Cardiovascular disease (CVD) such as heart attack or stroke is the leading cause of death, particularly in most developed countries (1). Therefore, continuous efforts are needed to reduce CVD risk. The health benefits of physical activity (PA), primarily aerobic exercise (AE), have been well documented from the perspective of CVD and premature mortality (2–4). However, most studies on resistance exercise (RE) have focused on bone health, physical function, and quality of life in older adults, or metabolic health outcomes such as type 2 diabetes (5–8). There is still limited research directly examining the association of RE with the risk of CVD and mortality, and studies have reported inconsistent results (9–11). Several studies have suggested favorable effects of muscular strength, as a proxy indicator of RE, on cardiovascular health and mortality (12–16). However, these results cannot directly inform recommendations on practical exercise. Thus, further evidence is warranted to reveal the association of RE and cardiovascular health and mortality independent of AE, as well as to inform recommendations on RE.
Obesity commonly classified using body mass index (BMI) is among the mediators in the mechanisms linking PA, focusing on AE, to cardiovascular health (17). Some individuals even including medical professionals believe that the cardiovascular benefits of exercise may be mostly from weight loss. Furthermore, to our knowledge, there is very limited study investigating the mechanism underlying the association of RE, independent of AE, with cardiovascular health. Investigating the potential mediation effect of BMI on the association between RE and CVD adjusting for other CVD risk factors provides us with important data on RE related CVD preventive strategies.
Our study aimed to investigate the associations of RE, independent of AE, with the risk of total CVD events (morbidity and mortality combined), CVD morbidity, and all-cause mortality in a large prospective cohort of adult men and women. On the basis of the hypothesis of the pairwise causal relationship of RE and BMI with CVD risk, we further examined the mediation effect of BMI on the associations of RE with total CVD events, CVD morbidity, and all-cause mortality through a joint modeling approach.
The Aerobics Center Longitudinal Study is a cohort study of individuals who received periodic preventive medical examinations at the Cooper Clinic in Dallas, Texas. The participants were volunteers sent by their employers, physicians, or were self-referred. They came to the Cooper Clinic periodically for preventive health examinations and for counseling on lifestyle habits, including exercise, nutrition, stress management, etc. The participants are primarily non-Hispanic white (>95%), well educated (80% college graduates), and from middle to upper socioeconomic strata (18). In the present study, we included participants who received at least two clinical examinations between 1987 and 2006. Among 13,722 individuals, 1131 participants were excluded because of reported myocardial infarction, stroke, or cancer at baseline. Our final sample included 12,591 participants (21% women) 18 to 89 yr of age (mean age, 47 yr) at baseline. The study was annually reviewed and approved by the Cooper Institute institutional review board. Written informed consents were obtained from all participants for baseline and follow-up examinations.
All participants received comprehensive medical examinations at baseline and follow-up visits after an overnight fast of at least 12 h. BMI was calculated as weight in kilograms divided by height in meters squared. Resting blood pressure was measured according to standard procedures with a mercury sphygmomanometer. Serum samples were analyzed for glucose and total cholesterol using standardized bioassays. The assessment of hypertension, diabetes, and hypercholesterolemia was based on a history of physician diagnosis or measured phenotypes that met clinical thresholds for each condition. Age, sex, smoking status, alcohol consumption, parental history of CVD, and PA were assessed by a self-reported medical history questionnaire. Participants were classified as nonsmokers or current smokers. Heavy alcohol drinker was defined as >14 alcohol drinks per week for men and more than seven for women (19). In the medical questionnaire, leisure-time aerobic and RE during the past 3 months were assessed as part of the medical examination. AE was categorized as meeting the recommended guidelines (≥500 MET·min·wk−1, which was equivalent to 150 min of moderate or 75 min of vigorous weekly AE) or not, according to the U.S. Department of Health and Human Services PA Guidelines (2).
Assessment of RE history
RE using either free weights or weight training machines was evaluated by weekly frequency (times per week) and average exercise time (min) for each session. The total weekly amount of RE was calculated by multiplying weekly frequency with the average minutes per session. Participants were classified into five categories by RE frequency of zero, one, two, three, and four or greater times per week and four categories by a total RE amount of 0, 1–59, 60–119, and ≥120 min·wk−1 for the main analyses. PA questionnaire including both resistance and aerobic exercise is available in an earlier study (20).
