Effects of the Task Complexity on the Single Movement Response Time of Upper and Lower Limbs in Police Officers.

Police officers occasionally encounter belligerents resisting or even physically assaulting them without or with objects. The self-defense or legal utilization of use of force to disable the offender from harming an officer or others may depend on a single movement speed of hands and legs. This study investigated the effects of task complexity on a single movement response time of the upper and lower limbs in police officers. The sample consisted of 32 male police officers aged between 23 and 50 years. They performed a single movement as fast as possible with their upper and lower limb in three incrementally more complex tasks. In the first task, participants acted on a light signal and with their dominant limb they had to turn off the signal as fast as possible. In the second task, on the light signal, participants could turn off the light with free choice of the upper limb in a hand task or lower limb in a leg task. In the third task, participants had to turn the light off with the right limb if the light turned red and with the left limb if the light turned blue. The BlazePod device was used to assess the movement response time. The results show that there was a significant effect of task complexity on the single movement response time of the hand (F = 24.5, p < 0.001) and leg (F = 46.2, p < 0.001). The training of police officers should utilize specific and situational tasks to improve movement response time by improving the redundancy in decision-making processes during work-specific tasks of different complexity.

Association of waist to height ratio with 2.4 kilometers running time among male police populations.

BACKGROUND: Body anthropometrics are biologically predetermined, while morphology responds to energy intake and output and stressors, thus impacting health. Fitness is impacted by these bodily characteristics. OBJECTIVE: This study determined to what degree anthropomorphic measures and age of police officers determined 2.4 km running performance. METHODS: Age, height, weight, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and 2.4 km running time (RUN) of 1916 male police officers were directly measured and analyzed. After determining correlations of anthropomorphic variables with RUN. Stepwise linear regressions evaluated individual associations of age, height, weight, BMI, WC, and WHtR with RUN, to determine the model with the highest predictive value of RUN performance. RESULTS: WHtR was the strongest RUN predictor (r = 0.672, R2 = 0.451, p < 0.001), while the best predictive model apart from WHtR also included age and BM (R2 = 0.556, p < 0.001). CONCLUSIONS: WHtR was the strongest anthropomorphic predictor of RUN performance. As a predictor, WHtR provides information on both anthropometric and morphology components of police officers. Its utilization among police occupations may be more effective than BMI as it better relates to performance.

Accuracy of Body Mass Index and Obesity Status in Police Trainees.

The first aim of this study was to compare body mass index (BMI) (indirect method) classification with the body fat percent (PBF) (direct method) and to determine how BMI classifies subjects with different levels of skeletal muscle mass percent (PSMM). The second aim was to determine the prevalence of overweight and obesity status among police trainees (PTs). A total of 103 male PTs participated in this research: age = 21.46 ± 0.64 years, body mass (BM) = 75.97 ± 8.10 kg, body height (BH) = 174.07 ± 6.31 cm, BMI = 25.05 ± 2.12 kg/m2. The InBody 370 multichannel bioelectrical impedance analysis (BIA) measured body composition. Study results indicated that muscular PTs could be misclassified as overweight and that PBF identified more subjects as obese. Namely, three PTs were obese according to BMI, while 13 were obese according to PBF. The information provided by this research could be used to help professionals understand the importance of measuring body composition, and the inaccuracies in BMI classification. In conclusion, whenever possible PSMM and PBF should replace the utilization of BMI to screen overweight and obesity in PTs. Agencies may think of using BIA as non-invasive, quick and inexpensive measurement tool.

Impact of a 12-Week Postgraduate Training Course on the Body Composition and Physical Abilities of Police Trainees.

