Obesity and stress are independently associated with decrements in neuromuscular functions. The present study examined the interplay of obesity and stress on neuromuscular fatigue and associated heart rate variability (HRV).
Forty-eight non-obese (18.5<body mass index (BMI)<25 kg m−2) and obese (30⩽BMI) adults performed repetitive handgrip exertions at 30% of their maximum strength until exhaustion in the absence and presence of a mental arithmetic stressor. Dependent measures included gold standard fatigue indicators (endurance time and rate of strength loss), perceived effort and mental demand, heart rate and temporal (RMSSD: root mean square of successive differences between N–N intervals) and spectral (LF/HF: ratio of low to high frequency) indices of HRV.
Stress negatively affected endurance time (P<0.0001) and rate of strength loss (P=0.029). In addition, significant obesity × stress interactions were found on endurance time (P=0.0073), rate of strength loss (P=0.027) and perceived effort (P=0.026), indicating that stress increased fatigability, particularly in the obese group. Both obesity (P=0.001) and stress (P=0.033) independently lowered RMSSD. Finally, stress increased LF/HF ratio (P=0.028) and the interaction of stress and obesity (P=0.008) indicated that this was augmented in the obese group.
The present study provides the first evidence that stress-related neuromuscular fatigue development is accelerated in obese individuals. In addition, the stress condition resulted in poorer HRV indices, which is indicative of autonomic dysfunction, particularly in the obese group. These findings indicate that workers are more susceptible to fatigue in high-stress work environments, particularly those with higher BMI, which can increase the risk of musculoskeletal injuries as well as cardiovascular diseases in this population.
The increasing prevalence of obesity, defined as having a body mass index (BMI)⩾30 kg m−2, in the United States affects more than 75 million adults and is accompanied with a growing burden of physical disability.1 Over two-thirds of the working population is now overweight or obese, and annual costs attributed to obesity in the workplace are estimated at $73 billion.2 Several studies have reported increased motor impairments, particularly fine motor skills, in the obese,3 and a growing number of studies have indicated that obesity leads to an increased risk of mobility limitation, when coupled with advancing age.4 In young adults, obesity has shown to impair neuromuscular function, that is, reduction in muscle strength5 (when corrected for fat-free mass)6,7 and increased muscle fatigability,7 which can increase injury risk in workers with higher BMI.8 Obesity-related neuromuscular alterations may be attributed to peripheral physiological factors such as decreased blood capillarity that can impede blood flow,9 increased proportion of fast-twitch (that is, fatigable) muscle fiber-type distribution,10 or central factors such as low motivation7 or alteration in the neural drive.11
Along with impaired neuromuscular function, obesity has been linked to increased work stress.12,13 Majority of the studies have focused on how stress influences eating behavior, controls fat accumulation and causes weight gain.12,14,15 However, stress can be both a cause as well as a consequence of obesity. In healthy adults, stress has shown to impair motor function,16, 17, 18 increase muscle fatigability19,20 and hinder muscular and cardiovascular recovery,21 which can ultimately put stressed workers at greater risks of developing musculoskeletal disorders and cardiovascular diseases.22,23 Recent investigations have suggested that obesity-linked structural changes in the brain24 can result in slower information processing speed and reduce efficiency of sensory integration25 that has shown to impair both cognitive26 and motor functions.11 Because obese adults perceive higher stress levels at work compared with their normal-weight colleagues,13,27,28 it is likely that stress, due to intense workload, may contribute to greater muscle fatigability in this population, though this has yet to be investigated.
Both obesity and stress are known risk factors for cardiovascular diseases,29,30 and have been linked to increased sympathetic activity that can disturb cardiovascular autonomic function.31,32 Obese individuals exhibit attenuated heart rate variability (HRV), which is generally considered to be an indicator of poorer autonomic function and increased sympathetic activity.31,33 Although several studies have demonstrated strong associations of stress to changes in HRV indices during physical work,18,19,34 little is known regarding the interplay of obesity and stress on HRV during tasks that are representative of occupational demands.
