The Active Female: Health Issues Throughout the Lifespan 2008th Edition

25. Screening Tools for Excessive Exercise in the Active Female

Maria Fernandez-del-Valle 


Department of Health, Exercise, and Sport Sciences, Texas Tech University, Exercise and Sport Sciences Building, 3204 Main, Lubbock, TX 49423, USA

Maria Fernandez-del-Valle



Excessive Exercise etiology and diagnosis has been deeply studied with inconclusive results. The criteria used for diagnosis are based on the Diagnostic and Statistical Manual for Mental Disorders (DSM) to diagnose addictive behaviors or substance abuse (alcohol, drugs, etc.). Moreover, the screening tools proposed by different authors have been subjective, inaccurate and co-assess other psychological and psychiatric disorders. Subjective screening tools (questionnaires, inventories, interviews, etc.) show information related to the psychological factors contributing to this behavior, and the information related to the characteristics of the exercise performed is scarce. Further, no validated cut-points exist to assess excessive exercise in different groups (children, adolescents, adults, elders, athletes, females, males, etc.). Therefore, the objective screening tools (accelerometers, pedometers, etc.) could add meaningful knowledge about the real characteristics of the activity performed by individuals.


FemaleExcessive exerciseExercise addictionObjectiveSubjectiveQuantitativeQualitativeScreening tool

25.1 Learning Objectives

After completing this chapter, you should have an understanding of the following:

·               What does excessive exercise, exercise addiction, or habit mean?

·               Concepts of Primary Exercise Addiction and Secondary Exercise Addiction.

·               Concepts of Positive Addiction and Negative Addiction.

·               When is exercise considered excessive? Excessive Exercise Thresholds.

·               Detecting unhealthy Physical Activity Levels: What are the recommendations?

·               Qualitative and quantitative screening tools. Are they diagnosing? Are they reporting exercise characteristics?

·               Excessive Exercise Comorbidity.

·               Physical Activity cut-points for Excessive Exercise Syndrome (EES).

25.2 Introduction

Physical Activity and Physical Exercise are considered by scientists as a determinant tool to prevent chronic physiological and psychological pathologies [15]. Performing and maintaining adequate physical activity levels have positive effects on physical and mental health [6]; therefore knowing the cut-points of excessive or insufficient exercise will allow the community to understand the dose–response relationship between exercise and health.

While sedentary life and its effects have been deeply researched, there are few studies that try to quantitatively or qualitatively analyze excessive exercise behaviors. This research conceptualizes it as Excessive Exercise Syndrome (EES).

25.3 Research Findings

25.3.1 Excessive Exercise Syndrome (EES) Definition

How are “excessive” and “exercise” defined? Excessive describes a quantity that is more than what is desirable, while exercise is defined as “planned, structured, and repetitive bodily movement done to improve or maintain one or more components of physical fitness” [7]. Therefore “excessive exercise” describes a quantity exercise performed beyond the physical healthy limits.

More than 30 terms have been adopted by researchers to describe the phenomenon [8], and the most frequents are “addiction” [9], “dependence” [10], “obligatory” [11], “abuse” [12], “compulsive” [13], “morbid,” and “driven” [14]. From these terms, “excessive exercise” does not reflect any etiological implications such as compulsion, addiction, abuse, etc., and therefore is the most used in the absence of consensus [15].

However, the most popular research etiological viewpoints are “addiction” and “compulsion” [1016]. Addiction is defined as “the behavioral process that can provide either pleasure or relief from internal discomfort (stress, anxiety, etc.) and it is characterized by repeated failure to control the behavior (state of powerlessness) and maintenance of the behavior in spite of negative consequences” [17]. Therefore, exercise addiction creates both physical and mental distress [18].

On the one hand, “addiction” seems to incorporate concepts describing the principal characteristics of the disorder, since it incorporates both dependence and compulsion [17]. These concepts add psychological aspects related to mental disorders to the excessive exercise syndrome (EES). “Addicts enjoy what they are doing and do not want to stop (ego syntonic)”while “obsessive-compulsive do not enjoy what they are doing but think they ought to do it (ego dystonic)” [15]. From the beginning, research has been focused solely on the population having both EES and mental disorders; however, there is insufficient research relating EES to the general and physical active population (recreational, amateur, or high performance athletes). Furthermore, no studies exist with a clinical sample of exercise addicts greater than 500 individuals, and those subjects demonstrated to suffer from other disorders [19].

