Physical Activity in German Adolescents Measured by Accelerometry and Activity Diary: Introducing a Comprehensive Approach for Data Management and Preliminary Results

Introduction

Surveillance of physical activity (PA) is increasingly based on accelerometry. However, data management guidelines are lacking. We propose an approach for combining accelerometry and diary based PA information for assessment of PA in adolescents and provide an example of this approach using data from German adolescents.

Methods

The 15-year-old participants comprised a subsample the GINIplus birth cohort (n = 328, 42.4% male). Data on PA was obtained from hip-worn accelerometers (ActiGraph GT3X) for seven consecutive days, combined with a prospective activity diary. Major aspects of data management were validity of wear time, handling of non-wear time and diary comments. After data cleaning, PA and percentage of adolescents meeting the recommendations for moderate-to-vigorous activity (MVPA) per day were determined.

Results

From the 2224 recorded days 493 days (25%) were invalid, mainly due to uncertainties relating to non-wear time (322 days). Ultimately, 269 of 328 subjects (82%) with valid data for at least three weekdays and one weekend day were included in the analysis. Mean MVPA per day was 39.1 minutes (SD ±25.0), with boys being more active than girls (41.8±21.5 minutes vs. 37.1±27.8 minutes, p<0.001). Accordingly, 24.7% of boys and 17.2% of girls (p<0.01) met the WHO recommendations for PA. School sport accounted for only 6% of weekly MVPA. In fact, most MVPA was performed during leisure time, with the majority of adolescents engaging in ball sports (25.4%) and endurance sports (19.7%). Girls also frequently reported dancing and gymnastics (23%).

Conclusion

For assessment of PA in adolescents, collecting both accelerometry and diary-based information is recommended. The diary is vital for the identification of invalid data and non-compliant participants. Preliminary results suggest that four out of five German adolescents do not meet WHO recommendations for PA and that school sport contributes only little to MVPA.     

Sport Engagement by Accelerometry under Field Conditions in German Adolescents: Results from GINIPlus

Introduction

Sporting activities differ in their ability to promote moderate-to-vigorous physical activity (MVPA). To assess adolescents’ engagement in sport under field conditions we used accelerometers to measure their MVPA levels during sport. We pay special attention to differences between team and individual sport and between common sports.

Methods

Diary data and 7-day accelerometry from 1054 Germans ages 15–17 were combined to measure physical activity. 1373 diaried episodes of more than 40 common sports were identified from 626 participants and grouped into team and individual sport. We modeled the effect of team and individual sport, and described levels of MVPA and episodes of no MVPA for all recorded sports.

Results

German boys and girls averaged 43 (SD 21) and 37 (SD 24) minutes MVPA per day. Boys got 2.2 times as much MVPA per minute during team compared to individual sport (p<0.0001) but there was no significant difference for girls. Percent of time spent in MVPA during sport ranged from 6% for weight training to 74% for jogging, with individual sports averaging 10–30% and team sports 30–50%. 11% of sport episodes had no MVPA: half of episodes of cycling, 5% of jogging, and none for tennis or badminton. An episode of individual sport was 17 times more likely to have no MVPA than an episode of team sport (p<0.0001).

Conclusion

Under field condition, adolescents were active for only a fraction of diaried sporting time. As measured by accelerometry, individual sport often produced no MVPA. Characteristics of the sport, such as team vs. individual, were more predictive of MVPA than were characteristics of the participant, such as background activity levels.     

Energy Expenditure Compared to Physical Activity Measured by Accelerometry and Self-Report in Adolescents: A Validation Study

Background

Physical inactivity is responsible for 5.3 million deaths annually worldwide. To measure physical activity energy expenditure, the doubly labeled water (DLW) method is the gold standard. However, questionnaires and accelerometry are more widely used. We compared physical activity measured by accelerometer and questionnaire against total (TEE) and physical activity energy expenditure (PAEE) estimated by DLW.

