Singh and colleagues’ comprehensive systematic review of meta-analyses (97 reviews of 1039 trials including 128,119 participants) confirms that ‘physical activity (PA) is highly beneficial for improving symptoms of depression, anxiety and psychological distress’ with ‘effect size reductions in symptoms of depression (−0.43) and anxiety (−0.42) comparable to or slightly greater than those observed for psychotherapy and pharmacotherapy’.
This finding has important clinical implications and the authors conclude that PA should be included in public health guidelines as a mainstay approach (i.e. not just as an adjunct to psychological therapy and medication). They also recognise that ‘while the benefit of exercise for depression and anxiety is generally recognised, it is often overlooked in the management of these conditions’ .
Despite these really impressive results and their important clinical implications, it is unfortunate that the Singh et al review is unlikely to make a significant difference to clinical practice. There are many reasons why physical activity is not used as a first-line intervention for depression and other mental health problems, but one of the problems is that the field has not really addressed an issue I highlighted in a review of the field a quarter of a century ago. The evidence that PA can be an effective stand-alone or adjunctive intervention for a range of mental health problems is diluted amongst the public health/ mental wellbeing st...
Singh and colleagues’ comprehensive systematic review of meta-analyses (97 reviews of 1039 trials including 128,119 participants) confirms that ‘physical activity (PA) is highly beneficial for improving symptoms of depression, anxiety and psychological distress’ with ‘effect size reductions in symptoms of depression (−0.43) and anxiety (−0.42) comparable to or slightly greater than those observed for psychotherapy and pharmacotherapy’.
This finding has important clinical implications and the authors conclude that PA should be included in public health guidelines as a mainstay approach (i.e. not just as an adjunct to psychological therapy and medication). They also recognise that ‘while the benefit of exercise for depression and anxiety is generally recognised, it is often overlooked in the management of these conditions’ .
Despite these really impressive results and their important clinical implications, it is unfortunate that the Singh et al review is unlikely to make a significant difference to clinical practice. There are many reasons why physical activity is not used as a first-line intervention for depression and other mental health problems, but one of the problems is that the field has not really addressed an issue I highlighted in a review of the field a quarter of a century ago. The evidence that PA can be an effective stand-alone or adjunctive intervention for a range of mental health problems is diluted amongst the public health/ mental wellbeing studies focusing on lifestyle/ general health/ quality of life outcomes. What we need are effectively powered randomised controlled trials of carefully designed PA interventions compared to medication and psychological therapy in primary and secondary care clinical populations. It is important to note that, similar to the Singh et al. review, the Cochrane review ‘Exercise for depression’ (Cooney et al., 2013) included a preponderance of trials with non-clinical populations (23 out of the 39 trials included in the review).
Nonetheless, it is encouraging to see that the 2022 update of the NICE Guideline for Depression in adults (NG222) now includes the following:
‘Advise people that doing any form of physical activity on a regular basis (for example, walking, jogging, swimming, dance, gardening) could help enhance their sense of wellbeing. The benefits can be greater if this activity is outdoors.’
The Singh et al. review has implications for future research (e.g. neuromolecular mechanisms by which PA appears to improve depression) and clinical practice (e.g. resistance exercise was most effective for depression, while Yoga and other mind–body exercises were most effective for anxiety).
Research should not focus on neuroscience alone, however, as the mechanism responsible for the relationship between physical activity and mental health is complex and lies in a combination of biological, psychological and social factors (Biddle & Mutrie, 2001). The field therefore would also benefit from in-depth qualitative studies. A good example is a study by Crone et al. (2005) of people referred to ‘exercise prescription’ schemes, which demonstrated the importance of contextual factors such as social network, environment, culture and social support. However, this study also concluded that PA referral schemes appeared to be better suited to the needs of physical- than mental- health patients. This points to the need to research which factors encourage people referred for different mental health problems to engage with, and benefit from, different types of physical activity. Motivational factors may be unique to an individual, but we may find that a physical activity intervention that optimises the ‘therapeutic ingredients’ will have the best outcomes; for example, a specialist PA activity which is provided within a setting which maximises both social support and interaction with nature.
REFERENCES
Burbach, F. R. (1997). The efficacy of physical activity interventions within mental health services: Anxiety and depressive disorders. Journal of Mental Health, 6(6), 543-566.
Cooney, G. M., Dwan, K., Greig, C. A., Lawlor, D. A., Rimer, J., Waugh, F. R., ... & Mead, G. E. (2013). Exercise for depression. Cochrane database of systematic reviews, (9).
Crone, D., Smith, A., & Gough, B. (2005). “I feel totally alive, totally happy and totally at one”: A psycho-social explanation of the physical activity and mental health relationship from the experiences of participants on exercise referral schemes. Health Education Research, 20(5), 600–611.
Biddle, S. J. H., & Mutrie, N. (2001). Psychology of physical activity determinants, well-being and interventions.Routledge: London.
Singh, B., Olds, T., Curtis, R., Dumuid, D., Virgara, R., Watson, A., ... & Maher, C. (2023). Effectiveness of physical activity interventions for improving depression, anxiety and distress: an overview of systematic reviews. British Journal of Sports Medicine.
I read with interest the Saavedra et al.’s study1 aiming to evaluate the associations of cardiorespiratory fitness and body-mass-index with incident restrictive-ventilatory-impairment (RVI). The study’ rational is interesting since the RVI is frequent (eg; prevalence: 3 to 50%).2 One strong point of the aforementioned study1 was the use of the 2012 global-lung-function-initiative (GLI) task force of multi-ethnic norms for spirometry (GLI-2012).3 Saavedra et al.1 retained the diagnosis of a RVI in front of the combination of a low forced-vital-capacity (FVC) (ie; FVC < lower-limit-of-normal (LLN)) and a normal ratio between forced-expiratory-volume-in-one-second (FEV1) and FVC (ie; FEV1/FVC ≥ LLN). Saavedra et al.1 followed some “old” approaches. In 2022, the European-respiratory-society and the American-thoracic-society (ERS/ATS) published a “new” technical standard on interpretive strategies for lung function tests.4 This guidelines should be considered by researchers in the field of sports medicine.4 The definition applied by Saavedra et al.1 to retain the diagnosis of a RVI is questionable, and the following two points need to be clarified: i) what is a low spirometric data?, ii) what is a RVI?
What is a low spirometric data?
Interpretation of spirometric data necessitates 2 steps: i) comparison of the spirometric data with these of reference.4 5 , and ii) comparison of the data’ value with the distinctive thresholds of the main ventilatory-impairment not...