ABSTRACT: Cvorovic, A, Kukic, F, Orr, RM, Dawes, JJ, Jeknic, V, and Stojkovic, M. Impact of a 12-week postgraduate training course on the body composition and physical abilities of police trainees. J Strength Cond Res 35(3): 826-832, 2021-The main objective of this study was to determine the effects of a 12-week physical training program on police trainees at the Abu Dhabi Police College. Anthropometric and fitness testing data for 325 healthy trainees, enrolled in an academic course for qualification as a police officer, were analyzed. The trainees were tested 3 times, during the initial (week 1), midpoint (week 7), and final testing (week 13) phases of the training program. The tested variables included anthropometry (body mass [BM]), body composition (body mass index [BMI]; waist circumference [WC]; waist-to-height ratio [WHtR]), upper-body muscular endurance (1-minute push-up [PU]), trunk muscular endurance (1-minute sit-up [SU]), and aerobic endurance (2.4-km run [RUN]). A 1-way analysis of variance with post hoc Bonferroni adjustment was performed to investigate the changes in anthropometry and fitness across the 3 testing periods with percentages of change calculated at each testing stage. Alpha levels were set at 0.05 a priori. Statistically significant differences (range of p values from p < 0.001 to p < 0.05) were found in all tested variables (BM, BMI, WC, WHtR, PU, SU, and RUN) and between all testing stages (initial, midpoint, and final). A progressive physical training program that incorporates mesocycles and midpoint evaluations can have a positive impact on the fitness of trainees even when undergoing a busy academy program.

Differences in Body Composition across Police Occupations and Moderation Effects of Leisure Time Physical Activity.

This study investigated differences in the body composition of police officers from different occupational groups and the moderation effects of leisure time physical activity (LTPA). A sample of 237 police officers (special anti-terrorist unit, gendarmerie, firefighters, and general duties) participated in the study. Body mass index (BMI), percent of body fat (%BF), percent of skeletal muscle mass (%SMM), and index of hypokinesia (IH) were assessed using a multichannel bioelectric impedance analyzer and officers reported the amount of LTPA using an international physical activity questionnaire. The sample was divided in three groups relative to LTPA, sedentary (0-149 min/week), moderately active (150-299 min/week), and very active (300+ min/week). Multiple analysis of variance (4 × 3) was used to analyze if occupational groups differed based solely on occupation, if officers from the same occupation differed in muscularity and fatness based on LTPA, and if any differences in body composition occurred between officers from different occupations with the same level of LTPA. Police officers from more physically demanding occupations demonstrated lower %BF and IH, while having higher %SMM. This was also observed among the officers of the same occupation who reported a higher LTPA, while officers who reported very high LTPA had similar body composition.

Association of sex-related differences in body composition to change of direction speed in police officers while carrying load / Asociación de diferencias relacionadas con el sexo en la composición corporal para cambiar la velocidad de dirección de oficiales de policía durante el transporte de carga

Regardless of sex or body size, police tasks may require officers to change direction speed (CODS) under occupational loads. The purpose of this study was to investigate body composition and CODS in female and male police cadets in both unloaded and occupationally loaded conditions. Body composition and CODS of 51 female (FPC) and 70 male police cadets (MPC) were assessed. Six body composition indices were used: Body mass index (BMI), percent body fat (PBF), percent of skeletal muscle mass (PSMM), protein fat index (PFI), index of hypokinesia (IH), and skeletal muscle mass index (SMMI). The CODS was assessed by Illinois Agility Test (IAT) and IAT while carrying a 10-kg load (LIAT). An independent sample t-test was used to identify the differences between the sexes. The regression determined associations between body composition and LIAT. The alpha level was set at p < 0.05 a priori. MPC had significantly higher (p < 0.001) BMI, PSMM, PFI and SMMI and lower PBF and IH than FPC. MPC were also faster in IAT and LIAT, carrying lower relative loads that imparted less of an impact on CODS performance. Body composition was strongly associated with the time to complete LIAT (R2 = 0.671, p < 0.001). Difference in relative load and body composition influenced CODS performance in both unloaded and loaded conditions. Thus, optimizing body composition through increasing skeletal muscle mass and reducing fat mass could positively influence unloaded and loaded CODS performance and improve elements of police task performance.