Methods

TEE, PAEE (TEE minus resting energy expenditure) and body composition were measured using the DLW technique in 25 adolescents (16 girls) aged 13 years living in Pelotas, Brazil. Physical activity was assessed using the Actigraph accelerometer and by self-report. Physical activity data from accelerometry and self-report were tested against energy expenditure data derived from the DLW method. Further, tests were done to assess the ability of moderate-to-vigorous intensity physical activity (MVPA) to predict variability in TEE and to what extent adjustment for fat and fat-free mass predicted the variability in TEE.

Results

TEE varied from 1,265 to 4,143 kcal/day. It was positively correlated with physical activity (counts) estimated by accelerometry (rho  = 0.57; p = 0.003) and with minutes per week of physical activity by questionnaire (rho  = 0.41; p = 0.04). An increase of 10 minutes per day in moderate-to-vigorous intensity physical activity (MVPA) relates to an increase in TEE of 141 kcal/day. PAEE was positively correlated with accelerometry (rho  = 0.64; p = 0.007), but not with minutes per week of physical activity estimated by questionnaire (rho  = 0.30; p = 0.15). Physical activity by accelerometry explained 31% of the vssariability in TEE. By incorporating fat and fat-free mass in the model, we were able to explain 58% of the variability in TEE.

Conclusion

Objectively measured physical activity significantly contributes to the explained variance in both TEE and PAEE in Brazilian youth. Independently, body composition also explains variance in TEE, and should ideally be taken into account when using accelerometry to predict energy expenditure values.     

Extremely Reduced Motion in Front of Screens: Investigating Real-World Physical Activity of Adolescents by Accelerometry and Electronic Diary

This paper reports accelerometer and electronic dairy data on typical daily activities of 139 school students from grade six and nine. Recordings covered a typical school day for each student and lasted on average for 23 h. Screen activities (watching television and using the computer) are compared to several other activities performed while sitting (e.g., playing, eating, sitting in school, and doing homework). Body movement was continuously recorded by four accelerometers and transformed into a motion sore. Our results show that extremely low motion scores, as if subjects were freezing, emerge to a greater extent in front of screens compared to other investigated activities. Given the substantial amount of time young people spend in front of screens and the rising obesity epidemic, our data suggest a mechanism for the association of screen time and obesity.     

Levels and Patterns of Objectively Assessed Physical Activity and Compliance with Different Public Health Guidelines in University Students

Background

Physical activity (PA) is associated with health enhancement. The aim of this study was to assess: 1) levels and patterns of PA in university students by using accelerometers; and 2) the percentage of fulfilment of PA recommendations for adults, according to different public health guidelines.

Methods

Observational cross-sectional study (Cuenca’s Adults Study) involving 296 (206 women) healthy Spanish university students aged 18–25 years old. Participants wore the ActiGraph GT1M accelerometer for seven consecutive days. Total PA, steps and time spent in sedentary time, light, moderate, vigorous, and moderate to vigorous PA (MVPA) was assessed, and the prevalence of sufficient PA was calculated according to various public health guidelines.

Results

No sex differences in total PA were found. University students were more sedentary during weekend days than weekdays (p<0.05). Only 30.3% of participants accumulated 30 min/day at least five days a week of MVPA. A total of 5.4% of students met the recommendation of 150 min/week of MVPA or 75 min/week of vigorous PA, in PA bouts of at least 10 min. using the same definition, but on five or more days a week, only 0.5% students were found to meet the recommendation. In addition, only 0.5% of students met the recommendation of 30 min/day of MVPA, at least five days a week and in bouts of at least 10 min. Finally, 28.1% of the students met the recommendation of 10,000 steps/day.

Conclusions

Our study shows a high incidence of sedentary time in university students. The number of students meeting PA recommendations significantly differed depending on the recommendation proposed. Specific strategies to promote PA in this population are necessary as well as an agreement as to which PA guidelines should be used.     