Therefore, the present study explored the impact of stress on muscle fatigability and HRV in non-obese and obese adults. Fatigability of the hand/arm muscles was examined during moderate intensity handgrip exercises in the absence and presence of a laboratory stressor to test two hypotheses. First, it was hypothesized that stress will increase handgrip fatigue and that this outcome will be augmented in obese adults. Second, it was hypothesized that obesity will be associated with attenuated HRV, particularly under stress.
Materials and Methods
Forty-eight participants, between the age range of 20–65 years, were recruited from the local community and stratified in two groups: non-obese (18.5⩽BMI<25 kg m−2) and obese (BMI>30 kg m−2). Demographic descriptions of the participants are presented in Table 1. Significant group-level differences in percent body fat and waist-to-hip ratio (WHR) support that BMI differences were due to obesity and not other confounding factors such as high muscularity.35 Only participants who were sedentary to recreationally active and who reported no musculoskeletal injuries or disorders of the upper extremity within the past year were recruited in this study. Informed consent, using procedures approved by the Institutional Review Board, was obtained prior to the experiment.
A 2 (obesity: non-obese vs obese) × 2 (stress: control vs stress) mixed-measure design was used to examine their main and interactive effects on handgrip fatigue and associated cardiovascular and perceptual responses during intermittent handgrip exertions. Participants in each group performed handgrip exertions at 30% of their maximum voluntary contraction until exhaustion in the absence and presence of a laboratory stressor. The stressor used in the current study included a serial-n addition/subtraction task. Mental arithmetic has been regarded as one of the core cognitive functions,36 and in addition to measuring cognitive ability, mental arithmetic tasks have frequently been used both as a laboratory-based mental distractor37 and as a mental stressor.38,39
Participants attended two experimental sessions, a control and a stress condition, that were counterbalanced in their presentation order within each obesity group. The sessions for each participant were separated by at least 48 h each to reduce any residual effects of stress or fatigue. At the start of the first session, demographic information, health history and anthropometric measurements were obtained from the participants. Included in these measurements were participant body weight, stature, body fat percentage, waist circumference and hip circumference. Isometric handgrip strengths (that is, pre strength) were measured at the start of each session, after instrumenting participants with a heart rate monitor chest strap (RS800 Polar Heart Rate Monitor, Polar, Finland). The strength values obtained during the first session determined the 30% maximum voluntary contraction load level for each participant’s endurance tasks. Participants were seated upright with their upper arm at their side. A digital grip dynamometer (BIOPAC Systems, Inc., Goleta, CA, USA) was held in the dominant hand and the participant maintained the standardized grip testing posture with the elbow at 90 degrees and lower arm strapped to the chair arm support.
After ample rest, participants began the fatiguing exercise. The control condition required them to maintain handgrip exertion at 30% maximum voluntary contraction target load level displayed on a computer screen, using the same posture as discussed above, until voluntary exhaustion. The task was intermittent in nature, with 15-s gripping period followed by a 15-s rest period, until exhaustion. In the stress condition (performed on a separate day), participants were instructed to perform serial-n addition/subtraction arithmetic tests while concurrently performing the handgrip exercise described earlier. A three-digit number was verbally provided at the start of each gripping period, and participants performed either subtraction or multiplication of this number continuously from a two-digit number throughout that period, as fast and accurately as they can. In both conditions, participants were instructed to maintain the target workload for as long as they were able to and track their generated force against the target as closely as possible based on real-time visual feedback. When the participant couldn’t exert at the target level any longer, the task ended and the endurance time was recorded.