I read with interest the Saavedra et al.’s study1 aiming to evaluate the associations of cardiorespiratory fitness and body-mass-index with incident restrictive-ventilatory-impairment (RVI). The study’ rational is interesting since the RVI is frequent (eg; prevalence: 3 to 50%).2 One strong point of the aforementioned study1 was the use of the 2012 global-lung-function-initiative (GLI) task force of multi-ethnic norms for spirometry (GLI-2012).3 Saavedra et al.1 retained the diagnosis of a RVI in front of the combination of a low forced-vital-capacity (FVC) (ie; FVC < lower-limit-of-normal (LLN)) and a normal ratio between forced-expiratory-volume-in-one-second (FEV1) and FVC (ie; FEV1/FVC ≥ LLN). Saavedra et al.1 followed some “old” approaches. In 2022, the European-respiratory-society and the American-thoracic-society (ERS/ATS) published a “new” technical standard on interpretive strategies for lung function tests.4 This guidelines should be considered by researchers in the field of sports medicine.4 The definition applied by Saavedra et al.1 to retain the diagnosis of a RVI is questionable, and the following two points need to be clarified: i) what is a low spirometric data?, ii) what is a RVI?
What is a low spirometric data?
Interpretation of spirometric data necessitates 2 steps: i) comparison of the spirometric data with these of reference.4 5 , and ii) comparison of the data’ value with the distinctive thresholds of the main ventilatory-impairment noted during chronic diseases [eg; obstructive-ventilatory-impairment (OVI), RVI, mixed-ventilatory-impairment (MVI)].4 5 In this context, norms are useful for classifying a spirometric data as decreased, normal, or increased based on the 95% confidence interval (eg; LLN and upper-limit-of-normal).4 5 After the development of the GLI-2012 spirometric norms,3 the application of a more suitable and new statistical techniques for determining the LLN is commended.3 6 The LMS [lambda, mu, sigma] technique was used.3 6 Based on the LMS method, a further approach based on the determined data’ z-scores, was suggested to interpret spirometric data.3 6 The z-score specifies by how many standard-deviations a subject’ spirometric data is deviated from its predicted normal value, with merely 5% of healthy subjects having a z-score ≤ -1.645.3 6 Disparate percentage predicted, z-score is free from bias due to sex, age, height, and ethnicity, and is consequently principally convenient in defining the LLN.3 6 Z-score simplifies uniform analysis of spirometric results.3 6 In brief, a lung function data value is considered low when its z-score is < -1.645, and normal when its z-score is ≥ -1.645.4 7 In Saavedra et al’s study.1, it is unclear if the authors have applied the z-score approach.
What is a RVI?
A reduction in lung volumes defines a RVI, which is classically characterized by a low total-lung-capacity (TLC).4 The presence of a RVI may be suspected (but not confirmed) from spirometry alone when FVC is low, FEV1/FVC is normal, and the flow-volume curve displays a convex pattern (ie; revealing a high elastic recoil).4 Nevertheless, a low FVC by itself does not confirm a RVI.2 4 Certainly, a low FVC is connected with a low TLC less than half the time.8 Contrariwise, normal “FVC and FEV1/FVC” are greatly trustworthy at ruling out a RVI as measured by low TLC.8 Finally, a MVI (ie, presence of both OVI and RVI) is retained in front of the association of “low TLC and low FEV1/FVC ratio”.4
To conclude, in practice, two distinct, yet complementary aspects of spirometry interpretation, should be considered.4 First, cataloging the observed values as within/outside the normal range with respect to the GLI-2012 norms (eg, z-score < 1.645 or ≥ 1.645). Second, incorporating information of physiologic factors of test results into a functional classification of the recognized impairments (eg, OVI, RVI, MVI).
REFERENCES
1. Saavedra JM, Brellenthin AG, Song BK, et al. Associations of cardiorespiratory fitness and body mass index with incident restrictive spirometry pattern. Br J Sports Med 2023 doi: 10.1136/bjsports-2022-106136 [published Online First: 20230106]
2. Backman H, Eriksson B, Hedman L, et al. Restrictive spirometric pattern in the general adult population: Methods of defining the condition and consequences on prevalence. Respir Med 2016;120:116-23. doi: 10.1016/j.rmed.2016.10.005 [published Online First: 20161012]
3. Quanjer PH, Stanojevic S, Cole TJ, et al. Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations. Eur Respir J 2012;40(6):1324-43. doi: 10.1183/09031936.00080312 [published Online First: 20120627]
4. Stanojevic S, Kaminsky DA, Miller MR, et al. ERS/ATS technical standard on interpretive strategies for routine lung function tests. Eur Respir J 2022;60(1) doi: 10.1183/13993003.01499-2021 [published Online First: 20220713]
5. Ben Saad H. Interpretation of respiratory functional explorations of deficiency and incapacity in adult. Tunis Med 2020;98(11):797-815. [published Online First: 2021/01/23]
6. Hall GL, Filipow N, Ruppel G, et al. Official ERS technical standard: Global Lung Function Initiative reference values for static lung volumes in individuals of European ancestry. Eur Respir J 2021;57(3) doi: 10.1183/13993003.00289-2020 [published Online First: 20210311]
7. Ben Saad H. Review of the current use of global lung function initiative norms for spirometry (GLI-2012) and static lung volumes (GLI-2021) in Great Arab Maghreb (GAM) countries and steps required to improve their utilization. Libyan J Med 2022;17(1):2031596. doi: 10.1080/19932820.2022.2031596
8. Aaron SD, Dales RE, Cardinal P. How accurate is spirometry at predicting restrictive pulmonary impairment? Chest 1999;115(3):869-73. doi: 10.1378/chest.115.3.869.
We wish to commend Horan et al. (Horan et al., 2022) on their systematic review and meta-analysis which established overall, match and training IIRs in senior women’s football. It is encouraging to see continued work in this specific area of women’s football epidemiological research.
We would like to draw the authors attention to the following error contained within their work. We respectfully request that it is amended accordingly so that the readership are aware of all available work in this area.
Horan et al. (Horan et al., 2022) refer to the systematic review and meta-analysis of López Valenciano et al (López-Valenciano et al., 2021) which they report was recently ‘criticised’ in a published commentary by Mayhew et al (2021). The authors use the following citation:
30. Mayhew, L. et al. (2021) ‘Incidence of injury in adult elite women’s football: a systematic review and meta-analysis’, BMJ Open Sport & Exercise Medicine, 7(3), p. e001094. doi:10.1136/bmjsem-2021-001094
The readership should be aware that the citation Horan et al. (Horan et al., 2022) use in their work is not a published commentary but a systematic review and meta-analysis on the incidence of injury in elite women’s football. Our publication was PROSPERO registered and published ahead of Horan et al. (Horan et al., 2022) in BJSM’s sister journal (BMJ Open Sport & Exercise Medicine).
We wish to commend Horan et al. (Horan et al., 2022) on their systematic review and meta-analysis which established overall, match and training IIRs in senior women’s football. It is encouraging to see continued work in this specific area of women’s football epidemiological research.
We would like to draw the authors attention to the following error contained within their work. We respectfully request that it is amended accordingly so that the readership are aware of all available work in this area.
