Abstract
Objectives
Lower limb tendinopathy (LLT) is highly prevalent in runners. Treatment can be challenging, and knowledge of risk factors may be valuable to develop preventive or treatment interventions for LLT. The aims of this study were (1) to assess the prevalence of three common LLTs (Achilles tendinopathy (AT), patellar tendinopathy and plantar fasciopathy) in a large cohort of Dutch and Belgian runners and (2) to investigate its association with potential risk factors, with a particular focus on nutritional factors in the habitual diet.
Methods
A total of 1993 runners were included in the study. They completed two online questionnaires: a general questionnaire on running habits and injuries and a Food Frequency Questionnaire. Runners with and without LLT were compared regarding personal characteristics, running characteristics and nutritional factors.
Results
The point prevalence for the three LLTs was 6%; 33% of the runners reported LLT in the past and 35% had either a current or past LLT. AT was the most prevalent type of LLT, and prevalence rates for all types of LLT were higher in men than women. Positive associations with LLT were observed for age and running years (men and women), running level and running distance (men). No associations between LLT and nutritional factors were observed.
Conclusion
One-third of this population of runners had ever experienced an LLT. These tendinopathies were associated with gender, age and running load, but not with nutritional factors.
Keywords: Tendinopathy, Nutrition, Running
WHAT IS ALREADY KNOWN ON THIS TOPIC
Lower limb tendinopathy (LLT) is highly prevalent in runners and has a multifactorial aetiology.
Preclinical and animal studies have shown that various nutrients can play a role in (mal)adaptation and repair of tendons. However, knowledge of the role of nutrition, and especially habitual dietary intake, in human tendon health is scarce.
WHAT THIS STUDY ADDS
This study confirms that LLT is common in runners and that running load is an associated factor.
LLT was not associated with habitual dietary intake in our population of runners with a relatively high diet quality.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
Future prospective studies in (novice) runners with an average or low diet quality could provide more insight into the relationship between nutrition and the development of LLT.
Introduction
Tendinopathy is persistent tendon pain and loss of function related to mechanical loading.1 Lower limb tendinopathy (LLT) is highly prevalent in runners. Common types of LLT in runners are Achilles tendinopathy (AT), patellar tendinopathy (PT) and plantar fasciopathy (PF).2 Prevalence rates vary between studies because of different definitions and study populations used. In a review on the prevalence of running-related injuries, prevalence rates of 6.2%–9.5% were found for AT, 12.5% for PT and 5.2%–17.5% for PF.2 Tendinopathy may negatively affect the quality of life by its impact on activities of daily living, health, sports performance, workability and other activities.3 4 Treatment of LLT can be challenging, is not completely evidence-based and should at least include load management, pain education and progressive tendon loading exercises.5 6
LLT is considered to have a multifactorial aetiology with mechanical overload as an important risk factor. Besides mechanical overload, sex, age, body weight, medical conditions such as obesity and diabetes as well as genetic factors are also associated with tendinopathy.7–9 More knowledge of risk factors may be valuable to develop preventive or treatment interventions for LLT.
Tendinopathy is characterised by altered tissue homoeostasis.10 Nutrition plays a major role in tendon homoeostasis; and adequate nutrient intake is essential for recovery and maintaining homoeostasis. Nutritional interventions may, therefore, be useful for the prevention or treatment of LLT. Preclinical and animal studies have shown that various nutrients such as collagen, proteins, specific amino acids (leucine, arginine, glutamine), vitamins C and D, manganese, copper and zinc can play a role in (mal)adaptation and repair of tendons.11 12 However, knowledge of the role of nutrition, especially habitual dietary intake, in human tendon health is scarce. More research on this topic is necessary to investigate the potential benefits of nutritional interventions.13
The aims of this study are (1) to assess the prevalence of three common LLTs (AT, PT and PF) in a large cohort of runners and (2) to investigate its association with potential risk factors, with a particular focus on nutritional factors in the habitual diet.
Methods
Study design
The Eat2Run study is an observational study with a cross-sectional design. Participants were runners who completed two online questionnaires: a general questionnaire and a Food Frequency Questionnaire (FFQ). The general questionnaire contained questions about gender, age, anthropometric data, running habits, current and past injuries, abdominal complaints, and general health issues. The FFQ was used to assess habitual dietary intake.
Study population
In July 2021, recruitment of runners started by requesting athletics clubs and running event organisations in the Netherlands and Belgium, among which the popular Dutch Seven Hills run in Nijmegen, to help with the recruitment by posting a news item in their newsletter or on their website. In the second stage, social media (Facebook, Twitter, Linkedin) were also used for recruitment. Finally, in March 2022, participants of the 2022 edition of the well-known Rotterdam Marathon who indicated a willingness to participate in scientific studies, were invited. When the recruitment period closed on 1 June 2022, 3643 runners had expressed interest for the study, although not all fulfilled the inclusion criteria.
To be included in the present analyses, runners (1) had to be at least 18 years old, (2) had to run at least once a week in the past year, no matter the time or distance, or would usually run at least once a week if they had not been injured, (3) had to complete both the general questionnaire and the FFQ and (4) their reported habitual dietary intake in the FFQ had to be plausible (see the paragraph on Assessment of dietary intake and diet quality). Finally, 1993 runners could be included in the data analyses (see the Results section).
Assessment of tendinopathy
Information on current or past injuries was obtained from the general questionnaire. An injury was defined according to the International Olympic Committee consensus statement: ‘Injury is tissue damage or other derangement of normal physical function due to participation in sports, resulting from rapid or repetitive transfer of kinetic energy’.14 The presence of current or past running-related AT, PT and PF was identified when this definition could be applied to specified locations on the heel, knee and foot, respectively, on standardised pain maps included in the questionnaire.
Runners with current LLT were asked to rate its severity. For this purpose, the Victorian Institute of Sport Assessment-Achilles tendon questionnaire (VISA-A),15 16 the Victorian Institute of Sport Assessment-Patellar tendon questionnaire (VISA-P)17 18 and the Foot Function Index with Verbal Rating Scales questionnaire (FFI-5pt)19 were included in the general questionnaire. The VISA-A and VISA-P questionnaires contain eight questions for rating pain, function and sports participation. The total scores range from 0 (worst) to 100 points. The FFI-5pt consists of 23 items. The FFI score is total points/230×100%, with 100% being the worst.