Measuring Free‐Living Energy Expenditure and Physical Activity with Triaxial Accelerometry

Objective: To investigate the ability of a newly developed triaxial accelerometer to predict total energy expenditure (EE) (TEE) and activity‐related EE (AEE) in free‐living conditions. Research Methods and Procedures: Subjects were 29 healthy subjects between the ages of 18 and 40. The Triaxial Accelerometer for Movement Registration (Tracmor) was worn for 15 consecutive days. Tracmor output was defined as activity counts per day (ACD) for the sum of all three axes or each axis separately (ACD‐X, ACD‐Y, ACD‐Z). TEE was measured with the doubly labeled water technique. Sleeping metabolic rate (SMR) was measured during an overnight stay in a respiration chamber. The physical activity level was calculated as TEE × SMR^?1, and AEE was calculated as [(0.9 × TEE) ? SMR]. Body composition was calculated from body weight, body volume, and total body water using Siri's three‐compartment model. Results: Age, height, body mass, and ACD explained 83% of the variation in TEE [standard error of estimate (SEE) = 1.00 MJ/d] and 81% of the variation in AEE (SEE = 0.70 MJ/d). The partial correlations for ACD were 0.73 (p < 0.001) and 0.79 (p < 0.001) with TEE and AEE, respectively. When data on SMR or body composition were used with ACD, the explained variation in TEE was 90% (SEE = 0.74 and 0.77 MJ/d, respectively). The increase in the explained variation using three axes instead of one axis (vertical) was 5% (p < 0.05). Discussion: The correlations between Tracmor output and EE measures are the highest reported so far. To measure daily life activities, the use of triaxial accelerometry seems beneficial to uniaxial.     

Localization of Physical Activity in Primary School Children Using Accelerometry and Global Positioning System

Background

Ecological approaches have highlighted the importance of the built environment as a factor affecting physical activity. However, knowledge on children’s activity patterns is still incomplete. Particularly, data on the spatial context of physical activity is limited, which limits the potential to design location-based interventions effectively. Using global positioning system (GPS) and accelerometry, this study aimed to identify locations where children engage in moderate-vigorous physical activity (MVPA).

Methods

Participants included 119 children (11–14 years, 57% girls) from public schools in Winterthur, Switzerland. During a regular school week between February and April 2013, children wore an accelerometer and GPS sensor for seven consecutive days. Time-matched accelerometer and GPS data was mapped with a geographic information system and each data point was assigned to one of seven defined activity settings. Both the absolute amount of MVPA and proportion of time in MVPA were calculated for every setting. Multilevel analyses accounting for the hierarchical structure of the data were conducted to investigate any gender differences.

Results

Children achieved most MVPA on streets (34.5%) and on school grounds (33.4%). The proportion children spent in MVPA was highest in recreational facilities (19.4%), at other schools (19.2%) and on streets (18.6%). Boys accumulated significantly more MVPA overall and on other school grounds (p < 0.05) and showed a significantly higher proportion of time in MVPA at own school and outside of Winterthur (p < 0.05).

Conclusions

The results indicate the importance of streets and school grounds as activity-promoting environments. The high use of streets may be an indicator for active transportation, which appears to contribute to an active lifestyle in both genders. In contrast, the school setting is more likely to encourage physical activity in boys. Recreational facilities seem to be conducive for MVPA among both genders, although infrequently visited during the week of measurement.     

Light-Intensity Physical Activity and Cardiometabolic Biomarkers in US Adolescents

Background

The minimal physical activity intensity that would confer health benefits among adolescents is unknown. The purpose of this study was to examine the associations of accelerometer-derived light-intensity (split into low and high) physical activity, and moderate- to vigorous-intensity physical activity with cardiometabolic biomarkers in a large population-based sample.