All of these definitions imply negative effects, although a large number of positive effects have been described by authors due to high levels of physical activity [2022]. It is possible that there is a close tie between such concepts (excessive and addictive) and other implicit concepts like habit. Habit is defined as a recurrent, often unconscious, pattern of behavior that is acquired through frequent repetition. Regularly practicing physical activity improves self-esteem, fitness, and social behavior, all of which promote continuous exercise behavior; such a process is known as intrinsic motivation to practice and results in a habit [23]. What happens when you remove a habit from daily life? Researchers have reported that 1–2 weeks of practice deprivation resulted in depression symptoms, negative mood states, or fatigue in habitual exercises [2426]. Do these effects mean that they are addicted or performing excessive exercise? Classifications

Coverley Veale et al. proposed a classification for exercise addiction (EA) depending on the causes or the role of the exercise [27]. they differentiated two types of EA: primary and secondary. On the one hand, in primary EA physical activity is an end in itself (exercise is the objective); hence practitioners are intrinsically motivated to exercise. On the other hand, secondary EA co-occurs with an eating disorder or other compulsive disorders, where individuals are extrinsically motivated to exercise according to their self-image (weight loss is the objective) (Table 25.1). Accordingly to this classification, it is important to lighten whether EES is affecting firstly practitioner life or whether it emerges as a derived problem from another psychological disorder [1727].

Table 25.1

Primary and secondary exercise addiction symptoms

Primary exercise addiction (PEA)

Secondary exercise addiction (SEA)

Preoccupation with exercise routine

Stereotyped pattern of exercise with regular schedule (one set or more a day)

Significant withdrawal symptoms if exercise ceases

Salience with and increasing priority over other daily tasks to maintain the routine

Significant distress or impairment in all their areas of functioning

Increased tolerance

Preoccupation with exercise cannot be explained by co-occurring with other mental disorder

Withdrawal symptoms if exercise ceases

Relief of withdrawal symptoms if exercise is restarted

Subjective awareness of a compulsion to exercise

Continues exercise despite of injuries or physical pain

Loss of weight by dieting to improve performance

Berczik et al. [17], Bamber [31], Coverley Veale [27]

EA criteria in literature are based on the substance abuse criteria from Diagnostic and Statistical Manual for Mental Disorders-IV (DSM-IV) [28] and other research. DSM does not have a specific exercise dependence standard, thus exercise addiction is conceptualized as a maladaptive pattern of exercise, leading to clinically significant impairment or distress. Diagnosis of the EES remains uncertain due to results obtained using different screening tools have not been deeply correlated with symptoms exposed below. It seems that exercise addiction disorder could manifest three or more of the following criteria (Table 25.2) [2930].

Table 25.2

Exercise addiction criteria adapted from DMS-IV




“Need for increased amounts of exercise to achieve desired effect; diminished effect with continued use of same amount of exercise”


“Characteristic withdrawal symptoms for exercise (e.g., anxiety, fatigue) or exercise is taken to relieve or avoid symptoms”

Intention effect

“Exercise is often taken in larger amounts or over a longer period than was intended”

Lack of control

“A persistent desire or unsuccessful effort to cut down or control exercise”


“A great deal of time is spent in activities necessary to obtain exercise (e.g., physical activity vacations)”

Reduction in other activities

“Social, occupational, or recreational activities are given up or reduced because of exercise”


“Exercise is continued despite knowledge of having a persisting/recurring physical or psychological problem that is likely to have been caused or exacerbated by the exercise (e.g., continued running despite injury)”

APA [28], Freimuth et al. [29]

In order to present the positive and negative issues of an elevated exercise practice, Glasser (1977) introduced the classification of Positive Addiction (PA) and Negative Addiction (NA) [32]. PA contributes to overall practitioner’s fitness by integrating exercise into daily activities. Moreover, individuals with PA schedule their sessions around other aspects of their social life and work commitment, increasing feelings of control, competence, and physical and psychological wellbeing. Thereupon, practice is not detrimental to a proper conduct of their life. Otherwise, NA involves a compulsive need to exercise that annuls the practitioner’s physical and mental regards including wellbeing and social life [32]. Etiology

Etiological theories are diverse and multifactorial, and based on physiological (endorphins hypothesis and sympathetic arousal hypothesis), psychological (general theory of addiction), or psychobiological (personality traits, or the anorexia analogue hypothesis) issues.