Horan et al. (Horan et al., 2022) refer to the systematic review and meta-analysis of López Valenciano et al (López-Valenciano et al., 2021) which they report was recently ‘criticised’ in a published commentary by Mayhew et al (2021). The authors use the following citation:
30. Mayhew, L. et al. (2021) ‘Incidence of injury in adult elite women’s football: a systematic review and meta-analysis’, BMJ Open Sport & Exercise Medicine, 7(3), p. e001094. doi:10.1136/bmjsem-2021-001094
The readership should be aware that the citation Horan et al. (Horan et al., 2022) use in their work is not a published commentary but a systematic review and meta-analysis on the incidence of injury in elite women’s football. Our publication was PROSPERO registered and published ahead of Horan et al. (Horan et al., 2022) in BJSM’s sister journal (BMJ Open Sport & Exercise Medicine).
The corrected citation should be:
Mayhew, L., Johnson, M.I. and Jones, G. (2021) ‘Comment on: “Injury Profile in Women’s Football: A Systematic Review and Meta‑analysis’’, Sports Medicine, 51(12), pp. 2665–2666. doi:10.1007/s40279-021-01531-9.
Our systematic review and meta-analysis is thus cited in Horan et al (2022) but is not referred to in text as a previous systematic review and meta-analysis within this area of research. The readership should be made aware of all relevant work and we invite the authors to comment on the contents of this letter.
I appreciate the thoughtful considerations raised. Scientific discussion is always the best way for the opportunity to review points, exchange thoughts and evolve in knowledge. Here are some additional considerations below:
- About strength and VO2peak controlled by FFM and/or weight:
We showed these data in the article (strength/FFM; VO2peak/FFM; VO2peak/weight) in the results and table 2. There are no statistical differences comparing all populations (TW,CM and CW).
- TW with 637 ng/dL testosterone on the day of the tests:
In the long-term follow-up of a cohort of individuals with daily medication use, temporary failures in the regular use of medications are not uncommon. One of the participants had a high level of testosterone at the time of the study. However, we emphasize that we were careful to assess testosterone levels in the year before the study so that we could confirm the correlation of the values obtained at the time of the study with those in the last year. In addition, the values of haemoglobin denoted testosterone supression in the past 4 months. Although one of the TW was not blocked on test day (total testosterone =637 ng/dL), her value was 79 ng/dL six months before the study. This point did not interfere with her VO2 results (supplementary figure 2).
- Weight and height:
Studies in sports medicine generally eliminate the height as an interfering factor in the analyses.
Height is a consequent characteristic o...
I appreciate the thoughtful considerations raised. Scientific discussion is always the best way for the opportunity to review points, exchange thoughts and evolve in knowledge. Here are some additional considerations below:
- About strength and VO2peak controlled by FFM and/or weight:
We showed these data in the article (strength/FFM; VO2peak/FFM; VO2peak/weight) in the results and table 2. There are no statistical differences comparing all populations (TW,CM and CW).
- TW with 637 ng/dL testosterone on the day of the tests:
In the long-term follow-up of a cohort of individuals with daily medication use, temporary failures in the regular use of medications are not uncommon. One of the participants had a high level of testosterone at the time of the study. However, we emphasize that we were careful to assess testosterone levels in the year before the study so that we could confirm the correlation of the values obtained at the time of the study with those in the last year. In addition, the values of haemoglobin denoted testosterone supression in the past 4 months. Although one of the TW was not blocked on test day (total testosterone =637 ng/dL), her value was 79 ng/dL six months before the study. This point did not interfere with her VO2 results (supplementary figure 2).
- Weight and height:
Studies in sports medicine generally eliminate the height as an interfering factor in the analyses.
Height is a consequent characteristic of the puberty pattern that the individual had (male or female) and cis women are 13 cm shorter on average when compared to men. We have to be careful when making the correlation of height and sports performance. Men are taller and also have more muscle mass, larger heart chambers, and larger diameter of the bronchial tree. Therefore, height cannot be identified as a cause of sporting abilities, but rather as a confounding factor.
It is not weight alone that may affect sporting abilities, but muscle mass and several other factors.
Gender studies in sport often use BMI for pairing.
- Grip strength test:
The grip strength test presents results that denote an overall assessment of the individual and is largely carried out in performance studies in the most diverse populations.
There is absolutely no doubt that physical activity is a beautiful phenomenon. In the above study, the study is fair to the extent that those subjects who regularly exercised had lesser hospitalisations. Here both reason and effect exist, but can a direct causal relationship be established between the two?
Can it be inferred beyond doubt that "the vaccine prevented complications of Covid-19 because exercise strengthened the immune response? The possibility of such a remarkable effect in the short term is pretty unlikely. And all the more, such findings can't be generalised to a larger population.
Authors seem to be ignoring a hidden confounder affecting the validity of the study, and this confounder is 'frailty'. Simply those doing less exercise were unable to do so because they were frail. And obviously, frailty can be present independent of comorbidities like DM, heart failure or obesity, which were evenly matched between the high and low-exercise groups.
So, the correct conclusions will likely differ if this confounder is considered. one may not forget that 'Correlation, even if present in a statistically significant portion, may not amount to causation.
The study might prompt some frail people or even morbidly obese people to engage in heavy exercise soon after the vaccination despite muscle aches and fever (common side effects of the Covid-19 vaccines). And these might have disastrous consequences. So the wo...
There is absolutely no doubt that physical activity is a beautiful phenomenon. In the above study, the study is fair to the extent that those subjects who regularly exercised had lesser hospitalisations. Here both reason and effect exist, but can a direct causal relationship be established between the two?
Can it be inferred beyond doubt that "the vaccine prevented complications of Covid-19 because exercise strengthened the immune response? The possibility of such a remarkable effect in the short term is pretty unlikely. And all the more, such findings can't be generalised to a larger population.
Authors seem to be ignoring a hidden confounder affecting the validity of the study, and this confounder is 'frailty'. Simply those doing less exercise were unable to do so because they were frail. And obviously, frailty can be present independent of comorbidities like DM, heart failure or obesity, which were evenly matched between the high and low-exercise groups.
So, the correct conclusions will likely differ if this confounder is considered. one may not forget that 'Correlation, even if present in a statistically significant portion, may not amount to causation.
The study might prompt some frail people or even morbidly obese people to engage in heavy exercise soon after the vaccination despite muscle aches and fever (common side effects of the Covid-19 vaccines). And these might have disastrous consequences. So the words of caution need to be stressed.
Nevertheless, the role of exercise in a healthy population should not be undermined.
Alvares et al. [1] conducted a study to compare performance-related measures such as cardiopulmonary exercise capacity and muscle strength in non-athlete transgender women (TW) undergoing long-term gender-affirming hormone therapy to non-athlete cisgender men (CM) and non-athlete cisgender women (CW). The authors report higher absolute VO2peak (L/min) and muscle strength (kg) in TW compared to CW and lower than CM. The authors conclude that their “…findings could inform policy and help in decisions about the participation of transgender women in sporting activities”.
However, the authors interpreted their findings on the basis of the absolute data they present and not the relative data that was controlled for body mass and fat-free mass (FFM), as would be appropriate for comparisons of such performance metrics (e.g., aerobic capacity and muscle strength). By focusing on the absolute data, the authors over-emphasise differences between comparison groups (e.g., TW and CW) that are clearly driven by differences in anthropometry. For example, when the data reported in Table 2 [1] are corrected for body mass and fat-free mass (FFM), differences in aerobic capacity and strength between TW and CW disappear. Yet, in the section “WHAT THIS STUDY ADDS” [1], which is the primary focus of many readers, the authors omit the results that control for body mass and FFM, instead leaving the reader with the misleading message that “[t]he mean strength and VO2peak...