Assessment of dietary intake and diet quality
The FFQ was used to assess dietary intake over the past month. A comprehensive FFQ, validated for energy intake, macronutrients, dietary fibre and vitamins, was used to assess the frequency of consumption of 180 food items.20 21 Portion sizes were estimated using natural portions and commonly used household measures. From the FFQ data, the average daily intake of foods and food groups was calculated. Data were also converted into average daily energy and nutrient intake using the Dutch food composition database of 2011.22 Runners reporting an implausible habitual dietary intake, that is, energy intake <800 and >4200 kcal for men and <500 and >3500 kcal for women,23 24 were excluded from the analyses.
In addition to absolute energy and nutrient intake, diet quality was also assessed. For this purpose, the Dutch Healthy Diet index 2015 (DHD2015-index)25 was calculated from FFQ data. The DHD2015-index is a measure of adherence to the 2015 Dutch dietary guidelines.26 27 The original index consists of 15 components; recently a component on unhealthy foods has been added.28 For all the components, a score is assigned based on the intake of the specific food group, ranging from 0 to 10 points (online supplemental table 1). This results in a total DHD2015-index score ranging from 0 to 160 points, with a higher score indicating better adherence to the guidelines. From the FFQ used in the current study, data on two components (coffee and salt) were unavailable, which were therefore not included in the DHD2015-index calculations. This results in total scores ranging from 0 to 140 points in the current study. A more detailed description of the DHD2015-index and scoring per component can be found elsewhere.25
bmjsem-2023-001570supp001.pdf (68KB, pdf)
Statistical analyses
Continuous data were first checked for normality using a Kolmogorov-Smirnov test and visual inspection of Q-Q normality plots. After that, descriptive analyses were performed. Personal characteristics, running characteristics, nutritional factors and prevalence of AT, PT and PF were examined in the total population and per gender. As the continuous data were not normally distributed, these data are presented as median (25–75th percentile); categorical variables are presented as n (%).
Differences between men and women were assessed using a Mann-Whitney U test for continuous variables and a Pearson χ2 test for categorical variables. Gender-neutral runners and runners who did not fill in their gender were not compared with other groups because these groups were too small.
Next, runners with any of the three common LLTs were compared with runners without any of these LLTs. Differences between these two groups in personal characteristics, running characteristics and nutritional factors were assessed using a Mann-Whitney U test for continuous variables and a Pearson χ2 test for categorical variables. No distinction was made between current or past LLT because the absolute number of runners with current tendinopathy was quite low. Analyses were performed separately for men and women.
The significance level for the above-mentioned statistical tests was set at 5%, that is, p<0.05.
Finally, associations between LLT and potential risk factors were investigated using logistic regression analysis. This analysis was performed in the total population. Prevalence of any of the three common LLTs, present or past (yes/no), was used as a dichotomous dependent variable. Personal characteristics, including gender and running characteristics that differed between runners with and without LLT in the total population (p<0.20), and the total DHD2015-index score, were used as independent variables. The linearity of continuous independent variables and log-odds of LLT prevalence was assessed using the Box-Tidwell procedure. In case of non-linearity, the independent variable was converted into a categorical variable. A full multivariable model was fitted using data from runners without missing values (n=1967) to estimate ORs with 95% CIs for the independent variables. A backward stepwise selection procedure was used to select the strongest risk factors. The selection was based on Akaike’s information criterion, corresponding to a p value of 0.157 for a predictor with one regression coefficient.29
Statistical analyses were performed with SPSS software (V.25, IBM).
Results
Study population
A total of 3643 runners expressed their interest for the study. From these, 2118 runners completed both questionnaires. Five runners were excluded because they were younger than 18 years or did not report their age. Sixty-nine runners were excluded because they did not run, or would not have run if not injured, at least once a week in the past year. Finally, 51 runners were excluded because they reported implausible dietary intake. A total of 1993 runners (891 men, 1095 women, 5 gender-neutral, 2 who did not fill in their gender) were included in the study.
The median (25–75th percentile) age for the total population was 44 (34–54) years. The running level of most runners (76%) was considered intermediate, and about half of the runners (49%) ran for at least 10 years. The median number of running sessions per week was 3 (2–4), and the median distance covered per week was 30 (20–42) km. Compared with women, men had been running for more years, ran more often and more kilometres per week, and trained at a higher intensity. A more detailed overview of personal and running characteristics is presented in online supplemental table 2.
bmjsem-2023-001570supp002.pdf (71KB, pdf)
The median energy intake in the total population was 2095 (1700–2538) kcal. Besides vitamin C, energy intake, and the intake of macronutrients and micronutrients were higher in men than women. When expressed as energy percentage (En%), intake of carbohydrates, fat and protein were comparable for men and women (online supplemental table 3). Diet quality (the total DHD2015-index score) was higher in women than men: median (25–75th percentile): 96.3 (85.0–106.3) vs 88.7 (77.1–100.2). Women scored higher on most component scores, except for wholegrain products, on which men scored higher (online supplemental table 4).
bmjsem-2023-001570supp003.pdf (77.1KB, pdf)
bmjsem-2023-001570supp004.pdf (66.2KB, pdf)
Prevalence of LLT
A total of 116 runners (6%) had current LLT; 3% AT, 2% PT and 1% PF. Past LLT was reported by 664 runners (33%); 19% AT, 12% PT and 8% PF. In total, 691 runners (35%) reported either having current or past LLT or both. For all types of tendinopathy, currently or in the past, prevalence rates were significantly higher in men than women (table 1).
Table 1.