Physiological Hypothesis

During 1980s and 1990s some authors had reported about the intense exercise effect in the endogenous opioid system, resulting in significant higher concentrations in blow stream and spinal fluids: the Endorphins Hypothesis. β-endorphin and catecholamine form part of the brain reward system, and it was thought to be related with exercise addiction due to their capacity to regulate physiological responses to stress and intense exercise [1833].

Endorphins are endogenous opioids derived from pro-opiocortin polypeptides. Moreover, endorphins are originated in the hypothalamus, and regulate pain perception increasing pain threshold, and showing a greater effort perception in trained people. Exercise intensity (performed above 60 % of the maximal oxygen uptake) and duration (sustained for at least 3 min) are related to increases plasma β-endorphin concentrations. However, plasma endorphins cannot cross the blood–brain barrier (BBB), whereby there is no evidence that changes in plasma levels could lead to simultaneous brain changes. Notwithstanding, some authors believe that endogenous opiates in plasma also operate in the central nervous system activity [1734]. In spite of the lack of sufficient direct evidence of association between exercise addiction and endogenous opioid system, and knowing that aerobic exercise stimulates the release of β-endorphin [33], an animal study with rats reported opioid tolerance and dependence in chronic exercisers [35]. Steinberg et al. established that chronic exercise practice [36]:

·  Provides an enjoyable effect that stimulates continuing practice

·  Triggers an excessive and compulsive behavior

·  Results in a reduced pain sensation dependent on the practitioners

·  Causes the emergence of a psychological and physiological withdrawal syndrome

Sympathetic Arousal Hypothesis was first proposed by Thompson et al. in 1987. Increased concentrations of catecholamine (adrenalin, noradrenalin, and dopamine) are induced by intense physiological or psychological stress (exercise or tasks). In addition, researchers have reported 1.5–20 times greater concentrations of catecholamine depending on exercise type, duration and intensity [37]. Catecholamine produces increases in heart rate, blood pressure, and a general reaction of the sympathetic nervous system known as “fight-or-flight response” (first stage of a general adaptation syndrome that regulates stress responses) [3338]. However, endorphins seem to attenuate their concentrations affecting the sympathetic nervous system regulation. On the one hand, habitual practitioners show a central effect of exercise that reduces the sensitivity to stress, producing lower concentrations of catecholamine and an increased efficiency of energy utilization [38]. On the other hand, research also has shown that greater physical fitness resulting in attenuated concentrations of these hormones could promote negative feelings such as lethargy, fatigue, depression, and decreased arousal [1833]. These findings suggest a possible association between addiction and catecholamine behaviors, due to the fact that habitual exercisers are motivated to engage in increased levels of exercise in order to achieve the same arousal levels and suppress symptoms [3339].

Psychological Hypothesis

Szabo et al. proposed a general theory of addiction or cognitive appraisal hypothesis to explain the etiology of exercise addiction. This theory means that habitual exercisers use exercise as a way to cope with stress, learning to need exercise for this purpose (coping mechanism). When the amounts are exaggerated, exerciser explains and justifies the practice, and slowly takes a principal role instead of normal daily activities. Negative psychological feelings (irritability, guilt, anxiousness, etc.) appear when the person is required to reduce or stop exercising, feelings that are believed to represent the withdrawal symptoms. There is also a loss of the coping mechanism where exerciser loses control over stressful situations increasing vulnerability to stress, and amplifying these negative psychological feelings when deprivation of exercise happens. The addicted exerciser is trapped in a vicious circle, exercising more to cope with daily stress that partly is caused by itself [40].

Psychobiological Hypothesis

Personality traits or anorexia analogue hypothesis shows to be the more postulated to explain EA despite the limited research support. Individuals addicted to exercise share common personality traits and behavioral dispositions with anorectic patients such as compulsiveness [41], neuroticism [42], low self-esteem [43], perfectionism [4345], high trait anxiety [46], high self-expectations, denial of potentially serious debility, and tendency towards depression [33]. These traits and dispositions seem to be more pathological in patients with anorexia nervosa than in addicted exercisers [47].