Assessment of end points
In this study, CVD morbidity was defined as an incidence of myocardial infarction or stroke and was assessed at baseline and each follow-up examination. Mortality through December 31, 2003, was ascertained by the National Death Index. Death from CVD was identified by the International Classification of Diseases, Ninth Revision codes 390–449.9 and Tenth Revision codes I00–I78. The primary outcomes were total CVD events (development of CVD morbidity or death from CVD), development of CVD morbidity, and all-cause mortality. In the corresponding longitudinal analysis, we included all the records from baseline to the end points for the participants with event, or from baseline to the last examination through 2006 for the participants who survived (did not develop the event). In Cox regression models, the follow-up years (survival time) of participants with event were calculated from baseline to the end points. For the ones who survived, follow-up years were counted from baseline to the last examination for CVD morbidity, and for CVD and all-cause mortality, from baseline to the end year of 2003 (since mortality data is available until 2003) or the last examination through 2006, which came later.
We described baseline characteristics of participants by their weekly frequency and amount of RE.
A series of Cox proportional hazard models were fitted to assess the effect of weekly RE frequency (times per week) and total amount (min·wk−1) on total CVD events, CVD morbidity, and all-cause mortality. Like all human activities, weekly RE and AE levels (represented by frequency or total amount) naturally vary over time. Such variations, broadly termed as measurement errors in the statistics literature (21), are known to cause estimation biases and reduced statistical power. Because the baseline RE and AE levels were subject to such measurement error, we instead used the long-term RE and AE levels, measured by average frequency or average minutes per week during the follow-ups (e.g., average 3.7 times of RE measurement during 5.3 yr of follow-up in total CVD events), as covariates in the Cox models. Using the average of repeated measurements as the covariate is a simple practice of regression calibration (21) and was used in a similar study (22). We classified participants according to average RE frequency and total amount in Cox models; therefore, the number of participants in corresponding categories for CVD outcomes and all-cause mortality was slightly different. We fitted the following two sets of Cox models to examine the associations of RE frequency and total amount with CVD events and all-cause mortality adjusting for different confounders: in model 1, the results were adjusted for baseline examination year, age, and sex; in model 2, we further adjusted for baseline smoking status, heavy alcohol drinking, BMI, parental history of CVD, meeting the AE guidelines, hypertension, diabetes, and hypercholesterolemia. To assess the effect of RE independent of AE, we further conducted stratified analysis by meeting AE guidelines or not. Interactions between AE and RE categories were also tested by comparing the Cox models containing both main effects and interaction terms with models containing main effects only using likelihood ratio test.
To investigate the association between RE and BMI, we applied a linear mixed effect model, which was a standard model in longitudinal data analysis taking into account the follow-up observations. We then examined the mediation relationship among RE, BMI, and the outcomes following the standard procedures of mediation analysis proposed by Baron and Kenny (23). With total CVD events as an example, we presented causal relationships between RE and BMI, BMI and the risk of total CVD events, and RE and the risk of total CVD events (Fig. 1). In the first step of mediation analysis, we ran a series of Cox models to examine the association of RE with total CVD events, with adjustment for all potential confounders excluding BMI. In the second step, we assessed the longitudinal association between RE and BMI with a linear mixed effect model. To model the variation in baseline BMI levels and temporal trend, we included subject-specific intercepts and slopes as random effects, while controlling the fixed effects of examination year, baseline age, sex, current smoking, heavy alcohol drinking, and meeting the AE guidelines. In the final step, we applied a joint model of longitudinal and survival data (24,25) in which the longitudinal observation of BMI was modeled through a linear mixed effect model, the risk of total CVD events was fitted by a Cox proportional hazard model, and the association of these two models lied in that BMI was simultaneously a covariate for the Cox model. Because joint modeling is a relatively new approach in epidemiological research, we provide here more detailed explanations and methods to help readers, including future investigators, understand it clearly. The hazard function of total CVD events is modeled as follows:
where Mi(t) denotes the true value of BMI of the i-th subject at time t; Xi represents confounding variables, including baseline examination year, age, sex, current smoking, heavy alcohol drinking, parental history of CVD, meeting the AE guidelines, hypertension, diabetes, and hypercholesterolemia; and h0(t) is a baseline risk function. Parameter α indicates the effect of the underlying true BMI on the risk of total CVD events, whereas γ1 and γ2 quantify the direct effect of RE on total CVD events. The longitudinal model for observations of BMI is as follows:
where the error item
, and the random intercept b0i and random slope b1i are assumed to follow a joint normal distribution with mean 0, and Zi represents covariates, including examination year, baseline age, sex, current smoking, heavy alcohol drinking, and meeting the AE guidelines. Because β2 represents the effect of RE on BMI, αβ2 represents an indirect effect of RE on the risk of total CVD events through the Cox model. We fitted this model with a Bayesian approach. The baseline hazard function in Cox model was estimated by penalized spline, and independent univariate diffuse normal priors were assumed for fixed effect parameters in the longitudinal model, and parameters in the Cox model (26). Mediation analyses were also conducted for CVD morbidity and all-cause mortality in the same way.
