 2011-2014 Lirong Chai, Dongfeng Zhang, Junning Fan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4733967/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background Little is known about the optimal measure of handgrip strength for predicting all-cause mortality and whether this association is modified by age or sex. Methods We used data from the 2011–2014 National Health and Nutrition Examination Survey (NHANES), 9,583 adults aged ≥ 20 years were included. Equal-length grip strength was measured using a digital handheld Takei dynamometer. We defined four measurements of grip strength, i.e., the average of the maximum of both hands (HGS), the maximum of dominant hand (MGS), HGS/BMI, and MGS/weight, and three indicators of low grip strength, namely, low reference grip strength, lowest 20% grip strength, and low grip strength in sarcopenia. Information on deaths were obtained through linkage to National Death Index (NDI). Cox regression was used to assess the association of grip strength with mortality risk. Results HGS, MGS, HGS/BMI, and MGS/weight were all inversely associated with all-cause mortality, with HGS (AUC = 0.714) being the optimal predictor of mortality, followed by MGS (AUC = 0.712). Participants with low grip strength showed increased risk of mortality regardless of which indicator was used, and the highest effect size was seen for lowest 20% grip strength group (HR = 2.20 for men, 2.52 for women). The above-mentioned correlations were consistently found in people of different age and sex. Conclusion This study suggests the simplest measure of absolute grip strength (HGS, MGS) was the optimal index for predicting all-cause mortality. Keep an adequate level of handgrip strength may be beneficial to reduce the risk of mortality. Grip strength All-cause mortality Optimal measurement index Interactions Figures Figure 1 Introduction Hand grip strength is a simple indicator of upper limb muscle strength, and a reflection of overall skeletal muscle strength [ 1 ] . As a measurement index, it has the advantages of easy to obtain, repeated application and cost effectiveness. It can quickly and quantitatively evaluate muscle function, which is one of the basic measurement indexes of physical examination [ 2 , 3 ] . Currently, the measurements of grip strength are not uniform, limiting the comparability of research results, and the optimal grip strength index is unclear [ 4 ] . Common grip strength indicators include the average of the maximum of both hands (HGS) [ 5 ] and maximum of dominant hand (MGS) [ 6 ] , which is often called absolute grip strength. However, in general, grip strength is easily affected by body measurement indicators such as height, weight, and BMI. Absolute grip strength as a simple indicator of grip strength cannot take into account the differences in body size, so some researchers combine absolute grip strength with body size indicators as a relative grip strength indicator [ 7 , 8 , 9 ] , e.g., HGS/BMI, MGS/body weight, HGS/muscle tissue content, and HGS/muscle mass. Of these, HGS/BMI is a widely used measure in academic research, while MGS/weight was officially used in National Standards for Students' Physical Fitness and Health in China to evaluate the muscle strength of adolescents [ 10 ] . Some studies showed that relative grip strength measurements may be a better indicator for muscle weakness and more predictive of adverse outcomes [ 8 , 11 ] , whereas others not [ 12 ] .The application conditions of absolute and relative grip strength indexes need to be further studied. Low grip strength represents a decline in muscle function, and increases the risk of frailty, disease, and death [ 13 , 14 , 15 , 16 ] . However, there is no consensus on the definition of low grip strength [ 17 ] . One of the definitions was “low reference grip strength”, defined as the HGS lower than the population reference value of grip strength calculated by the equation according to the gender, age, height, and weight of the sample population [ 18 ] . Another definition was “lowest 20% grip strength”, defined as the lowest 20% of grip strength in the population sampled adjusted for gender and body mass index according to the definition of frailty [ 19 , 20 ] . “Sarcopenia low grip strength” was defined as MGS less than 26 kg in men or less than 16 kg in women [ 21 ] . Previous evidence suggested an inverse association between hand grip strength and all-cause mortality [ 22 , 23 , 24 ] . However, whether the association between grip strength and death differed by age or sex was inconsistent [ 25 , 26 ] . The comparison and predictive ability of mortality for different grip strength have not reached a consensus [ 27 ] . Therefore, the aim of this study was to determine the association of the indicators of grip strength level and low grip strength with the risk of all-cause mortality in adults registered in the National Health and Nutrition Examination Survey (NHANES), and to explore the optimal measure of grip strength for predicting all-cause mortality. Methods The NHANES is a national, periodic, cross-sectional survey which aims to obtain the number, distribution and influence factors of disease and disability in the United States. The data were acquired from a complex, multistage probability sampling design in noninstitutionalized civilian resident, and information about questionnaire, physical examination, and laboratory examination were collected. The NHANES study was approved by the Research Ethics Review Board of the National Center for Health Statistics, and all study participants provided written informed consent. More details about NHANES have been described elsewhere [ 28 ] . This study was a secondary data analysis of publicly available federal data without personal identifiers, therefore, did not require Institutional Review Board review. We used data from the 2011–2014 cycle of NHANES. A total of 19,931 people were recruited and 19,151 people attended the mobile examination center (MEC) physical examination. We included adults aged ≥ 20 years and excluded those pregnant and with incomplete or unqualified death information recall or missing data on grip strength and BMI, finally 9,583 subjects were included in this study (Figure S1 ). Assessment of grip strength Equal-length grip strength was measured using a digital handheld Takei dynamometer (Model T.K.K.5401). After the inspector's demonstration adjustment and practice test, participants took a standing position and squeezed the dynamometer as hard as they could with one hand, then repeated the test with the other hand. Grip strength was measured 3 times in each hand, alternating hands between trials with at least 60 seconds between each test. We defined four measurements of handgrip strength. Absolute grip strength (HGS) was calculated as the average of the maximum values of the readings in both hands, expressed in kg. Relative grip strength (HGS/BMI) was obtained by the ratio of HGS to BMI. The maximum value of handedness (in kg) (MGS) was the maximum value of six measurements, and MGS/weight was the maximum value of handedness /body weight (in kg) *100. We also defined three measurements of low grip strength. Low reference grip strength referred to the MGS lower than the calculated reference value in men and women respectively, according to the formula raised by Ying-Chih Wang [ 18 ] . Lowest 20% grip strength was defined as the lowest 20% of the maximum dominant hand of the sample population stratified by gender and BMI [ 19 ] , specific cutoff value was shown in Table S1 . Low grip strength in sarcopenia was defined as less than 26 kg in men’s dominant hand or less than 16 kg in women’s dominant hand [ 21 ] . Assessment of covariates Information on covariates was obtained through questionnaires, physical examinations, and laboratory tests. Covariates considered in this study mainly included gender (men, women), age (< 65, ≥ 65)/(in years), race (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Asian and other non-Hispanic groups), education level (less than 9th grade, 9-11th grade, high school graduate, some college or AA degree and college graduate or above), marital status (live with someone, live alone), poverty-to-income ratio (PIR) grouped into quartiles (≤ 1.06, 1.07–2.15, 2.16–4.19, > 4.19), BMI (kg/m 2 : <18.5, 18.5–24.9, 25-29.9, ≥ 30), smoking status (never, former, current), alcohol consumption (never, current), regular physical activity (MET-min/week), and underlying chronic diseases (no, yes) included hypertension, hyperlipidemia, diabetes, cardiovascular diseases (CVD), and cancer. Detailed definition of covariates was displayed in Supplementary Text S1. Assessment of mortality Information on deaths were obtained through linkage to National Death Index (NDI) to 31 December 2019 via participants’ serial numbers ( https://www.cdc.gov/nchs/data-linkage/mortality-public.htm ). Statistical analysis All statistical analyses were conducted using Stata 15.0. A two-sided P < 0.05 was considered statistically significant. We adjusted the data using appropriate survey weights, strata, and primary sampling units in accordance with the complex sample design of the NHANES and oversampling of subgroups of the sample. Baseline characteristics of participants were presented by sex-specific quartiles of HGS. Analysis of variance was used for continuous variables and the chi-square test was used for categorical variables, with correction for sample weights. The follow-up time of the study was calculated from the NHANES 2011–2014 examination date until the last known date alive or censored, or 31 December 2019, whichever occurred first. Cox proportional hazards models was used to analyze the association of grip strength measurements which included HGS, HGS/BMI, MGS, and MGS/weight and low grip strength with all-cause mortality, indicators of low grip strength included low reference grip strength, lowest 20% grip strength, and low grip strength in sarcopenia. To achieve comparability of grip strength measures, we standardized both absolute and relative grip strength measurements to investigate their association with the risk of all-cause mortality. Considering the difference in grip strength values between men and women, we analyzed the data by gender. In Cox proportional hazards regression analyses, model 1 was adjusted for age and race, model 2 was further adjusted for education level, marital status, PIR, smoking status, alcohol consumption, regular exercise, model 3 was further adjusted for baseline chronic diseases (hypertension, hyperlipidemia, diabetes, CVD, and cancer). To assess the possible non-linear association of handgrip measurements with mortality risk, we performed restricted cubic spline regression, with Z-scores of handgrip strength measurements modelled as natural cubic splines with four knots (the 5th, 35th, 65th, and 95th percentiles). The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated to compare the ability of different grip strength indexes in predicting the risk of all-cause mortality. Based on gender stratification, we further conducted age stratification analysis (< 65 years, ≥ 65 years). To examine the robustness of our findings, we did the following two sensitivity analyses: First, subjects who died in the first year after MEC follow-up were excluded to reduce the influence of reverse causation. Second, subjects who already had cancer or CVD at baseline were excluded since these diseases may affect grip strength. Results The mean age of all participants was 47.4 ± 16.8 years, and 49.9% were men (Table 1 ). In general, with the decline of grip strength, participants were more likely to be older, being non-Hispanic Asian, and have lower level of education and income. They also tended to be former smokers, current drinkers, have less regular physical activity and lower values of BMI, and have higher prevalence of chronic diseases (hypertension, hyperlipidemia, diabetes, CVD, and cancer). Table 1 Baseline characteristics of participants by sex-specific