The main effects of EA in female are: concern about body image and appearance, development of anxiety and depression disorders, as well as the emergence of other behaviors as compulsive buying [48], whereas male have an uncertain identity, low self-esteem, AND anxiety about physical ineffectiveness [49]. Some authors have reported that exercise addiction coexist with eating disorders [50], results supported by animal models demonstrating that running-wheel is induced when rats are food-restricted 1 day. This vicious cycle is reinforced by a reward mechanism [51]. However, no evidence was reported in human runners compared with anorexic patients [47]. Prevalence

The prevalence of EA is variable and uncertain, owing the lack of research of clinical cases methodologically comparable (heterogeneity of the instruments used to assess EA, the insufficient sample size, and heterogeneity of the population studied). However, Sussman et al. showed a prevalence of 3 % at risk of EA, results that were supported by other authors that reported a 2.5 % [5253] and 3.6 % of general exercisers [54]. A greater prevalence (7 %) was found by Szabo et al. among university sport science students. “Maybe those results were induced by the awareness about the benefits of exercise on the well-being” [54].

Lejoyeux et al. analyzed exercise behaviors on 300 practitioners from a fitness room (18 years and older). A total of 125 (42 %) presented risk factors of EA, and from those risk “dependants” spent more hours each day in the fitness center compared with “no-dependants”(2.1 vs. 1.5 h/day), and they went more often each week (3.5 vs. 2.9 days/week). Moreover, exercise addicts smoked less and were significantly more compulsive buyers (63 % vs. 38 %) [48]. Exercise Addiction in Active Female

Gender incidence remains unclear, although some researchers reported equal prevalence in both males and females, while others have shown a higher prevalence of a primary EA in males, compared with an increased secondary EA in female [5355].

Villella et al. reported results in behavioral addictions in adolescents and young adults using the Exercise Addiction Inventory (EAI). This inventory was validated for university students, not high school students [5657]. Participants with scores of 24 or more were identified as at risk for exercise addiction. From a total of 2,853 high school students (1,142 girls—40 %) ranged between 13 and 20 years old, 8.5 % were at risk of EA. Segregating the sample in adolescents and young adults, both groups presented similar percentages (8.7 % and 8.3 % respectively), and females presented lower percentage (6.3 %) compared to males (10.1 %) [58].

EAI was used by Griffiths et al. who identified 3 % of the sample (n = 200) of adults between 18 and 40 years old at risk of EA scoring above 24, but no gender differences were reported [57].

Johnston et al. recruited 32 women (16–77 years old) from exercise facilities, weight-loss organizations, and school and university classes [15]. Participants were engaged in a wide variety of activities (hockey, diving, exercise classes, running, weight training, etc.), where the active time spent weekly ranged from 1 to 16 h (mean of 5 h/week). A total of 18.75 % scored above cutoff points of the Obligatory Exercise Questionnaire (OEQ), and half of them were defined as chronic dieters. They also showed that behavioral criteria such as frequency and amount of exercise (quantitative) are as important as psychological factors such as effort and enthusiasm (qualitative).

Exercise addiction in adult runners has been reported, showing that the more they exercise the more addicted they are to exercise with no gender differences. In addition, these results were constantly significant in exercisers of health club [59].

Authors such as Crossman et al. reported no exercise addiction in preadolescents, adolescents, and young adult runners (13–26 years) and swimmers (10–19 years) of different competitive levels (from international to regional) [60]. Results reported that 1–5 days of layoff are perceived by athletes as positive, showing greater positive mood states when competition level is lower, and when female group is analyzed compared to male [60].

Edgar et al. recruited a total of 102 female athletes where 47 were dancers, 39 runners and 16 hockey players. EA is lower in women who participate in collaborative sports (hockey, or soccer), followed by endurance practitioners (marathon or ultra-marathon), with a higher rates in women practicing activities such as ballet or modern dance. Higher addiction in dancers and ballerinas could be due to the expectations of technical, aerobic and anaerobic fitness, intensity, body image, and weight control requirements [6162].