El trabajo policial puede requerir que los oficiales cambien la velocidad de dirección (CVD) bajo cargas ocupacionales, indistintamente del sexo o tamaño corporal. El propósito de este estudio fue investigar la composición corporal y los CVD en cadetes de policía de ambos sexos, tanto en condiciones de descarga como de trabajo. Se evaluaron la composición corporal y los CVD de 51 mujeres (CPF) y 70 cadetes de policía masculinos (CPM). Se utilizaron seis índices de composición corporal: índice de masa corporal (IMC), porcentaje de grasa corporal (PGC), porcentaje de masa muscular esquelética (PMME), índice de grasa proteica (IGP), índice de hipocinesia (IH) e índice de masa muscular esquelética (IMME). El CVD fue evaluado por Illinois Agility Test (IAT) y IAT mientras transportaba una carga de 10 kg (LIAT). Se usó una prueba t de muestra independiente para identificar las diferencias entre los sexos. La regresión determinó asociaciones entre la composición corporal y LIAT. El nivel alfa se estableció en p <0,05 a priori. CPM registraron un IMC, PMME, PGC y IMME significativamente más altos (p <0,001) y PGC e IH más bajos que las mujeres (CPF). Los CPM también fueron más rápidos en IAT y LIAT, llevando cargas más bajas, las que tuvieron un impacto menor en el rendimiento de CVD. La composición corporal estaba asociada con el tiempo para completar LIAT (R2 = 0,671, p <0,001). La diferencia en la carga relativa y la composición corporal influyeron en el rendimiento de CVD tanto en condiciones descargadas como cargadas. Por lo tanto, la optimización de la composición corporal a través del aumento de la masa del músculo esquelético, y la reducción de la masa grasa podrían influir de manera positiva en el rendimiento de CVD descargados y cargados, mejorando el rendimiento del trabajo policial.

Relations Between Frequency and Volume of Leisure-Time Physical Activity and Body Composition in Police Officers.

Purpose: Leisure-time physical activity (LTPA) has always been very important for the maintenance and improvement of body composition. Thus, the aim of this study was to examine if the frequency and volume of LTPA (F-LTPA and V-LTPA) were related to indices of body composition in police officers. Method: A physical activity questionnaire was used to collect data from 346 male police officers regarding their F-LTPA and V-LTPA. They were divided into four groups relative to the frequency, and four groups relative to the volume of LTPA, labeled as inactive, seldom active, moderately active and very active for each LTPA indicator. Percent body fat (PBF), skeletal muscle mass (PSMM), skeletal muscle mass index (SMMI) and body fat mass index (BFMI) were assessed. Correlation analyses investigated associations and multivariate analysis of variance analysed the differences between body composition and LTPA, with significance set at p < .05. Results: The F-LTPA correlated (p < .001) to PBF (r = -0.306), BFMI (r = -0.289), PSMM (r = 0.309) and SMMI (r = -0.138, p = .010). The V-LTPA correlated (p < .001) to PBF (r = -0.370), BFMI (r = -0.348), PSMM (r = 0.311), and SMMI (r = -0.106, p = .049). The differences that occurred between more and less active police officers, whereby those who were very active had lower values of PBF and BFMI and higher values of PSMM and SMMI regardless of the frequency and volume of LTPA. PBF and PSMM were more affected by LTPA than SMMI and BFMI. Conclusions: F-LTPA and V-LTPA were considered important for police officers, whereby F-LTPA was related to muscle and V-LTPA to fat parameters of body composition.

Associations between Fitness Measures and Change of Direction Speeds with and without Occupational Loads in Female Police Officers.

Female police officers may be required to pursue offenders on foot while wearing occupational loads. The aim of this study was to determine relationships between fitness measures and change of direction speed (CODS) in female police officers and the influence of their occupational loads. Retrospective data were provided for 27 female police officers (age = 32.19 ± 5.09 y, height = 162.78 ± 5.01 cm, and mass = 71.31 ± 13.42 kg) and included fitness measures of: lower-body power (standing long jump (SLJ)), upper-body and trunk muscle endurance (push-up (PU) and sit-up (SU)), aerobic power (estimated VO2max), and CODS (Illinois agility test). The CODS test was performed without and with occupational load (10 kg). Paired sample t-tests (between-load conditions) and Pearson's correlations (relationships between measures) were performed with linear regression analysis used to account for the contribution of measures to unloaded and loaded CODS performance. CODS was significantly slower when loaded (unloaded = ~23.17 s, loaded = ~24.14 s, p < 0.001) with a strong, significant relationship between load conditions (r = 0.956, p < 0.001). Moderate to strong, significant relationships were found between all fitness measures ranging from estimated VO2max (r = -0.448) to SU (r = -0.673) in the unloaded condition, with the strength of these relationships increasing in the loaded condition accounting for 61% to 67% of the variance, respectively. While unloaded agility test performance was strongly associated with loaded performance, female police officer CODS was significantly reduced when carrying occupational loads. A variety of fitness measures that influence officer CODS performances become increasingly important when occupational loads are carried.