On the basis of no significant interactions by sex on the associations between the RE and the outcomes using interaction terms in the regression and by comparing risk estimates in the sex-stratified analyses, pooled analyses including both men and women were performed. Also, the proportional hazard assumptions were confirmed by Schoenfeld tests (27). All statistical analyses were conducted using R version 3.3.2. R package “JMbayes” was applied for joint modeling analysis, and two-sided P values <0.05 were deemed significant.
Among 12,591 participants, 205 total CVD events, 127 CVD morbidity (nonfatal CVD events), and 276 all-cause deaths occurred during an average follow-up of 5.4, 5.3 and 10.5 yr. Table 1 shows baseline characteristics of participants according to their frequency of RE (see Table, Supplemental Digital Content 1, Baseline characteristics by weekly amount of resistance exercise, http://links.lww.com/MSS/B424). At baseline, 3438 individuals (27%) engaged in some RE in this population. Compared with nonparticipants of RE, the participants of RE tend to be male, younger, nonsmokers, more aerobically active, and with lower BMI. They also had a lower rate of hypertension, diabetes, hypercholesterolemia, and history of parental CVD.
Compared with no RE, hazard ratios (HR) (95% confidence intervals [CI]) of total CVD events across weekly RE frequencies of one, two, three, and four or greater times were 0.26 (0.16–0.42), 0.41 (0.27–0.63), 0.52 (0.31–0.86), and 1.17 (0.67–2.04), respectively, after adjusting for examination year, age, and sex in model 1 (Table 2). The HR (95% CI) values of total CVD events across weekly total RE amount of 1–59, 60–119, and ≥120 min were 0.33 (0.23–0.47), 0.57 (0.36–0.91), and 0.81 (0.46–1.44), respectively, in the same model 1. These associations were slightly attenuated but mostly remained significant after additional adjustment for potential confounders, including meeting the AE guidelines and health conditions in the full model 2. When assessed as a continuous variable, weekly RE frequency had a U-shaped association with total CVD events (P value for quadratic trend <0.001), which reached the lowest HR (95% CI) of 0.51 (0.35–0.68) at about two times per week (Fig. 2A). We observed similar trend for the total amount of weekly RE, with the lowest HR at 1.5 h·wk−1 (Fig. 2B) although not significant. For CVD morbidity, we observed reduced risk of adverse events for RE frequency of one, two times per week and total amount of 1–59 min·wk−1 compared with no RE, after adjusting for all potential confounders. For all-cause mortality, decreased risk was observed for RE frequency of one time per week and total amount of 1–59 min·wk−1. In the dose–response analysis, the association of RE frequency with both CVD morbidity and all-cause mortality showed a U-shaped curve, with the lowest risk achieved at RE frequency of two times per week (Fig. 2C and E). However, quadratic trends for the associations of total RE amount with CVD morbidity and all-cause mortality were not significant (P values were 0.21 and 0.75, respectively). When we used the baseline values of RE frequency and amount in further sensitivity analyses, we did not observe significant results after adjusting for all potential confounders (data not shown). Therefore, it is possible that the risks of CVD and all-cause mortality were associated with long-term RE, rather than one time baseline value of RE, which has significant measurement errors because people in general overreport their PA. When we excluded those early cases of CVD events and all-cause mortality within the first 2 yr of follow-up to reduce potential subclinical conditions on the associations of RE with outcomes and minimize possible reverse causation, we found similar results (data not shown).
