Niels Christian Møller

The effects of physical activity and exercise on brain-derived neurotrophic factor in healthy humans: A review

The purpose of this study was to summarize the effects of physical activity and exercise on peripheral brain‐derived neurotrophic factor (BDNF) in healthy humans. Experimental and observational studies were identified from PubMed, Web of Knowledge, Scopus, and SPORT Discus. A total of 32 articles met the inclusion criteria. Evidence from experimental studies suggested that peripheral BDNF concentrations were elevated by acute and chronic aerobic exercise. The majority of the studies suggested that strength training had no influence on peripheral BDNF. The results from most observational studies suggested an inverse relationship between the peripheral BDNF level and habitual physical activity or cardiorespiratory fitness. More research is needed to confirm the findings from the observational studies.

Longitudinal associations of cycling to school with adolescent fitness

OBJECTIVE To investigate whether change in transport to school from non-cycling to cycling was associated with change in cardio-respiratory fitness (CRF) over a six-year follow-up. METHODS Participants were 384 children (9.7 (0.5) years) who participated in the Danish arm of the European Youth Heart Study in 1997 and who were followed up 6 years later. CRF was assessed by a maximal cycle ergometer test and travel to school was investigated by questionnaire at both time points. Linear regression models were used to investigate associations between CRF and change in mode of travel to school between baseline and follow-up. RESULTS Higher CRF was significantly associated with cycling to school in children and adolescents of both sexes. Longitudinal regression models showed that a change in travel mode from non-cycling to cycling was a significant predictor of CRF at follow-up (P<0.001) after adjustment for potential confounders. Participants who did not cycle to school at baseline, but who had changed to cycling at follow-up, were significantly fitter (0.33 W kg(-1)) than those who did not cycle to school at either time point (P=0.001), a difference of 9%. CONCLUSION Cycling to school may contribute to higher cardiovascular fitness in young people.

Tracking of objectively measured physical activity from childhood to adolescence: The European youth heart study

A number of studies have investigated tracking of physical activity from childhood to adolescence and, in general, these studies have been based on methods with some degree of subjectivity (e.g., questionnaires). The aim of the present study was to evaluate tracking of physical activity from childhood to adolescence using accelerometry, taking into account major sources of variation in physical activity. Both a crude and an adjusted model was fitted, and, in the adjusted model, analyses were corrected for seasonal variation, within‐week variation, activity registration during night time sleep, within instrumental measurement error, and day‐to‐day variation in physical activity. In all, 208 subjects were included in the crude analyses. Stability coefficients estimated from the crude model were low (i.e., 0.18 and 0.19 for boys and girls, respectively) and only borderline significant. However, in the adjusted model highly significant stability coefficients of 0.53 and 0.48 for boys and girls, respectively, were observed. It was concluded that physical activity behavior tends to track moderately from childhood to adolescence.

Sources of variation in habitual physical activity of children and adolescents: the European youth heart study

The present study examined the influence of gender, maturity state, seasonality, type of measurement day and socioeconomic status (SES) on habitual physical activity in 8–10‐year‐old children and 14–16‐year‐old adolescents (n=1318). Physical activity was assessed objectively by accelerometry. The results showed a significant effect of the type of measurement day on physical activity with a general pattern of lower activity levels in weekends compared with weekdays. Furthermore, higher physical activity levels were observed during the months of spring/summer compared with the months of autumn/winter for the 8–10‐year‐olds, whereas no significant effect of months was observed for the 14–16‐year‐olds, possibly due to exam preparations and lack of physical activity registration during the months of summer for this cohort. SES was unrelated to physical activity in the 8–10‐year‐olds, whereas an inverse association was observed in the 14–16‐year‐olds. However, a post hoc analysis provided strong evidence that this latter result was biased by the accelerometers inability to pick up bicycling activities. Finally, boys were more physically active compared with girls, and maturity state was unrelated to physical activity. The results could prove useful for working out strategies to prevent inactivity and for adjusting for temporal sources of variation in physical activity in future studies.

Tracking and prevalence of cardiovascular disease risk factors across socio-economic classes: A longitudinal substudy of the European Youth Heart Study

BackgroundThe highest prevalence of several cardiovascular disease risk factors including obesity, smoking and low physical activity level is observed in adults of low socioeconomic status. This study investigates whether tracking of body mass index and physical fitness from childhood to adolescence differs between groups of socioeconomic status. Furthermore the study investigates whether social class differences in the prevalence of overweight and low physical fitness exist or develop within the age range from childhood to adolescence.MethodsIn all, 384 school children were followed for a period of six years (from third to ninth grade). Physical fitness was determined by a progressive maximal cycle ergometer test and the classification of overweight was based on body mass index cut-points proposed by the International Obesity Task Force. Socioeconomic status was defined according to The International Standard Classification of Occupation scheme.ResultsModerate and moderately high tracking was observed for physical fitness and body mass index, respectively. No significant difference in tracking was observed between groups of socioeconomic status. A significant social gradient was observed in both the prevalence of overweight and low physical fitness in the 14–16-year-old adolescents, whereas at the age of 8–10 years, only the prevalence of low physical fitness showed a significant inverse relation to socioeconomic status. The odds of both developing and maintaining risk during the measurement period were estimated as bigger in the group of low socioeconomic status than in the group of high socioeconomic status, although differences were significant only with respect to the odds of developing overweight.ConclusionThe results indicate that the fundamental possibilities of predicting overweight and low physical fitness at an early point in time are the same for different groups of socio-economic status. Furthermore, the observed development of social inequalities in the absolute prevalence of overweight and low physical fitness underline the need for broad preventive efforts targeting children of low socioeconomic status in early childhood.