Methods

The study is based on 1,731 adolescents, aged 12–19 years from the 2003/04 and 2005/06 National Health and Nutrition Examination Survey. Low light-intensity activity (100–799 counts/min), high light-intensity activity (800 counts/min to <4 METs) and moderate- to vigorous-intensity activity (≥4 METs, Freedson age-specific equation) were accelerometer-derived. Cardiometabolic biomarkers, including waist circumference, systolic blood pressure, diastolic blood pressure, HDL-cholesterol, and C-reactive protein were measured. Triglycerides, LDL- cholesterol, insulin, glucose, and homeostatic model assessments of β-cell function (HOMA-%B) and insulin sensitivity (HOMA-%S) were also measured in a fasting sub-sample (n = 807).

Results

Adjusted for confounders, each additional hour/day of low light-intensity activity was associated with 0.59 (95% CI: 1.18–0.01) mmHG lower diastolic blood pressure. Each additional hour/day of high light-intensity activity was associated with 1.67 (2.94–0.39) mmHG lower diastolic blood pressure and 0.04 (0.001–0.07) mmol/L higher HDL-cholesterol. Each additional hour/day of moderate- to vigorous-intensity activity was associated with 3.54 (5.73–1.35) mmHG lower systolic blood pressure, 5.49 (1.11–9.77)% lower waist circumference, 25.87 (6.08–49.34)% lower insulin, and 16.18 (4.92–28.53)% higher HOMA-%S.

Conclusions

Time spent in low light-intensity physical activity and high light-intensity physical activity had some favorable associations with biomarkers. Consistent with current physical activity recommendations for adolescents, moderate- to vigorous-intensity activity had favorable associations with many cardiometabolic biomarkers. While increasing MVPA should still be a public health priority, further studies are needed to identify dose-response relationships for light-intensity activity thresholds to inform future recommendations and interventions for adolescents.     

Physical Activity Energy Expenditure of Adolescents in India

Physical activity (PA) has rarely been quantified in adolescent populations undergoing economic transition; therefore relationships with disease still remain uncertain. This study assessed whether absolute PA energy expenditure (PAEE), PAEE/kg, and PAEE/kg_FFM could be accurately estimated using accelerometry and a questionnaire in Indian adolescents and how these values compared to those of other populations. PAEE was assessed using doubly labeled water (DLW) in 30 adolescents from Chennai, India, over seven consecutive days, simultaneous with the measurement of PA using accelerometry and a previous‐week recall questionnaire. Accelerometry counts (regression analysis) and questionnaire data were used to estimate PAEE; estimates were cross‐validated using the Bland‐Altman method. Accelerometry data and DLW‐derived PAEE were visually compared to values from four North American and European populations. For boys, 49% of the variance in DLW‐derived PAEE was explained with an equation including accelerometry counts and fat‐free mass (FFM). Questionnaire‐derived estimates did not contribute to the explained variance in DLW derived PAEE. The group‐level PA of these Indian adolescents was successfully assessed using accelerometry, but not questionnaire. DLW‐derived PAEE/kg_FFM (mean (s.d.): 53.0 (27.5) kJ/kg_FFM/day) was lower in this group than other adolescent populations in Europe and similar to those in North America. Additionally, four boys and none of the girls accumulated ≥60 min/day of accelerometry‐derived moderate intensity activity, indicating low levels of PAEE and PA in these adolescents. Further research is necessary to investigate the association between PA and health outcomes in Indian adolescents.     

Predicting Physical Activity Energy Expenditure Using Accelerometry in Adults From Sub‐Sahara Africa