quartiles of absolute grip strength All (n = 9,583) Q4 (highest) (n = 2,390) Q3 (n = 2,382) Q2 (n = 2,409) Q1 (lowest) (n = 2,402) P value Age (years) 47.4 (16.8) 39.2 (11.7) 44.5 (13.7) 49.7 (16.6) 59.6 (20.2) < 0.001 Men (%) 49.9 51.8 51.5 47.0 45.6 0.029 Race (%) < 0.001 Mexican American 11.2 7.2 8.6 8.1 8.3 Other Hispanic 9.2 4.7 5.1 7.1 6.7 Non-Hispanic White 41.0 65.5 69.9 66.7 66.6 Non-Hispanic Black 23.4 17.7 10.0 8.2 7.9 Non-Hispanic Asian 12.2 2.1 3.6 7.3 7.9 Others 3.0 2.8 2.9 2.5 2.4 Educational level (%) < 0.001 Less than 9th grade 7.7 2.2 3.2 5.0 8.9 9-11th grade 13.7 9.0 9.6 10.9 14.1 High school graduate 21.8 19.9 21.1 20.8 22.6 Some college or AA degree 31.1 36.9 33.9 30.3 28.9 College graduate or above 25.7 32.0 32.2 32.9 25.4 Marital status (%) * 0.001 Live with someone 57.4 64.7 63.2 62.3 55.4 Live alone 42.6 35.3 36.8 37.7 44.6 Income-to-poverty Ratio (%) 4.19 23.0 34.0 35.0 32.0 24.6 Smoke status (%) < 0.001 Never 56.5 58.3 55.7 53.8 56.2 Former 22.9 20.3 23.1 26.2 27.7 Current 20.6 21.3 21.1 20.0 16.0 Alcohol status (%) < 0.001 Never 68.2 77.4 76.2 75.2 65.5 Current 24.5 17.4 18.1 20.3 28.7 MET-h/w 56.2 (91.8) 75.8 (104.4) 59.1 (86.3) 51.9 (87.0) 31.3 (69.8) < 0.001 BMI (kg/m 2 ) 29.0 (6.9) 30.5 (6.9) 28.8 (6.3) 28.2 (6.6) 28.1 (7.5) < 0.001 Prevalence of chronic diseases (%) Hypertension 43.4 31.3 35.6 39.8 56.7 < 0.001 Hyperlipemia 54.0 48.0 51.3 55.2 64.4 < 0.001 Diabetes 17.5 6.9 10.9 14.4 24.4 < 0.001 CVD 9.9 2.9 5.0 8.6 19.9 < 0.001 Cancer 9.0 5.3 8.9 11.0 18.1 < 0.001 Abbreviations: BMI, body mass index; CVD, Cardiovascular Disease; MET, metabolic equivalent. Values are expressed as mean (SD) or percentage. Analysis of variance was used for continuous variables and the chi-square test was used for categorical variables, with correction for sample weights. * "Live with someone" includes married and living together, "Live alone" includes widowed, divorced, separated and unmarried. Over a median of 6.75 years of follow-up, 805 deaths occurred. As shown in Table 2 , in men, when grip strength was used as a continuous variable, the fully adjusted HRs (95% CIs) for per 5 kg lower of HGS and MGS were 1.36 (1.26, 1.48) and 1.34 (1.24, 1.46); and the HRs (95% CIs) for one unit decrease of HGS/BMI and MGS/weight were 3.65 (2.32, 5.75) and 1.04 (1.02, 1.05), respectively. When we treated grip strength as a quartile variable, there was an increased mortality risk with the decline of grip strength ( P trend <0.05). Compared with the highest quartile (Q4), the lowest quartile (Q1) had about 2-fold higher hazard for all-cause mortality, irrespective of which grip strength measures was applied. Table 2 Association between different handgrip strength measurements and risk of all-cause mortality in men Q4 (highest) HR (95%CI) Q3 HR (95%CI) Q2 HR (95%CI) Q1 (lowest) HR (95%CI) Continuous * P trend HGS Number of deaths 26 45 86 296 453 Mortality rate (/1,000 PYs) 3.2 5.5 10.6 40.1 14.2 Model 1 reference 1.54 (0.63, 3.75) 1.98 (0.94, 4.16) 4.55 (2.44, 8.49) 1.46 (1.36, 1.57) < 0.001 Model 2 reference 1.29 (0.53, 3.15) 1.59 (0.77, 3.28) 3.10 (1.74, 5.51) 1.37 (1.27, 1.48) < 0.001 Model 3 reference 1.27 (0.53, 3.03) 1.54 (0.76, 3.11) 3.00 (1.72, 5.22) 1.36 (1.26, 1.48) < 0.001 HGS/BMI Number of deaths 36 48 112 257 453 Mortality rate (/1,000 PYs) 4.4 5.9 14.0 34.4 14.2 Model 1 reference 1.20 (0.57, 2.51) 1.79 (1.04, 3.07) 3.16 (1.85, 5.39) 4.51 (2.95, 6.90) < 0.001 Model 2 reference 1.25 (0.59, 2.65) 1.85 (1.09, 3.15) 2.81 (1.64, 4.81) 3.45 (2.14, 5.54) < 0.001 Model 3 reference 1.29 (0.61, 2.72) 1.99 (1.19, 3.35) 2.88 (1.66, 5.00) 3.65 (2.32, 5.75) < 0.001 MGS Number of deaths 31 43 76 303 453 Mortality rate (/1,000 PYs) 3.8 5.3 9.5 40.5 14.2 Model 1 reference 1.66 (0.72, 3.81) 1.68 (0.82, 3.47) 4.66 (2.57, 8.45) 1.44 (1.34, 1.55) < 0.001 Model 2 reference 1.47 (0.65, 3.29) 1.38 (0.70, 2.71) 3.26 (1.90, 5.58) 1.35 (1.25, 1.46) < 0.001 Model 3 reference 1.47 (0.66, 3.29) 1.33 (0.68, 2.59) 3.16 (1.88, 5.29) 1.34 (1.24, 1.46) < 0.001 MGS/weight Number of deaths 32 67 96 258 453 Mortality rate (/1,000 PYs) 3.9 8.2 12.0 34.5 14.2 Model 1 reference 1.60 (0.78, 3.30) 1.36 (0.75, 2.49) 3.00 (1.62, 5.56) 1.04 (1.02, 1.06) < 0.001 Model 2 reference 1.80 (0.82, 3.95) 1.58 (0.83, 3.03) 2.87 (1.50, 5.47) 1.03 (1.02, 1.05) 0.001 Model 3 reference 1.89 (0.86, 4.16) 1.72 (0.89, 3.32) 3.09 (1.55, 6.15) 1.04 (1.02, 1.05) 0.001 Abbreviations: HGS: hand grip strength; MGS: maximum value of dominant hand; MGS/weight: MGS/body weight *100; PYs: person-years. *Continuous was calculated as per 5kg decrease in HGS and MGS, and per one unit decrease in HGS/BMI and MGS/weight. Model 1: adjusted for age and race; Model 2: Model 1 + adjusted for education level, marital status, income-to-poverty ratio, smoking status, alcohol drinking, regular exercise; Model 3: Model 2 + adjusted for baseline chronic diseases (cancer, CVD, hypertension, hyperlipidemia, diabetes); Cox regression was corrected for sample weights. HR (95%CI) in bold indicates P ≤ 0.05. In Table 3 for women, the associations of continuous grip strength were similar to men, the HRs (95% CIs) for per 5 kg lower of HGS and MGS were 1.49 (1.30, 1.69) and 1.45 (1.27, 1.66); and the HRs (95% CIs) for one unit decrease of HGS/BMI and MGS/weight were 2.22 (1.28, 3.83) and 1.02 (1.00, 1.03). When we treated grip strength as a quartile variable, except for HGS/BMI, the lowest quartile (Q1) in grip strength measurements were associated with a higher hazard for all-cause mortality compared with the highest quartile (Q4). After standardization of grip strength, the highest risk of all-cause death per 1-SD decrease in grip strength was found in HGS (men; adjusted HR = 1.81, 95% CI = 1.55–2.11, women; 1.62, 1.38–1.90), followed by MGS (men; 1.79, 1.53–2.09, women; 1.60, 1.36–1.90) (Table S2). Table 3 Association between different handgrip strength measurements and risk of all-cause mortality in women Q4 (highest) HR (95%CI) Q3 HR (95%CI) Q2 HR (95%CI) Q1 (lowest) HR (95%CI) Continuous * P trend HGS Number of deaths 22 50 49 231 352 Mortality rate (/1,000 PYs) 2.7 6.2 5.9 30.3 10.9 Model 1 reference 1.55 (0.86, 2.82) 1.43 (0.75, 2.73) 3.47 (1.81, 6.66) 1.67 (1.45, 1.93) < 0.001 Model 2 reference 1.52 (0.83, 2.77) 1.41 (0.72, 2.77) 3.05 (1.59, 5.88) 1.55 (1.37, 1.75) < 0.001 Model 3 reference 1.50 (0.84, 2.67) 1.38 (0.72, 2.64) 2.81 (1.49, 5.27) 1.49 (1.30, 1.69) 0.001 HGS/BMI Number of deaths 32 48 60 212 352 Mortality rate (/1,000 PYs) 3.9 5.8 7.4 27.6 10.9 Model 1 reference 0.87 (0.46, 1.65) 0.65 (0.37, 1.14) 1.85 (1.00, 3.41) 4.44 (2.45, 8.07) 0.001 Model 2 reference 0.78 (0.43, 1.43) 0.60 (0.36, 1.00) 1.48 (0.86, 2.54) 2.94 (1.71, 5.03) 0.005 Model 3 reference 0.80 (0.46, 1.38) 0.58 (0.36, 0.92) 1.32 (0.81, 2.16) 2.22 (1.28, 3.83) 0.022 MGS Number of deaths 21 50 47 234 352 Mortality rate (/1,000 PYs) 2.6 6.1 5.7 30.4 10.9 Model 1 reference 1.38 (0.63, 3.03) 1.13 (0.50, 2.55) 2.92 (1.30, 6.54) 1.63 (1.41, 1.88) 0.001 Model 2 reference 1.40 (0.64, 3.02) 1.14 (0.50, 2.60) 2.68 (1.22, 5.88) 1.52 (1.34, 1.72) 0.002 Model 3 reference 1.34 (0.62, 2.91) 1.12 (0.50, 2.47) 2.44 (1.13, 5.27) 1.45 (1.27, 1.66) 0.004 MGS/weight Number of deaths 23 59 72 198 352 Mortality rate (/1,000 PYs) 2.8 7.2 8.9 25.7 10.9 Model 1 reference 1.28 (0.69, 2.39) 1.07 (0.56, 2.06) 2.38 (1.25, 4.51) 1.03 (1.02, 1.05) < 0.001 Model 2 reference 1.19 (0.66, 2.16) 1.01 (0.55, 1.85) 1.96 (1.10, 3.47) 1.02 (1.01, 1.04) 0.002 Model 3 reference 1.19 (0.67, 2.10) 0.98 (0.56, 1.72) 1.72 (1.01, 2.91) 1.02 (1.00, 1.03) 0.009 Abbreviations: HGS: hand grip strength; MGS: maximum value of dominant hand; MGS/weight: MGS/body weight *100; PYs: person-years. *Continuous was calculated as per 5kg decrease in HGS and MGS, and per one unit decrease in HGS/BMI and MGS/weight. Model 1: adjusted for age and race; Model 2: Model 1 + adjusted for education level, marital status, income-to-poverty ratio, smoking status, alcohol drinking, regular exercise; Model 3: Model 2 + adjusted for baseline chronic diseases (cancer, CVD, hypertension, hyperlipidemia, diabetes); Cox regression was corrected for sample weights. HR (95%CI) in bold indicates P ≤ 0.05. For low grip strength, although different definitions were applied, the higher mortality risk was consistently found in the low grip strength group compared with the normal grip strength group (Table 4 ). We observed an interaction of low reference grip strength and sex on the risk of all-cause mortality ( P interaction =0.013), the HR (95% CI) was 1.91 (1.54, 2.35) in men, but lost significance in model 3 for women. Subgroup analyses by age showed no difference in association among those 0.05). Table 4 Association between low grip strength of different definitions and the risk of all-cause mortality Men Women P interaction Normal grip strength Low grip strength Normal grip strength Low grip strength Low reference grip strength 0.013 Number of deaths 211 242 189 163 Mortality rate (/1,000 PYs) 10.6 20.3 9.0 14.5 Model 1 reference 2.12 (1.70, 2.64) reference 1.61 (1.22, 2.11) Model 2 reference 1.84 (1.49, 2.28) reference 1.37 (1.08, 1.74) Model 3 reference 1.91 (1.54, 2.35) reference 1.22 (0.99, 1.51) Lowest 20% grip strength 0.174 Number of deaths 189 264 128 224 Mortality rate (/1,000 PYs) 7.2 45.5 4.9 37.1 Model 1 reference 2.70 (2.12, 3.44) reference 3.03 (2.11, 4.34) Model 2 reference 2.24 (1.77, 2.82) reference 2.67 (1.94, 3.66) Model 3 reference 2.20 (1.71, 2.83) reference 2.52 (1.83, 3.46) Men ≤ 26kg, Women ≤ 16kg 0.661 Number of deaths 395 58 298 54 Mortality rate (/1,000 PYs) 12.6 106.6 9.4 101.3 Model 1 reference 2.94 (1.97, 4.39) reference 3.37 (2.34, 4.86) Model 2 reference 2.10 (1.37, 3.23) reference 2.58 (1.77, 3.77) Model 3 reference 2.06 (1.33, 3.19) reference 2.29 (1.55, 3.38) Abbreviations: PYs: person-years. Model 1: adjusted for age (except for low reference grip strength) and race; Model 2: Model 1 + adjusted for education level, marital status, income-to-poverty ratio, smoking status, alcohol drinking, regular exercise; Model 3: Model 2 + adjusted for baseline chronic diseases (cancer, CVD, hypertension, hyperlipidemia, diabetes); Cox regression was corrected for sample weights. HR (95%CI) in bold indicates P ≤ 0.05. In the restricted cubic spline regression, we observed a non-linear inverse association of Z-scores of grip strength with mortality risk, which was similar across different hand strength measurements (Figure S2). By comparing the AUC of the four grip strength measurements, HGS (AUC = 0.714) was the best predictor of all-cause mortality risk, followed by MGS (AUC = 0.712) (Fig. 1 ). In sensitivity analyses, when we excluded deaths during the first year of follow-up, or excluded participants with CVD or caner at baseline, the result remained almost unchanged (Table S5, Table S6). Discussion The main finding of this study was that decreased grip strength in adults was associated with an increased risk for all-cause mortality. Using four different measures of grip strength, we found similar non-linear inverse correlations. HGS (AUC = 0.714) had the best ability to predict all-cause mortality, followed by MGS (AUC = 0.712). Participants with low grip strength were at increased risk of mortality, and the HR was highest in the lowest 20% grip strength group (HR = 2.20 for men, 2.52 for women). We found no significant interaction of age, sex, and grip strength, except for low reference grip strength and gender ( P interaction =0.013). Our finding of inverse associations between grip strength and all-cause mortality were in agreement with previous studies. A meta-analysis conducted on 42 studies including 3,002,203 participants showed that grip strength was an independent predictor of all-cause mortality, the HRs (95% CIs) with per-5-kg decrease in grip strength was 1.16 (1.12, 1.20) for all-cause mortality [ 22 ] . These results were comparable to our findings, where we found that 5-kg lower HGS in men was associated with an HR of 1.36 in men for all-cause mortality, and an HR of 1.49 in women. Cai, Y. et al. [ 