Prevalence of tendinopathy
| Total (n=1993)* |
Men (n=891) |
Women (n=1095) |
P value men vs women† | |
| Current lower limb tendinopathy‡ | 116 (6) | 68 (8) | 48 (4) | 0.002 |
| Current Achilles tendinopathy | 63 (3) | 38 (4) | 25 (2) | 0.012 |
| Current patellar tendinopathy | 31 (2) | 20 (2) | 11 (1) | 0.027 |
| Current plantar fasciopathy | 25 (1) | 10 (1) | 15 (1) | 0.623 |
| Past lower limb tendinopathy‡ | 664 (33) | 344 (39) | 318 (29) | <0.001 |
| Past Achilles tendinopathy | 383 (19) | 219 (25) | 163 (15) | <0.001 |
| Past patellar tendinopathy | 240 (12) | 124 (14) | 116 (11) | 0.024 |
| Past plantar fasciopathy | 152 (8) | 66 (7) | 85 (8) | 0.766 |
| Current or past lower limb tendinopathy‡ | 691 (35) | 361 (41) | 328 (30) | <0.001 |
Data are presented as n (%).
*The total population includes five gender-neutral runners and two runners who did not fill in their gender.
†P values were obtained with a Pearson χ2 test; statistical significance (p<0.05) is indicated in bold.
‡Either Achilles tendinopathy, patellar tendinopathy and/or plantar fasciopathy. The prevalence of any injuries is unequal to the sum of the prevalence of the separate injuries because some runners had more than one injury, currently and/or in the past.
The VISA-A. VISA-P and FFI questionnaires were completed by 55 runners with current AT, 26 with current PT and 23 with current PF. The median (25–75th percentile) score for the VISA-A was 44 (39–51), for the VISA-P 46 (40–54) and for the FFI 18 (13–25).
Association of population characteristics and nutritional factors with LLT
In both men and women, runners with LLT were older and had been running for more years than runners without LLT. In men only, runners with LLT were more competitive, ran more kilometres per week and ran more often in competitions. In women only, runners with LLT ran less often on a hard surface and more often on other surfaces than runners without LLT (table 2).
Table 2.
Personal characteristics and running characteristics in runners with and without current or past tendinopathy
| Men (n=891) | Women (n=1095) | |||||
| No LLT (n=530) | LLT (n=361) | P value* | No LLT (n=767) | LLT (n=328) | P value* | |
| Age, years | 45 (36–56) | 51 (40–58) | <0.001 | 41 (31–51) | 47 (34–54) | <0.001 |
| BMI, kg/m2 | 23.0 (21.5–24.5) | 22.7 (21.5–24.3) | 0.343 | 21.6 (20.2–23.3) | 21.9 (20.2–23.7) | 0.171 |
| Running level | 0.026 | 0.701 | ||||
| Beginner | 13 (3) | 3 (1) | 28 (4) | 9 (3) | ||
| Intermediate, not competitive | 381 (72) | 237 (66) | 624 (81) | 266 (81) | ||
| Competitive (in age group) | 133 (25) | 117 (32) | 110 (14) | 52 (16) | ||
| (Semi)professional | 3 (1) | 4 (1) | 5 (1) | 1 (0) | ||
| Running years | <0.001 | <0.001 | ||||
| < 1 year | 10 (2) | 2 (1) | 23 (3) | 6 (2) | ||
| 1–2 years | 49 (9) | 13 (4) | 77 (10) | 16 (5) | ||
| 3–5 years | 102 (19) | 51 (14) | 176 (23) | 63 (19) | ||
| 6–9 years | 111 (21) | 69 (19) | 178 (23) | 60 (18) | ||
| ≥ 10 years | 256 (48) | 225 (62) | 313 (41) | 183 (56) | ||
| Running, times/week | 3.0 (2.0–4.0) | 3.0 (3.0–4.0) | 0.196 | 3.0 (2.0–3.0) | 3.0 (2.0–3.0) | 0.948 |
| Running, km/week | 30 (22–48) | 35 (25–50) | 0.047 | 25 (17–40) | 25 (18–40) | 0.990 |
| Longest distance per week (km) | 16 (12–21) | 16 (12–20) | 0.943 | 12 (10–17) | 12 (10–16) | 0.848 |
| Intensity most intensive training | 0.213 | 0.531 | ||||
| Moderately intensive | 127 (24) | 70 (19) | 212 (28) | 81 (25) | ||
| Moderately intensive | 261 (49) | 181 (50) | 395 (52) | 180 (55) | ||
| Moderately intensive | 142 (27) | 110 (31) | 160 (21) | 67 (20) | ||
| Running in competitions (yes) | 415 (78) | 319 (88) | <0.001 | 156 (20) | 273 (83) | 0.170 |
| Km on current shoes | 500 (250–700) | 500 (200–700) | 0.700 | 400 (200–643) | 450 (200–689) | 0.585 |
| Main surface | 0.305 | 0.027 | ||||
| Running track | 2 (0) | 6 (2) | 10 (1) | 5 (2) | ||
| Hard surface | 326 (62) | 209 (58) | 453 (59) | 162 (49) | ||
| Soft surface | 36 (7) | 27 (8) | 68 (9) | 43 (13) | ||
| Treadmill | 2 (0) | 1 (0) | 2 (0) | 0 (0) | ||
| Various | 164 (31) | 118 (33) | 234 (31) | 118 (36) | ||
| Warming up (yes) | 322 (61) | 247 (68) | 0.050 | 472 (62) | 221 (67) | 0.156 |
| Other sports besides running in past year (yes) | 277 (52) | 182 (50) | 0.837 | 503 (66) | 235 (72) | 0.050 |
| Other sports besides running (hours per week) |
3.0 (2.0–5.0) | 3.0 (2.0–5.0) | 0.121 | 3.0 (2.0–5.0) | 3.0 (2.0–4.0) | 0.136 |
Data are presented as median (25–75th percentile) for continuous variables, and n (%) for categorical variables.
*P values were obtained with a Mann-Whitney U test for continuous variables and a Pearson χ2 test for categorical variables; statistical significance (p<0.05) is indicated in bold.
BMI, body mass index; LLT, lower limb tendinopathy.
No energy and nutrient intake differences were observed between runners with and without LLT. When we corrected energy and nutrient intake for body weight, also no differences in intake between participants with and without LLT were observed (table 3).
Table 3.