Lack of physical activity may be an important etiological factor in the current epidemiological transition characterized by increasing prevalence of obesity and chronic diseases in sub‐Sahara Africa. However, there is a dearth of data on objectively measured physical activity energy expenditure (PAEE) in this region. We sought to develop regression equations using body composition and accelerometer counts to predict PAEE. We conducted a cross‐sectional study of 33 adult volunteers from an urban (n = 16) and a rural (n = 17) residential site in Cameroon. Energy expenditure was measured by doubly labeled water (DLW) over a period of seven consecutive days. Simultaneously, a hip‐mounted Actigraph accelerometer recorded body movement. PAEE prediction equations were derived using accelerometer counts, age, sex, and body composition variables, and cross‐validated by the jack‐knife method. The Bland and Altman limits of agreement (LOAs) approach was used to assess agreement. Our results show that PAEE (kJ/kg/day) was significantly and positively correlated with activity counts from the accelerometer (r = 0.37, P = 0.03). The derived equations explained 14–40% of the variance in PAEE. Age, sex, and accelerometer counts together explained 34% of the variance in PAEE, with accelerometer counts alone explaining 14%. The LOAs between DLW and the derived equations were wide, with predicted PAEE being up to 60 kJ/kg/day below or above the measured value. In summary, the derived equations performed better than existing published equations in predicting PAEE from accelerometer counts in this population. Accelerometry could be used to predict PAEE in this population and, therefore, has important applications for monitoring population levels of total physical activity patterns.     

Patterns and Associated Factors of Physical Activity among Adolescents in Nigeria

Introduction

Understanding the context where adolescents’ physical activity (PA) takes place could impact a more targeted approach to implement PA promotion and interventions in Africa. However, standardized data on adolescents’ PA behaviour is lacking in Nigeria. We described PA patterns in the various domains (home, school, transport, leisure-time) and intensity categories (light-intensity PA, moderate- to vigorous- intensity physical activity [MVPA] and total PA), and their associations with sociodemographic factors and socioeconomic status (SES) among secondary school adolescents in Nigeria.

Methods

A cross-sectional survey was conducted in a representative sample of 1006 secondary school adolescents (12–18 years, 50.4% girls) in Maiduguri, Nigeria. Self-reported PA was assessed with an adapted version of the Activity Questionnaire for Adolescents and Young Adults. Outcomes were weekly minutes (min/wk) of PA spent in the various domains and intensity categories. Multivariate ANOVA was used to examine associations of PA scores (domains and intensity levels) with adolescents’ sociodemographic characteristics and SES, and track differences in PA scores between subgroups.

Results

The total sample reported most PA at school (1525 min/wk), the least during active transportation (210 min/wk), and only 37% engaged in 60 min of MVPA daily. Boys reported significantly more leisure-time PA (P<0.001), active transportation (P<0.001), MVPA (P = 0.023) and total PA (P = 0.003) than girls, while girls reported more school-based PA (P = 0.009), home-based PA (P<0.001) and light-intensity PA (P<0.001) than boys. Moderate-intensity PA (P = 0.024) and total PA (P = 0.049) were significantly higher in younger age group than in older group. Household car ownership was associated with less active transportation (P = 0.009), less moderate-intensity PA (P = 0.048) and with more leisure-time PA (P = 0.013). High parental SES was associated with more leisure-time PA (P = 0.002), more MVPA (P = 0.047) and less active transportation (P<0.001). Adolescents of various weight status differed significantly in their leisure-time PA (P<0.001), moderate-intensity PA (P = 0.011) and total PA (P = 0.033).

Conclusions

The patterns and levels of physical activity among adolescents in Nigeria vary according to the adolescents’ age, gender, weight status and SES. These findings have important public health implications for identifying subgroups of Nigerian adolescents that should be targeted for effective physical activity promoting interventions.     

Physical Performance and Physical Activity in Older Adults: Associated but Separate Domains of Physical Function in Old Age

Background

Physical function is a crucial factor in the prevention and treatment of health conditions in older adults and is usually measured objectively with physical performance tests and/or physical activity monitoring.

Objective

To examine whether 1) physical performance (PP) and physical activity (PA) constitute separate domains of physical function; 2) differentiation of PA classes is more informative than overall PA.

Design

Cross-sectional study to explore the relationships within and among PP and PA measures.

Methods

In 49 older participants (83±7 years; M±SD), performance-based tests were conducted and PA was measured for one week. Activity monitor data were reduced in terms of duration, periods, and mean duration of periods of lying, sitting, standing and locomotion. The relation between and within PP scores and PA outcomes were analysed using rank order correlation and factor analysis.