To assess the effects of RE on the risks of CVD and all-cause mortality independent of AE, stratified analyses were conducted by meeting the recommended AE guidelines or not (see Table, Supplemental Digital Content 2, Hazard ratio of total CVD events, CVD morbidity, and all-cause mortality by resistance exercise for participants meeting and not meeting recommended aerobic exercise, http://links.lww.com/MSS/B425). Compared with no RE, RE frequency of one time per week and the total amount of 1–59 min·wk−1 were associated with 75% (HR = 0.25, 95% CI = 0.14–0.46) and 60% (HR = 0.40, 95% CI = 0.21–0.52) lower risk of total CVD events, respectively, among the ones meeting AE guidelines, and 65% (HR = 0.35, 95% CI = 0.16–0.77) and 59% (HR = 0.41, 95% CI = 0.23–0.74) lower risk of total CVD events, respectively, among those not meeting AE guidelines. We also observed similar results for CVD morbidity with significantly reduced risks in one time per week of RE frequency and the total amount of 1–59 min·wk−1 of RE regardless of meeting AE guidelines. Compared with no RE, engaging in RE of one, two, or three times per week and 1–59 min·wk−1 was associated with decreased risk of all-cause mortality among participants meeting recommended AE. However, we did not observe significant all-cause mortality risk reduction with doing RE in the group of not meeting AE guidelines. These stratified analyses suggest that one could get CVD benefits from RE whether they meet the AE guidelines or not. However, all-cause mortality benefits from RE are only obtained when they meet the recommended AE (P values for the interaction between RE and AE for all-cause mortality were 0.06 and 0.04 for RE frequency and amount, respectively).
Before testing the mediation effect of BMI between RE and CVD, we investigated the longitudinal association of RE with BMI in additional analyses. When taken as continuous variable, weekly frequency and total amount of RE were significantly associated with BMI after adjusting for all potential confounders including AE (P value <0.001). Participants who did any RE would have a 0.13 kg·m−2 (SE = 0.017 kg·m−2) lower level of BMI compared with the ones with no RE. We then examined the mediation associations among RE, BMI, and total CVD events, CVD morbidity, and all-cause mortality by a joint modeling approach (Table 3). For the risk of total CVD events, in the longitudinal model, weekly frequency of RE was inversely associated with BMI (coefficient = −0.04, 95% CI = −0.05 to −0.03 in each RE frequency); in the Cox model, higher BMI was associated with a higher risk of total CVD events (HR = 1.06, 95% CI = 1.02–1.10 in each BMI unit), and RE frequency had a U-shaped association with the risk of total CVD events (P value for quadratic trend <0.001 between each RE frequency and total CVD events). On the basis of this joint modeling result, we found that RE frequency was associated with the reduced risk of total CVD events in two ways: RE had a U-shaped association with the risk of total CVD events. On the other hand, RE also lowered the risk of total CVD events through decreasing BMI, which is depicted in Figure 1. However, the mediation effects of BMI were relatively weaker on the associations of RE frequency with CVD morbidity (HR = 1.04, 95% CI = 0.99–1.09) and all-cause mortality (HR = 1.03, 95% CI = 0.996–1.07). For the total amount of RE (weekly hours), we did not observe significant associations between weekly hours of RE and three outcomes in Cox model part. The inverse association between RE hours and BMI in the longitudinal model, combined with the significant effect of BMI on risk of total CVD event and all-cause mortality in Cox model, implies that RE hours lower the risk of total CVD event and all-cause mortality indirectly through BMI.