27 ] similarly found that the HR (95% CI) for all-cause mortality per 5-kg reduction in grip strength was 1.11(1.06, 1.18) in men and 1.17(1.08, 1.28) in women. In our study, we found that after standardizing all grip strength indicators, the association of absolute grip strength indicators with the risk of all-cause mortality was stronger than that of relative grip strength indicators, with the highest being for HGS (HR = 1.81 for men and HR = 1.62 for women). Inconsistently, a study, also based on NHANES, found that compared with the sum of the maximum values of both hands (GS), GS/BMI had a stronger correlation with cardiovascular biomarkers as a relative grip strength indicator [ 7 ] . Wonjeong Jeong et al. [ 29 ] also found that HGS/BMI was more associated with risk of all-cause mortality compared with HGS, the associations persisted after adjustment for chronic diseases. Similarly, Yanan Gao et al. [ 9 ] also recommended HGS/BMI or HGS/body weight as the best choice for grip strength expression to predict the risk of CVD risk factors. However, by comparing AUC in our study, we recommend HGS or MGS as the optimal predictor of all-cause mortality risk. Meanwhile, Ho FKW et al. [ 12 ] compared different expressions of grip strength in adults with an average age of 56 years (range 37–73) based on UK Biobank and found no difference in the association between absolute and relative grip strength and all-cause mortality. They believed that the simplest method of handgrip strength measurement, i.e., the absolute unit (kg), was perfectly suitable for predicting health outcomes in clinical practice. We found participants with low grip strength carried higher mortality risk, irrespective of which definition was used, which was in line with previous studies [ 20 , 25 , 30 ] . However, few studies have compared the effect of different measures of low grip strength in the same population. Our study showed that the HRs was highest when using the definition of “lowest 20% grip strength” (HR = 2.20 for men, 2.52 for women), possibly because this definition could identify participants with the worst muscle strength, and better distinguish them from people with normal grip strength. Overall, we did not find significant modifying effect of gender and age on the association between grip strength and all-cause mortality, except for the interaction between low reference grip strength and gender, where the effect of low grip strength was only found in men, which was consistent with the previous conclusion of Strand BH et al in Tromsø database [ 24 ] . However, this was opposite to the results of a previous KORA-based study [ 31 ] , which found that the association between muscular strength and all-cause mortality tended to be stronger in women. Actually, most previous studies suggested no interaction of grip strength and gender, on the risk of death [ 22 , 24 , 25 ] . Existing evidence stratified by age also suggested inconclusive results. A study based on UK Biobank demonstrated that the hazard ratio of grip strength with all-cause death was higher in the younger age group in both genders [ 25 ] . Similar results were also found in the China Health and Retirement Longitudinal Study (CHARLS) study in China, where the association between MGS and all-cause mortality was stronger in young men (HR = 0.29, 95% CI: 0.18–0.45) than in older men (HR = 0.49, 95% CI:0.33–0.73) [ 32 ] . Whereas Rachel et al. [ 26 ] found that the association between low grip strength and all-cause mortality was higher in people over 70 years old (HR = 1.80, 95% CI: 1.48–2.18) than those of under 60 years old (HR = 1.43, 95% CI: 1.07–1.91). Further research is needed to examine the interaction effect of age and sex. Our study had several advantages. First, we used relatively comprehensive measures of grip strength, including absolute grip strength (HGS, MGS), relative grip strength (HGS/BMI, MGS/weight), and low grip strength, to examine and compare their associations with all-cause mortality. Meanwhile, by using the relative grip strength index, the influence of body shape factors (such as fat, weight, BMI) can be effectively excluded to some extent, so that more reliable conclusions can be obtained. Second, this study used a large representative sample from the American NHANES. The grip strength was standardized (Z score) to further study the correlation between grip strength and all-cause mortality. ROC curve was used to compare the area under the curve (AUC) to obtain the optimal index of grip strength to predict the risk of all-cause death. However, our study had some limitations. First, as the NHANES is a repeated cross-sectional study, it cannot provide data on changes in grip strength, so we could only examine the association of baseline grip strength with all-cause death. Nevertheless, previous studies have found that baseline grip strength measures are the best predictors of cardiovascular mortality [ 33 ] . Second, as an outcome variable in handgrip strength studies, the composition of all-cause mortality tends to be more complex. For example, accidental death may not be intrinsically related to grip strength, so if accidental death accounted for a substantial proportion during the study, it is likely to affect the validity of the study results. Third, we only employed two widely-used relative grip strength indicators (HGS/BMI, MGS/weight), exploring other combinations such as MGS/BMI or HGS/weight may also be of great value in the future. Finally, although we have accounted for as many confounding factors as possible, residual confounding still exists. Conclusion The present study has shown that all four measures of grip strength level are significantly and inversely associated with all-cause mortality, and the simple absolute grip strength (HGS) is the best predictor of all-cause mortality. Our results show that low grip strength is associated with an increased risk of all-cause mortality, with the strongest association observe in the lowest 20% grip strength group. The above results remain significant in different age and gender. We recommend that the simplest measure of absolute grip strength (HGS, MGS) be used as the optimal indicator for predicting all-cause mortality. Keep an adequate level of handgrip strength may be beneficial to reduce the risk of mortality. Declarations Contributors JF conceived and designed the study. JF and LC analyzed the data. LC drafted the manuscript. JF and LC helped the interpretation of the results. JF contributed to the critical revision of the manuscript for important intellectual content and approved the final version of the manuscript. All authors reviewed and approved the final manuscript. DZ is the guarantor. Acknowledgments We acknowledge the staff at the National Center for Health Statistics at the CDC, who design, collect, administer the NHANES data and release the data available for public use. We are thankful to all study participants for their cooperation. Funding This work was supported by Natural Science Foundation of Shandong Province (ZR2023QH188), China Postdoctoral Science Foundation (2023M731839), Qingdao Postdoctoral Innovation Project (QDBSH20230102012), Qingdao University Scientific Research Startup Fund (DC2200002531), Mount Taishan Scholar Youth Program. The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report, or the decision to submit the article for publication. Conflict of interest None declared. Consent for publication Not applicable. Data sharing Publicly available datasets were analyzed in this study. This data can be found here: https://wwwn.cdc.gov/nchs/nhanes/ (accessed on 14 February 2023). Ethics approval and consent to participate The NHANES study was approved by the Research Ethics Review Board of the National Center for Health Statistics, and all study participants provided written informed consent. This study was a secondary data analysis of publicly available federal data without personal identifiers, therefore, did not require Institutional Review Board review. References Porto JM, Nakaishi APM, Cangussu-Oliveira LM, Freire Júnior RC, Spilla SB, Abreu DCC. Relationship between grip strength and global muscle strength in community-dwelling older people. Archives of gerontology and geriatrics. 2019;82:273-8. Bohannon RW. Muscle strength: clinical and prognostic value of hand-grip dynamometry. Current opinion in clinical nutrition and metabolic care. 2015;18(5):465-70. Bohannon RW. Grip Strength: An Indispensable Biomarker For Older Adults. Clinical interventions in aging. 2019;14:1681-91. Schaap LA, Fox B, Henwood T, Bruyère O, Reginster JY, Beaudart C, et al. Grip strength measurement: Towards a standardized approach in sarcopen ia research and practice. European Geriatric Medicine. 2016;7(3):247-55. Leong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A, Jr., Orlandini A, et al. Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet (London, England). 2015;386(9990):266-73. Yoo JI, Choi H, Ha YC. Mean Hand Grip Strength and Cut-off Value for Sarcopenia in Korean Adults Using KNHANES VI. Journal of Korean medical science. 2017;32(5):868-72. Lawman HG, Troiano RP, Perna FM, Wang CY, Fryar CD, Ogden CL. Associations of Relative Handgrip Strength and Cardiovascular Disease Biomarkers in U.S. Adults, 2011-2012. Am J Prev Med. 2016;50(6):677-83. Parra-Soto S, Pell JP, Celis-Morales C, Ho FK. Absolute and relative grip strength as predictors of cancer: prospective cohort study of 445 552 participants in UK Biobank. Journal of cachexia, sarcopenia and muscle. 2022;13(1):325-32. Gao Y, Huang H, Ni C, Feng Y, Yu J, Huang Y, et al. Comparison of Five Expressions of Handgrip Strength for Predicting Cardiovascular Disease Risk Factors in Chinese Middle-Aged Community Residents. Frontiers in public health. 2022;10:903036. Yan XJ, Zhang JS, Liu YF, Ma N, Luo DM, Song Y. [The application of the National Standards for Students' Physical Health (2014 revision) in SPSS]. Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]. 2020;54(6):708-12. Alley DE, Shardell MD, Peters KW, McLean RR, Dam TT, Kenny AM, et al. Grip strength cutpoints for the identification of clinically relevant weakness. The journals of gerontology Series A, Biological sciences and medical sciences. 2014;69(5):559-66. Ho FKW, Celis-Morales CA, Petermann-Rocha F, Sillars A, Welsh P, Welsh C, et al. The association of grip strength with health outcomes does not differ if grip strength is used in absolute or relative terms: a prospective cohort study. Age and ageing. 2019;48(5):684-91. Xie KH, Han X, Zheng WJ, Zhuang SF. Low Grip Strength and Increased Mortality Hazard among Middle-Aged and Older Chinese Adults with Chronic Diseases. Biomedical and environmental sciences : BES. 2023;36(3):213-21. Norman K, Stobäus N, Gonzalez MC, Schulzke JD, Pirlich M. Hand grip strength: outcome predictor and marker of nutritional status. Clinical nutrition (Edinburgh, Scotland). 2011;30(2):135-42. Kim Y, Wijndaele K, Lee DC, Sharp SJ, Wareham N, Brage S. Independent and joint associations of grip strength and adiposity with all-cause and cardiovascular disease mortality in 403,199 adults: the UK Biobank study. The American journal of clinical nutrition. 2017;106(3):773-82. Liu W, Leong DP, Hu B, AhTse L, Rangarajan S, Wang Y, et al. The association of grip strength with cardiovascular diseases and all-cause mortality in people with hypertension: Findings from the Prospective Urban Rural Epidemiology China Study. Journal of sport and health science. 2021;10(6):629-36. Dodds RM, Syddall HE, Cooper R, Kuh D, Cooper C, Sayer AA. Global variation in grip strength: a systematic review and meta-analysis of normative data. Age and ageing. 2016;45(2):209-16. Wang YC, Bohannon RW, Li X, Sindhu B, Kapellusch J. Hand-Grip Strength: Normative Reference Values and Equations for Individuals 18 to 85 Years of Age Residing in the United States. The Journal of orthopaedic and sports physical therapy. 2018;48(9):685-93. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. The journals of gerontology Series A, Biological sciences and medical sciences. 