Deflation and Downward Nominal Wage Rigidity: Evidence from Japan

This study empirically analyzed downward nominal wage rigidity using time-series cross-industry data from 1981 to 2002, a period which included deflation. We found that nominal wages remained rigid to downward pressure by expected deflation and labor-market tightness. Estimations according to worker age categories revealed downward wage rigidity with deflationary pressure for most age categories. Wage rigidity during labor-market tightness was greater for younger workers.wage rigidity, nominal wage, deflation, unemployment, Japan

Decline in Telomere Length by Age and Effect Modification by Gender, Allostatic Load and Comorbidities in National Health and Nutrition Examination Survey (1999-2002)

Background: This study aims to assess the decline in telomere length (TL) with age and evaluate effect modification by gender, chronic stress, and comorbidity in a representative sample of the US population. Methods: Cross-sectional data on 7826 adults with a TL measurement, were included from the National Health and Nutrition Examination Survey, years 1999–2002. The population rate of decline in TL across 10-year age categories was estimated using crude and adjusted regression. Results: In an adjusted model, the population rate of decline in TL with age was consistent and linear for only three age categories: 20–29 (β = -0.0172, 95% CI: -0.0342, -0.0002), 50–59 (β = -0.0182, 95% CI: -0.0311, -0.0054) and 70–79 (β = -0.0170, 95% CI: -0.0329, -0.0011) years. The population rate of decline in TL with age was significantly greater for males and those with high allostatic load and a history of comorbidities. When the population rate of decline in TL was analyzed by gender in 10-year age bins, a fairly consistent yet statistically non-significant decline for males was observed; however, a trough in the rate was observed for females in the age categories 20–29 years (β = -0.0284, 95% CI: -0.0464, -0.0103) and 50–59 years (β = -0.0211, 95% CI: -0.0391, -0.0032). To further elucidate the gender difference observed in the primary analyses, secondary analyses were conducted with reproductive and hormonal status; a significant inverse association was found between TL and parity, menopause, and age at menopause. Conclusions: TL was shorter with increasing age and this decline was modified by gender, chronic stress and comorbidities; individuals with chronic morbidity and/or chronic stress and females in their twenties and fifties experienced greater decline. Female reproductive factors, i.e., parity and menopause, were associated with TL

An individualized longitudinal approach to monitoring the dynamics of growth and fitness development in adolescent athletes.

This study evaluated the development of anthropometric and fitness characteristics of 3 individual adolescent junior rugby league players and compared their characteristics with a cross-sectional population matched by age and skill level. Cross-sectional anthropometric and fitness assessments were conducted on 1,172 players selected to the Rugby Football League's talent development program (i.e., the Player Performance Pathway) between 2005 and 2008. Three players of differing relative age, maturational status, and playing position were measured and tracked once per year on 3 occasions (Under 13s, 14s, 15s age categories) and compared against the cross-sectional population. Results demonstrated that the later maturing players increased height (player 1 = 9.2%; player 2 = 7.8%) and a number of fitness characteristics (e.g., 60-m speed-player 1 = -14.9%; player 2 = -9.9%) more than the earlier maturing player (player 3-Height = 2.0%, 60-m sprint = -0.7%) over the 2-year period. The variation in the development of anthropometric and fitness characteristics between the 3 players highlights the importance of longitudinally monitoring individual characteristics during adolescence to assess the dynamic changes in growth, maturation, and fitness. Findings showcase the limitations of short-term performance assessments at one-off time points within annual-age categories, instead of advocating individual development and progression tracking without deselection. Coaches should consider using an individual approach, comparing data with population averages, to assist in the prescription of appropriate training and lifestyle interventions to aid the development of junior athletes

Change of direction asymmetry across different age categories in youth soccer

Background In youth, the development of change of direction (COD) and sprint performance is a key component for successfully competing in soccer across age. During a COD, the presence of directional asymmetries may be detrimental due to the unpredictable nature of the sport. Therefore, the aims of the study were to investigate asymmetries in COD ability and to examine the differences in COD and sprint performance across age in young soccer players. Methods Sixty-eight sub-elite soccer players of different age categories (U18, U17, U16, U15) were tested on a 10-m linear sprint test and 90°COD (5-m entry and exit) test in both directions. Asymmetric index (AI) of COD deficit was obtained for dominant (fastest) and non-dominant directions (slowest). Results The results showed that U16 were more asymmetrical than U18, U17, and U15 from large to moderate effects. The sprint time improved linearly across age with U18 and U15 displaying the fastest and slowest 10-m sprint performance (p 0.05). Conclusion Given the results of this study, practitioners are encouraged to assess asymmetries between dominant and non-dominant directions rather than solely players’ COD ability in young soccer players

The New Segregation: A Perspective on Age Categories and Social Conflict

http://deepblue.lib.umich.edu/bitstream/2027.42/50816/1/31.pd

Anthropometric and physical characteristics of english academy rugby league players.