Exhaustion is defined as an inability to sustain contractions/exercise at the target force/intensity.40 As such, endurance time here was defined as the time at which the participant dropped>5% below the target without re-attaining it. Rate of strength loss was determined from a post-task maximum isometric strength (that is, post strength) performed immediately following the endurance task, and was calculated as the ratio of ((post strength – pre strength) to (pre strength)) to endurance time. This provides a direct measure of localized muscle fatigue progression, as muscle fatigue is defined as a reduction in force generating capacity, a separate process from exhaustion.40 Additionally, at the end of every 2 minutes during the task, participants provided Ratings of Perceived Exertion (RPEs) using a 10-point scale (‘0: nothing at all’ to ‘10: extremely strong, almost maximum’)41 and perceived mental demand using the mental demand subscale of the NASA Task Load Index questionnaire that has a 20-point scale (‘1: very low’ to ‘20: very high‘),42 and the rate of change of RPE and mental demand were calculated to monitor perceived exertion and mental demand respectively. A disproportionate increase in subjects’ perceived effort when maintaining a relative target force is indicative of the increasing contribution of central factors in fatigue development.43 To evaluate mental stress, both heart rate (HR) and HRV were obtained during the tasks using a HR monitor. Average HR across the entire task in each condition along with HRV measures, determined as root mean square of successive differences (RMSSD) and the ratio of low to high frequency (LF/HF) respectively, were computed to provide an assessment of sympathetic and parasympathetic activity due to the stressor.44 Finally, to ensure that the exposure to mental stress was consistent across the two obesity groups, performance on the mental arithmetic task, that is, percent error (errors made/total attempts) and normalized attempts (total attempts/endurance time), were recorded.
Separate mixed factor analyses of variances were performed to determine the main and interactive effects of obesity and stress on all outcome measures described earlier. Included in these models were participants as the random effect, obesity (non-obese vs obese), stress (control vs stress), their interactions and gender as fixed effects. Parametric model assumptions were assessed and log transformations of endurance time, rate of strength loss, RPE and mental demand rates, as well as HRV, RMSSD and LF/HF were utilized to achieve homoscedasticity. Separate analyses of variances were performed to determine the main effects of obesity and gender on the mental arithmetic performance measures. Where required, post hoc comparisons were performed using Tukey’s HSD. The level of significance for all analyses was set at P<0.05, and the analyses were conducted using JMP Pro 11.0 (SAS Institute Inc., Cary, NC, USA). All summary values are presented as means (s.d.).
Stress significantly decreased endurance time (F(1,47)=51.86, P<0.0001) and increased rate of strength loss (F(1,47)=5.07, P=0.029). Although the main effect of obesity was not significant, the interaction between obesity and stress was significant on endurance time (F(1,47)=7.82, P=0.007; Figure 1) and rate of strength loss (F(1,47)=5.25, P=0.027; Figure 2). Post hoc tests revealed that the obese group had 36.3% lower endurance than the non-obese group (22.33(12.82) min) in the stress condition while both groups had comparable endurance times in the control condition. Additionally, the obese group displayed 47.1% faster strength decline in the stress condition when compared with the control condition (2.39(1.16) %maximum voluntary contraction min−1), whereas no such differences were observed in the non-obese group. Endurance time and rate of strength loss were comparable across males and females, and no interactions between gender, obesity and stress on these fatigue indicators were observed.
Both obesity and stress significantly increased RPE (obesity: F(1,45)=4.28, P=0.044; stress: F(1,45)=14.36, P=0.0004) and mental demand (obesity: F(1,46)=5.23, P=0.0267; stress: F(1,46)=16.78, P<0.0001) rates. In addition, a significant obesity × stress interaction was found on RPE rate (F(1,45)=5.33, P=0.026, Figure 3). The obese group reported greater perceived effort over time in the stress condition (0.87(0.6) /min) compared with the control condition (0.47(0.22) /min), whereas no such differences were observed in the non-obese group. Perceived effort and mental demand remained similar across gender and were not influenced by any gender, obesity or stress interactions.