2001;56(3):M146-56. Chainani V, Shaharyar S, Dave K, Choksi V, Ravindranathan S, Hanno R, et al. Objective measures of the frailty syndrome (hand grip strength and gait speed) and cardiovascular mortality: A systematic review. International journal of cardiology. 2016;215:487-93. Studenski SA, Peters KW, Alley DE, Cawthon PM, McLean RR, Harris TB, et al. The FNIH sarcopenia project: rationale, study description, conference recommendations, and final estimates. The journals of gerontology Series A, Biological sciences and medical sciences. 2014;69(5):547-58. Wu Y, Wang W, Liu T, Zhang D. Association of Grip Strength With Risk of All-Cause Mortality, Cardiovascular Diseases, and Cancer in Community-Dwelling Populations: A Meta-analysis of Prospective Cohort Studies. Journal of the American Medical Directors Association. 2017;18(6):551.e17-.e35. Pavasini R, Serenelli M, Celis-Morales CA, Gray SR, Izawa KP, Watanabe S, et al. Grip strength predicts cardiac adverse events in patients with cardiac disorders: an individual patient pooled meta-analysis. Heart (British Cardiac Society). 2019;105(11):834-41. Strand BH, Cooper R, Bergland A, Jørgensen L, Schirmer H, Skirbekk V, et al. The association of grip strength from midlife onwards with all-cause and cause-specific mortality over 17 years of follow-up in the Tromsø Study. Journal of epidemiology and community health. 2016;70(12):1214-21. Celis-Morales CA, Welsh P, Lyall DM, Steell L, Petermann F, Anderson J, et al. Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: prospective cohort study of half a million UK Biobank participants. BMJ. 2018;361:k1651. Cooper R, Kuh D, Hardy R. Objectively measured physical capability levels and mortality: systematic review and meta-analysis. Bmj. 2010;341:c4467. Cai Y, Liu L, Wang J, Gao Y, Guo Z, Ping Z. Linear association between grip strength and all-cause mortality among the elderly: results from the SHARE study. Aging clinical and experimental research. 2021;33(4):933-41. J C, Rothwell MS, editors. National Health and Nutrition Examination Survey: Plan and Operations, 1999–2010. Hyattsville , Maryland: U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES, Centers for Disease Control and Prevention, National Center for Health Statistics; August 2013. Jeong W, Moon JY, Kim JH. Association of absolute and relative hand grip strength with all-cause mortality among middle-aged and old-aged people. BMC geriatrics. 2023;23(1):321. Mickute M, Zaccardi F, Razieh C, Sargeant J, Smith AC, Wilkinson TJ, et al. Individual frailty phenotype components and mortality in adults with type 2 diabetes: A UK Biobank study. Diabetes research and clinical practice. 2023;195:110155. Arvandi M, Strasser B, Meisinger C, Volaklis K, Gothe RM, Siebert U, et al. Gender differences in the association between grip strength and mortality in older adults: results from the KORA-age study. BMC geriatrics. 2016;16(1):201. Wang Y, Liu Y, Hu J, Guan H, Wang Y, Liu M, et al. Association of handgrip strength with all-cause mortality: a nationally longitudinal cohort study in China. Journal of science and medicine in sport. 2022;25(11):878-83. Prasitsiriphon O, Pothisiri W. Associations of Grip Strength and Change in Grip Strength With All-Cause and Cardiovascular Mortality in a European Older Population. Clinical Medicine Insights Cardiology. 2018;12:1179546818771894. Additional Declarations No competing interests reported. Supplementary Files Supplementary0614.docx Cite Share Download PDF Status: Published Journal Publication published 25 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 16 Oct, 2024 Reviews received at journal 11 Oct, 2024 Reviewers agreed at journal 10 Oct, 2024 Reviews received at journal 06 Aug, 2024 Reviewers agreed at journal 01 Aug, 2024 Reviewers invited by journal 31 Jul, 2024 Editor assigned by journal 31 Jul, 2024 Editor invited by journal 15 Jul, 2024 Submission checks completed at journal 13 Jul, 2024 First submitted to journal 13 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4733967","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":335429044,"identity":"5f9481d7-32f9-4aa6-b1ee-2bea0127564e","order_by":0,"name":"Lirong Chai","email":"","orcid":"","institution":"Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Lirong","middleName":"","lastName":"Chai","suffix":""},{"id":335429045,"identity":"3dea9beb-f121-43ca-b28c-83a43d3079d7","order_by":1,"name":"Dongfeng Zhang","email":"","orcid":"","institution":"Qingdao University","correspondingAuthor":false,"prefix":"","firstName":"Dongfeng","middleName":"","lastName":"Zhang","suffix":""},{"id":335429046,"identity":"bea4d610-1d18-4ccd-9088-f2bbccc77f9d","order_by":2,"name":"Junning Fan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIie2PsYrCQBCGJwQ2zS5pF5TkFTYseFr5KkkfbGwsjmMhkGdIocc9hVw5S8BKSWthET24SiHgC5wEc91tLIXbr/ln4P8YBsBieUI8BSBuSQFcxGbBg7BPofirkEQX27GM1ANKN8qS5YsE8M/yveftcM4+D8MX/0OU7J3HjnKPp71JobNYsu03nRR1rFdrPvOASJkalCmkQrK8pGKPiJc1nzuKkoFJof65U7RCtuSJwj6Fd1eqDDRTDylnEa3aKwR0seEyynp+oX46Epe8nIqqujbN61sQetnxy6TcIKINHt9311xvK3UbPvZXLRaL5X/yA4/xTwwOxqFiAAAAAElFTkSuQmCC","orcid":"","institution":"Qingdao University","correspondingAuthor":true,"prefix":"","firstName":"Junning","middleName":"","lastName":"Fan","suffix":""}],"badges":[],"createdAt":"2024-07-13 07:14:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4733967/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4733967/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-80487-y","type":"published","date":"2024-11-25T15:57:32+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62221304,"identity":"aa6e43fd-89cd-4525-94e4-cf6725a52467","added_by":"auto","created_at":"2024-08-11 12:27:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":136525,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver operating characteristic (ROC) curve of all-cause mortality risk after adjusting for age, gender and race predicted with different\u003c/strong\u003e \u003cstrong\u003ehandgrip strength measurements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHGS: hand grip strength; MGS: maximum value of dominant hand; MGS/weight: MGS/body weight *100.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4733967/v1/c3ecc2abba01d0846df3a032.png"},{"id":70382524,"identity":"a003d267-88cb-4e3b-93b9-ce922aa640b8","added_by":"auto","created_at":"2024-12-02 16:27:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1415852,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4733967/v1/a9a24d79-69e1-43d8-a0e8-fc99b654aeb4.pdf"},{"id":62221305,"identity":"6c64ed27-4627-48b0-a310-c45cba0391b3","added_by":"auto","created_at":"2024-08-11 12:27:08","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":662530,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary0614.docx","url":"https://assets-eu.researchsquare.com/files/rs-4733967/v1/7f99fa515419f53484b28a27.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of grip strength measurements for predicting all-cause mortality among adult aged 20+ years: NHANES 2011-2014","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHand grip strength is a simple indicator of upper limb muscle strength, and a reflection of overall skeletal muscle strength\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. As a measurement index, it has the advantages of easy to obtain, repeated application and cost effectiveness. It can quickly and quantitatively evaluate muscle function, which is one of the basic measurement indexes of physical examination\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCurrently, the measurements of grip strength are not uniform, limiting the comparability of research results, and the optimal grip strength index is unclear\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Common grip strength indicators include the average of the maximum of both hands (HGS)\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e and maximum of dominant hand (MGS)\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, which is often called absolute grip strength. However, in general, grip strength is easily affected by body measurement indicators such as height, weight, and BMI. Absolute grip strength as a simple indicator of grip strength cannot take into account the differences in body size, so some researchers combine absolute grip strength with body size indicators as a relative grip strength indicator \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, e.g., HGS/BMI, MGS/body weight, HGS/muscle tissue content, and HGS/muscle mass. Of these, HGS/BMI is a widely used measure in academic research, while MGS/weight was officially used in National Standards for Students' Physical Fitness and Health in China to evaluate the muscle strength of adolescents\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Some studies showed that relative grip strength measurements may be a better indicator for muscle weakness and more predictive of adverse outcomes\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e, whereas others not\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.The application conditions of absolute and relative grip strength indexes need to be further studied.\u003c/p\u003e \u003cp\u003eLow grip strength represents a decline in muscle function, and increases the risk of frailty, disease, and death\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. However, there is no consensus on the definition of low grip strength\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. One of the definitions was \u0026ldquo;low reference grip strength\u0026rdquo;, defined as the HGS lower than the population reference value of grip strength calculated by the equation according to the gender, age, height, and weight of the sample population\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Another definition was \u0026ldquo;lowest 20% grip strength\u0026rdquo;, defined as the lowest 20% of grip strength in the population sampled adjusted for gender and body mass index according to the definition of frailty\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. \u0026ldquo;Sarcopenia low grip strength\u0026rdquo; was defined as MGS less than 26 kg in men or less than 16 kg in women\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrevious evidence suggested an inverse association between hand grip strength and all-cause mortality \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. However, whether the association between grip strength and death differed by age or sex was inconsistent\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. The comparison and predictive ability of mortality for different grip strength have not reached a consensus\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, the aim of this study was to determine the association of the indicators of grip strength level and low grip strength with the risk of all-cause mortality in adults registered in the National Health and Nutrition Examination Survey (NHANES), and to explore the optimal measure of grip strength for predicting all-cause mortality.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe NHANES is a national, periodic, cross-sectional survey which aims to obtain the number, distribution and influence factors of disease and disability in the United States. The data were acquired from a complex, multistage probability sampling design in noninstitutionalized civilian resident, and information about questionnaire, physical examination, and laboratory examination were collected. The NHANES study was approved by the Research Ethics Review Board of the National Center for Health Statistics, and all study participants provided written informed consent. More details about NHANES have been described elsewhere\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. This study was a secondary data analysis of publicly available federal data without personal identifiers, therefore, did not require Institutional Review Board review.