Age-related body composition differences in female police officers / Diferencias de composición corporal relacionadas con la edad en oficiales de la policía femenina

SUMMARY: Since performance in police occupations may depend on body composition and physical abilities, women are less likely to become police officers. However, information on age-related differences in body composition among female police officers (FPO) barely exists. Thus, this study aimed to investigate the association between age and body composition in FPO. Body composition of 95 FPO was assessed and divided into 4 age groups: 21-25 (age = 23.58 ± 0.84 years, body height [BH] = 1.61 ± 0.04 m, body mass [BM] = 65.55 ± 12.59 kg); 26-30 (age = 28.24 ± 1.20 years, BH = 1.61 ± 0.04 m, BM = 72.08 ± 12.80 kg); 31-35 (age = 32.73 ± 1.59 years, BH = 1.62 ± 0.06 m, BM = 74.88 ± 12.22 kg); and 36-40 (age = 37.71 ± 1.40 years, BH = 1.61 ± 0.08 cm, BM = 77.38 ± 11.61 kg). Eight body composition characteristics were measured using bioelectrical impedance (InBody 720): BM, body mass index (BMI), fat mass index (FMI), fat mass (FM), trunk fat mass (TFM), percent body fat mass (PBF), skeletal muscle mass (SMM), and percent skeletal muscle mass (PSMM). A multivariate analysis of variance (MANOVA) with Bonferroni post-hoc test (p<0.05) and Cohen's effect size (ES) were used to determine significant differences in anthropometric variables by age. Statistically significant differences occurred in BM (F = 3.412, p = 0.021), BMI (F = 3.662, p = 0.015), FM (F = 3.411, p = 0.021) and FMI (F = 3.479, p = 0.019). A large inverse ES occurred in trend of age-related differences in PBF and PSMM. The BM is higher relative to age due to FM, which may cause a decrease in PSMM. The most critical period seems to be between 30-35 years.

RESUMEN: Debido a que el desempeño en los trabajos policiales puede depender de la composición corporal y las capacidades físicas, las mujeres tienen menos probabilidades de convertirse en agentes de policía. Sin embargo, existe escasa información sobre las diferencias relacionadas con la edad en la composición corporal entre las mujeres policías (MP). Por lo tanto, el objetivo de este estudio fue investigar la asociación entre la edad y la composición corporal en la MP. La composición corporal de 95 MP se evaluó y dividió en 4 grupos etarios: 21-25 (edad = 23.58 ± 0.84 años, altura corporal [AC] = 1.61 ± 0.04 m, masa corporal [MC] = 65,55 ± 12,59 kg); 26-30 (edad = 28,24 ± 1.20 años, AC = 1,61 ± 0,04 m, MC = 72,08 ± 12,80 kg); 31-35 (edad = 32,73 ± 1,59 años, AC = 1,62 ± 0,06 m, MC = 74,88 ± 12,22 kg); y 36-40 (edad = 37,71 ± 1.40 años, AC = 1,61 ± 0,08 cm, MC = 77,38 ± 11,61 kg). Se midieron ocho características de la composición corporal utilizando la impedancia bioeléctrica (InBody 720): MC, índice de masa corporal (IMC), índice de masa grasa (IMC), masa grasa (MG), masa grasa del tronco (MGT), porcentaje de masa corporal grasa (PMC) , masa muscular esquelética (MME) y porcentaje de masa muscular esquelética (PMME). Se utilizó un análisis de varianza multivariable (MANOVA) con la prueba post-hoc de Bonferroni (p <0.05) y el tamaño del efecto de Cohen (ES) para determinar diferencias significativas en las variables antropométricas por edad. Se observaron diferencias estadísticamente significativas en MC (G = 3,412, p = 0,021), IMC (G = 3,662, p = 0,015), MG (G = 3,411, p = 0,021) y IMG (G = 3,479, p = 0,019). Se produjo un ES inverso grande en la tendencia de las diferencias relacionadas con la edad en PGC y PMME. La MC es más alta en relación con la edad debido a la MG, lo que puede causar una disminución en el PMME. El período más crítico parece ser entre 30-35 años.