In this study, we found that RE, especially low-to-moderate frequency (one to three times per week) or even <1 h·wk−1, was associated with lower risks of total CVD events, independent of AE, compared with no RE, in a large cohort of men and women (mean age = 46.5 yr, range = 18–96 yr). In addition, higher RE frequency of at least four times per week and amount of ≥120 min·wk−1 did not show significant cardiovascular benefits. These results are consistent with the findings of the U-shaped associations between RE and CVD events from the dose–response analyses using the continuous variables of weekly RE frequency and amount (Fig. 2A and B). For the associations of RE with CVD morbidity and all-cause mortality, the results of the dose–response analyses were similar although less strong. Previous studies have shown mixed results regarding the association between RE and CVD risk. In the Women’s Health Study, Kamada et al. (22) also found that strength training for 1–59 min·wk−1 was associated with lower risk of CVD mortality (including death from myocardial infarction, stroke, angioplasty, and coronary artery bypass grafting), compared with no strength training, for a cohort of middle-age and older women. They also observed significant quadratic associations between the amount of weekly RE with CVD mortality and the all-cause mortality. For the same study, another research showed that strength training for 60–120 min·wk−1 was associated with significant risk reduction of CVD events, and no further significant benefits were observed for strength training of >120 min·wk−1 (9). Although not tested statistically, the results implied the quadratic association as similar with the current findings. In this study, they also observed a 17% risk reduction for CVD events among women engaging in strength training, compared with the ones who reported no strength training. In our study, the corresponding reduction of risk was 55% (HR = 0.45, 95% CI = 0.33–0.61). The possible explanations of the higher total CVD risk reduction in our study would be related to the facts that our study includes both men and women who are also younger (mean age = 46.5 yr, range = 18–96 yr) than the participants in the Women’s Health Study (mean age = 62.6 yr, range = 47–98 yr). It is noteworthy that results in the last research were not adjusted for CVD risk factors, including hypertension, diabetes, and hypercholesterolemia. In a cohort of middle-age and older men from the Health Professionals’ Follow-Up Study, Tanasescu et al. (10) found that weight training for at least 30 min·wk−1 was associated with a 23% risk reduction of coronary heart disease compared with no weight training after adjusting for potential confounders excluding baseline diabetes, high cholesterol levels, and hypertension. However, in another report from the same study with higher amounts of weight training categories, they found a U-shaped association between weight training and total CVD events (fatal and nonfatal myocardial infarction and stroke) with significant benefits below 120 min·wk−1, but no further benefits in ≥120 min·wk−1 of weight training (11).
There has been compelling evidence that RE prevents decline in skeletal muscle mass (28), and long-term participation in RE increases energy expenditure (29,30) and relieves anxiety, depression, and insomnia in clinical depression (31). It was also shown that RE had beneficial effects on cardiovascular risk factors, including obesity, diabetes, hypertension, hypercholesterolemia, and decreased physical function (5–8,32–36). We observed a significant U-shaped association between RE and CVD risk after adjusting for BMI, diabetes mellitus, hypertension, and hypercholesterolemia. Possible explanations for the CVD benefits from low-to-moderate RE might include improved physical function, increased energy expenditure, and emotional factors as mentioned above. Although there is no clear understanding why there is no further cardiovascular benefits in the higher amounts of RE, a meta-analysis suggested that high-intensity RE may increase arterial stiffness leading to subsequent CVD events (37). A significant pressure load is imposed on the heart during RE, and heavy RE may lead to a mild form of cardiac hypertrophy (38). In addition, a marked rise in blood pressure is secondary to RE; thus, a high level of RE may have adverse effect on those with uncontrolled hypertension (6,39). Another possible explanation of no further cardiovascular benefits in the higher amounts of RE would be that the room for benefits could be much smaller for those participants in the higher amounts of RE (four or more times per week) in which 85% of them met the AE guidelines compared with those doing one time per week of RE in which 72% of them met the AE guidelines. However, further investigations are clearly needed on this controversial issue of the dose–response relationship between RE and CVD risk.
We also confirmed that BMI was a mediator in the relationship of RE with total CVD events. Several studies in the literature took BMI into account as a potential mediator in the relationship of PA and CVD risk. Erez et al. (40) indicated that BMI was among the CVD risk factors affecting the association of cardiorespiratory fitness and CVD morbidity. The Women’s Health Study reported that BMI contributed 10% of the observed inverse association between PA and risk of CVD events (17). The previous research mostly focused on associations between baseline cardiorespiratory fitness (baseline PA), baseline observations of CVD risk factors, and subsequent CVD outcomes (17,20,40). Mora et al. (17) showed no significant association existed between baseline PA and risk of CVD after adjusting for baseline levels of known risk factors. However, Kamada et al. (22) revealed a quadratic association between cumulative-averaged amount of strength training and mortality of CVD after adjusting for baseline CVD risk factors. In the current study, we considered the associations between long-term RE, longitudinal observation of BMI, and risk of CVD events in mediation analysis, and the result showed that weekly RE frequency had a U-shaped relationship with risk of CVD events (lowest risk attained at two times per week, not shown) after adjusting for AE, longitudinal observation of BMI, and other potential confounders. The result implies that one would get CVD benefits from RE regardless of the long-term levels of BMI. On the other hand, the result seems more convincible, including the baseline as well as the dynamic information of variables into mediation analysis.