Daily energy and nutrient intake in runners with and without current or past tendinopathy
| Men (n=891) | Women (n=1095) | |||||
| No LLT (n=530) | LLT (n=361) | P value* | No LLT (n=767) | LLT (n=328) | P value* | |
| Energy (kcal) | 2373 (1950–2775) | 2347 (1971–2875) | 0.797 | 1901 (1580–2251) | 1853 (1525–2304) | 0.698 |
| Total carbohydrates | ||||||
| (g) | 260 (211–310) | 257 (209–317) | 0.900 | 209 (170–250) | 206 (168–253) | 0.905 |
| (En%) | 44 (41–47) | 44 (41–47) | 0.377 | 44 (41–48) | 44 (41–48) | 0.323 |
| Monosaccharides and disaccharides (g) | 103 (81–127) | 104 (78–129) | 0.777 | 94 (74–115) | 96 (76–117) | 0.362 |
| Polysaccharides (g) | 155 (124–191) | 154 (121–186) | 0.585 | 113 (87–142) | 115 (85–142) | 0.871 |
| Total fat | ||||||
| (g) | 92 (73–114) | 95 (74–116) | 0.616 | 75 (58–92) | 76 (59–97) | 0.232 |
| (En%) | 36 (32–39) | 36 (32–39) | 0.664 | 36 (32–39) | 37 (33–40) | 0.148 |
| Saturated fatty acids (g) | 31 (24–38) | 31 (23–40) | 0.911 | 25 (19–31) | 25 (19–35) | 0.242 |
| Monounsaturated fatty acids (g) | 33 (26–42) | 35 (27–42) | 0.447 | 28 (21–35) | 28 (23–36) | 0.267 |
| Polyunsaturated fatty acids (g) | 20 (15–25) | 20 (15–25) | 0.997 | 15 (11–20) | 15 (12–20) | 0.638 |
| Alpha-linoleic acid (g) | 1.95 (1.53–2.50) | 1.96 (1.47–2.56) | 0.555 | 1.61 (1.24–2.02) | 1.58 (1.25–2.09) | 0.539 |
| Eicosapentaenoic acid (g) | 0.08 (0.04–0.13) | 0.08 (0.5–0.14) | 0.633 | 0.08 (0.03–0.14) | 0.09 (0.04–0.13) | 0.331 |
| Docosahexaenoic acid (g) | 0.10 (0.04–0.17) | 0.10 (0.05–0.17) | 0.616 | 0.10 (0.02–0.18) | 0.12 (0.04–0.17) | 0.574 |
| Cholesterol (mg) | 218 (158–295) | 217 (155–298) | 0.963 | 182 (126–249) | 183 (134–241) | 0.947 |
| Total protein | ||||||
| (g) | 86 (72–102) | 87 (73–103) | 0.349 | 70 (57–83) | 70 (56–85) | 0.955 |
| (En%) | 14 (13–16) | 15 (13–16) | 0.110 | 15 (13–16) | 15 (13–16) | 0.721 |
| Vegetable protein (g) | 44 (35–55) | 43 (35–55) | 0.943 | 36 (27–43) | 34 (27–43) | 0.832 |
| Animal protein (g) | 41 (31–52) | 41 (31–54) | 0.533 | 35 (25–45) | 35 (25–45) | 0.796 |
| Alcohol (g) | 6 (2-13) | 6 (1-13) | 0.660 | 3 (0–8) | 3 (0–8) | 0.672 |
| Fibre (g) | 29 (22–36) | 28 (23–35) | 0.861 | 24 (19–30) | 24 (19–30) | 0.945 |
| Retinol (µg) | 467 (296–670) | 475 (311–700) | 0.605 | 325 (213–469) | 319 (213–465) | 0.806 |
| Retinol equivalents (µg) | 843 (611–1170) | 848 (607–1136) | 0.870 | 785 (587–1039) | 812 (550–1058) | 0.611 |
| Vitamin B1 (mg) | 1.1 (0.9–1.3) | 1.1 (0.9–1.3) | 0.444 | 0.9 (0.7–1.0) | 0.9 (0.7–1.1) | 0.438 |
| Vitamin B2 (mg) | 1.6 (1.3–2.0) | 1.6 (1.3–2.0) | 0.495 | 1.3 (1.1–1.6) | 1.3 (1.1–1.7) | 0.294 |
| Vitamin B6 (mg) | 1.8 (1.4–2.2) | 1.8 (1.5–2.1) | 0.753 | 1.5 (1.2–1.8) | 1.5 (1.2–1.8) | 0.842 |
| Folate (present in food by nature) (µg) | 275 (222–340) | 277 (223–340) | 0.919 | 261 (209–316) | 256 (213–317) | 0.960 |
| Folate equivalents (µg) | 300 (239–384) | 296 (238–379) | 0.835 | 279 (223–342) | 275 (227–343) | 0.943 |
| Vitamin B12 (µg) | 4.2 (3.2–5.7) | 4.3 (3.0–5.9) | 0.746 | 3.6 (2.5–4.9) | 3.7 (2.6–5.2) | 0.461 |
| Vitamin C (mg) | 89 (62–121) | 87 (65–117) | 0.678 | 93 (72–120) | 95 (75–123) | 0.301 |
| Vitamin D (µg) | 3.1 (2.2–4.5) | 3.3 (2.2–4.4) | 0.878 | 2.4 (1.7–3.4) | 2.4 (1.6–3.1) | 0.493 |
| Vitamin E (mg) | 15 (12–20) | 15 (12–19) | 0.483 | 13 (10–16) | 13 (10–16) | 0.893 |
| Calcium (mg) | 1007 (798–1303) | 1088 (810–1324) | 0.164 | 923 (734–1173) | 977 (723–1214) | 0.221 |
| Total iron (mg) | 13 (11–16) | 13 (11–16) | 0.544 | 11 (9–13) | 11 (9–13) | 0.735 |
| Haem iron (mg) | 0.8 (0.5–1.2) | 0.8 (0.5–1.2) | 0.709 | 0.6 (0.2–1.0) | 0.6 (0.3–1.1) | 0.965 |
| Non-haemiron (mg) | 12 (10–15) | 12 (10–15) | 0.578 | 11 (9–13) | 10 (9–13) | 0.970 |
| Magnesium (mg) | 429 (348–512) | 432 (355–524) | 0.659 | 362 (292–435) | 356 (293–435) | 0.878 |
| Zinc (mg) | 11 (9–14) | 12 (10–14) | 0.448 | 9 (8-11) | 9 (8-12) | 0.585 |
| Selenium (µg) | 47 (39–57) | 49 (40–57) | 0.548 | 40 (32–48) | 40 (33–49) | 0.631 |
Data are presented as median (25–75th percentile).