There are few studies with a low sample size that differentiate the prevalence of this disorder based on the level of performance (high performance, amateur or physical activity for health), with higher levels of dependence in high performance and professionals (64.3 %) compared to amateur athletes (43.3 %). Moreover, athletes who presented eating disorders associated to exercise addiction where 34 % of 203 recruited (50 % in female, 27 % in male). In addition, eating disorders had a greater presence in amateurs compared to professionals (35.7 % vs. 31.5 %) [55]. According to these results, it seems that the volume of exercise (time, frequency, and intensity) has no validated cut-points for excessive exercisers [5560].

One study analyzed the exercise addiction using the Obligatory Exercise Scale (OES) in a group of 183 active female from 18 to 71 years. From all 7.1 % met exercise addiction criteria presenting scores equal or above to 50, and there were no differences between age groups: Group 1: 6.6 % (18–25 years); Group 2: 3.3 % (26–35 years); Group 3: 16.1 % (36–45 years); Group 4: 3.1 % (46–55 years); Group 5: 6.9 % (56–71 years). Furthermore, older showed to be more concerned with their health than younger women. Besides, they reported that from the total of the sample 82 % were concerned with their appearance, 30.6 % with their weight, and 41 % perceived themselves as being overweight [63].

25.3.2 Screening Tools for Excessive Exercise Syndrome (EES)

As EES could trigger in serious psychological and physiological consequences, it is necessary to detect excessive practice, and reeducate the practitioner to healthy exercise habits. Detecting the disorder could be accomplished by different screening tools. Which kind of screening tools could help? There are many tools in the literature that have been developed since 1970s, and therefore the most updated and used in the literature have been explained. Classification of the Screening Tools

Choosing one screening tool over the other could give the researchers different validity levels of data from the most objective to the most subjective measurements. When is a screening tool considered objective or subjective? A screening tool is considered to be highly objective when it measures what it intends to, and when it approaches the fact. subjective screening tools approximate the data by delayed information where the perception of researchers or participants could alienate results. Using objective or subjective screening tools depend on which characteristics of the excessive exercise are aimed to be analyzed: minutes per day, week or month, intensity of exercise, mood state, or eating disturbances. Researchers are more likely to use objective tools when the assessment does not need from the participation of individuals, or subjective tools when the participation of one or both researcher and individual is needed. Therefore, screening tools like mechanical devices are shown as objective tools, and inventories, questioners, self-report diaries, and interviews are shown as subjective tools [6465].

Given that, screening tools could be classified by what they are measuring (quantity or quality of excessive exercise). Therefore, quantitative characteristics assess the minutes, intensity, or time spent exercising, while qualitative characteristics assess the psychological effects such as mood state, anxiety, or eating disturbances. Daily logs, questionnaires, inventories, and observations are the most used subjective instruments due to their easy application and low cost. Nevertheless, they are limited by their validity and reliability depending on the sample size and targeted population (children and elder) [66] that obstruct the validation process. When these screening tools are compared with criteria methods, the results presented become overestimated. What is more, when the variables assessed are physiological they result in a greater overvalue, because they do not analyze all dimensions of physical activity [65].

Regarding objective instruments, pedometers, heart rate devices, and accelerometers are the most common devices used to assess spontaneous activity during prolonged periods of time. Of these, the accelerometer is a practical and precise device which has a friendly cost [67].

Finally, criteria instruments are used as a reference to validate all the instruments mentioned above. Doubly Labeled Water (DLW) is considered as the “Gold Standard,” and is used to determine daily life energy uptake, nevertheless it is not often used due to its elevated cost [6870].

Both subjective and objective screening tools can be classified as qualitative [Obligatory Exercise Questionnaire (OEQ), Exercise Dependence Scale Revised (EDS-R) or Exercise Addiction Inventory (EAI)], and quantitative [International Physical Activity Questionnaire (IPAQ), and mechanical devices as accelerometers or pedometers]; all of which are subjective except mechanical devices. Qualitative Screening Tools

Qualitative screening tools report information about the characteristics of the exercise regarding to psychological and physiological issues. The main characteristics of these instruments (QEQ, EDS-R, and EAI), as well as principal sources, can be found at http://​www.​knowmo.​ca.