The purpose of the present study was to evaluate the anthropometric and physical characteristics of English academy rugby league players by annual-age category (under 16s-under 20s) and between backs and forwards. Data were collected on 133 academy players over a 6-year period (resulting in a total of 257 assessments). Player assessments comprised of anthropometric (height, body mass, sum of 4 skinfolds) and physical (vertical jump, 10- and 20-m sprint, estimated V[Combining Dot Above]O2max via the yo-yo intermittent recovery test level 1, absolute 1 repetition maximum [1RM], and relative squat, bench press, and prone row) measures. Univariate analysis of variance demonstrated significant (p ≤ 0.05) increases in height, body mass, vertical jump, absolute, and relative strength measures across the 5 annual-age categories (e.g., body mass: under 16s = 75.2 ± 11.1, under 20s = 88.9 ± 8.5 kg; vertical jump: under 16s = 45.7 ± 5.2, under 20s = 52.8 ± 5.4 cm; 1RM bench press: under 16s = 73.9 ± 13.2, under 20s = 114.3 ± 15.3 kg). Independent t-tests identified significant (p ≤ 0.05) differences between backs and forwards for anthropometric (e.g., under 16s body mass: backs = 68.4 ± 8.6, forwards = 80.9 ± 9.7 kg) and physical (e.g., under 19s 20-m sprint: backs = 3.04 ± 0.08, forwards = 3.14 ± 0.12s; under 18s relative squat: backs = 1.65 ± 0.18, forwards = 1.51 ± 0.17 kg·kg) characteristics that were dependent on the age category and measure assessed. Findings highlight that anthropometric and physical characteristics develop across annual-age categories and between backs and forwards in academy rugby league players. These findings provide comparative data for such populations and support the need to monitor player development in junior rugby league players

How does curve sprint evolve across different age categories in soccer players?

: Research has shown that soccer players regularly execute curved sprints during matches. The purpose of this study was to determine the age-related effects on curve sprint (CS) performance to both sides, asymmetry, and association with linear sprint (LS). Eighty-four soccer players (aged 16.1 ± 1.6 categorized in U15, U17, and U20) were recruited, who performed CS and LS tests. One-way analysis of variance (ANOVA) and effect size (ES) were used to compare CS performance between age categories, and relationships between physical performance measures were calculated using Pearson’s correlation coefficient. The main findings of this study were that: 1) there were significant differences in the “good” side CS among age groups (p < 0.001; ES from moderate to large), but not in the “weak” side CS, 2) curve asymmetry was significantly higher in U20 than U15 (p < 0.05; ES large) and U17 players (p < 0.05; ES moderate), and 3) relationships between CS and LS times decreased with age (from significant and very large [p 0.05]). This study highlights the importance of assessing and training CS in different age categories, an action that becomes less correlated with LS as age increases, with the aim of mitigating the increase in asymmetries as a result of the specialization process, focusing interventions mainly on improving the CS “weak” sideThanks to all the participants in this study, to Football Science Institute, and to the soccer clu

We know they train, but what do they do? Implications for coaches working with adolescent rugby union players

Limited information is available regarding the training loads (TLs) of adolescent rugby union players. One-hundred and seventy male players (age 16.1 ± 1.0 years) were recruited from ten teams representing two age categories (under-16 and under-18) and three playing standards (school, club and academy). Global positioning systems, accelerometers, heart rate and session-rating of perceived exertion (s-RPE) methods were used to quantify mean session TLs. Session demands differed between age categories and playing standards. Under-18 academy players were exposed to the highest session TLs in terms of s-RPE (236 ± 42 AU), total distance (4176 ± 433 m), high speed running (1270 ± 288 m) and PlayerLoadTM (424 ± 56 AU). Schools players had the lowest session TLs in both respective age categories. Training loads and intensities increased with age and playing standard. Individual monitoring of TL is key to enable coaches to maximise player development and minimise injury risk