Although not significant (P=0.075), both participant groups had greater HR in the stress condition compared with the control condition. There were significant main effects of obesity (F(1,43)=12.4, P=0.001) and stress (F(1,43)=4.86, P=0.032) on HRV RMSSD, with lower RMSSD in the obese group compared with the non-obese group (21.27(12.08) ms vs 35.39(20.27) ms) and in the stress condition compared with the control condition (27.17(18.9) ms vs 29.62(17.3) ms). The spectral HRV measure, that is, HRV LF/HF, increased significantly (~14%) in the stress condition (F(1,43)=5.15, P=0.028) when compared with the control condition (431.35(243.2)). In addition, there was a significant obesity × stress interaction found on HRV LF/HF (F(1,43)=7.84, P=0.008, Figure 4), with a greater LF/HF ratio observed in the stress condition but only in the obese group. There was no main effect of gender, or its interaction with obesity or stress, on HR or HRV measures.
Performance on the mental arithmetic tasks was found to be similar across both obesity groups (percent error: P=0.889; normalized attempts: P=0.556). Although there were no gender differences in normalized attempts (P=0.06), females demonstrated ~40% higher error rate than males (F(1,46)=6.09, P=0.017).
The current study explored for the first time the impact of stress on neuromuscular fatigue development and associated HRV in obese adults. Key findings include: (1) significant obesity-related decline in neuromuscular responses (that is, fatigue indicators and perceived effort) in stress compared with no stress conditions, and (2) stunted HRV during the stressful condition, with greatest HRV attenuation observed in the obese group. These findings indicate that workers with higher BMI are more susceptible to fatigue, particularly in high-stress work environments that can increase the risk of musculoskeletal injuries as well as cardiovascular diseases in this population.
The present study did not find any obesity-related differences in handgrip fatigability, measured as endurance times and rate of strength loss. In general, obesity is linked to increased fatigability,7,45 however this relationship may be muscle- and intensity-dependent. Most research have focused on neuromuscular impairments of larger postural muscles, such as the quadriceps muscle group, that undergo chronic training due to the obesity-related additions in body mass.46 Compared with the quadriceps, muscles of the hand and arm have dissimilar muscular architecture, and are responsible for fine motor control that are less frequently recruited for support of body segment mass. Current literature regarding the impact of obesity on handgrip function is at best inconclusive, with studies reporting either increased fatigability47 or similar fatigue levels,48 similar to that observed in the present study, with obesity. Differences in personal factors such as obesity characterization (BMI, WHR or percent body fat), age or physical activity levels, along with methodological inconsistencies between these studies may account for the differing obesity effects reported in the literature.
It is well established that stress impairs motor performance and increases fatigability. Numerous experimental studies have attributed stress-related increase in fatigability to increases in autonomic responses,49 muscle tension,50 biomechanical demand51 and perception of effort,20 as well as an interference at the prefrontal cortex (PFC) that alters central command to the fatiguing muscles.52 As these studies have primarily focused on normal-weight adults, the present study tested the hypothesis that stress-related increases in the fatigue development will be accelerated with obesity. The main findings of the present study were that stress increased handgrip fatigue and that stress-related increased fatigability was augmented with obesity. Both fatigue indicators, that is, endurance time that is a discrete indicator of exhaustion and rate of strength loss that indicated localized muscle fatigue progression, were impacted by the obesity and stress interaction. These outcomes were also accompanied with increased perception of exertion (that is, RPE) in obese individuals during the stress conditions. Thus, it is possible that heightened perception of exertions in the stress condition may have played a contributive role in accelerating central, rather than peripheral, fatigue development with obesity.43 In support of this, recent neuroimaging studies have suggested that neural interference in the PFC during handgrip exercises under stress or dual-task conditions, such as that used in the present study, contributes to central fatigue development in normal-weight adults.52,53
Imaging of the brain has revealed that obesity-related decline in cognitive function may be due to alterations in the brain structure or function.24,26 Thus it is likely that the obese group in the present study found the laboratory stressor to be both cognitively demanding and mentally stressful. In accordance with this claim, the present study found higher mental demand scores with obesity. Thus it is possible that the mental arithmetic stressor had a stronger impact on the PFC with obesity that may further contribute to fatigue development in this group. In addition, a recent study demonstrated the obesity was associated with stunted PFC activity during handgrip exercises that was accompanied by decreased joint steadiness.11 Thus it is hypothesized that attenuated PFC activity during motor actions and increased information processing requirements to maintain cognitive control that are otherwise compromised with obesity25 may have a compounding effect on central fatigue development with obesity and stress. Neuroimaging studies are warranted to confirm this hypothesis that the PFC mediates obesity-related increase in neuromuscular fatigue development under stress. Moreover, studies that use different types of stressors, such as social or emotional stress, to examine neuromuscular fatigue across different muscle groups are also needed to test the neural pathways through which obesity and stress impact fatigue development.
