BackgroundThe popularity of running continues to increase, which means that the incidence of running-related injuries will probably also continue to increase. Little is known about risk factors for running injuries and whether they are sex-specific.ObjectivesThe aim of this study was to review information about risk factors and sex-specific differences for running-induced injuries in adults.Search StrategyThe databases PubMed, EMBASE, CINAHL and Psych-INFO were searched for relevant articles.Selection CriteriaLongitudinal cohort studies with a minimal follow-up of 1 month that investigated the association between risk factors (personal factors, running/training factors and/or health and lifestyle factors) and the occurrence of lower limb injuries in runners were included.Data Collection and AnalysisTwo reviewers’ independently selected relevant articles from those identified by the systematic search and assessed the risk of bias of the included studies. The strength of the evidence was determined using a best-evidence rating system. Sex differences in risk were determined by calculating the sex ratio for risk factors (the risk factor for women divided by the risk factor for men).Main ResultsOf 400 articles retrieved, 15 longitudinal studies were included, of which 11 were considered high-quality studies and 4 moderate-quality studies. Overall, women were at lower risk than men for sustaining running-related injuries. Strong and moderate evidence was found that a history of previous injury and of having used orthotics/inserts was associated with an increased risk of running injuries. Age, previous sports activity, running on a concrete surface, participating in a marathon, weekly running distance (30–39 miles) and wearing running shoes for 4 to 6 months were associated with a greater risk of injury in women than in men. A history of previous injuries, having a running experience of 0–2 years, restarting running, weekly running distance (20–29 miles) and having a running distance of more than 40 miles per week were associated with a greater risk of running-related injury in men than in women.ConclusionsPrevious injury and use of orthotic/inserts are risk factors for running injuries. There appeared to be differences in the risk profile of men and women, but as few studies presented results for men and women separately, the results should be interpreted with caution. Further research should attempt to minimize methodological bias by paying attention to recall bias for running injuries, follow-up time, and the participation rate of the identified target group.

Background Increasing protein intake has been suggested as an effective strategy to ameliorate age-related loss of muscle mass and strength. Current reviews assessing the effect of protein supplementation are strongly influenced by the inclusion of studies with frail older adults. Objectives We assessed the effect of protein supplementation on lean body mass, muscle strength, and physical performance in exclusively nonfrail community-dwelling older adults. Moreover, we assessed the superior effects of protein supplementation during concomitant resistance exercise training on muscle characteristics. Design A systematic literature search was conducted on PubMed, Embase, and Web of Science up to 15 May 2018. We included randomized controlled trials that assessed the effect of protein supplementation on lean body mass, muscle thigh cross-sectional area, muscle strength, gait speed, and chair-rise ability and performed random-effects meta-analyses. Results Data from 36 studies with 1682 participants showed no significant effects of protein supplementation on changes in lean body mass [standardized mean difference (SMD): 0.11; 95% CI: −0.06, 0.28], handgrip strength (SMD: 0.58; 95% CI: −0.08, 1.24), lower extremity muscle strength (SMD: 0.03; 95% CI: −0.20, 0.27), gait speed (SMD: 0.41; 95% CI: −0.04, 0.85), or chair-rise ability (SMD: 0.10; 95%: CI −0.08, 0.28) compared with a control condition in nonfrail community-dwelling older adults. Moreover, no superior effects of protein supplementation were found during concomitant resistance exercise training on muscle characteristics. Conclusions Protein supplementation in nonfrail community-dwelling older adults does not lead to increases in lean body mass, muscle cross-sectional area, muscle strength, or physical performance compared with control conditions; nor does it exert superior effects when added to resistance exercise training. Habitual protein intakes of most study participants were already sufficient, and protein interventions differed in terms of type of protein, amount, and timing. Future research should clarify what specific protein supplementation protocol is beneficial for nonfrail community-dwelling older adults with low habitual protein intake.