Alvares et al. [1] conducted a study to compare performance-related measures such as cardiopulmonary exercise capacity and muscle strength in non-athlete transgender women (TW) undergoing long-term gender-affirming hormone therapy to non-athlete cisgender men (CM) and non-athlete cisgender women (CW). The authors report higher absolute VO2peak (L/min) and muscle strength (kg) in TW compared to CW and lower than CM. The authors conclude that their “…findings could inform policy and help in decisions about the participation of transgender women in sporting activities”.
However, the authors interpreted their findings on the basis of the absolute data they present and not the relative data that was controlled for body mass and fat-free mass (FFM), as would be appropriate for comparisons of such performance metrics (e.g., aerobic capacity and muscle strength). By focusing on the absolute data, the authors over-emphasise differences between comparison groups (e.g., TW and CW) that are clearly driven by differences in anthropometry. For example, when the data reported in Table 2 [1] are corrected for body mass and fat-free mass (FFM), differences in aerobic capacity and strength between TW and CW disappear. Yet, in the section “WHAT THIS STUDY ADDS” [1], which is the primary focus of many readers, the authors omit the results that control for body mass and FFM, instead leaving the reader with the misleading message that “[t]he mean strength and VO2peak in non-athlete TW … were higher than those in non-athlete CW.”
Relatedly, we question the authors’ reliance on expressing lung volume relative to body mass and FFM, when expressing relative to height would be more informative. The important relationship between height and indices of cardiovascular function/capacity is widely recognised [2]. However, Alvares et al. only report the heights of participants in their supplementary data [1] – which will mostly be overlooked by many reading the paper. Our own analysis of the supplementary data shows that height differences between TW and CW could fully account for the absolute differences in lung capacity. Again, the key finding here would be an absence of difference in relative aerobic capacity of cisgender versus transgender women.
In addition to the biased message, there are also many other basic errors in this manuscript that questions its value as published to inform policy. In the interest of brevity our main concerns are listed below as follow:
1. We question why one of the TW participants had a very high level of testosterone on the day of testing (TT=637 ng/dL). The authors justified the inclusion of this subject’s testing results on the basis of her having had a lower testosterone level six months prior. However, this is a cross-sectional study, meaning this participant should have been excluded. Without access to the raw data it is impossible to know the impact of the inclusion of this data in the comparison between groups.
2. VO2peak rather than VO2max is listed as the measure of aerobic capacity, even though VO2peak is known to underestimate the value of VO2max by 0.1-0.4 l/min [3]. It is unknown whether this represent a semantic error, or the authors have indeed measured VO2peak.
3. The authors rely on the International Physical Activity Questionnaire (IPAQ) to assess the physical activity levels of participants and match subjects in the comparison groups for meaningful data interpretation. However, the IPAQ is considered a valid instrument for measuring physical activity in large study populations, and not for such small studies needing validity at the individual level. This makes the interpretation of the comparisons between “matched” groups very difficult, if not impossible.
4. The number of participants reported in the abstract (i.e. 15 TW, 13 CM and 14 CW) does not match the number reported later in the article. The units of measurement for maximum aerobic capacity are clearly erroneous as physiologically implausible (e.g. Table 2 and VO2peak (L/min) was 2606±416.9 in TW, 2167±408.8 in CW and 3358±436.3 in CM).
5. The authors imply that gender dysphoria is a mental disorder, stating that “the criteria for gender dysphoria diagnosis were in accordance with the Diagnostic and Statistical Manual of Mental Disorder.” However, Gender Dysphoria is no longer classed as a mental health disorder [4].
In conclusion, we suggest that, as presented, the paper by Alvares et al. [1] cannot be used to “inform policy and help in decisions about the participation of transgender women in sporting activities”. Instead, the scientific community including these authors should be encouraged to conduct and publish high quality studies involving trained transgender individuals (and athletes where possible) and involving sport-specific measures to inform policy and guidelines [5].
References
1. Alvares LAM, Santos MR, Souza FR, Santos LM, Mendonça BB, Costa EMF, Alves MJNN, Domenice S. Cardiopulmonary capacity and muscle strength in transgender women on long-term gender-affirming hormone therapy: a cross-sectional study. Br J Sports Med. 2022 Nov;56(22):1292-1298.
2. HEPPER NG, FOWLER WS, HELMHOLZ HF Jr. Relationship of height to lung volume in healthy men. Dis Chest. 1960 Mar;37:314-20. PMID: 14401182.
3. Smirmaul BP, Bertucci DR, Teixeira IP. Is the VO2max that we measure really maximal? Front Physiol. 2013 Aug 5;4:203.
4. Rodríguez MF, Granda MM, González V. Gender incongruence is no longer a mental disorder. Journal of Mental Health & Clinical Psychology. 2018;2(5).
5. Martowicz M, Pape M, Budgett R, Mascagni K, Engebretsen L, Dienstbach-Wech L, Pitsiladis Y, Pigozzi F, Erdener U. Position Statement: IOC Framework on Fairness, Inclusion and Non-Discrimination on the Basis of Gender Identity and Sex Variations. British Journal of Sports Medicine. In review.
The topic of transgender inclusion in women’s sports is politically fraught. Sport’s governing bodies are grappling with the competing priorities of inclusivity and fairness due to any perceived competitive advantage above and beyond the large and broad continuum of biological variables found within cisgender women (e.g. height, bone mass, bone length, fiber cross-sectional diameter, etc.) associated with testosterone exposure during puberty. This active area of research is rapidly evolving due to the multitude of new studies published over the previous 5 years. In fact, there have been over a dozen primary prospective and case-control research studies published on this topic since 2018 resulting in the lowering of the maximum allowable testosterone level in transgender elite athletes (i.e., from 5.0 to 2.5nmol/L) by several sports’ governing bodies.
The preponderance of evidence suggests that hematological differences in hematocrit, red cell number, and hemoglobin are largely normalized within 120 days of testosterone suppression, which is biologically plausible as this corresponds with the average lifespan of a red cell (~ 120 days). Since oxygen delivery to peripheral tissues is performance limiting in aerobic sports, any competitive advantage is likely largely diminished within a year of testosterone suppression. Studies evaluating changes in strength, muscle mass, and body composition are more equivocal and most likely occur over a longer time span (12-36 mon...
The topic of transgender inclusion in women’s sports is politically fraught. Sport’s governing bodies are grappling with the competing priorities of inclusivity and fairness due to any perceived competitive advantage above and beyond the large and broad continuum of biological variables found within cisgender women (e.g. height, bone mass, bone length, fiber cross-sectional diameter, etc.) associated with testosterone exposure during puberty. This active area of research is rapidly evolving due to the multitude of new studies published over the previous 5 years. In fact, there have been over a dozen primary prospective and case-control research studies published on this topic since 2018 resulting in the lowering of the maximum allowable testosterone level in transgender elite athletes (i.e., from 5.0 to 2.5nmol/L) by several sports’ governing bodies.