\u003c/p\u003e \u003cp\u003eWe used data from the 2011\u0026ndash;2014 cycle of NHANES. A total of 19,931 people were recruited and 19,151 people attended the mobile examination center (MEC) physical examination. We included adults aged\u0026thinsp;\u0026ge;\u0026thinsp;20 years and excluded those pregnant and with incomplete or unqualified death information recall or missing data on grip strength and BMI, finally 9,583 subjects were included in this study (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of grip strength\u003c/h2\u003e \u003cp\u003eEqual-length grip strength was measured using a digital handheld Takei dynamometer (Model T.K.K.5401). After the inspector's demonstration adjustment and practice test, participants took a standing position and squeezed the dynamometer as hard as they could with one hand, then repeated the test with the other hand. Grip strength was measured 3 times in each hand, alternating hands between trials with at least 60 seconds between each test.\u003c/p\u003e \u003cp\u003eWe defined four measurements of handgrip strength. Absolute grip strength (HGS) was calculated as the average of the maximum values of the readings in both hands, expressed in kg. Relative grip strength (HGS/BMI) was obtained by the ratio of HGS to BMI. The maximum value of handedness (in kg) (MGS) was the maximum value of six measurements, and MGS/weight was the maximum value of handedness /body weight (in kg) *100.\u003c/p\u003e \u003cp\u003eWe also defined three measurements of low grip strength. Low reference grip strength referred to the MGS lower than the calculated reference value in men and women respectively, according to the formula raised by Ying-Chih Wang\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Lowest 20% grip strength was defined as the lowest 20% of the maximum dominant hand of the sample population stratified by gender and BMI \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, specific cutoff value was shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Low grip strength in sarcopenia was defined as less than 26 kg in men\u0026rsquo;s dominant hand or less than 16 kg in women\u0026rsquo;s dominant hand\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of covariates\u003c/h2\u003e \u003cp\u003eInformation on covariates was obtained through questionnaires, physical examinations, and laboratory tests. Covariates considered in this study mainly included gender (men, women), age (\u0026lt;\u0026thinsp;65, \u0026ge;\u0026thinsp;65)/(in years), race (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Asian and other non-Hispanic groups), education level (less than 9th grade, 9-11th grade, high school graduate, some college or AA degree and college graduate or above), marital status (live with someone, live alone), poverty-to-income ratio (PIR) grouped into quartiles (\u0026le;\u0026thinsp;1.06, 1.07\u0026ndash;2.15, 2.16\u0026ndash;4.19, \u0026gt;\u0026thinsp;4.19), BMI (kg/m\u003csup\u003e2\u003c/sup\u003e: \u0026lt;18.5, 18.5\u0026ndash;24.9, 25-29.9, \u0026ge;\u0026thinsp;30), smoking status (never, former, current), alcohol consumption (never, current), regular physical activity (MET-min/week), and underlying chronic diseases (no, yes) included hypertension, hyperlipidemia, diabetes, cardiovascular diseases (CVD), and cancer. Detailed definition of covariates was displayed in Supplementary Text S1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of mortality\u003c/h2\u003e \u003cp\u003eInformation on deaths were obtained through linkage to National Death Index (NDI) to 31 December 2019 via participants\u0026rsquo; serial numbers (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/data-linkage/mortality-public.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/data-linkage/mortality-public.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using Stata 15.0. A two-sided \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. We adjusted the data using appropriate survey weights, strata, and primary sampling units in accordance with the complex sample design of the NHANES and oversampling of subgroups of the sample.\u003c/p\u003e \u003cp\u003eBaseline characteristics of participants were presented by sex-specific quartiles of HGS. Analysis of variance was used for continuous variables and the chi-square test was used for categorical variables, with correction for sample weights. The follow-up time of the study was calculated from the NHANES 2011\u0026ndash;2014 examination date until the last known date alive or censored, or 31 December 2019, whichever occurred first. Cox proportional hazards models was used to analyze the association of grip strength measurements which included HGS, HGS/BMI, MGS, and MGS/weight and low grip strength with all-cause mortality, indicators of low grip strength included low reference grip strength, lowest 20% grip strength, and low grip strength in sarcopenia. To achieve comparability of grip strength measures, we standardized both absolute and relative grip strength measurements to investigate their association with the risk of all-cause mortality. Considering the difference in grip strength values between men and women, we analyzed the data by gender.\u003c/p\u003e \u003cp\u003eIn Cox proportional hazards regression analyses, model 1 was adjusted for age and race, model 2 was further adjusted for education level, marital status, PIR, smoking status, alcohol consumption, regular exercise, model 3 was further adjusted for baseline chronic diseases (hypertension, hyperlipidemia, diabetes, CVD, and cancer).\u003c/p\u003e \u003cp\u003eTo assess the possible non-linear association of handgrip measurements with mortality risk, we performed restricted cubic spline regression, with Z-scores of handgrip strength measurements modelled as natural cubic splines with four knots (the 5th, 35th, 65th, and 95th percentiles). The receiver operating characteristic (ROC) curve was drawn, and the area under the curve (AUC) was calculated to compare the ability of different grip strength indexes in predicting the risk of all-cause mortality.\u003c/p\u003e \u003cp\u003eBased on gender stratification, we further conducted age stratification analysis (\u0026lt;\u0026thinsp;65 years, \u0026ge;\u0026thinsp;65 years). To examine the robustness of our findings, we did the following two sensitivity analyses: First, subjects who died in the first year after MEC follow-up were excluded to reduce the influence of reverse causation. Second, subjects who already had cancer or CVD at baseline were excluded since these diseases may affect grip strength.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe mean age of all participants was 47.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8 years, and 49.9% were men (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In general, with the decline of grip strength, participants were more likely to be older, being non-Hispanic Asian, and have lower level of education and income. They also tended to be former smokers, current drinkers, have less regular physical activity and lower values of BMI, and have higher prevalence of chronic diseases (hypertension, hyperlipidemia, diabetes, CVD, and cancer).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of participants by sex-specific quartiles of absolute grip strength\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9,583)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,390)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,382)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,409)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2,402)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47.4 (16.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.2 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.5 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49.7 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.6 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e66.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Asian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 9th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9-11th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college or AA degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege graduate or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e25.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (%) \u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLive with someone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLive alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome-to-poverty Ratio (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.07\u0026ndash;2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.16\u0026ndash;4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke status (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol status (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e65.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMET-h/w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.2 (91.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.8 (104.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.1 (86.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.9 (87.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e31.3 (69.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.0 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.5 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.8 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.2 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.1 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevalence of chronic diseases (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: BMI, body mass index; CVD, Cardiovascular Disease; MET, metabolic equivalent. Values are expressed as mean (SD) or percentage. Analysis of variance was used for continuous variables and the chi-square test was used for categorical variables, with correction for sample weights. \u003csup\u003e*\u003c/sup\u003e\"Live with someone\" includes married and living together, \"Live alone\" includes widowed, divorced, separated and unmarried.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOver a median of 6.75 years of follow-up, 805 deaths occurred. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, in men, when grip strength was used as a continuous variable, the fully adjusted HRs (95% CIs) for per 5 kg lower of HGS and MGS were 1.36 (1.26, 1.48) and 1.34 (1.24, 1.46); and the HRs (95% CIs) for one unit decrease of HGS/BMI and MGS/weight were 3.65 (2.32, 5.75) and 1.04 (1.02, 1.05), respectively. When we treated grip strength as a quartile variable, there was an increased mortality risk with the decline of grip strength (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e \u0026lt;0.05). Compared with the highest quartile (Q4), the lowest quartile (Q1) had about 2-fold higher hazard for all-cause mortality, irrespective of which grip strength measures was applied.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between different handgrip strength measurements and risk of all-cause mortality in men\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eContinuous\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHGS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54 (0.63, 3.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.98 (0.94, 4.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4.55 (2.44, 8.49)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.46 (1.36, 1.57)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29 (0.53, 3.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.59 (0.77, 3.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.10 (1.74, 5.51)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.37 (1.27, 1.48)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.27 (0.53, 3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.54 (0.76, 3.