Six-Year Change in Youth Physical Activity and Effect on Fasting Insulin and HOMA-IR

BACKGROUND There is a shortage of longitudinal data analyzing associations between physical activity and indicators of insulin resistance among children and adolescents after accounting for adiposity change. To guide future prevention efforts, data were used from the Danish arm of the European Youth Heart Study to examine these issues. METHODS Participants were 384 students in Grade 9 (aged 15 years) from the municipality of Odense, Denmark, who participated in surveys in 1997 and 2003. Physical activity was monitored for at least 3 days by accelerometer, and mean counts per minute (CPM) and minutes >3000 CPM per day were obtained. Blood samples were collected, and levels of fasting insulin, fasting glucose, and homeostasis model of assessment of insulin resistance (HOMA-IR) were obtained. Data were analyzed in 2008. RESULTS Physical activity declined from 45 minutes >3000 CPM in 1997 to 35 minutes >3000 CPM in 2003. Longitudinal regression analyses showed that a change in minutes >3000 CPM was negatively associated with fasting insulin levels (z=-2.47, p=0.014) and HOMA-IR (z=-2.31, p=0.021) in 2003. Similar findings were found when CPM was used as the physical activity variable. Results demonstrated that a 6-year decline in physical activity was associated with higher insulin and HOMA-IR levels. CONCLUSIONS The 6-year change in the volume of physical activity engaged in by adolescents aged 15 years was negatively associated with fasting insulin and HOMA-IR. Preventing an age-related decline in physical activity may be an effective means of preventing youth insulin resistance.

Study protocol. The Childhood Health, Activity, and Motor Performance School Study Denmark (The CHAMPS-study DK)

BackgroundAn increasingly passive life-style in the Western World has led to a rise in life-style related disorders. This is a major concern for all segments of society. The county council of the municipality of Svendborg in Denmark, created six Sport Schools with increased levels of suitable physical activities, which made it possible to study the health outcomes in these children whilst comparing them to children who attended the ‘normal’ schools of the region using the design of a “natural experiment”.MethodsChildren from the age of 6 till the age of 10, who accepted to be included in the monitoring process, were surveyed at baseline with questionnaires, physical examinations and physical and biological testing, including DXA scans. The physical examination and testing was repeated during the early stage of the study. Every week over the whole study period, the children will be followed with an automated mobile phone text message (SMS-Track) asking questions on their leisure time sports activities and the presence of any musculoskeletal problems. Children who report any such problems are monitored individually by health care personnel. Data are collected on demography, health habits and attitudes, physical characteristics, physical activity using accelerometers, motor performance, fitness, bone health, life-style disorders, injuries and musculoskeletal problems. Data collection will continue at least once a year until the children reach grade 9.DiscussionThis project is embedded in a local community, which set up the intervention (The Sport Schools) and thereafter invited researchers to provide documentation and evaluation. Sport schools are well matched with the ‘normal’ schools, making comparisons between these suitable. However, subgroups that would be specifically targeted in lifestyle intervention studies (such as the definitely obese) could be relatively small. Therefore, results specific to minority groups may be diluted. Nonetheless, the many rigorously collected data will make it possible to study, for example, the general effect that different levels of physical activity may have on various health conditions and on proxy measures of life-style conditions. Specifically, it will help answer the question on whether increased physical activity in school has a positive effect on health in children.

Mechanical and free living comparisons of four generations of the Actigraph activity monitor