Obligatory Exercise Questionnaire (OEQ)

The OEQ [11] was the first scale to measure obligatory exercise. It was modified from the Obligatory Running Questionnaire [47], and its psychometric properties have been well established [71].

This is a self-report questionnaire consisted on 20 items with a 4 point Likert scale scored at the extremes with never (1) to always (4); scores can add up to a total of 20 [72], and it can be used to identify psychological characteristics of committed adult and adolescent athletes, covering a wide range of exercise behavior such as running and weight lifting.

The OEQ also looks at the relationship between exercise behavior, eating disturbance, and body image in obligatory exercisers. Therefore, is often used to detect anorexia athletica or eating disorder induced by exercise abuse. Besides, OEQ has three subscales: exercise fixation (items associated with missed exercise and exercise to compensate for perceived overeating), exercise frequency (addressing frequency and type of exercise), and exercise commitment (indicating a sense of routine which cannot be missed) [73]. The primary weaknesses of this excessive exercise screening tool consist of different versions that have been developed, and the lack of validated cut-points.

Exercise Dependence Scale Revised (EDS-R)

The EDS was created by Downs et al. [74], and revised from the Hausenblas et al. Exercise Dependence Scale (EDS) [10]. Criterion was based upon DSM-IV [28]. The EDS-R provides the following information: mean score of exercise dependence symptoms, differences between at-risk for exercise dependence, nondependent-symptomatic, and nondependent-asymptomatic, and specifies if there is evidence of physiological dependence or no physiological dependence [75].

The EDS-R can be administered in adults 18 years and older, indicating responses to 21-items (28 items initially) of a Likert scale scored at the extremes with never (1) and always (6). EDS-R can provide information about the mean of each one of the symptoms or of the mean total score, allowing to differentiate individuals in three groups: at risk of exercise dependence (scores of 5–6 on the Likert scale in at least three of the seven criteria), nondependent symptomatic (scores of 3–4 on the Likert scale in at least three criteria, or scores of 5–6 combined with scores of 3–4 in three criteria, but without meeting the at-risk conditions), and nondependent asymptomatic (scores of 1–2 on the Likert scale in at least three criteria, without meeting the conditions of the nondependent symptomatic). The primary strength is the large sample size (college students), whereas weaknesses are the lack of validated cut-points, and the instrument length.

Exercise Addiction Inventory (EAI)

The EAI was developed by Terry et al. in 2004 [56]. This inventory was developed as a self-report to examine beliefs towards exercise in habitual adult exercisers. The inventory is made up of six statements: the importance of exercise for the individual, personal conflicts due to exercise, how mood changes with exercise, the amount of time spent exercising, the outcome of a missing workout, and the effects of decreasing physical activity. Individuals are asked to rate each statement from 1 (strongly disagree) to 5 (strongly agree). If an individual scores 24 or greater they are at-risk for exercise addiction, from 13 to 23 they are symptomatic individuals, and from 0 to 12 they are asymptomatic individuals. While this is an instrument quick and easy to use, validity data on cut-points are limited. Quantitative Screening Tools

International Physical Activity Questionnaire (IPAQ)

The purpose of the International Physical Activity Questionnaires (IPAQ) is to provide a set of well-developed instruments that can be used internationally to obtain comparable estimates of physical activity. IPAQ was created as a tool to universalize research worldwide in different human races, age, and gender to enable the comparison of data [76]. This questionnaire was the first international rule for subjective assess of physical activity, and it has two versions (short and long). The short version is suitable for use in national and regional prevention and the long version provides more detailed information [7778]. This instrument brings detailed information about the amount of physical activity (recreational, work, sports, or transportation activity), and has great weaknesses such as its length taking more than 30 min in the long version [79].

The scoring protocol presents three categories of physical activity: Low, Moderate, and High. First, those individuals who do not meet criteria of 2 or 3 days of practice are considered low physical active or inactive. Second, is the moderate physical activity level where individuals participate in 3 or more days of vigorous activity of at least 20 min, 5 or more days of moderate activity or walking at least 30 min, or 5 or more days of any combination of walking, moderate or vigorous activity achieving a minimum of 600 MET-min/week. Finally, high physical activity individuals show vigorous activity on at least 3 days accumulating 1,500 MET-min/week, or 7 or more days of any combination of walking, moderate or vigorous activities achieving a minimum of 3,000 MET-min/week. Cut-points for excessive exercise were not studied. MET values for each domain and intensity are reported in http://​www.​ipaq.​ki.​se/​ for free use as well as questionnaire in different languages.