Two indices of HRV were used in the present study; RMSSD is a time domain HRV index that is indicative of parasympathetic function and LF/HF ratio is a frequency domain HRV index that represents the balance between sympathetic and parasympathetic function.44 In the present study, the stress condition was associated with attenuated RMSSD, that is, poorer parasympathetic function, and marked increase in LF/HF ratio, that is, greater relative sympathetic dominance.54 Of note, lower RMSSD and higher LF/HF values are physiological markers of stress,54 thus these values, in addition to participants’ perceptions of mental demand, confirmed successful manipulation of stress through the use of a mental arithmetic stressor in the present study. In general, the present study observed stunted RMSSD with obesity that is consistent with previous research.31,33,55 Whereas there was no difference in the LF/HF ratio between the two groups, higher values of LF/HF ratio, in in the stress condition were observed in the obese group alone, indicating that stress at work can exacerbate autonomic imbalance in obese individuals and can put them at a greater risk of developing cardiovascular diseases. Given that neuromuscular capacity under stress is significantly compromised with obesity, additional imbalance in the autonomic nervous system due to stress in obese workers can further exacerbate fatigability and associated cardiovascular risk in this population. Future studies are needed that investigate potential multifactorial pathways of stress-mediated neuromuscular impairments with obesity, such as insufficient recovery, decreased vagal function and attenuated central command to descending motor neurons.
Several limitations of the present study warrant discussion. First, as BMI is a practical measure of obesity particularly during workplace risk assessments, characterization of obesity levels was based on BMI ranges, supported by significant group differences observed in percent body fat and WHR. Presence of other chronic conditions such as metabolic syndrome, insulin resistance, hypertension, and so on, was not controlled, thus future work is needed to determine whether these comorbidities mediate the relationship between stress and fatigue in obese individuals. Second, because participant recruitment in the present study was open to individuals between 20–65 years of age to represent the working age range, substantial variability in the ages in both obesity groups were observed (Table 1). Although several studies have noted the interplay of obesity with age on neuromuscular function, obesity-specific muscle decline is evident at age ranges (that is, 75–85 years)56 greater than that seen in the present study. Third, the present study used mental arithmetic as a laboratory stressor, as it has shown to increase cortisol levels and impact HRV.38,39 Moreover, both mental arithmetic and handgrip tasks have shown to involve similar frontal lobe regions.52 It can be argued that mental arithmetic may thus pose as a distractor rather than a mental stressor that led to shorter time on tasks during the stress condition. It should be noted that participants reported similar exertion levels, early on during the stress condition, which is in accordance with results from previous studies implicating central fatigue rather than distraction as a limiting factor to endurance.19,20 However, further investigations are warranted to determine neuroimaging markers of fatigue due to different types of stressors. Differences in cognitive ability due to obesity may influence the extent to which an individual is stressed owing to the mental arithmetic. Because performance metrics used in the present study, that is, normalized attempts and percent error, did not differ between the two obesity groups, it can be argued that both groups had similar exposure level to the stressor.