The preponderance of evidence suggests that hematological differences in hematocrit, red cell number, and hemoglobin are largely normalized within 120 days of testosterone suppression, which is biologically plausible as this corresponds with the average lifespan of a red cell (~ 120 days). Since oxygen delivery to peripheral tissues is performance limiting in aerobic sports, any competitive advantage is likely largely diminished within a year of testosterone suppression. Studies evaluating changes in strength, muscle mass, and body composition are more equivocal and most likely occur over a longer time span (12-36 months).
Few studies have evaluated cardiopulmonary differences in transgender women relative to cisgender women or men. The recent publication by Alvares et. al. evaluated cardiopulmonary capacity and grip strength in a small cohort of non-athlete cisgender and transgender women (CW and TW) and cisgender men (CM) in San Paulo, Brazil. 15 transgender women were recruited from a clinic that specializes in the treatment transgender patients. The average age of the TW was 34.2 +/- 5.2 years with an average duration of hormonal treatment of 14.4+/-3.5 years (median age of treatment initiation was 17 years old). Although the TW subjects were on hormonal treatment for over a decade, 11 of the 15 subjects were dependent on chemical testosterone suppression (i.e., non-gonadectomized). The median testosterone level over the previous 12 months for the TW subjects was 3.5nmol/L with 4 of the subjects above 7nmol/L, which is within the range observed CM group. As noted above, several sports’ governing bodies require testosterone suppression below 2.5nmol/L throughout the entire year. Prospective testosterone data for each subject was not provided so it is unclear how many TW subjects meet these criteria, however median levels presented in supplemental figure 1 suggest that at least 8 out of 15 of the subjects do not meet this criterion. Despite the suboptimal hormonal control, hemoglobin levels of the TW were not different than CW and both groups were significantly lower than the CM group. Although the groups were matched by age and activity, they were not weight matched. The average body weights were 60.8kg, 78.1kg, and 81.3kg for the CW, TW, CM groups respectively (CW vs TW and CW vs CM were significantly different; P < 0.001).
The authors performed cardiopulmonary exercise testing on a treadmill using a ramp protocol to exhaustion. They measured oxygen consumption at rest (prior to running), at anaerobic threshold (AT), at respiratory compensation point (RCP), and peak consumption. Values were provided on an absolute basis (mL/min) at rest, AT, RCP. VO2 peak was presented on absolute and relative basis (relative to total body weight and fat free mass [FFM]; L/min/kg). The absolute oxygen consumption at rest, at RCP, and peak consumption were higher in the TW group relative to the CW group. This is not surprising since the average body weight of the TW was 22% heavier than the CW group.
Conceptually speaking, someone that is heavier (i.e. has a higher fat free mass) is more metabolically active and will consume more oxygen per time period. The authors do present peak oxygen consumption normalized to total body weight and fat free mass. When doing so, differences in the peak oxygen consumption disappear. In fact, when normalized to FFM, VO2 peak was 11% less in the TW group relative to the CW group although the differences were not statistically different. When corrected to body weight, no differences in oxygen consumption were observed between the CW and TW groups (Rest - 4.2 vs 4.0L/kg/min; AT - 21.6 vs. 21.5L/kg/min; RCP - 29.6 vs. 31.5 L/kg/min; Peak - 33.4 vs 35.7 L/kg/min). This is an important point because it suggests that there are no differences in cardiopulmonary capacity in TW compared to CW when normalized to body weight. Although these subjects reported high activity levels, the peak oxygen consumption (VO2 peak) for the CW, TW, and CM groups was roughly half the VO2 peak observed in most elite athletes (>60 L/kg/min). These results should not be extrapolated to elite athletes.
The authors also assessed grip strength to evaluate whether there were any strength differences between TW and CW and CM. There was a statistically significant increase in grip strength between TW and CW, however this finding was no longer significant after normalizing to body weight. Nevertheless, it is unclear the relevance of grip strength to predicting any performance advantage to most elite or professional sports.
Owing to the scientific rigor and careful interpretation of results from previous case-control and prospective research studies, the results from these studies have advanced our understanding of the physiological changes associated with testosterone exposure during puberty and subsequent withdrawal on human exercise performance. The amalgamation of the available data has allowed sports’ governing bodies the ability to make highly informed policy decisions on managing a balance between inclusivity and fairness in female transgender athletes. It is incumbent that all new studies in this area of research are of high scientific rigor and the associated conclusions are appropriate for the data that are presented because the results and the language used have imminent ramifications for the inclusion of transgender athletes to compete in sport. The conclusions presented by Alvares et al are incomplete and not fully supported by the data. Further and perhaps more importantly, the conclusions by the authors suggesting that TW have higher cardiopulmonary function (unadjusted for body weight) is harmful to the sporting community at large because it submits false evidence of a competitive advantage. Although the study was conducted in non-athletes, the authors suggest the results from their study may inform inclusion policies for transgender athletes. In fact, the data from Alvares et al suggest that TW do not have improved cardiopulmonary function relative to CW or TW when normalized to body weight. Thus, the study does not provide evidence of a competitive advantage in sports in this small cohort of non-athletes. As such, it does not support further restrictions of transgender athletes from sport.
Tarp et al. evaluated the associations of total and intensity-specific physical activity and all-cause mortality (1). Compared with the obese-low total physical activity reference, the hazard ratios (HRs) (95% confidence intervals [CIs]) of subjects with normal weight-high total activity and obese-high total activity for mortality were 0.59 (0.44 to 0.79) 0.67 (0.48 to 0.94), respectively. In contrast, the HR (95% CI) of subjects with normal weight-low total physical activity for mortality was 1.28 (0.99 to 1.67). Physical activity has a preventive effect on mortality regardless of obesity, and I have some comments about the study with special reference to sedentary time and aging.
Li et al. reported that the adjusted HRs (95% CIs) of daily sedentary time per 1 hour increase for all-cause mortality was 1.03 (1.01-1.05) and significant increase of the adjusted HR was observed in subjects with daily sedentary time of 8 or longer (2). This means that physically inactive lifestyle has an effect on increased risk in mortality, and physical activity and sedentary behaviour should be checked simultaneously. In addition, I suppose that the content of physical activity should be specified; such as leisure-time and work-related activity.
Yang et al. conducted a meta-analysis to evaluate the effect of physical activity and sedentary behaviour over adulthood on all-cause and cause-specific mortality (3). They clarified that active subjects over adulthood was significantl...
Tarp et al. evaluated the associations of total and intensity-specific physical activity and all-cause mortality (1). Compared with the obese-low total physical activity reference, the hazard ratios (HRs) (95% confidence intervals [CIs]) of subjects with normal weight-high total activity and obese-high total activity for mortality were 0.59 (0.44 to 0.79) 0.67 (0.48 to 0.94), respectively. In contrast, the HR (95% CI) of subjects with normal weight-low total physical activity for mortality was 1.28 (0.99 to 1.67). Physical activity has a preventive effect on mortality regardless of obesity, and I have some comments about the study with special reference to sedentary time and aging.