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.00 (1.72, 5.22)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.36 (1.26, 1.48)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHGS/BMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.20 (0.57, 2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.79 (1.04, 3.07)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.16 (1.85, 5.39)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4.51 (2.95, 6.90)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.25 (0.59, 2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.85 (1.09, 3.15)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.81 (1.64, 4.81)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.45 (2.14, 5.54)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29 (0.61, 2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.99 (1.19, 3.35)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.88 (1.66, 5.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.65 (2.32, 5.75)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMGS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.66 (0.72, 3.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.68 (0.82, 3.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4.66 (2.57, 8.45)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.44 (1.34, 1.55)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.47 (0.65, 3.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 (0.70, 2.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.26 (1.90, 5.58)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.35 (1.25, 1.46)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.47 (0.66, 3.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33 (0.68, 2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.16 (1.88, 5.29)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.34 (1.24, 1.46)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMGS/weight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60 (0.78, 3.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36 (0.75, 2.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.00 (1.62, 5.56)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.04 (1.02, 1.06)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.80 (0.82, 3.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.58 (0.83, 3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.87 (1.50, 5.47)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.03 (1.02, 1.05)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.89 (0.86, 4.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.72 (0.89, 3.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.09 (1.55, 6.15)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.04 (1.02, 1.05)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: HGS: hand grip strength; MGS: maximum value of dominant hand; MGS/weight: MGS/body weight *100; PYs: person-years. *Continuous was calculated as per 5kg decrease in HGS and MGS, and per one unit decrease in HGS/BMI and MGS/weight. Model 1: adjusted for age and race; Model 2: Model 1\u0026thinsp;+\u0026thinsp;adjusted for education level, marital status, income-to-poverty ratio, smoking status, alcohol drinking, regular exercise; Model 3: Model 2\u0026thinsp;+\u0026thinsp;adjusted for baseline chronic diseases (cancer, CVD, hypertension, hyperlipidemia, diabetes); Cox regression was corrected for sample weights. HR (95%CI) in bold indicates \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for women, the associations of continuous grip strength were similar to men, the HRs (95% CIs) for per 5 kg lower of HGS and MGS were 1.49 (1.30, 1.69) and 1.45 (1.27, 1.66); and the HRs (95% CIs) for one unit decrease of HGS/BMI and MGS/weight were 2.22 (1.28, 3.83) and 1.02 (1.00, 1.03). When we treated grip strength as a quartile variable, except for HGS/BMI, the lowest quartile (Q1) in grip strength measurements were associated with a higher hazard for all-cause mortality compared with the highest quartile (Q4). After standardization of grip strength, the highest risk of all-cause death per 1-SD decrease in grip strength was found in HGS (men; adjusted HR\u0026thinsp;=\u0026thinsp;1.81, 95% CI\u0026thinsp;=\u0026thinsp;1.55\u0026ndash;2.11, women; 1.62, 1.38\u0026ndash;1.90), followed by MGS (men; 1.79, 1.53\u0026ndash;2.09, women; 1.60, 1.36\u0026ndash;1.90) (Table S2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between different handgrip strength measurements and risk of all-cause mortality in women\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ4 (highest)\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1 (lowest)\u003c/p\u003e \u003cp\u003eHR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eContinuous\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHGS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.55 (0.86, 2.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43 (0.75, 2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.47 (1.81, 6.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.67 (1.45, 1.93)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.52 (0.83, 2.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.41 (0.72, 2.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.05 (1.59, 5.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.55 (1.37, 1.75)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.50 (0.84, 2.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38 (0.72, 2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.81 (1.49, 5.27)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.49 (1.30, 1.69)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHGS/BMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.46, 1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65 (0.37, 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.85 (1.00, 3.41)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4.44 (2.45, 8.07)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78 (0.43, 1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 (0.36, 1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48 (0.86, 2.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.94 (1.71, 5.03)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.46, 1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58 (0.36, 0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.32 (0.81, 2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.22 (1.28, 3.83)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMGS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.38 (0.63, 3.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13 (0.50, 2.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.92 (1.30, 6.54)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.63 (1.41, 1.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.40 (0.64, 3.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14 (0.50, 2.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.68 (1.22, 5.88)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.52 (1.34, 1.72)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34 (0.62, 2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12 (0.50, 2.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.44 (1.13, 5.27)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.45 (1.27, 1.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMGS/weight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.28 (0.69, 2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (0.56, 2.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.38 (1.25, 4.51)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.03 (1.02, 1.05)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19 (0.66, 2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.55, 1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.96 (1.10, 3.47)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.02 (1.01, 1.04)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19 (0.67, 2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98 (0.56, 1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.72 (1.01, 2.91)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.02 (1.00, 1.03)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: HGS: hand grip strength; MGS: maximum value of dominant hand; MGS/weight: MGS/body weight *100; PYs: person-years. *Continuous was calculated as per 5kg decrease in HGS and MGS, and per one unit decrease in HGS/BMI and MGS/weight. Model 1: adjusted for age and race; Model 2: Model 1\u0026thinsp;+\u0026thinsp;adjusted for education level, marital status, income-to-poverty ratio, smoking status, alcohol drinking, regular exercise; Model 3: Model 2\u0026thinsp;+\u0026thinsp;adjusted for baseline chronic diseases (cancer, CVD, hypertension, hyperlipidemia, diabetes); Cox regression was corrected for sample weights. HR (95%CI) in bold indicates \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor low grip strength, although different definitions were applied, the higher mortality risk was consistently found in the low grip strength group compared with the normal grip strength group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). We observed an interaction of low reference grip strength and sex on the risk of all-cause mortality (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003einteraction\u003c/em\u003e\u003c/sub\u003e =0.013), the HR (95% CI) was 1.91 (1.54, 2.35) in men, but lost significance in model 3 for women. Subgroup analyses by age showed no difference in association among those\u0026thinsp;\u0026lt;\u0026thinsp;65 years and \u0026ge;\u0026thinsp;65 years, no matter expressed in continuous grip strength or low grip strength (Table S3, Table S4, \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003einteraction\u003c/em\u003e\u003c/sub\u003e \u0026gt;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between low grip strength of different definitions and the risk of all-cause mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003einteraction\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal grip strength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow grip strength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNormal grip strength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow grip strength\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow reference grip strength\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.12 (1.70, 2.64)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.61 (1.22, 2.11)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.84 (1.49, 2.28)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.37 (1.08, 1.74)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.91 (1.54, 2.35)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.22 (0.99, 1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLowest 20% grip strength\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.70 (2.12, 3.44)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.03 (2.11, 4.34)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.24 (1.77, 2.82)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.67 (1.94, 3.66)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.20 (1.71, 2.83)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.52 (1.83, 3.46)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMen\u0026thinsp;\u0026le;\u0026thinsp;26kg, Women\u0026thinsp;\u0026le;\u0026thinsp;16kg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.661\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMortality rate (/1,000 PYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e101.