In conclusion, the present study demonstrated that stress-mediated increase in neuromuscular fatigue development, that is, lower endurance and faster rate of strength loss, is augmented with obesity. These findings were accompanied with heighted perception of exertions, that is, higher RPE rates, and increased sympathetic activation, that is, higher LF/HF ratio of HRV, in obese individuals under stress. It is hypothesized that decline in the central command processes, due to obesity- and stress-related changes in neural and autonomic functions, that regulate downstream peripheral responses may explain the accelerated nature of fatigue development. However, future research is warranted to test this hypothesis under different experimental conditions, that is, testing neuromuscular fatigue of different muscle groups under varying stress conditions.
Flegal KM, Carroll MD, Ogden CL, Curtin LR . Prevalence and trends in obesity among US adults, 1999-2008. Jama 2010; 303: 235–241.
Finkelstein EA, Burgess SM, Hale BC . The costs of obesity in the workplace. J Occup Env Med 2010; 52: 971.
Sartorio A, Proietti M, Marinone P, Agosti F, Adorni F, Lafortuna C . Influence of gender, age and BMI on lower limb muscular power output in a large population of obese men and women. Int J obes 2004; 28: 91–98.
Houston DK, Ding J, Nicklas BJ, Harris TB, Lee JS, Nevitt MC et al. Overweight and Obesity Over the Adult Life Course and Incident Mobility Limitation in Older Adults. The Health, Aging and Body Composition Study. Am J Epidemiol 2009; 169: 927–936.
Mehta RK, Cavuoto LA . The effects of obesity, age, and relative workload levels on handgrip endurance. Appl Ergon; e-pub ahead of print 31 July 2014; doi:10.1016/j.apergo.2014.07.007.
Hilton TN, Tuttle LJ, Bohnert KL, Mueller MJ, Sinacore DR . Excessive adipose tissue infiltration in skeletal muscle in individuals with obesity, diabetes mellitus, and peripheral neuropathy: association with performance and function. Physical Therapy 2008; 88: 1336–1344.
Maffiuletti NA, Jubeau M, Munzinger U, Bizzini M, Agosti F, De Col A et al. Differences in quadriceps muscle strength and fatigue between lean and obese subjects. Eur J Appl Physiol 2007; 101: 51–59.
Østbye T, Dement JM, Krause KM . Obesity and workers' compensation: results from the Duke Health and Safety Surveillance System. Arch Intern Med 2007; 167: 766–773.
Kern PA, Simsolo RB, Fournier M . Effect of weight loss on muscle fiber type, fiber size, capillarity, and succinate dehydrogenase activity in humans 1. J Clin Endocrinol Metab 1999; 84: 4185–4190.
Tanner CJ, Barakat HA, Dohm GL, Pories WJ, MacDonald KG, Cunningham PRG et al. Muscle fiber type is associated with obesity and weight loss. Am J Physiol EndocrinolMetab 2002; 282: E1191–E1196.
Mehta RK, Shortz A . Obesity-related differences in neural correlates of force control. Eur J Appl Physiol 2014; 114: 197–204.
Schulte PA, Wagner GR, Ostry A, Blanciforti LA, Cutlip RG, Krajnak KM et al. Work, obesity, and occupational safety and health. Am J Public Health 2007; 97: 428–436.
Nishitani N, Sakakibara H . Relationship of obesity to job stress and eating behavior in male Japanese workers. Int J Obesity 2006; 30: 528–533.
Weber A, Fussler C, O'Hanlon JF, Gierer R, Grandjean E . Psychophysiological effects of repetitive tasks. Ergonomics 1980; 23: 1033–1046.
Kivimäki M, Head J, Ferrie J, Shipley M, Brunner E, Vahtera J et al. Work stress, weight gain and weight loss: evidence for bidirectional effects of job strain on body mass index in the Whitehall II study. Int J Obesity 2006; 30: 982–987.
Mehta RK, Agnew MJ . Effects of concurrent physical and mental demands for a short duration static task. Int J Ind Ergon 2011; 41: 488–493.
Mehta RK, Agnew MJ . Exertion-dependent effects of physical and mental workload on physiological outcomes and task performance. IIE Trans Occup 2012; 1: 3–15.