Strengths of this study include the large sample size across a wide age range, extensive CVD morbidity and mortality follow-up, and repeated measures of exposures. In addition, we proposed the application of a joint modeling approach in mediation analysis to more rigorously investigate the effect of BMI on the association between the RE and the risks of CVD as well as all-cause mortality.
There are several limitations in this study. We used self-reported AE and RE in the current study, and people tend to overreport their leisure-time exercise, especially RE possibly more in men (e.g., a competitive, bragging culture in weight lifting). Therefore, this overestimation of self-reported RE may have induced possible underestimation of the true health effects of RE on BMI, CVD, and mortality outcomes. For example, the possible explanation of the weaker associations between the total amount of RE (total weekly hours) and all three outcomes may be related to the additive overreporting of RE because total weekly hours of RE were calculated by multiplying self-reported weekly frequency of RE with self-reported average exercise time (min) per session. However, to our knowledge, this is the first comprehensive study investigating the independent associations among RE, BMI, and CVD morbidity and mortality in both men and women in a large cohort study. Furthermore, the intensities of AE and RE were not evaluated in this study. Therefore, more studies on the effects of different intensities of RE on cardiovascular health are clearly warranted. In addition, we assumed causal associations for this observational study. However, it is possible that healthier individuals were more likely to participate in RE who are less likely to develop CVD and die prematurely, which refers to a possible reverse causality. Therefore, further studies with objective measurement of RE and a large randomized clinical trials of RE training are clearly warranted to examine the causal effects of RE on the risk of developing CVD and mortality as well as to confirm the U-shaped dose–response association between RE and CVD risk.
This study suggests that low-to-moderate frequency and amount of RE are associated with reduced risk of nonfatal CVD events, total CVD events, and all-cause mortality independent of AE, and high frequency and amount of RE did not show significant cardiovascular benefits. A mediation association exists among RE, BMI, and the risks of total CVD events, showing that RE has a direct U-shaped association with the risk of total CVD events, and RE also decreases the risk of CVD events indirectly by lowering BMI. These results have potential public health applications, especially for the prevention of CVD, as RE is needed in addition to AE to maximize CVD prevention.
The authors thank the Cooper Clinic physicians and technicians for collecting the data and staff at the Cooper Institute for data entry and data management.
This study was supported by the National Institutes of Health (grant nos. AG06945, HL62508, DK088195, and HL133069). Steven N. Blair has received unrestricted research grants from the Coca-Cola Company, but the grants were not used to support this manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
The authors report no conflicts of interest. The results of the study are presented clearly, honestly, without fabrication, falsification, or inappropriate data manipulation and do not constitute endorsement by the American College of Sports Medicine.
1. Mendis S, Puska P, Norrving B. Global Atlas on Cardiovascular Disease Prevention and Control
. World Health Organization; 2011.
2. US Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans
; 2008. Available at: http://health.gov/PAGuidelines
. Accessed December 1, 2017.
3. Lee DC, Pate RR, Lavie CJ, Sui X, Church TS, Blair SN. Leisure-time running reduces all-cause and cardiovascular mortality
risk. J Am Coll Cardiol
4. Lavie CJ, Arena R, Swift DL, et al. Exercise and the cardiovascular system: clinical science and cardiovascular outcomes. Circ Res
5. Williams MA, Haskell WL, Ades PA, et al. Resistance exercise
in individuals with and without cardiovascular disease
: 2007 update. Circulation
6. Braith RW, Stewart KJ. Resistance exercise
7. Grøntved A, Pan A, Mekary RA, et al. Muscle-strengthening and conditioning activities and risk of type 2 diabetes: a prospective study in two cohorts of US women. PLoS Med
8. Church TS, Blair SN, Cocreham S, et al. Effects of aerobic and resistance training on hemoglobin A1c levels in patients with type 2 diabetes: a randomized controlled trial. JAMA
9. Shiroma EJ, Cook NR, Manson JE, et al. Strength training and the risk of type 2 diabetes and cardiovascular disease
. Med Sci Sports Exerc
10. Tanasescu M, Leitzmann MF, Rimm EB, et al. Exercise type and intensity in relation to coronary heart disease in men. JAMA
11. Chomistek AK, Cook NR, Flint AJ, et al. Vigorous-intensity leisure-time physical activity and risk of major chronic disease in men. Med Sci Sports Exerc
12. Lawman HG, Troiano RP, Perna FM, et al. Associations of relative handgrip strength and cardiovascular disease
biomarkers in US adults, 2011–2012. Am J Prev Med
13. Ruiz JR, Sui X, Lobelo F, et al. Association between muscular strength and mortality
in men: prospective cohort study. BMJ
14. Leong DP, Teo KK, Rangarajan S, et al. Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet
15. Gale CR, Martyn CN, Cooper C, et al. Grip strength, body composition, and mortality
. Int J Epidemiol
16. Artero EG, Lee D, Lavie CJ, et al. Effects of muscular strength on cardiovascular risk factors and prognosis. J Cardiopulm Rehabil Prev
17. Mora S, Cook N, Buring JE, Ridker PM, Lee IM. Physical activity and reduced risk of cardiovascular events: potential mediating mechanisms. Circulation
18. Blair SN, Kannel WB, Kohl HW, et al. Surrogate measures of physical activity and physical fitness: evidence for sedentary traits of resting tachycardia, obesity, and low vital capacity. Am J Epidemiol
19. National Institute on Alcohol Abuse and Alcoholism. Alcohol Use and Alcohol Use Disorders in the United States: Main Findings from the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC)
. NIH Publication No. 05-5737; 2006.