Increasing total protein intake and a spread protein intake distribution are potential strategies to attenuate sarcopenia related loss of physical function and quality of life. The aim of this cross-sectional study was to investigate whether protein intake and protein intake distribution are associated with muscle strength, physical function and quality of life in community-dwelling elderly people with a wide range of physical activity. Dietary and physical activity data were obtained from two studies (N = 140, age 81 ± 6, 64% male), with the following outcome measures: physical functioning (Short Physical Performance Battery (SPPB), comprising balance, gait speed and chair rise tests), handgrip strength and quality of life (EQ-5D-5L). Protein intake distribution was calculated for each participant as a coefficient of variance (CV = SD of grams of protein intake per main meal divided by the average total amount of proteins (grams) of the main meals). Based on the CV, participants were divided into tertiles and classified as spread, intermediate or pulse. The average total protein intake was 1.08 ± 0.29 g/kg/day. Total protein intake was not associated with outcome measures using multivariate regression analyses. Individuals with a spread protein diet during the main meals (CV < 0.43) had higher gait speed compared to those with an intermediate diet (CV 0.43–0.62) (β = −0.42, p = 0.035), whereas a spread and pulse protein diet were not associated with SPPB total score, chair rise, grip strength and Quality-Adjusted Life Year (QALY). The interaction of higher physical activity and higher total protein intake was significantly associated with higher quality of life (β = 0.71, p = 0.049). While this interaction was not associated with SPPB or grip strength, the association with quality of life emphasizes the need for a higher total protein intake together with an active lifestyle in the elderly.

Background An inadequate protein intake may offset the muscle protein synthetic response after physical activity, reducing the possible benefits of an active lifestyle for muscle mass. We examined the effects of 12 weeks of daily protein supplementation on lean body mass, muscle strength, and physical performance in physically active older adults with a low habitual protein intake (<1.0 g/kg/day). Methods A randomized double‐blinded controlled trial was performed among 116 physically active older adults [age 69 (interquartile range: 67–73) years, 82% male] who were training for a 4 day walking event of 30, 40, or 50 km/day. Participants were randomly allocated to either 31 g of milk protein or iso‐caloric placebo supplementation for 12 weeks. Body composition (dual‐energy X‐ray absorptiometry), strength (isometric leg extension and grip strength), quadriceps contractile function, and physical performance [Short Physical Performance Battery, Timed Up‐and‐Go test, and cardiorespiratory fitness (Åstrand–Rhyming submaximal exercise test)] were measured at baseline and after 12 weeks. We assessed vitamin D status and markers of muscle damage and renal function in blood and urine samples before and after intervention. Results A larger increase in relative lean body mass was observed in the protein vs. placebo group (∆0.93 ± 1.22% vs. ∆0.44 ± 1.40%, P Interaction = 0.046). Absolute and relative fat mass decreased more in the protein group than in the placebo group (∆−0.90 ± 1.22 kg vs. ∆−0.31 ± 1.28 kg, P Interaction = 0.013 and ∆−0.92 ± 1.19% vs. ∆−0.39 ± 1.36%, P Interaction = 0.029, respectively). Strength and contractile function did not change in both groups. Gait speed, chair‐rise ability, Timed Up‐and‐Go, and cardiorespiratory fitness improved in both groups ( P < 0.001), but no between‐group differences were observed. Serum urea increased in the protein group, whereas no changes were observed in the placebo group ( P Interaction < 0.001). No between‐group differences were observed for vitamin D status, muscle damage, and renal function markers. Conclusions In physically active older adults with relatively low habitual dietary protein consumption, an improvement in physical performance, an increase in lean body mass, and a decrease in fat mass were observed after walking exercise training. A larger increase in relative lean body mass and larger reduction in fat mass were observed in participants receiving 12 weeks of daily protein supplementation compared with controls, whereas this was not accompanied by differences in improvements between groups in muscle strength and physical performance.

PurposeThe aim of the present study was to assess the effect of prolonged and repeated exercise on iron metabolism in middle-aged adults and to compare differences between sexes.Methods50 male (58.9 ± 9.9 year) and 48 female (50.9 ± 11.2 year) individuals were monitored on 4 consecutive days at which they walked on average 8 h and 44 min per day at a self-determined pace. Blood samples were collected 1 or 2 days prior to the start of the exercise (baseline) and every day immediately post-exercise. Samples were analysed for iron, ferritin, haemoglobin, and haptoglobin concentrations.ResultsPlasma iron decreased across days, while ferritin increased across days (both p < 0.001). Haptoglobin showed a decrease (p < 0.001) after the first day and increased over subsequent days (p < 0.001). Haemoglobin did not change after the first day, but increased during subsequent days (p < 0.05). At baseline, 8% of the participants had iron concentrations below minimum reference value (10 µmol/L), this increased to 43% at day 4. There was an interaction between sex and exercise days on iron (p = 0.028), ferritin (p < 0.001) and haemoglobin levels (p = 0.004), but not on haptoglobin levels.ConclusionThis study showed decreases in iron, increases in ferritin, a decrease followed by increases in haptoglobin and no change followed by increases in haemoglobin. This is most likely explained by (foot strike) haemolysis, inflammation, and sweat and urine losses. These processes resulted in iron levels below minimum reference value in a large number of our participants.