Li et al. reported that the adjusted HRs (95% CIs) of daily sedentary time per 1 hour increase for all-cause mortality was 1.03 (1.01-1.05) and significant increase of the adjusted HR was observed in subjects with daily sedentary time of 8 or longer (2). This means that physically inactive lifestyle has an effect on increased risk in mortality, and physical activity and sedentary behaviour should be checked simultaneously. In addition, I suppose that the content of physical activity should be specified; such as leisure-time and work-related activity.
Yang et al. conducted a meta-analysis to evaluate the effect of physical activity and sedentary behaviour over adulthood on all-cause and cause-specific mortality (3). They clarified that active subjects over adulthood was significantly associated with lower all-cause and cardiovascular-disease mortality compared with inactive subjects. Lowering sedentary time is important for the risk reduction of mortality, and physical activity in adults with daily sedentary job may be effective to avoid the mortality risk. To evaluate the beneficial health effects of keeping activity and avoiding sedentary time, health-related behaviours such as smoking, alcohol consumption, sleeping habit and diet, should be appropriately adjusted. In addition, socioeconomic differences might mediate the effect of these health behaviours on subsequent risk of all-cause and cause-specific mortality (4).
Aging is closely related to subsequent comorbidities and status of medical cares may influence the risk of mortality (5). This means that age-related factors, including the level of frailty, would interact with the association between physical activity, sedentary behaviour and mortality (6). Recommendation of desirable health habits should be made to reduce the mortality risk among older subjects.
References
1. Tarp J, Fagerland MW, Dalene KE, et al. Device-measured physical activity, adiposity and mortality: a harmonised meta-analysis of eight prospective cohort studies. Br J Sports Med 2022;56:725-32.
2. Li Y, Zhou Q, Luo X, et al. Association between sedentary time and 6-year all-cause mortality in adults: The rural Chinese cohort study. J Nutr Health Aging 2022;26:236-42.
3. Yang Y, Dixon-Suen SC, Dugué PA, et al. Physical activity and sedentary behaviour over adulthood in relation to all-cause and cause-specific mortality: a systematic review of analytic strategies and study findings. Int J Epidemiol 2022;51:641-67.
4. Petrovic D, de Mestral C, Bochud M, et al. The contribution of health behaviors to socioeconomic inequalities in health: A systematic review. Prev Med 2018;113:15-31.
5. Dugravot A, Fayosse A, Dumurgier J, et al. Social inequalities in multimorbidity, frailty, disability, and transitions to mortality: a 24-year follow-up of the Whitehall II cohort study. Lancet Public Health 2020;5:e42-e50.
6. Hanlon P, Nicholl BI, Jani BD, et al. Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants. Lancet Public Health 2018;3:e323-e332.
I read with great interest the study by Atakan et al., (2022) where they summarize existing evidence regarding the effect of high intensity interval training (HIIT) and sprint interval training (SIT) over fat oxidation during sub-maximal intensity exercise. An impaired fat oxidation is a common feature of patients with obesity and type 2 diabetes. Thus, this meta-analysis provides novel information that could be used by physicians and personal trainers to improve the metabolic health of the above mentioned populations. In this rapid response, I discuss several issues regarding data collection process, statistical modelling and interpretation of the reported findings that raised up after a deep analysis of the studies included in this meta-analysis.
The first meta-analysis of this study evaluated the effect of HIIT/SIT over exercise fat oxidation, summarizing the data from nine studies (Fig. 1). The findings of this meta-analysis are reported in g/min, nevertheless, Arad et al. (60) reported fat oxidation (Fox) relative to fat-free mass (mg∙kg FFM-1∙ min-1), Nybo et al. (30) reported Fox in kJ/min while Zapata-Lamana et al. (64) reported the relative contribution of lipids to energy expenditure. Of note, the authors do not report to request the fat oxidation in g/min from these studies (see data extraction section). Then, ¿How did the authors computed Fox in g∙min-1?
Otherwise, Astorino et al. (44) and Schubert et al (33), evaluated the effect of both HIIT a...
I read with great interest the study by Atakan et al., (2022) where they summarize existing evidence regarding the effect of high intensity interval training (HIIT) and sprint interval training (SIT) over fat oxidation during sub-maximal intensity exercise. An impaired fat oxidation is a common feature of patients with obesity and type 2 diabetes. Thus, this meta-analysis provides novel information that could be used by physicians and personal trainers to improve the metabolic health of the above mentioned populations. In this rapid response, I discuss several issues regarding data collection process, statistical modelling and interpretation of the reported findings that raised up after a deep analysis of the studies included in this meta-analysis.
The first meta-analysis of this study evaluated the effect of HIIT/SIT over exercise fat oxidation, summarizing the data from nine studies (Fig. 1). The findings of this meta-analysis are reported in g/min, nevertheless, Arad et al. (60) reported fat oxidation (Fox) relative to fat-free mass (mg∙kg FFM-1∙ min-1), Nybo et al. (30) reported Fox in kJ/min while Zapata-Lamana et al. (64) reported the relative contribution of lipids to energy expenditure. Of note, the authors do not report to request the fat oxidation in g/min from these studies (see data extraction section). Then, ¿How did the authors computed Fox in g∙min-1?
Otherwise, Astorino et al. (44) and Schubert et al (33), evaluated the effect of both HIIT and SIT over fat oxidation. According to the study selection criteria employed by the authors, data from both training regimes must be included in the meta-analysis, giving a total of 11 data for the forest plot. Nevertheless, only the data from 9 studies is reported.
With regard to the first analysis reported in this study (Fig. 1), the authors stated that a random effects meta-analysis was performed. According to the description of the reported data “, a positive value indicates a larger increase in fat oxidation as a result of interval training compared with no exercise”, which suggest that authors employed the inverse-variance approach (not specified by the authors). If this is true, the forest plot suggest that 8/9 studies reported a larger increment of Fox in the experimental group when compared to observed modifications in the control group. Nevertheless, from 9 studies investigating the effects of HIIT/SIT over Fox (including 6 studies that evaluated maximal fat oxidation, MFO), only Jabbour and Lancu (47) and Zapata-Lamana et al. (64) reported a significant increment of Fox. Thus, there is a disagreement between the data reported by the studies and the data presented in the meta-analysis. Moreover, because Fox is reported in different units across studies, authors must employ standardized mean difference instead of mean difference. In addition, three of the included studies (44, 56, 64) performed the assessments of fat oxidation on three or more separate occasions. However, the authors do not describe how did they adjusted for repeated measures/multiple comparisons in their analysis. In this sense it would be more appropriate to employ the reported effect size reported or computed by each study (Cohens d for studies that performed only 2 measurements and n2p for studies that performed 3 measurements).