Results

Factor structure after varimax rotation revealed two orthogonal factors explaining 78% of the variance in the data: one comprising all PA variables and one comprising all PP variables. PP scores correlated moderately with PA in daily life. Differentiation of activity types and quantification of their duration, intensity and frequency of occurrence provided stronger associations with PP, as compared to a single measure of acceleration expressing overall PA.

Limitations

For independent validation, the conclusions about the validity of the presented conceptual framework and its clinical implications need to be confirmed in other studies.

Conclusions

PP and PA represent associated but separate domains of physical function, suggesting that an improvement of PP does not automatically imply an increase of PA, i.e. a change to a more active lifestyle. Differentiation of activity classes in the analysis of PA provides more insights into PA and its association with PP than using a single overall measure of acceleration.     

Association between Physical Activity Knowledge and Levels of Physical Activity in Chinese Adults with Type 2 Diabetes

BackgroundPhysical activity (PA) is an important treatment regimen for diabetes. The purposes of this study were to evaluate people’s knowledge of how exercise influences wellbeing (termed “PA knowledge” or “knowledge of PA” in this paper) and the resulting association with levels of PA in Chinese adults with Type 2 diabetes, and to identify the valuable demographic and lifestyle factors that possibly influence the association between PA knowledge and level of PA.MethodsTwo hundred and fifty-eight adults with Type 2 diabetes completed an interviewer-administered survey at a diabetes clinic in Hong Kong. Data on demographics, lifestyle factors and diabetes-related medical indicators were obtained. A 20-item questionnaire was developed to measure PA-related knowledge (one point scored for each correct answer; aggregate score up to 20 points). level of PA was measured by the International Physical Activity Questionnaire.ResultsThe proportions of correct answers to each question ranged from 19.4 to 90.7%. Compared with poorly educated participants, those with university education level and above had PA knowledge scores 1.7 points higher (14.3 vs. 12.6, P<0.05). Younger, female, and obese participants were more likely to have lower level of PA (all P<0.05). After adjustment for age, gender, (BMI) and education level, the odds of having a moderate-to-high level of PA was 19% greater with 1 unit increase in PA knowledge score [95% confidence interval (CI): 1.09–1.29; P<0.001], this association was strongest in participants with tertiary education level or above [odds ratio (OR): 1.35; 95% CI: 1.03–1.77; P<0.05].ConclusionsPA knowledge was positively associated with level of PA. Education level significantly influenced the association between PA knowledge and level of PA, leading to the suggestion of vulnerable groups to target for PA improvement in the face of diabetes.     

The Role of School Environment in Physical Activity among Brazilian Adolescents

Objective

To analyze the association of physical activity facilities and extracurricular sports activities in schools with physical activity among adolescents.

Methodology/Principal Findings

We used data collected for the National Survey of School Health in 2012. The national representative sample comprised 109,104 Brazilian students from 2,842 schools. We calculated the prevalence of participation in physical education classes, leisure-time physical activity, and total physical activity level. We also evaluated the following physical activity facilities: sports courts, running/athletics tracks, schoolyard with teacher-directed physical activities, swimming pools, locker rooms; and the offer of extracurricular sports activities. Schools with at least one physical activity facility had increased odds of participation in physical education (OR 1.59; 95% CI 1.20 to 2.10). However, in order to increase leisure-time physical activity (OR1.14; 95% CI 1.03 to 1.26) and total physical activity level (OR 1.15; 95% CI 1.06 to 1.24) at least four and two facilities, respectively, were necessary. Extracurricular sports activities in schools were positively associated with leisure-time physical activity and physical activity level. The number of sports courts and swimming pool in a school were associated with participation in physical education classes. Availability of sports courts, running/athletics tracks, and swimming pool in schools were associated with leisure-time physical activity. Total physical activity was associated with schools with sports courts, schoolyard with teacher-directed physical activities, and swimming pool.

Conclusions

School-level characteristics have important potential to increase the possibility of engagement in physical activity in and out of school, and therefore have a fundamental role in promoting these practices.     