*P values were obtained with a Mann-Whitney U test.
LLT, lower limb tendinopathy.
The DHD2015-index score was not different between runners with and without LLT. Regarding component scores, women with LLT scored higher on legumes and nuts than women without LLT, and men with LLT scored higher on tea than men without LLT (table 4).
Table 4.
DHD2015-index score and its component scores in runners with and without current or past tendinopathy
| Men (n=891) | Women (n=1095) | |||||
| No LLT (n=530) | LLT (n=361) | P value* | No LLT (n=767) | LLT (n=328) | P value* | |
| DHD2015-index total score | 88.6 (76.6–99.7) | 89.0 (77.7–100.9) | 0.337 | 96.0 (84.5–105.6) | 97.6 (86.4–107.3) | 0.053 |
| DHD2015-index component scores | ||||||
| 1. Vegetables | 6.8 (3.8–10.0) | 6.8 (4.1–10.0) | 0.904 | 9.1 (5.8–10.0) | 9.9 (6.1–10.0) | 0.224 |
| 2. Fruit | 10.0 (5.1–10.0) | 10.0 (4.9–10.0) | 0.990 | 10.0 (6.4–10.0) | 10.0 (6.3–10.0) | 0.683 |
| 3a. Wholegrain products intake | 5.0 (4.8–5.0) | 5.0 (5.0–5.0) | 0.538 | 4.8 (2.4–5.0) | 4.3 (2.2–5.0) | 0.124 |
| 3b. Ratio of wholegrain/refined grains | 5.0 (2.6–5.0) | 5.0 (3.0–5.0) | 0.432 | 5.0 (3.2–5.0) | 5.0 (3.4–5.0) | 0.593 |
| 3. Wholegrain products total† | 10.0 (7.0–10.0) | 10.0 (7.3–10.0) | 0.428 | 8.9 (6.2–10.0) | 8.7 (6.2–10.0) | 0.592 |
| 4. Legumes | 10.0 (5.5–10.0) | 10.0 (6.4–10.0) | 0.878 | 10.0 (4.9–10.0) | 10.0 (7.3–10.0) | 0.042 |
| 5. Nuts | 7.9 (2.6–10.0) | 8.8 (3.2–10.0) | 0.175 | 7.7 (2.5–10.0) | 9.0 (3.8–10.0) | 0.012 |
| 6. Dairy | 6.6 (3.4–9.4) | 6.8 (2.9–9.8) | 0.698 | 5.8 (2.7–8.9) | 6.4 (3.0–9.3) | 0.151 |
| 7. Fish | 6.3 (2.7–9.9) | 6.3 (2.9–10.0) | 0.478 | 6.4 (1.8–10.0) | 7.0 (2.9–9.9) | 0.279 |
| 8. Tea | 1.8 (0.0–7.4) | 2.6 (0.1–7.6) | 0.045 | 6.5 (1.6–10.0) | 6.5 (0.9–10.0) | 0.312 |
| 9. Fats and oils | 10.0 (1.8–10.0) | 10.0 (1.8–10.0) | 0.588 | 10.0 (1.7–10.0) | 10.0 (1.3–10.0) | 0.691 |
| 11. Red meat | 10.0 (7.5–10.0) | 10.0 (6.9–10.0) | 0.387 | 10.0 (8.6–10.0) | 10.0 (8.6–10.0) | 0.587 |
| 12. Processed meat | 4.9 (0.7–8.0) | 5.4 (1.3–8.4) | 0.166 | 7.4 (4.2–9.7) | 7.7 (5.1–9.7) | 0.449 |
| 13. Sweetened beverages and fruit juices | 7.6 (3.4–9.4) | 7.9 (3.7–9.4) | 0.432 | 9.0 (7.0–9.9) | 9.0 (6.5–10.0) | 0.837 |
| 14. Alcohol | 10.0 (8.7–10.0) | 10.0 (8.6–10.0) | 0.800 | 10.0 (10.0–10.0) | 10.0 (10.0–10.0) | 0.966 |
| 16. Unhealthy choices | 0.0 (0.0–0.0) | 0.0 (0.0–0.0) | 0.965 | 0.0 (0.0–0.0) | 0.0 (0.0–0.0) | 0.620 |
Data are presented as median (25–75th percentile).
Component 10 (coffee) and 15 (salt) could not be calculated from FFQ data.
*P values were obtained with a Mann-Whitney U test; statistical significance (p<0.05) is indicated in bold.
†Sum score of components 3a and 3b.
DHD2015-index, Dutch Healthy Diet index 2015; FFQ, Food Frequency Questionnaire; LLT, lower limb tendinopathy.
Results of the logistic regression analyses showed that gender, age, running years, the intensity of most intensive training and warming up were retained in the multivariable model. The Nagelkerke R2 of the multivariable model was low: 0.061 (table 5).
Table 5.
Multivariable associations between risk factors and tendinopathy
| OR (95% CI)* | P value† | |
| Gender, women vs men | 0.69 (0.57 to 0.84) | <0.001 |
| Age, years | 1.01 (1.00 to 1.02) | 0.016 |
| Running years | <0.001 | |
| 1–2 years vs <1 year | 0.92 (0.38 to 2.21) | 0.849 |
| 3–5 years vs <1 year | 1.62 (0.72 to 3.64) | 0.243 |
| 6–9 years vs <1 year | 1.67 (0.74 to 3.74) | 0.214 |
| ≥ 10 years vs <1 year | 2.45 (1.10 to 5.43) | 0.028 |
| Intensity most intensive training | 0.102 | |
| Intensive vs moderately intensive | 1.24 (0.98 to 1.58) | 0.076 |
| Very intensive vs moderately intensive | 1.34 (1.01 to 1.78) | 0.043 |
| Warming up, no vs yes | 0.78 (0.64 to 0.96) | 0.018 |
*OR=exp (beta). A value <1 indicates a decreased risk and a value >1 indicates an increased risk.