BackgroundMore studies include multiple generations of the Actigraph activity monitor. So far no studies have compared the output including the newest generation and investigated the impact on the output of the activity monitor when enabling the low frequency extension (LFE) option. The aims were to study the responses of four generations (AM7164, GT1M, GT3X and GT3X+) of the Actigraph activity monitor in a mechanical setup and a free living environment with and without enabling the LFE option.MethodsThe monitors were oscillated in a mechanical setup using two radii in the frequency range 0.25-3.0 Hz. Following the mechanical study a convenience sample (N = 20) wore three monitors (one AM7164 and two GT3X) for 24 hours.ResultsThe AM7164 differed from the newer generations across frequencies (p < 0.05) in the mechanical setup. The AM7164 produced a higher output at the lower and at the highest intensities, whereas the output was lower at the middle intensities in the mid-range compared to the newer generations. The LFE option decreased the differences at the lower frequencies, but increased differences at the higher. In free living, the mean physical activity level (PA) of the GT3X was 18 counts per minute (CPM) (8%) lower compared to the AM7164 (p < 0.001). Time spent in sedentary intensity was 26.6 minutes (95% CI 15.6 to 35.3) higher when assessed by the GT3X compared to the AM7164 (p < 0.001). Time spend in light and vigorous PA were 23.3 minutes (95% CI 31.8 to 14.8) and 11.7 minutes (95% CI 2.8 to 0.7) lower when assessed by the GT3X compared to the AM7164 (p < 0.05). When enabling the LFE the differences in the sedentary and light PA intensity (<333 counts*10 sec-1) were attenuated (p > 0.05 for differences between generations) thus attenuated the difference in mean PA (p > 0.05) when the LFE option was enabled. However, it did not attenuate the difference in time spend in vigorous PA and it introduced a difference in time spend in moderate PA (+ 3.0 min (95% CI 0.4 to 5.6)) between the generations.ConclusionWe observed significant differences between the AM7164 and the newer Actigraph GT-generations (GT1M, GT3X and GT3X+) in a mechanical setup and in free-living. Enabling the LFE option attenuated the differences in mean PA completely, but induced a bias in the moderate PA intensities.

Youth screen-time behaviour is associated with cardiovascular risk in young adulthood: the European Youth Heart Study

Aims: We prospectively examined the association of TV viewing, computer use, and total screen time in adolescence, and change in these behaviours, with cardiovascular disease (CVD) risk factors in young adulthood. Methods and results: This was a prospective cohort study among Danish men and women (n = 435) followed for up to 12 years. Adiposity, blood pressure (BP), triglycerides, high-density lipoprotein (HDL), glucose, insulin, and self-reported TV viewing and computer use were obtained in adolescence and in young adulthood. A continuous metabolic syndrome z-score was calculated as the sum of standardized values of each risk factor (inverse of HDL). In multivariable-adjusted analyses, TV viewing and total screen time in adolescence were positively associated with adiposity, triglycerides, and metabolic syndrome z-score in young adulthood (p < 0.05). Individuals who increased their TV viewing, computer use, or total screen time with more than 2 hours/day from adolescence to young adulthood had 0.90 (95% CI 0.12 to 1.69), 0.95 (95% CI 0.01 to 1.88), and 1.40 (95% CI 0.28 to 2.51) kg/m2 higher body mass index, respectively, in young adulthood compared with individuals who remained stable or decreased their viewing time. Insulin and metabolic syndrome z-scores were also higher among individuals who increased their TV viewing, computer use, or total screen time more than 2 hours/day compared with individuals who remained stable or decreased their viewing time (p < 0.05). Conclusions: Prolonged TV viewing and total screen time during leisure time in adolescence, and increases in these behaviours, are associated with unfavourable levels of several cardiovascular risk factors in young adulthood.

Television viewing, food preferences, and food habits among children: a prospective epidemiological study.

BackgroundObesity has increased since the early 1980s, and despite numerous attempts, effective strategies to counter this worldwide epidemic are lacking. Food preferences are established early in life and are difficult to change later. There is therefore a need to identify factors that influence the development of food preferences. Our aim was therefore, to investigate cross-sectional and prospective associations between TV viewing habits and food preferences and habits, respectively. We hypothesized that more TV viewing was associated with less healthy concomitant and future food preferences and food habits.MethodsData are from the Danish part of European Youth Heart Study (EYHS) I and II, a prospective cohort study conducted among 8-10-year-old and 14-16-year-old Danes in 1997-98. Six years later 2003-04 the 8-10-year-olds were followed up at age 14-16 years, and a new group of 8-10-year olds were included. Data were analysed using mixed linear regression analysis. Cross-sectional analyses included 697 8-10-year-olds and 495 14-16-year-olds. Prospective analyses included 232 pupils with complete data at baseline and follow-up. Associations between TV viewing habits and the sum of healthy food preferences (ΣHFP), and the sum of healthy food habits (ΣHFH), respectively, were examined.ResultsInverse cross-sectional associations between TV viewing (h/day) and both ΣHFP and ΣHFH were present for both the 8-10-year-old and the 14-16-year-old boys and girls. The frequency of meals in front of the TV (times/week) was also inversely associated with ΣHFP among 8-10-year-old boys, and with ΣHFH in all sex- and age groups. Among girls, baseline TV viewing (h/day) was directly associated with adverse development in the ΣHFP during follow-up. The concomitant 6-year changes in ΣHFH and TV viewing (h/day) were inversely associated in boys.ConclusionsLong time spent on TV viewing, and possibly to a lesser degree, frequent consumption of meals during TV viewing, seem to be associated with generally having unhealthy food preferences and food habits among school-aged children. These associations, however, were not generally persistent after 6 years of follow-up.