Provides information about objective quantification of physical activity, researchers have been using multiple movement devices: accelerometers, pedometers, etc. Among them accelerometers are most popular, and Actigraph has been the most used to quantify free-living physical activity levels and patterns (Fig. 25.1). Moreover, Actigraph accelerometer has been used not only in healthy children, adolescents, adults and elders both genders, but also in different pathologies owing to its low cost, storage capacity (up to 22 days), programming, data download, validity, and reliability [6870].


Fig. 25.1


Actigraph has to be placed at waist using a belt (Fig. 25.2). Participants have to where it for a period of 7 days, at least 10 h/day to consider it a valid measure. This device needs to be programmed and downloaded using a software.


Fig. 25.2

Actigraph placement

The data obtained is as follows: sedentary activity (min/day), and active levels (min/day) (light, moderate, vigorous, and very vigorous levels). These levels have been correlated with metabolic equivalent of task (MET), where sedentary is 1–2 METs, light level is <3 METs, moderate level between 3 and 5.9 METs, vigorous level between 6 and 9 METs, and very vigorous level >9 METs [8081].

Depending on the age, physical activity intensities are determined using different cut-points, because the physical activity patterns change from childhood to elder. The cut-points refer to the daily minutes that individual spent depending on the intensity, and knowing the age [8284]. Choosing an Appropriate Screening Tool

Considerations for choosing an appropriate screening tool:

·  Application: easy to apply and interpret.

·  Validity: capable to measure what it was created for, and reproducible.

·  Reliability: inter- and intra-subject.

·  Cost–benefits: sample size could limit to choose one or other.

·  Objectivity: the most objective instrument has to be used.

·  Reactivity: participants tend to change behaviors.

Choosing an appropriate screening tool has to be made taking in account strengths and weaknesses of the instruments (Table 25.3) [85].

Table 25.3

Screening tools population applicability, strengths, and weaknesses





Obligatory exercise questionnaire (OEQ)



Cheap applicability (public domain)

Exercise fixation, frequency and commitment

Lack of validated cut-points

Different versions developed

Instrument length

Subjective (self-report)

Exercise dependence scale revised (EDS-R)


Cheap applicability (public domain)

DMS-IV addiction criteria (withdrawal, continuance, lack of control, reductions in other activities, time, intention)

Lack of validated cut-points

Instrument length

Subjective (self-report)

Exercise addiction inventory (EAI)

Adults (university students)

Cheap (public domain), and quick applicability

General components of addiction (salience, mood modification, tolerance, withdrawal, conflict, relapse)

Lack of validated cut-points

Subjective (self-report)

International physical activity questionnaire (IPAQ)

15–69 years

Cheap applicability (public domain)

Worldwide instrument

Self or telephone report

Length in long form

Details in short form

Subjective (self-report)


All ages

Objective instrument

Low reactivity on participants

Assess sedentary and active free lifestyle levels

Daily energy expenditure could be estimated

One of the cheapest devices, but more expensive than questionnaires

25.3.3 Cut-Points to Detect Unhealthy Exercise Levels

Since “health” is considered a state of complete physical, mental, and social well-being and not merely the absence of disease, physical activity levels could determine the healthy status of the population [86]. Quantification of free-living physical activity could be used to detect and establish the cut-points of exercise behaviors in different healthy and clinical population regarding to absence or excess of active lifestyle. However, while sedentary lifestyle has been deeply researched using accelerometers, excess of physical activity has been poorly studied. Only a few studies related with eating disorders has been developed; all of them have shown no abuse of exercise at the moment of assessment compared to healthy lifestyle recommendations and eating disorders cut-points for excessive exercise [8789].

The Center for Disease Control and Prevention and American College of Sport Medicine reported the first physical activity recommendations, 30 or more minutes of moderate–vigorous physical activity in almost every day [790]. Currently this recommendation has been increased, especially in children, where at least 60 min of moderate to vigorous physical activity (MVPA) should be performed 5 days a week and ideally every day (see Chaps. 21 and 22).