†The selection of risk factors in the multivariable logistic regression model was based on Akaike’s information criterion (AIC), corresponding to a p value of 0.157 for a predictor with one regression coefficient.29
Discussion
We aimed to assess the prevalence of three common LLTs (AT, PT and PF) in a large cohort of runners and to investigate its association with potential risk factors, particularly nutritional factors in the habitual diet. The point prevalence of all three LLTs was rather low (6%), although one-third had ever experienced LLT. AT was the most prevalent type of LLT, and prevalence rates for all types of LLT were higher in men than women. In both men and women, age and running years were positively associated with LLT. In addition, in men running level, weekly running distance and running in competitions were positively associated with LLT, while in women running on a hard surface was negatively associated with LLT. No associations between nutritional factors and LLT were observed in this population of runners with a relatively high diet quality.
Compared with other studies, the point prevalence in the current study was low (6%). Prevalence rates of 6.2%–9.5% are reported for AT only, 12.5% for PT and 5.2%–17.5% for PF.2 Also, the percentage of runners that had ever experienced LLT was rather low (35%) in the current study. One other study showed that former elite runners have a 52% chance of acquiring Achilles tendon injuries in their lifetime.30 Our recruitment of runners via running event organisations could have caused this low prevalence to some extent. Likely, runners with LLT are not registered for a running event, although LLT may still have occurred after registration. Moreover, runners with past LLT may refrain from participation in running events to prevent the recurrence of injuries, resulting in low numbers of runners with current or past LLT in our study population.
LLT was more prevalent among men than women. The higher running load in man may partly explain this, as mechanical loading is related to LLT.1 7 Indeed, male runners with LLT ran more kilometres a week than male runners without LLT, and in the multivariable regression model, the running intensity was positively associated with LLT. Thus, men ran more kilometres a week at a higher intensity than women, which may explain the higher LLT prevalence in men. However, when we corrected for running load factors in the multivariable regression model, and for body weight in a separate regression model, an association with gender was still observed, indicating a true gender effect that may be related to hormonal factors. The positive association with age we observed could result from decreased tendon cell regeneration and a reduction in cell density, and changes in tendon cell morphology and in tendon structure and composition, leading to reduced ability to tolerate high loads at older age.31 32 However, one should recognise that older runners might have a longer running history, with presumably more tendon load and thus a higher chance of LLT occurrence in their running career. This could also explain the positive association between LLT and running years.
An important aim of this study was to investigate the association of LLT with nutritional factors. We did find no evidence for such an association, although preclinical and animal studies have shown that various nutrients can play a role in (mal)adaptation and repair of tendons.11 12 Only a few studies investigated the impact of nutrition on tendon health and tendinopathy in human.13 One earlier study investigated the effect of the habitual diet on Achilles tendon structure and found no associations between dietary parameters and tendon structure.33 A few studies investigated the effect of alcohol. Alcohol intake was associated with an increased risk of AT34 and rotator cuff tears.35 However, in another study, no association was found between alcohol consumption and rotator cuff tendinitis.36 We did not explicitly investigate an association of LLT with absolute alcohol intake, but an association with adherence to the Dutch dietary guideline on alcohol intake. It turned out that both runners with and without LLT scored high on adherence to this guideline, indicating a limited intake of only one Dutch unit alcohol per day. This is much lower than the alcohol consumption reported in previous studies in which an association between alcohol and tendon problems was found.34 35
Although there might be a relationship between nutritional factors and LLT, we did not find it in this study, which might be explained by the relatively high diet quality in our study population compared with the general population. For example, in the Lifelines Cohort Study,37 which is a large cohort study among inhabitants of the northern three provinces of the Netherlands, a much lower total DHD2015-index score (which was based on the same 14 components as in the current study) was observed compared with both runners with and without LLT in our population; on average 15 points lower (unpublished data). The total DHD2015-index scores in our population are comparable to those observed in another Dutch population when, like in our study, the coffee and salt components are not included.28 It is likely that this population also had an above-average diet quality as it contained a large proportion of highly educated participants with interest in participating in a study on nutrition and health. We can easily imagine that a physically active population of runners as ours is more health conscious and hence has an above-average diet quality, which applies to both runners with and without LLT, limiting the ability to find associations between nutritional factors and LLT. Otherwise, the impact of habitual dietary intake and nutritional factors on LLT could be limited in this population, if present, compared with other factors such as mechanical loading. Future prospective studies in (novice) runners with a lower diet quality could shed another light on the relationship between nutritional factors and the development of LLT.
Strengths and limitations
To our knowledge, this is the first study investigating the association of LLT and nutrition in runners. A strength of the study is the large study population of 1993 runners, covering a broad range in age, running load and running level. Another strength is the availability of comprehensive dietary intake data of the habitual diet, which allowed us to investigate many macronutrients and micronutrients as well as general diet quality.
Due to the nature of the study, a limitation is the self-reporting method of data collection. Although we used validated methods and questionnaires, these methods are prone to bias. A health professional did not diagnose the occurrence of tendinopathy, but runners had to indicate whether they had pain on specific locations on pain maps. Although we used a standardised pain map, this method is prone to bias. Assessment of dietary intake using an FFQ is prone to several types of error such as recall bias or the tendency to provide socially desirable answers.38 Moreover, an FFQ is not the best method to assess absolute dietary intake. In addition, nutrient intake from supplements could not be assessed. However, an FFQ is a reliable method to rank participants to their intake levels,20 21 and in epidemiological studies on associations of dietary intake with diseases, such as LLT, the ranking of participants according to their intake levels is more relevant than absolute levels of intake.