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.94 (1.97, 4.39)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.37 (2.34, 4.86)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.10 (1.37, 3.23)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.58 (1.77, 3.77)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.06 (1.33, 3.19)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ereference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.29 (1.55, 3.38)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: PYs: person-years. Model 1: adjusted for age (except for low reference grip strength) and race; Model 2: Model 1\u0026thinsp;+\u0026thinsp;adjusted for education level, marital status, income-to-poverty ratio, smoking status, alcohol drinking, regular exercise; Model 3: Model 2\u0026thinsp;+\u0026thinsp;adjusted for baseline chronic diseases (cancer, CVD, hypertension, hyperlipidemia, diabetes); Cox regression was corrected for sample weights. HR (95%CI) in bold indicates \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the restricted cubic spline regression, we observed a non-linear inverse association of Z-scores of grip strength with mortality risk, which was similar across different hand strength measurements (Figure S2). By comparing the AUC of the four grip strength measurements, HGS (AUC\u0026thinsp;=\u0026thinsp;0.714) was the best predictor of all-cause mortality risk, followed by MGS (AUC\u0026thinsp;=\u0026thinsp;0.712) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In sensitivity analyses, when we excluded deaths during the first year of follow-up, or excluded participants with CVD or caner at baseline, the result remained almost unchanged (Table S5, Table S6).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main finding of this study was that decreased grip strength in adults was associated with an increased risk for all-cause mortality. Using four different measures of grip strength, we found similar non-linear inverse correlations. HGS (AUC\u0026thinsp;=\u0026thinsp;0.714) had the best ability to predict all-cause mortality, followed by MGS (AUC\u0026thinsp;=\u0026thinsp;0.712). Participants with low grip strength were at increased risk of mortality, and the HR was highest in the lowest 20% grip strength group (HR\u0026thinsp;=\u0026thinsp;2.20 for men, 2.52 for women). We found no significant interaction of age, sex, and grip strength, except for low reference grip strength and gender (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003einteraction\u003c/em\u003e\u003c/sub\u003e=0.013).\u003c/p\u003e \u003cp\u003eOur finding of inverse associations between grip strength and all-cause mortality were in agreement with previous studies. A meta-analysis conducted on 42 studies including 3,002,203 participants showed that grip strength was an independent predictor of all-cause mortality, the HRs (95% CIs) with per-5-kg decrease in grip strength was 1.16 (1.12, 1.20) for all-cause mortality\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. These results were comparable to our findings, where we found that 5-kg lower HGS in men was associated with an HR of 1.36 in men for all-cause mortality, and an HR of 1.49 in women. Cai, Y. et al.\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e similarly found that the HR (95% CI) for all-cause mortality per 5-kg reduction in grip strength was 1.11(1.06, 1.18) in men and 1.17(1.08, 1.28) in women.\u003c/p\u003e \u003cp\u003eIn our study, we found that after standardizing all grip strength indicators, the association of absolute grip strength indicators with the risk of all-cause mortality was stronger than that of relative grip strength indicators, with the highest being for HGS (HR\u0026thinsp;=\u0026thinsp;1.81 for men and HR\u0026thinsp;=\u0026thinsp;1.62 for women). Inconsistently, a study, also based on NHANES, found that compared with the sum of the maximum values of both hands (GS), GS/BMI had a stronger correlation with cardiovascular biomarkers as a relative grip strength indicator\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Wonjeong Jeong et al. \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e also found that HGS/BMI was more associated with risk of all-cause mortality compared with HGS, the associations persisted after adjustment for chronic diseases. Similarly, Yanan Gao et al. \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e also recommended HGS/BMI or HGS/body weight as the best choice for grip strength expression to predict the risk of CVD risk factors. However, by comparing AUC in our study, we recommend HGS or MGS as the optimal predictor of all-cause mortality risk. Meanwhile, Ho FKW et al.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e compared different expressions of grip strength in adults with an average age of 56 years (range 37\u0026ndash;73) based on UK Biobank and found no difference in the association between absolute and relative grip strength and all-cause mortality. They believed that the simplest method of handgrip strength measurement, i.e., the absolute unit (kg), was perfectly suitable for predicting health outcomes in clinical practice.\u003c/p\u003e \u003cp\u003eWe found participants with low grip strength carried higher mortality risk, irrespective of which definition was used, which was in line with previous studies \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. However, few studies have compared the effect of different measures of low grip strength in the same population. Our study showed that the HRs was highest when using the definition of \u0026ldquo;lowest 20% grip strength\u0026rdquo; (HR\u0026thinsp;=\u0026thinsp;2.20 for men, 2.52 for women), possibly because this definition could identify participants with the worst muscle strength, and better distinguish them from people with normal grip strength.\u003c/p\u003e \u003cp\u003eOverall, we did not find significant modifying effect of gender and age on the association between grip strength and all-cause mortality, except for the interaction between low reference grip strength and gender, where the effect of low grip strength was only found in men, which was consistent with the previous conclusion of Strand BH et al in Troms\u0026oslash; database\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. However, this was opposite to the results of a previous KORA-based study\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e, which found that the association between muscular strength and all-cause mortality tended to be stronger in women. Actually, most previous studies suggested no interaction of grip strength and gender, on the risk of death\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eExisting evidence stratified by age also suggested inconclusive results. A study based on UK Biobank demonstrated that the hazard ratio of grip strength with all-cause death was higher in the younger age group in both genders\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Similar results were also found in the China Health and Retirement Longitudinal Study (CHARLS) study in China, where the association between MGS and all-cause mortality was stronger in young men (HR\u0026thinsp;=\u0026thinsp;0.29, 95% CI: 0.18\u0026ndash;0.45) than in older men (HR\u0026thinsp;=\u0026thinsp;0.49, 95% CI:0.33\u0026ndash;0.73)\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Whereas Rachel et al. \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e found that the association between low grip strength and all-cause mortality was higher in people over 70 years old (HR\u0026thinsp;=\u0026thinsp;1.80, 95% CI: 1.48\u0026ndash;2.18) than those of under 60 years old (HR\u0026thinsp;=\u0026thinsp;1.43, 95% CI: 1.07\u0026ndash;1.91). Further research is needed to examine the interaction effect of age and sex.\u003c/p\u003e \u003cp\u003eOur study had several advantages. First, we used relatively comprehensive measures of grip strength, including absolute grip strength (HGS, MGS), relative grip strength (HGS/BMI, MGS/weight), and low grip strength, to examine and compare their associations with all-cause mortality. Meanwhile, by using the relative grip strength index, the influence of body shape factors (such as fat, weight, BMI) can be effectively excluded to some extent, so that more reliable conclusions can be obtained. Second, this study used a large representative sample from the American NHANES. The grip strength was standardized (Z score) to further study the correlation between grip strength and all-cause mortality. ROC curve was used to compare the area under the curve (AUC) to obtain the optimal index of grip strength to predict the risk of all-cause death. However, our study had some limitations. First, as the NHANES is a repeated cross-sectional study, it cannot provide data on changes in grip strength, so we could only examine the association of baseline grip strength with all-cause death. Nevertheless, previous studies have found that baseline grip strength measures are the best predictors of cardiovascular mortality\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. Second, as an outcome variable in handgrip strength studies, the composition of all-cause mortality tends to be more complex. For example, accidental death may not be intrinsically related to grip strength, so if accidental death accounted for a substantial proportion during the study, it is likely to affect the validity of the study results. Third, we only employed two widely-used relative grip strength indicators (HGS/BMI, MGS/weight), exploring other combinations such as MGS/BMI or HGS/weight may also be of great value in the future. Finally, although we have accounted for as many confounding factors as possible, residual confounding still exists.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe present study has shown that all four measures of grip strength level are significantly and inversely associated with all-cause mortality, and the simple absolute grip strength (HGS) is the best predictor of all-cause mortality. Our results show that low grip strength is associated with an increased risk of all-cause mortality, with the strongest association observe in the lowest 20% grip strength group. The above results remain significant in different age and gender. We recommend that the simplest measure of absolute grip strength (HGS, MGS) be used as the optimal indicator for predicting all-cause mortality. Keep an adequate level of handgrip strength may be beneficial to reduce the risk of mortality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eContributors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJF conceived and designed the study. JF and LC analyzed the data. LC drafted the manuscript. JF and LC helped the interpretation of the results. JF contributed to the critical revision of the manuscript for important intellectual content and approved the final version of the manuscript. All authors reviewed and approved the final manuscript. DZ is the guarantor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the staff at the National Center for Health Statistics at the CDC, who design, collect, administer the NHANES data and release the data available for public use. We are thankful to all study participants for their cooperation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Natural Science Foundation of Shandong Province (ZR2023QH188), China Postdoctoral Science Foundation (2023M731839), Qingdao Postdoctoral Innovation Project (QDBSH20230102012), Qingdao University Scientific Research Startup Fund (DC2200002531), Mount Taishan Scholar Youth Program. The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report, or the decision to submit the article for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData sharing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in this study. This data can be found here: https://wwwn.cdc.gov/nchs/nhanes/ (accessed on 14 February 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe NHANES study was approved by the Research Ethics Review Board of the National Center for Health Statistics, and all study participants provided written informed consent. This study was a secondary data analysis of publicly available federal data without personal identifiers, therefore, did not require Institutional Review Board review.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePorto JM, Nakaishi APM, Cangussu-Oliveira LM, Freire J\u0026uacute;nior RC, Spilla SB, Abreu DCC. Relationship between grip strength and global muscle strength in community-dwelling older people. Archives of gerontology and geriatrics. 2019;82:273-8.