Mehta RK, Nussbaum MA, Agnew MJ . Muscle- and task-dependent responses to concurrent physical and mental workload during intermittent static work. Ergonomics 2012; 59: 1166–1179.
Mehta RK, Agnew MJ . Influence of mental workload on muscle endurance, fatigue, and recovery during intermittent static work. Eur J Appl Physiol 2012; 112: 2891–2902.
Marcora SM, Staiano W, Manning V . Mental fatigue impairs physical performance in humans. J Appl Physiol 2009; 106: 857–864.
Melin B, Lundberg U . A biopsychosocial approach to work-stress and musculoskeletal disorders. J Psychophysiol 1997; 11: 238–247.
Kuper H, Singh-Manoux A, Siegrist J, Marmot M . When reciprocity fails: effort–reward imbalance in relation to coronary heart disease and health functioning within the Whitehall II study. Occup Environ Med 2002; 59: 777–784.
Kivimäki M, Virtanen M, Elovainio M, Kouvonen A, Väänänen A, Vahtera J . Work stress in the etiology of coronary heart disease—a meta-analysis. Scand J Work Environ Health 2006; 32: 431–442.
Stanek KM, Grieve SM, Brickman AM, Korgaonkar MS, Paul RH, Cohen RA et al. Obesity Is Associated With Reduced White Matter Integrity in Otherwise Healthy Adults*. Obesity 2011; 19: 500–504.
Gentier I, D’Hondt E, Shultz S, Deforche B, Augustijn M, Hoorne S et al. Fine and gross motor skills differ between healthy-weight and obese children. Res Dev Disab 2013; 34: 4043–4051.
Wolf PA, Beiser A, Elias MF, Au R, Vasan RS, Seshadri S . Relation of obesity to cognitive function: importance of central obesity and synergistic influence of concomitant hypertension. The Framingham Heart Study. Curr Alzheimer Res 2007; 4: 111–116.
Lallukka T, Laaksonen M, Martikainen P, Sarlio-Lähteenkorva S, Lahelma E . Psychosocial working conditions and weight gain among employees. Int J obesity 2005; 29: 909–915.
Kouvonen A, Kivimäki M, Cox SJ, Cox T, Vahtera J . Relationship between work stress and body mass index among 45,810 female and male employees. Psychosom Med 2005; 67: 577–583.
Logue J, Murray HM, Welsh P, Shepherd J, Packard C, Macfarlane P et al. Obesity is associated with fatal coronary heart disease independently of traditional risk factors and deprivation. Heart 2011; 97: 564–568.
Juonala M, Magnussen CG, Berenson GS, Venn A, Burns TL, Sabin MA et al. Childhood adiposity, adult adiposity, and cardiovascular risk factors. N Eng J Med 2011; 365: 1876–1885.
Karason K, Mølgaard H, Wikstrand J, Sjöström L . Heart rate variability in obesity and the effect of weight loss. Am J Cardiol 1999; 83: 1242–1247.
Steptoe A, Kivimäki M . Stress and cardiovascular disease. Nat Rev Cardiol 2012; 9: 360–370.
Windham BG, Fumagalli S, Ble A, Sollers JJ, Thayer JF, Najjar SS et al. The relationship between heart rate variability and adiposity differs for central and overall adiposity. Journal of obesity 2012; 2012: 149516.
Chandola T, Britton A, Brunner E, Hemingway H, Malik M, Kumari M et al. Work stress and coronary heart disease: what are the mechanisms? Eur Heart J 2008; 29: 640–648.
(NIH) NIoH, National Heart L, and Blood Institute (NHLBI), (NAASO) NAAftSoO. The Practical Guide: Identification, Evaluation, and Treatment of Overweight and Obesity in Adults. Rockville, MD: National Institutes of Health, 2000.
Fleishman EA . Toward a Taxonomy of Human Performance. Am Psychol 1975; 30: 1127–1149.