Use of human body morphology as an indication of physical fitness: implications for police officers / Uso de la morfología del cuerpo humano como una indicación de la condición física: implicancias en oficiales de policía

Research with police officers (POs) suggests an association between body composition, physical performance and health. The aim of the study was to investigate the associations between body composition and measures of physical fitness, and their use to predict estimated physical fitness score (EPFS). The sample included 163 male POs (age = 31.61 ± 4.79 years, height = 172.97 ± 6.09 cm, body mass = 77.53 ± 11.66 kg). Eight body composition variables: body mass index (BMI), body fat mass index (BFMI), percent of body fat (PBF), percent skeletal muscle mass (PSMM), index of hypokinezia (IH), skeletal muscle mass index (SMMI), protein mass index (PMI), and fat-free mass index (FFMI); and four physical fitness measures: a 3.2 km run, a 2-minute push-up, 2-minute sit-up and estimated physical fitness score (EPFS) were correlated, followed by the regression analysis for causal relationship between body composition and EPFS. Running 3.2 km test correlated to BMI, PBF, PSMM, BFMI, and SMMI (r = 0.274, 0.250, -0.234, 0.311, p<0.01, respectively); 2-minute push-up correlated to PBF, PSMM, BFMI, SMMI, PMI, IH, and FFMI (r = -0.413, 0.436, -0.375, 0.221, 0.231, -0.411, 0.261, p<0.01, respectively); 2-minute sit-up correlated to PBF, PSMM, BFMI, and IH (r = -0.237, 0.250, -0.236, -0.218, p<0.01, respectively); and EPFS correlated to BMI, FFMI, PBF, PSMM, BFMI, and IH (r = -0.200, 0.168, p<0.05, and r = -0.369, 0.378, 0.376, -0.317, p <0.01, respectively). Two models of predictions were extracted: 1) PBF, BFMI, PMI and FFMI (R2 = 0.250, p<0.001); 2) PBF, BFMI and PMI (R2 = 0.244, p<0.001). Obtained prediction models may be a promising screening method of a POs' fitness, when conducting the physical tests is not possible or safe (obese and injured POs or bad weather conditions).

En este trabajo realizado con oficiales de policía (OP) se sugiere una asociación entre la composición corporal y el rendimiento físico y la salud. El objetivo del estudio fue investigar las asociaciones entre la composición corporal y las medidas de aptitud física, y su uso para predecir el puntaje de aptitud física estimado (PAFE). La muestra incluyó 163 OP masculinos (edad = 31,61 ± 4,79 años, altura = 172,97 ± 6,09 cm, masa corporal = 77,53 ± 11,66 kg). Se analizaron ocho variables de composición corporal: índice de masa corporal (IMC), índice de masa corporal grasa (IMCG), porcentaje de grasa corporal (PGC), porcentaje de masa muscular esquelética (PMME), índice de hipoquinezia (IH), índice de masa muscular esquelética (IMME), índice de masa proteica (IMP) e índice de masa libre de grasa (IMLG); y cuatro medidas de aptitud física: se correlacionaron una carrera de 3,2 km, una elevación de 2 minutos, una postura de 2 minutos y un puntaje de aptitud física estimada (PAFE), seguido del análisis de regresión para la relación causal entre la composición corporal y el PAFE. La prueba de ejecución de 3,2 km se correlacionó con el IMC, PGC, PMME, IMCG y IMME (r = 0,274, 0,250, -0,234, 0,311, p <0,01, respectivamente); Push-up de 2 minutos correlacionado con PGC, PMME, IMCG, IMME, PMI, IH y IMLG (r = -0,413, 0,436, -0,375, 0,221, 0,231, 0,411, 0,261, p <0,01, respectivamente); Sit-up de 2 minutos correlacionado con PGC, PMME, IMCG e IH (r = -0,237, 0,250, 0,236, -0,218, p <0,01, respectivamente); y EPFS correlacionado con IMC, IMLG, PGC , PMME, IGMC e IH (r = -0,200, 0,168, p <0,05, y r = -0,369, 0,378, 0,376, -0,317, p <0,01, respectivamente). Se extrajeron dos modelos de predicción: 1) PGC, IGMC, IMP y IMLG (R2 = 0,250, p <0,001); 2) PGC, IGMC y IMP (R2 = 0,244, p <0,00). Los modelos de predicción obtenidos pueden ser un método prometedor de detección de la condición física de los OP, cuando no es posible o seguro realizar las pruebas físicas (OP obesos y lesionados o condiciones climáticas adversas).