In agreement with the authors, criteria for interpreting whether the enhancement of Fox was substantial or poor remains undefined. However, from the analytical point of view, the observed increment of Fox must be higher than inter-day Fox variation. For example, previous studies report that MFO shows an inter-day variation between 11-26%1-3. Thus the increment of MFO must be larger than such variation, otherwise, authors are only reporting the variation in MFO between exercise test performed at baseline and after training intervention.
Finally, I would like to highlight that in spite HIIT/SIT induced a larger increment on fat oxidation rates in comparison to moderate intensity training (MOD), HIIT/SIT is not better for burning fat in comparison to MOD as equivocally interpreted by many readers who shared the findings from this study in different websites (see altmetric). Indeed, enhancing Fox would be useless if people keep training at high intensity (>85% of VO2max or %PPO) where fat oxidation became negligible. Of note, this meta-analysis does not discuss whether HIIT/SIT improves Fox in different intensity domains, including vigorous intensity. On the contrary, the results from this meta-analysis, suggest that HIIT/SIT and MOD must be combined; the HIIT/SIT will increase Fox during MOD which might contribute to reach a negative fat balance and prevent lipid accumulation in the sarcolemma which impairs insulin signaling.
Note: numbers in the parenthesis correspond to the reference number of the studies included in the meta-analysis.
References
1. Croci I, Borrani F, Byrne NM, et al. Reproducibility of Fatmax and fat oxidation rates during exercise in recreationally trained males [published correction appears in PLoS One. 2014;9(11):e114115. Byrne, Nuala [corrected to Byrne, Nuala M]; Wood, Rachel [corrected to Wood, Rachel E]; Hickman, Ingrid [corrected to Hickman, Ingrid J]]. PLoS One. 2014;9(6):e97930. Published 2014 Jun 2. doi:10.1371/journal.pone.0097930
2. Dandanell S, Præst CB, Søndergård SD, et al. Determination of the exercise intensity that elicits maximal fat oxidation in individuals with obesity. Appl Physiol Nutr Metab. 2017;42(4):405-412. doi:10.1139/apnm-2016-0518
3. Robles-González L, Gutiérrez-Hellín J, Aguilar-Navarro M, et al. Inter-Day Reliability of Resting Metabolic Rate and Maximal Fat Oxidation during Exercise in Healthy Men Using the Ergostik Gas Analyzer. Nutrients. 2021;13(12):4308. Published 2021 Nov 29. doi:10.3390/nu13124308
Singh and colleagues’ comprehensive systematic review of meta-analyses (97 reviews of 1039 trials including 128,119 participants) confirms that ‘physical activity (PA) is highly beneficial for improving symptoms of depression, anxiety and psychological distress’ with ‘effect size reductions in symptoms of depression (−0.43) and anxiety (−0.42) comparable to or slightly greater than those observed for psychotherapy and pharmacotherapy’.
This finding has important clinical implications and the authors conclude that PA should be included in public health guidelines as a mainstay approach (i.e. not just as an adjunct to psychological therapy and medication). They also recognise that ‘while the benefit of exercise for depression and anxiety is generally recognised, it is often overlooked in the management of these conditions’ .
Despite these really impressive results and their important clinical implications, it is unfortunate that the Singh et al review is unlikely to make a significant difference to clinical practice. There are many reasons why physical activity is not used as a first-line intervention for depression and other mental health problems, but one of the problems is that the field has not really addressed an issue I highlighted in a review of the field a quarter of a century ago. The evidence that PA can be an effective stand-alone or adjunctive intervention for a range of mental health problems is diluted amongst the public health/ mental wellbeing st...
Show MoreI read with interest the Saavedra et al.’s study1 aiming to evaluate the associations of cardiorespiratory fitness and body-mass-index with incident restrictive-ventilatory-impairment (RVI). The study’ rational is interesting since the RVI is frequent (eg; prevalence: 3 to 50%).2 One strong point of the aforementioned study1 was the use of the 2012 global-lung-function-initiative (GLI) task force of multi-ethnic norms for spirometry (GLI-2012).3 Saavedra et al.1 retained the diagnosis of a RVI in front of the combination of a low forced-vital-capacity (FVC) (ie; FVC < lower-limit-of-normal (LLN)) and a normal ratio between forced-expiratory-volume-in-one-second (FEV1) and FVC (ie; FEV1/FVC ≥ LLN). Saavedra et al.1 followed some “old” approaches. In 2022, the European-respiratory-society and the American-thoracic-society (ERS/ATS) published a “new” technical standard on interpretive strategies for lung function tests.4 This guidelines should be considered by researchers in the field of sports medicine.4 The definition applied by Saavedra et al.1 to retain the diagnosis of a RVI is questionable, and the following two points need to be clarified: i) what is a low spirometric data?, ii) what is a RVI?
Show MoreWhat is a low spirometric data?
Interpretation of spirometric data necessitates 2 steps: i) comparison of the spirometric data with these of reference.4 5 , and ii) comparison of the data’ value with the distinctive thresholds of the main ventilatory-impairment not...
We wish to commend Horan et al. (Horan et al., 2022) on their systematic review and meta-analysis which established overall, match and training IIRs in senior women’s football. It is encouraging to see continued work in this specific area of women’s football epidemiological research.
We would like to draw the authors attention to the following error contained within their work. We respectfully request that it is amended accordingly so that the readership are aware of all available work in this area.
Horan et al. (Horan et al., 2022) refer to the systematic review and meta-analysis of López Valenciano et al (López-Valenciano et al., 2021) which they report was recently ‘criticised’ in a published commentary by Mayhew et al (2021). The authors use the following citation:
30. Mayhew, L. et al. (2021) ‘Incidence of injury in adult elite women’s football: a systematic review and meta-analysis’, BMJ Open Sport & Exercise Medicine, 7(3), p. e001094. doi:10.1136/bmjsem-2021-001094
The readership should be aware that the citation Horan et al. (Horan et al., 2022) use in their work is not a published commentary but a systematic review and meta-analysis on the incidence of injury in elite women’s football. Our publication was PROSPERO registered and published ahead of Horan et al. (Horan et al., 2022) in BJSM’s sister journal (BMJ Open Sport & Exercise Medicine).
The corrected citation should be:
Mayhew, L., Johnson, M.I. and...
Show MoreI appreciate the thoughtful considerations raised. Scientific discussion is always the best way for the opportunity to review points, exchange thoughts and evolve in knowledge. Here are some additional considerations below:
- About strength and VO2peak controlled by FFM and/or weight:
We showed these data in the article (strength/FFM; VO2peak/FFM; VO2peak/weight) in the results and table 2. There are no statistical differences comparing all populations (TW,CM and CW).
- TW with 637 ng/dL testosterone on the day of the tests:
In the long-term follow-up of a cohort of individuals with daily medication use, temporary failures in the regular use of medications are not uncommon. One of the participants had a high level of testosterone at the time of the study. However, we emphasize that we were careful to assess testosterone levels in the year before the study so that we could confirm the correlation of the values obtained at the time of the study with those in the last year. In addition, the values of haemoglobin denoted testosterone supression in the past 4 months. Although one of the TW was not blocked on test day (total testosterone =637 ng/dL), her value was 79 ng/dL six months before the study. This point did not interfere with her VO2 results (supplementary figure 2).