20. Pereira MA, FitzerGerald SJ, Gregg EW, et al. A collection of Physical Activity Questionnaires for health-related research. Med Sci Sports Exerc
. 1997;29(6 Suppl):S1–205.
21. Carroll RJ, Ruppert D, Stefanski LA, et al. Measurement Error in Nonlinear Models: A Modern Perspective
. CRC Press; 2006. 71 pp.
22. Kamada M, Shiroma EJ, Buring JE, et al. Strength training and all-cause, cardiovascular disease
, and cancer mortality
in older women: a cohort study. J Am Heart Assoc
23. Baron RM, Kenny DA. The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol
24. Rizopoulos D. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R
. CRC Press; 2012. pp. 51–6.
25. Rizopoulos D. Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data. Biometrics
26. Rizopoulos D. The R package JMbayes for fitting joint models for longitudinal and time-to-event data using MCMC. J Stat Softw
27. Schoenfeld D. Partial residuals for the proportional hazards regression model. Biometrika
28. American College of Sports Medicine position stand: the recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscular fitness, and flexibility in healthy adults. Med Sci Sports Exerc
29. Nelson ME, Fiatarone MA, Morganti CM, Trice I, Greenberg RA, Evans WJ. Effects of high-intensity strength training on multiple risk factors for osteoporotic fractures: a randomized controlled trial. JAMA
30. Vincent KR, Braith RW, Feldman RA, Kallas HE, Lowenthal DT. Improved cardiorespiratory endurance following 6 months of resistance exercise
in elderly men and women. Arch Intern Med
31. Singh NA, Clements KM, Fiatarone MA. A randomized controlled trial of progressive resistance training in depressed elders. J Gerontol A Biol Sci Med Sci
32. Cornelissen VA, Fagard RH, Coeckelberghs E, et al. Impact of resistance training on blood pressure and other cardiovascular risk factors. Hypertension
. 2011; HYPERTENSIONAHA: 111.177071.
33. Strasser B, Siebert U, Schobersberger W. Resistance training in the treatment of the metabolic syndrome. Sports Med
34. Bakker EA, Lee D, Sui X, et al. Association of resistance exercise
, independent of and combined with aerobic exercise
, with the incidence of metabolic syndrome. Mayo Clin Proc
35. Bakker EA, Lee D, Sui X, et al. Association of resistance exercise
with the incidence of hypercholesterolemia in men. Mayo Clin Proc
36. Mann S, Beedie C, Jimenez A. Differential effects of aerobic exercise
, resistance training and combined exercise modalities on cholesterol and the lipid profile: review, synthesis and recommendations. Sports Med
37. Miyachi M. Effects of resistance training on arterial stiffness: a meta-analysis. Br J Sports Med
38. Longhurst JC, Stebbins CL. The power athlete. Cardiol Clin
39. McKelvie RS, McCartney N, Tomlinson C, Bauer R, MacDougall JD. Comparison of hemodynamic responses to cycling and resistance exercise
in congestive heart failure secondary to ischemic cardiomyopathy. Am J Cardiol
40. Erez A, Kivity S, Berkovitch A, et al. The association between cardiorespiratory fitness and cardiovascular risk may be modulated by known cardiovascular risk factors. Am Heart J