Related to the cut-points some authors established that more than 6 h of physical activity per week during at least four consecutive weeks indicate excessive exercise (EE) practice [91]. This cut-point was proposed by Davis et al. regarding to eating disorder use of physical activity as a compensatory behavior, therefore it is related with secondary exercise addiction [90]. Later, the intensity of this EE (first postulated by Davis et al.), was defined by Bratland-Sanda et al. in 2010 to be moderate to vigorous intensity. Therefore, those who perform more than 52 min/day of MVPA will be considered as SEA. Nevertheless, this cut-point has to be taken carefully, since it has been established for a mental disorder [92].

Comparing Davis et al. recommendations (1997) with ACSM recommendations [93] is contradictory because healthy population is expected to practice at least 60 min every day, while those who practice more than 52 min every day of MVPA are considered addicted to exercise. There is a lack of studies comparing both healthy and disordered populations that could put as in acquaintance of how much activity is performed by addicted individuals. Such lack of knowledge is extended to other population groups such as amateur or high performance athletes which lack reference values that could clear how much activity is too much for such groups. In relation to the level of practice, physical activity thresholds seem to change, therefore cut-points for EES are different depending on the level of practice and expertise.

An article of 2001 reported a direct relationship between greater increases in physical health parameters and the number of weekly hours spent exercising (from 2 to 7 weekly hours). Lower cardiovascular risks of mortality were reported in those who practiced between 4 and 7 weekly hours of regular physical activity. However, some cardiovascular risks were reported when more than 7 weekly hours where performed. By contrast, lower risk of cancer, respiratory disease, or other diseases where addressed when the practice was more than 7 h/week of MVPA [20]. Other authors show that physical activity benefits depend on the intensity of the practice, where greater benefits and lower mortality rates where associated to vigorous activity, nor light activity practice [94].

25.4 Contemporary Understanding of the Issue

Up to date, the research about the excess of exercise as a syndrome has been insufficient to fully understand, detect, diagnose, and manage exercise abuse-related problems. During the last 20 years different authors have shown that each group behave different, and in many cases the EES is accompanied or caused by a mental disease. There is much more work to be done, because it is necessary to detect when the practice of exercise is an acquired habit, or when is turning into a pathology depending on the group that is analyzed.

25.5 Future Directions

25.5.1 Reference Values for Female and Clinical Population

There is a lack of research on reference values for excessive exercise in healthy and clinical population in all ages. Validation, association, and correlation studies are needed to establish cut-points and reference values using different instruments and technics: physical activity levels using accelerometers or pedometers, plasma endogenous opioids level correlations with excessive exercise levels (endorphin, or catecholamine), psychological personality traits, etc.

More research has to be conducted to find out if exercise addiction is a consequence of other mental disorders (obsessive-compulsive, compulsive, addictive disorders, eating disorders, disordered eating, etc.)

25.5.2 Female Athletes and EES

Future research is needed to obtain reference values for excessive physical activity levels in high performance due to training requirements in different sports and disciplines which requirements are different from general population, distinguishing professional, and amateur, or international, national, or regional competition level.

25.6 Concluding Remarks

There is a fine line between regular and healthy exercise and excessive practice. There is not a clear relationship between high levels of exercise and other mental disorders. Although other mental illnesses may be the source, there are no studies to confirm or deny it.

Excessive exercise is greatly present in high performance compared to recreational; this may be due to the habitual practice, frequency and quantity of exercise performed. When 15 years of experience are exceeded, the rate of excessive exercisers decreases, likely because practice is highly integrated in daily life. Moreover, when excessive exercisers are females the features are different compared to males, such as weight preoccupation, appearance, body image and body composition commitment. These features are closely related with eating disturbances and eating disorder symptoms.

Screening tools need to be more specific and detailed, and validated as well. No cut-points for excessive exercise were established in any of the instruments purposed. However, there are some recommendations reported for eating disorders, weekly physical activity practice, and mortality research. Additionally, a deep analysis (using one or more screening tools) of quantitative and qualitative is needed to set the most appropriate assessment.



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