- Weight and height:
Show MoreStudies in sports medicine generally eliminate the height as an interfering factor in the analyses.
Height is a consequent characteristic o...
There is absolutely no doubt that physical activity is a beautiful phenomenon. In the above study, the study is fair to the extent that those subjects who regularly exercised had lesser hospitalisations. Here both reason and effect exist, but can a direct causal relationship be established between the two?
Can it be inferred beyond doubt that "the vaccine prevented complications of Covid-19 because exercise strengthened the immune response? The possibility of such a remarkable effect in the short term is pretty unlikely. And all the more, such findings can't be generalised to a larger population.
Authors seem to be ignoring a hidden confounder affecting the validity of the study, and this confounder is 'frailty'. Simply those doing less exercise were unable to do so because they were frail. And obviously, frailty can be present independent of comorbidities like DM, heart failure or obesity, which were evenly matched between the high and low-exercise groups.
So, the correct conclusions will likely differ if this confounder is considered. one may not forget that 'Correlation, even if present in a statistically significant portion, may not amount to causation.
The study might prompt some frail people or even morbidly obese people to engage in heavy exercise soon after the vaccination despite muscle aches and fever (common side effects of the Covid-19 vaccines). And these might have disastrous consequences. So the wo...
Show MoreDear Editor:
Alvares et al. [1] conducted a study to compare performance-related measures such as cardiopulmonary exercise capacity and muscle strength in non-athlete transgender women (TW) undergoing long-term gender-affirming hormone therapy to non-athlete cisgender men (CM) and non-athlete cisgender women (CW). The authors report higher absolute VO2peak (L/min) and muscle strength (kg) in TW compared to CW and lower than CM. The authors conclude that their “…findings could inform policy and help in decisions about the participation of transgender women in sporting activities”.
However, the authors interpreted their findings on the basis of the absolute data they present and not the relative data that was controlled for body mass and fat-free mass (FFM), as would be appropriate for comparisons of such performance metrics (e.g., aerobic capacity and muscle strength). By focusing on the absolute data, the authors over-emphasise differences between comparison groups (e.g., TW and CW) that are clearly driven by differences in anthropometry. For example, when the data reported in Table 2 [1] are corrected for body mass and fat-free mass (FFM), differences in aerobic capacity and strength between TW and CW disappear. Yet, in the section “WHAT THIS STUDY ADDS” [1], which is the primary focus of many readers, the authors omit the results that control for body mass and FFM, instead leaving the reader with the misleading message that “[t]he mean strength and VO2peak...
Show MoreThe topic of transgender inclusion in women’s sports is politically fraught. Sport’s governing bodies are grappling with the competing priorities of inclusivity and fairness due to any perceived competitive advantage above and beyond the large and broad continuum of biological variables found within cisgender women (e.g. height, bone mass, bone length, fiber cross-sectional diameter, etc.) associated with testosterone exposure during puberty. This active area of research is rapidly evolving due to the multitude of new studies published over the previous 5 years. In fact, there have been over a dozen primary prospective and case-control research studies published on this topic since 2018 resulting in the lowering of the maximum allowable testosterone level in transgender elite athletes (i.e., from 5.0 to 2.5nmol/L) by several sports’ governing bodies.
The preponderance of evidence suggests that hematological differences in hematocrit, red cell number, and hemoglobin are largely normalized within 120 days of testosterone suppression, which is biologically plausible as this corresponds with the average lifespan of a red cell (~ 120 days). Since oxygen delivery to peripheral tissues is performance limiting in aerobic sports, any competitive advantage is likely largely diminished within a year of testosterone suppression. Studies evaluating changes in strength, muscle mass, and body composition are more equivocal and most likely occur over a longer time span (12-36 mon...
Show MoreI suggest the basis of the Ezzatvar, et al., report is increased dehydroepiandrosterone (DHEA). It is known exercise increases DHEA. It is my hypothesis of 2020 that low DHEA is linked to the severity of Covid-19 infection and subsequent pathology (© Copyright 2020, James Michael Howard, Fayetteville, Arkansas, U.S.A.) New research, 2022, regarding DHEA has been published that supports my hypothesis that severe Covid-19 illness is associated with low DHEA: “COVID-19 patients with altered steroid hormone levels are more likely to have higher disease severity,” ( 2022 Jul 30. doi: 10.1007/s12020-022-03140-6.) “DHEA was an independent indicator of the disease severity with COVID-19.”
Tarp et al. evaluated the associations of total and intensity-specific physical activity and all-cause mortality (1). Compared with the obese-low total physical activity reference, the hazard ratios (HRs) (95% confidence intervals [CIs]) of subjects with normal weight-high total activity and obese-high total activity for mortality were 0.59 (0.44 to 0.79) 0.67 (0.48 to 0.94), respectively. In contrast, the HR (95% CI) of subjects with normal weight-low total physical activity for mortality was 1.28 (0.99 to 1.67). Physical activity has a preventive effect on mortality regardless of obesity, and I have some comments about the study with special reference to sedentary time and aging.
Li et al. reported that the adjusted HRs (95% CIs) of daily sedentary time per 1 hour increase for all-cause mortality was 1.03 (1.01-1.05) and significant increase of the adjusted HR was observed in subjects with daily sedentary time of 8 or longer (2). This means that physically inactive lifestyle has an effect on increased risk in mortality, and physical activity and sedentary behaviour should be checked simultaneously. In addition, I suppose that the content of physical activity should be specified; such as leisure-time and work-related activity.
Yang et al. conducted a meta-analysis to evaluate the effect of physical activity and sedentary behaviour over adulthood on all-cause and cause-specific mortality (3). They clarified that active subjects over adulthood was significantl...
Show MoreI read with great interest the study by Atakan et al., (2022) where they summarize existing evidence regarding the effect of high intensity interval training (HIIT) and sprint interval training (SIT) over fat oxidation during sub-maximal intensity exercise. An impaired fat oxidation is a common feature of patients with obesity and type 2 diabetes. Thus, this meta-analysis provides novel information that could be used by physicians and personal trainers to improve the metabolic health of the above mentioned populations. In this rapid response, I discuss several issues regarding data collection process, statistical modelling and interpretation of the reported findings that raised up after a deep analysis of the studies included in this meta-analysis.
The first meta-analysis of this study evaluated the effect of HIIT/SIT over exercise fat oxidation, summarizing the data from nine studies (Fig. 1). The findings of this meta-analysis are reported in g/min, nevertheless, Arad et al. (60) reported fat oxidation (Fox) relative to fat-free mass (mg∙kg FFM-1∙ min-1), Nybo et al. (30) reported Fox in kJ/min while Zapata-Lamana et al. (64) reported the relative contribution of lipids to energy expenditure. Of note, the authors do not report to request the fat oxidation in g/min from these studies (see data extraction section). Then, ¿How did the authors computed Fox in g∙min-1?
Otherwise, Astorino et al. (44) and Schubert et al (33), evaluated the effect of both HIIT a...
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