No cross-sectional and longitudinal association of ferritin and symptoms of attention-deficit-/hyperactivity disorder in a large population-based sample of children: results from the GINIplus and LISAplus studies

Attention-deficit/hyperactivity disorder (ADHD) has been associated with alterations in iron metabolism, and low ferritin concentrations in peripheral blood have inconsistently been reported in clinically referred samples of children with ADHD. This study examined whether higher peripheral concentrations of ferritin, the major iron storage protein, are associated with decreased symptoms of ADHD in 2,805 children aged 10 years participating in two large population-based birth cohorts (GINIplus and LISAplus). Whether high ferritin concentrations at age 4 months predict lower ADHD symptoms at age 10 years was also investigated using a longitudinal approach in a subsample of 193 children. No indications for an association between peripheral ferritin concentrations and ADHD symptoms were found in this large population-based study. Re-evaluating iron substitution as a therapeutic measure for ADHD may be warranted.     

Longitudinal Changes in the Physical Activity of Adolescents with Anorexia Nervosa and Their Influence on Body Composition and Leptin Serum Levels after Recovery

Objective

Patients with anorexia nervosa (AN) are often observed to have high levels of physical activity, which do not necessarily diminish after a successful therapy. Previous studies have shown that body fat tissue recovery in these patients is associated with a disproportional restoration of the adipocyte hormone, leptin. Therefore, we wondered whether the individual variation in physical activity in AN patients prior to treatment may be related to body fat percentage and plasma leptin level outcome.

Method

Body fat percentage, leptin serum, and physical activity levels (accelerometer) were measured in adolescents with an (n=37, age 13 to 17.5 years) at initial assessment, at the end of study participation (median 12 months), and at one-year follow-up.

Results

Accelerometer data were used to split the patients in two groups: those with low (n=26) and those with high levels of physical activity (HLPA, n=11). These groups did not differ in terms of age, IQ, presence of menses, BMI and season of admission. The HLPA group was characterized by a longer total duration of illness. Physical activity levels during therapy decreased for the group with initially HLPA and increased for the group with low levels of physical activity (to comparable levels). Physical activity remained stable after one year. The increase in body fat percentage and leptin levels were dependent on the recovery status; however, recovered patients with initially HLPA had significantly higher fat mass during the follow-up.

Discussion

HLPA, an important modulator of AN progression in adolescents, can be successfully diminished by therapeutic intervention. Among recovered patients, those with initially HLPA had higher fat mass levels than those with low levels of physical activity. This finding suggests that HLPA are an important modulator of the body composition recovery mechanism.     

Influential Factors of Insufficient Physical Activity among Adolescents with Asthma in Taiwan

Purpose

Little research has been reported concerning insufficient physical activity in Taiwanese adolescents with asthma. The aims of this paper are to compare the amount of physical activity between asthmatic and non-asthmatic adolescents in Taiwan, as well as to investigate the influential factors associated with insufficient physical activity in asthmatic adolescents.

Methods

Self-reporting structured questionnaires (socio-economic status, scale of family support for physical activity, amount of physical activity) and peak expiratory flow were assessed from 286 adolescents with asthma and 588 non-asthmatic adolescents in a cross-sectional design. Insufficient amount of physical activity was based on less than 300 minutes per week of moderate and vigorous physical activity.

Results

Adolescents with asthma have a greater amount of physical activity and a higher level of family support than those who are non-asthmatic. In Taiwan, adolescents with asthma, girls relative to boys, obesity relative to average weight, and low family support relative to high family support were found to be associated with insufficient physical activity.

Conclusion

Physical activity in adolescents with asthma is insufficient especially in girls, in asthmatics with obesity, and in those with low family support. We suggest that physical activity programs should be applied to Taiwan adolescents with asthma in order to match the criteria of 300 minutes per week of moderate and vigorous physical activity, especially for girls, the obese and those with a low level of family support.