Peterson L, Peterson MJ . Short-term retention of individual verbal items. J Exp Psychol 1959; 58: 193–198.
Schleifer LM, Spalding TW, Kerick SE, Cram JR, Ley R, Hatfield BD . Mental stress and trapezius muscle activation under psychomotor challenge: A focus on EMG gaps during computer work. Psychophysiology 2008; 45: 356–365.
Allen M, Crowell M . Patterns of autonomic response during laboratory stressors. Psychophysiology 1989; 26: 603–614.
Vøllestad NK . Measurement of human muscle fatigue. J Neurosci Methods 1997; 74: 219–227.
Borg G . Psychophysical scaling with applications in physical work and the perception of exertion. Scand J Work Environ Health 1990; 16: 55.
Hart SG, Staveland LE . Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Adv Psychology 1988; 52: 139–183.
Taylor JL, Gandevia SC . A comparison of central aspects of fatigue in submaximal and maximal voluntary contractions. J Appl Physiol 2008; 104: 542–550.
Malik M, Bigger J, Camm A, Kleiger R, Malliani A, Moss A et al. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Circulation 1996; 93: 1043.
Hulens M, Vansant G, Lysens R, Claessens AL, Muls E . Assessment of isokinetic muscle strength in women who are obese. J Orthop Sport Phys Ther 2002; 32: 347.
Lafortuna C, Agosti F, Marinone P, Marazzi N, Sartorio A . The relationship between body composition and muscle power output in men and women with obesity. J Endocrinol Invest 2004; 27: 854.
Eksioglu M . Endurance time of grip-force as a function of grip-span, posture and anthropometric variables. Int J Ind Ergon 2011; 41: 401–409.
Cavuoto L, Nussbaum M . Obesity-related differences in muscular capacity during sustained isometric exertions. Appl Ergon 2013; 44: 254–260.
Hjortskov N, Rissen D, Blangsted AK, Fallentin N, Lundberg U, Søgaard K . The effect of mental stress on heart rate variability and blood pressure during computer work. Eur J Appl Physiol 2004; 92: 84–89.
Lundberg Forsman M, Zachau G, Ekloèf M, Palmerud G, Melin B et al. Effects of experimentally induced mental and physical stress on motor unit recruitment in the trapezius muscle. Work Stress 2002; 16: 166–178.
Marras WS, Davis KG, Heaney CA, Maronitis AB, Allread WG . The Influence of psychosocial stress, gender, and personality on mechanical loading of the lumbar spine. Spine 2000; 25: 3045–3054.
Mehta RK, Parasuraman R . The effect of mental fatigue on the development of physical fatigue: a neuroergonomic approach. Human Factors 2014; 56: 645–656.
Mandrick K, Derosiere G, Dray G, Coulon D, Micallef J-P, Perrey S . Prefrontal cortex activity during motor tasks with additional mental load requiring attentional demand: a near-infrared spectroscopy study. Neurosci Res 2013; 76: 156–162.
Thayer JF, Yamamoto SS, Brosschot JF . The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors. Int J Cardiol 2010; 141: 122–131.
Martini G, Riva P, Rabbia F, Molini V, Ferrero GB, Cerutti F et al. Heart rate variability in childhood obesity. Clin Auton Res 2001; 11: 87–91.
Villareal DT, Banks M, Siener C, Sinacore DR, Klein S . Physical frailty and body composition in obese elderly men and women. Obesity Res 2004; 12: 913–920.
Funding for this project was provided by Grant No. 5T42OH008421 from the National Institute for Occupational and Environmental Health (NIOSH)/Centers for Disease Control and Prevention to the Southwest Center for Occupational and Environmental Health (SWCOEH), a NIOSH Education and Research Center.
The author declares no conflict of interest.
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Mehta, R. Impacts of obesity and stress on neuromuscular fatigue development and associated heart rate variability. Int J Obes 39, 208–213 (2015). https://doi.org/10.1038/ijo.2014.127
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