\u003c/li\u003e\n\u003cli\u003eBohannon RW. Muscle strength: clinical and prognostic value of hand-grip dynamometry. Current opinion in clinical nutrition and metabolic care. 2015;18(5):465-70.\u003c/li\u003e\n\u003cli\u003eBohannon RW. Grip Strength: An Indispensable Biomarker For Older Adults. Clinical interventions in aging. 2019;14:1681-91.\u003c/li\u003e\n\u003cli\u003eSchaap LA, Fox B, Henwood T, Bruy\u0026egrave;re O, Reginster JY, Beaudart C, et al. Grip strength measurement: Towards a standardized approach in sarcopen ia research and practice. European Geriatric Medicine. 2016;7(3):247-55.\u003c/li\u003e\n\u003cli\u003eLeong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A, Jr., Orlandini A, et al. Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet (London, England). 2015;386(9990):266-73.\u003c/li\u003e\n\u003cli\u003eYoo JI, Choi H, Ha YC. Mean Hand Grip Strength and Cut-off Value for Sarcopenia in Korean Adults Using KNHANES VI. Journal of Korean medical science. 2017;32(5):868-72.\u003c/li\u003e\n\u003cli\u003eLawman HG, Troiano RP, Perna FM, Wang CY, Fryar CD, Ogden CL. Associations of Relative Handgrip Strength and Cardiovascular Disease Biomarkers in U.S. Adults, 2011-2012. Am J Prev Med. 2016;50(6):677-83.\u003c/li\u003e\n\u003cli\u003eParra-Soto S, Pell JP, Celis-Morales C, Ho FK. Absolute and relative grip strength as predictors of cancer: prospective cohort study of 445 552 participants in UK Biobank. Journal of cachexia, sarcopenia and muscle. 2022;13(1):325-32.\u003c/li\u003e\n\u003cli\u003eGao Y, Huang H, Ni C, Feng Y, Yu J, Huang Y, et al. Comparison of Five Expressions of Handgrip Strength for Predicting Cardiovascular Disease Risk Factors in Chinese Middle-Aged Community Residents. Frontiers in public health. 2022;10:903036.\u003c/li\u003e\n\u003cli\u003eYan XJ, Zhang JS, Liu YF, Ma N, Luo DM, Song Y. [The application of the National Standards for Students\u0026apos; Physical Health (2014 revision) in SPSS]. Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]. 2020;54(6):708-12.\u003c/li\u003e\n\u003cli\u003eAlley DE, Shardell MD, Peters KW, McLean RR, Dam TT, Kenny AM, et al. Grip strength cutpoints for the identification of clinically relevant weakness. The journals of gerontology Series A, Biological sciences and medical sciences. 2014;69(5):559-66.\u003c/li\u003e\n\u003cli\u003eHo FKW, Celis-Morales CA, Petermann-Rocha F, Sillars A, Welsh P, Welsh C, et al. The association of grip strength with health outcomes does not differ if grip strength is used in absolute or relative terms: a prospective cohort study. Age and ageing. 2019;48(5):684-91.\u003c/li\u003e\n\u003cli\u003eXie KH, Han X, Zheng WJ, Zhuang SF. Low Grip Strength and Increased Mortality Hazard among Middle-Aged and Older Chinese Adults with Chronic Diseases. Biomedical and environmental sciences : BES. 2023;36(3):213-21.\u003c/li\u003e\n\u003cli\u003eNorman K, Stob\u0026auml;us N, Gonzalez MC, Schulzke JD, Pirlich M. Hand grip strength: outcome predictor and marker of nutritional status. Clinical nutrition (Edinburgh, Scotland). 2011;30(2):135-42.\u003c/li\u003e\n\u003cli\u003eKim Y, Wijndaele K, Lee DC, Sharp SJ, Wareham N, Brage S. Independent and joint associations of grip strength and adiposity with all-cause and cardiovascular disease mortality in 403,199 adults: the UK Biobank study. The American journal of clinical nutrition. 2017;106(3):773-82.\u003c/li\u003e\n\u003cli\u003eLiu W, Leong DP, Hu B, AhTse L, Rangarajan S, Wang Y, et al. The association of grip strength with cardiovascular diseases and all-cause mortality in people with hypertension: Findings from the Prospective Urban Rural Epidemiology China Study. Journal of sport and health science. 2021;10(6):629-36.\u003c/li\u003e\n\u003cli\u003eDodds RM, Syddall HE, Cooper R, Kuh D, Cooper C, Sayer AA. Global variation in grip strength: a systematic review and meta-analysis of normative data. Age and ageing. 2016;45(2):209-16.\u003c/li\u003e\n\u003cli\u003eWang YC, Bohannon RW, Li X, Sindhu B, Kapellusch J. Hand-Grip Strength: Normative Reference Values and Equations for Individuals 18 to 85 Years of Age Residing in the United States. The Journal of orthopaedic and sports physical therapy. 2018;48(9):685-93.\u003c/li\u003e\n\u003cli\u003eFried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. The journals of gerontology Series A, Biological sciences and medical sciences. 2001;56(3):M146-56.\u003c/li\u003e\n\u003cli\u003eChainani V, Shaharyar S, Dave K, Choksi V, Ravindranathan S, Hanno R, et al. Objective measures of the frailty syndrome (hand grip strength and gait speed) and cardiovascular mortality: A systematic review. International journal of cardiology. 2016;215:487-93.\u003c/li\u003e\n\u003cli\u003eStudenski SA, Peters KW, Alley DE, Cawthon PM, McLean RR, Harris TB, et al. The FNIH sarcopenia project: rationale, study description, conference recommendations, and final estimates. The journals of gerontology Series A, Biological sciences and medical sciences. 2014;69(5):547-58.\u003c/li\u003e\n\u003cli\u003eWu Y, Wang W, Liu T, Zhang D. Association of Grip Strength With Risk of All-Cause Mortality, Cardiovascular Diseases, and Cancer in Community-Dwelling Populations: A Meta-analysis of Prospective Cohort Studies. Journal of the American Medical Directors Association. 2017;18(6):551.e17-.e35.\u003c/li\u003e\n\u003cli\u003ePavasini R, Serenelli M, Celis-Morales CA, Gray SR, Izawa KP, Watanabe S, et al. Grip strength predicts cardiac adverse events in patients with cardiac disorders: an individual patient pooled meta-analysis. Heart (British Cardiac Society). 2019;105(11):834-41.\u003c/li\u003e\n\u003cli\u003eStrand BH, Cooper R, Bergland A, J\u0026oslash;rgensen L, Schirmer H, Skirbekk V, et al. The association of grip strength from midlife onwards with all-cause and cause-specific mortality over 17 years of follow-up in the Troms\u0026oslash; Study. Journal of epidemiology and community health. 2016;70(12):1214-21.\u003c/li\u003e\n\u003cli\u003eCelis-Morales CA, Welsh P, Lyall DM, Steell L, Petermann F, Anderson J, et al. Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: prospective cohort study of half a million UK Biobank participants. BMJ. 2018;361:k1651.\u003c/li\u003e\n\u003cli\u003eCooper R, Kuh D, Hardy R. Objectively measured physical capability levels and mortality: systematic review and meta-analysis. Bmj. 2010;341:c4467.\u003c/li\u003e\n\u003cli\u003eCai Y, Liu L, Wang J, Gao Y, Guo Z, Ping Z. Linear association between grip strength and all-cause mortality among the elderly: results from the SHARE study. Aging clinical and experimental research. 2021;33(4):933-41.\u003c/li\u003e\n\u003cli\u003eJ C, Rothwell MS, editors. National Health and Nutrition Examination Survey: Plan and Operations, 1999\u0026ndash;2010. Hyattsville , Maryland: U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES, Centers for Disease Control and Prevention, National Center for Health Statistics; August 2013.\u003c/li\u003e\n\u003cli\u003eJeong W, Moon JY, Kim JH. Association of absolute and relative hand grip strength with all-cause mortality among middle-aged and old-aged people. BMC geriatrics. 2023;23(1):321.\u003c/li\u003e\n\u003cli\u003eMickute M, Zaccardi F, Razieh C, Sargeant J, Smith AC, Wilkinson TJ, et al. Individual frailty phenotype components and mortality in adults with type 2 diabetes: A UK Biobank study. Diabetes research and clinical practice. 2023;195:110155.\u003c/li\u003e\n\u003cli\u003eArvandi M, Strasser B, Meisinger C, Volaklis K, Gothe RM, Siebert U, et al. Gender differences in the association between grip strength and mortality in older adults: results from the KORA-age study. BMC geriatrics. 2016;16(1):201.\u003c/li\u003e\n\u003cli\u003eWang Y, Liu Y, Hu J, Guan H, Wang Y, Liu M, et al. Association of handgrip strength with all-cause mortality: a nationally longitudinal cohort study in China. Journal of science and medicine in sport. 2022;25(11):878-83.\u003c/li\u003e\n\u003cli\u003ePrasitsiriphon O, Pothisiri W. Associations of Grip Strength and Change in Grip Strength With All-Cause and Cardiovascular Mortality in a European Older Population. Clinical Medicine Insights Cardiology. 2018;12:1179546818771894.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Grip strength, All-cause mortality, Optimal measurement index, Interactions","lastPublishedDoi":"10.21203/rs.3.rs-4733967/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4733967/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLittle is known about the optimal measure of handgrip strength for predicting all-cause mortality and whether this association is modified by age or sex.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe used data from the 2011\u0026ndash;2014 National Health and Nutrition Examination Survey (NHANES), 9,583 adults aged\u0026thinsp;\u0026ge;\u0026thinsp;20 years were included. Equal-length grip strength was measured using a digital handheld Takei dynamometer. We defined four measurements of grip strength, i.e., the average of the maximum of both hands (HGS), the maximum of dominant hand (MGS), HGS/BMI, and MGS/weight, and three indicators of low grip strength, namely, low reference grip strength, lowest 20% grip strength, and low grip strength in sarcopenia. Information on deaths were obtained through linkage to National Death Index (NDI). Cox regression was used to assess the association of grip strength with mortality risk.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHGS, MGS, HGS/BMI, and MGS/weight were all inversely associated with all-cause mortality, with HGS (AUC\u0026thinsp;=\u0026thinsp;0.714) being the optimal predictor of mortality, followed by MGS (AUC\u0026thinsp;=\u0026thinsp;0.712). Participants with low grip strength showed increased risk of mortality regardless of which indicator was used, and the highest effect size was seen for lowest 20% grip strength group (HR\u0026thinsp;=\u0026thinsp;2.20 for men, 2.52 for women). The above-mentioned correlations were consistently found in people of different age and sex.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study suggests the simplest measure of absolute grip strength (HGS, MGS) was the optimal index for predicting all-cause mortality. Keep an adequate level of handgrip strength may be beneficial to reduce the risk of mortality.\u003c/p\u003e","manuscriptTitle":"Comparison of grip strength measurements for predicting all-cause mortality among adult aged 20+ years: NHANES 2011-2014","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-11 12:27:03","doi":"10.21203/rs.3.rs-4733967/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-16T06:10:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-11T18:43:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12093086619202650762684935218617711296","date":"2024-10-10T20:53:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-06T19:48:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"63816937020147956384355332688306947338","date":"2024-08-01T21:49:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-01T02:06:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-01T01:54:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-15T14:57:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-13T10:50:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-07-13T07:13:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"df9c9982-df31-4e5b-b1e2-c8b42393f045","owner":[],"postedDate":"August 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T16:01:39+00:00","versionOfRecord":{"articleIdentity":"rs-4733967","link":"https://doi.org/10.1038/s41598-024-80487-y","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-11-25 15:57:32","publishedOnDateReadable":"November 25th, 2024"},"versionCreatedAt":"2024-08-11 12:27:03","video":"","vorDoi":"10.1038/s41598-024-80487-y","vorDoiUrl":"https://doi.org/10.1038/s41598-024-80487-y","workflowStages":[]},"version":"v1","identity":"rs-4733967","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4733967","identity":"rs-4733967","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}