The absolute number of runners with current tendinopathy was quite low, which is too low to investigate many potential associations. Therefore, we decided to include also runners with past tendinopathy in the ‘LLT group’ for comparison with the ‘no (never) LLT group’. For runners with past tendinopathy, it could have been that changes in dietary intake and/or running characteristics had occurred between the period that tendinopathy was present and the current time, which may or may not be a consequence of the injury. This could introduce reversed causation, for example, in the LLT group fewer runners ran predominantly on a hard surface compared with the no LLT group. It may be that runners started to run more often on soft surfaces after injury to prevent future injuries. Regarding dietary intake, stable food consumption patterns over time can be assumed.39 However, data collection took place during the COVID-19 pandemic, and studies have shown that the lockdown due to this pandemic resulted in changes in dietary intake and physical activity in many people.40 41 Thus, the COVID-19 pandemic could also have influenced our results.
Conclusion
In this population of runners, the occurrence of LLT was common. One-third had ever experienced an LLT, while 6% had present symptoms. AT was the most prevalent type of LLT, and prevalence rates for all types of LLT were higher in men than in women. Age and running load were positively associated with LLT. An association between nutritional factors in the habitual diet and LLT was not observed, which might be explained by the relatively high diet quality in this cohort of runners compared with the general population.
Acknowledgments
We are thankful to athletics clubs and running event organisations and all other persons who helped with the recruitment of participants. We acknowledge the help of MSc students Daan Groenendijk, Susanne Wildemast, Floris Barnhoorn, Sanne de Vries and Dani Wolters.
Footnotes
Contributors: AMB, RT, MN, EN, MM, BJWM and JZ were involved in the design of the study. AMB analysed the data and prepared tables and figures, AMB MM and JZ interpreted the results. AMB drafted the manuscript, RT, MM, BJMW and JZ critically reviewed it. All authors have read and approved the final manuscript. JZ is the study guarantor.
Funding: This study was financially supported by the EAT2MOVE project, a grant from the Province of Gelderland, proposal PS2014-49, and a grant from the Gelderse Vallei Hospital Research Fund.
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available on reasonable request.
Ethics statements
Patient consent for publication
Not applicable.
Ethics approval
This study involves human participants the Medical Ethical Review Commission from Wageningen University & Research assessed the study protocol and concluded that it did not fall within the scope of the Medical Research Involving Human Subjects Act (WMO), and formal medical ethical approval was not required. This study was, however, conducted following the ethical principles contained in the current revision of the Declaration of Helsinki. Participants gave informed consent to participate in the study before taking part.
References
- 1.Scott A, Squier K, Alfredson H, et al. Icon 2019: international scientific tendinopathy symposium consensus: clinical terminology. Br J Sports Med 2020;54:260–2. 10.1136/bjsports-2019-100885 [DOI] [PubMed] [Google Scholar]
- 2.Lopes AD, Hespanhol Júnior LC, Yeung SS, et al. What are the main running-related musculoskeletal injuries? A systematic review. Sports Med 2012;42:891–905. 10.1007/BF03262301 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.De Vries AJ, Koolhaas W, Zwerver J, et al. The impact of Patellar tendinopathy on sports and work performance in active athletes. Res Sports Med 2017;25:253–65. 10.1080/15438627.2017.1314292 [DOI] [PubMed] [Google Scholar]
- 4.Sleeswijk Visser TSO, van der Vlist AC, van Oosterom RF, et al. Impact of chronic Achilles tendinopathy on health-related quality of life, work performance, healthcare utilisation and costs. BMJ Open Sport Exerc Med 2021;7:e001023. 10.1136/bmjsem-2020-001023 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Aicale R, Oliviero A, Maffulli N. Management of Achilles and patellar tendinopathy: what we know, what we can do. J Foot Ankle Res 2020;13:59. 10.1186/s13047-020-00418-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Trojian T, Tucker AK. Plantar fasciitis. Am Fam Physician 2019;99:744–50. [PubMed] [Google Scholar]
- 7.Scott A, Backman LJ, Speed C. Tendinopathy: update on pathophysiology. J Orthop Sports Phys Ther 2015;45:833–41. 10.2519/jospt.2015.5884 [DOI] [PubMed] [Google Scholar]
- 8.Macchi M, Spezia M, Elli S, et al. Obesity increases the risk of tendinopathy, tendon tear and rupture, and postoperative complications: a systematic review of clinical studies. Clin Orthop Relat Res 2020;478:1839–47. 10.1097/CORR.0000000000001261 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ahmed AS. Does diabetes mellitus affect tendon healing? Adv Exp Med Biol 2016;920:179–84. 10.1007/978-3-319-33943-6_16 [DOI] [PubMed] [Google Scholar]
- 10.Magnusson SP, Langberg H, Kjaer M. The pathogenesis of tendinopathy: balancing the response to loading. Nat Rev Rheumatol 2010;6:262–8. 10.1038/nrrheum.2010.43 [DOI] [PubMed] [Google Scholar]
- 11.Curtis L. Nutritional research may be useful in treating tendon injuries. Nutrition 2016;32:617–9. 10.1016/j.nut.2015.12.039 [DOI] [PubMed] [Google Scholar]
- 12.Loiacono C, Palermi S, Massa B, et al. Tendinopathy: pathophysiology, therapeutic options, and role of nutraceutics. A narrative literature review. Medicina (Kaunas) 2019;55:447. 10.3390/medicina55080447 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Hijlkema A, Roozenboom C, Mensink M, et al. The impact of nutrition on tendon health and tendinopathy: a systematic review. J Int Soc Sports Nutr 2022;19:474–504. 10.1080/15502783.2022.2104130 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Bahr R, Clarsen B, Derman W, et al. International Olympic Committee consensus statement: methods for recording and reporting of epidemiological data on injury and illness in sport 2020 (including STROBE extension for sport injury and illness surveillance (STROBE-SIIS)). Br J Sports Med 2020;54:372–89. 10.1136/bjsports-2019-101969 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Robinson JM, Cook JL, Purdam C, et al. The VISA-A questionnaire: a valid and reliable index of the clinical severity of Achilles tendinopathy. Br J Sports Med 2001;35:335–41. 10.1136/bjsm.35.5.335 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sierevelt I, van Sterkenburg M, Tol H, et al. Dutch version of the Victorian Institute of sports assessment-achilles questionnaire for Achilles tendinopathy: reliability, validity and applicability to non-athletes. World J Orthop 2018;9:1–6. 10.5312/wjo.v9.i1.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Visentini PJ, Khan KM, Cook JL, et al. The visa score: an index of severity of symptoms in patients with jumper’s knee (patellar tendinosis). JSAMS 1998;1:22–8. 10.1016/S1440-2440(98)80005-4 [DOI] [PubMed] [Google Scholar]
- 18.Zwerver J, Kramer T, van den Akker-Scheek I. Validity and reliability of the Dutch translation of the VISA-P questionnaire for patellar tendinopathy. BMC Musculoskelet Disord 2009;10:102. 10.1186/1471-2474-10-102 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Kuyvenhoven MM, Gorter KJ, Zuithoff P, et al. The foot function index with verbal rating scales (FFI-5pt): a Clinimetric evaluation and comparison with the original FFI. J Rheumatol 2002;29:1023–8. [PubMed] [Google Scholar]
- 20.Siebelink E, Geelen A, de Vries JHM. Self-reported energy intake by FFQ compared with actual energy intake to maintain body weight in 516 adults. Br J Nutr 2011;106:274–81. 10.1017/S0007114511000067 [DOI] [PubMed] [Google Scholar]
- 21.Streppel MT, de Vries JHM, Meijboom S, et al. Relative validity of the food frequency questionnaire used to assess dietary intake in the Leiden longevity study. Nutr J 2013;12:75. 10.1186/1475-2891-12-75 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.NEVO-tabel . Dutch Food Composition Table 2011 / version 3. the Netherlands: RIVM, 2011. [Google Scholar]
- 23.Willett W. Nutritional epidemiology. Oxford University Press, 2013. [Google Scholar]
- 24.Rhee JJ, Sampson L, Cho E, et al. Comparison of methods to account for implausible reporting of energy intake in epidemiologic studies. Am J Epidemiol 2015;181:225–33. 10.1093/aje/kwu308 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Looman M, Feskens EJ, de Rijk M, et al. Development and evaluation of the Dutch healthy diet index 2015. Public Health Nutr 2017;20:2289–99. 10.1017/S136898001700091X [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Health Council of the Netherlands . Dutch dietary guidelines 2015. Health Council of the Netherlands, 2015. [Google Scholar]
- 27.Kromhout D, Spaaij CJK, de Goede J, et al. The 2015 Dutch food-based dietary guidelines. Eur J Clin Nutr 2016;70:869–78. 10.1038/ejcn.2016.52 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.de Rijk MG, Slotegraaf AI, Brouwer-Brolsma EM, et al. Development and evaluation of a diet quality screener to assess adherence to the Dutch food-based dietary guidelines. Br J Nutr 2021;128:1–11. 10.1017/S0007114521004499 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Sauerbrei W, Royston P, Binder H. Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Stat Med 2007;26:5512–28. 10.1002/sim.3148 [DOI] [PubMed] [Google Scholar]
- 30.Kujala UM, Sarna S, Kaprio J. Cumulative incidence of Achilles tendon rupture and tendinopathy in male former elite athletes. Clin J Sport Med 2005;15:133–5. 10.1097/01.jsm.0000165347.55638.23 [DOI] [PubMed] [Google Scholar]
- 31.Zhou B, Zhou Y, Tang K. An overview of structure, mechanical properties, and treatment for age-related tendinopathy. J Nutr Health Aging 2014;18:441–8. 10.1007/s12603-014-0026-2 [DOI] [PubMed] [Google Scholar]
- 32.Svensson RB, Heinemeier KM, Couppé C, et al. Effect of aging and exercise on the tendon. J Appl Physiol (1985) 2016;121:1237–46. 10.1152/japplphysiol.00328.2016 [DOI] [PubMed] [Google Scholar]
- 33.Hjerrild JN, Wobbe A, Stausholm MB, et al. Effects of long-term physical activity and diet on skin glycation and Achilles tendon structure. Nutrients 2019;11:1409. 10.3390/nu11061409 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Owens BD, Wolf JM, Seelig AD, et al. Risk factors for lower extremity tendinopathies in military personnel. Orthop J Sports Med 2013;1:2325967113492707. 10.1177/2325967113492707 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Passaretti D, Candela V, Venditto T, et al. Association between alcohol consumption and rotator cuff tear. Acta Orthopaedica 2016;87:165–8. 10.3109/17453674.2015.1119599 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Rechardt M, Shiri R, Karppinen J, et al. Lifestyle and metabolic factors in relation to shoulder pain and rotator cuff tendinitis: a population-based study. BMC Musculoskelet Disord 2010;11:165. 10.1186/1471-2474-11-165 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Scholtens S, Smidt N, Swertz MA, et al. Cohort profile: lifelines, a three-generation cohort study and Biobank. Int J Epidemiol 2015;44:1172–80. 10.1093/ije/dyu229 [DOI] [PubMed] [Google Scholar]
- 38.Naska A, Lagiou A, Lagiou P. Dietary assessment methods in epidemiological research: current state of the art and future prospects. F1000Res 2017;6:926. 10.12688/f1000research.10703.1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Goldbohm RA, van ’t Veer P, van den Brandt PA, et al. Reproducibility of a food frequency questionnaire and stability of dietary habits determined from five annually repeated measurements. Eur J Clin Nutr 1995;49:420–9. [PubMed] [Google Scholar]
- 40.Mignogna C, Costanzo S, Ghulam A, et al. Impact of nationwide lockdowns resulting from the first wave of the COVID-19 pandemic on food intake, eating behaviours and diet quality: a systematic review. Adv Nutr 2021;13:388–423. 10.1093/advances/nmab130 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Stockwell S, Trott M, Tully M, et al. Changes in physical activity and sedentary behaviours from before to during the COVID-19 pandemic lockdown: a systematic review. BMJ Open Sport Exerc Med 2021;7:e000960. 10.1136/bmjsem-2020-000960 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
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Supplementary Materials
bmjsem-2023-001570supp001.pdf (68KB, pdf)
bmjsem-2023-001570supp002.pdf (71KB, pdf)
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Data Availability Statement
Data are available on reasonable request.