Physical activity, sedentary behaviors, and Epstein-Barr virus antibodies in young adults

Screen Time from Adolescence to Adulthood and Cardiometabolic Disease: a Prospective Cohort Study

BACKGROUND

Previous studies have analyzed the relationship between screen time and cardiometabolic disease risk factors among adolescents, but few have examined the longitudinal effects of screen time on cardiometabolic health into adulthood using nationally representative data.

OBJECTIVE

To determine prospective associations between screen time and later cardiometabolic disease over a 24-year period using a nationally representative adolescent cohort.

DESIGN

Longitudinal prospective cohort data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) collected from 1994 to 2018.

PARTICIPANTS

Adolescents aged 11-18 years old at baseline (1994-1995) followed for 24 years.

MAIN MEASURES

Predictors: screen time (five repeated measures of self-reported television and video watching from adolescence to adulthood).

OUTCOMES

Five repeated measures of body mass index (BMI); two repeated measures of waist circumference, hypertension, hyperlipidemia, and diabetes collected at 15- and 24-year follow-up exams.

KEY RESULTS

For the 7105 adolescents in the sample (49.7% female, 35.0% non-white), the baseline adolescent average screen time per day was 2.86 ± 0.08 hours per day, which generally declined through 24-year follow-up. Average BMI at baseline was 22.57 ± 0.13 kg/m2, which increased to 30.27 ± 0.18 kg/m2 through follow-up. By 24-year follow-up, 43.4% of participants had obesity, 8.4% had diabetes, 31.8% had hypertension, and 14.9% had hyperlipidemia. In mixed-effects generalized linear models, each additional hour of screen time per day was associated with 0.06 (95% CI 0.04-0.09) within-person increase in BMI. Each additional hour of screen time per day was associated with higher within-person odds of high waist circumference (AOR 1.17, 95% CI 1.09-1.26), obesity (AOR 1.09, 95% CI 1.03-1.15), and diabetes (AOR 1.17, 95% CI 1.07-1.28). Screen time was not significantly associated with hypertension or hyperlipidemia.

CONCLUSIONS

In this prospective cohort study, higher screen time in adolescence was associated with higher odds of select indicators of cardiometabolic disease in adulthood.

Independence and Sex Differences in Physical Activity and Sedentary Behavior Trends from Middle Adolescence to Emerging Adulthood: A Latent Class Growth Curve Analysis

The purpose of this study was to examine the relationship and sex differences in the growth patterns of moderate-to-vigorous physical activity (MVPA) and sedentary behavior (SB) from middle adolescence (around age 15) to emerging adulthood (18–29 years old). We used the secondary data from the National Longitudinal Study of Adolescent Health’s (Add Health) publicly accessible database. MVPA and SB were assessed four times (1995, 1996, 2000–2001, and 2008–2009) for a total of 681 individuals from middle adolescence to emerging adulthood. Latent class growth modeling was utilized to identify heterogeneous growth patterns in MVPA and SB. Chi-square tests were used to assess group dependence and sex differences in MVPA and SB growth patterns. Seven quadratic growth patterns for MVPA and two linear growth patterns for SB were found. Both MVPA and SB growth patterns exhibited slow or rapid rate of change at different periods of adolescence and emerging adulthood. MVPA growth patterns included: decline (slow)-and-rise (rapid), rise-and-decline (both rapid), decline-and-rise (both rapid), consistently low, consistently high, decline (rapid)-and-decline (slow), and decline (rapid)-and-rise (slow). SB growth patterns included: consistently low (slow decline) and consistently high (rapid decline). While women were more likely to be involved in consistently low group for MVPA and consistently low (slow decline) group for SB, men were more likely to be involved in rise-and-decline (both rapid) group, consistently high group, and decline (rapid)-and-rise (slow) group for MVPA and consistently high (rapid decline) group for SB. SB growth patterns were independent of MVPA growth patterns. SB should not be assumed to decrease as a result of MVPA intervention. Treatment of MVPA should prioritize adolescence over emerging adulthood, with an emphasis on preventing men’s MVPA levels from decreasing in emerging adulthood and increasing women’s overall MVPA levels.

Disentangling individual, school, and neighborhood effects on screen time among adolescents and young adults in the United States

OBJECTIVES

To examine the association between individual, neighborhood, and school-level influences on individual screen time among adolescents and young adults (AYAs) in the National Longitudinal Study of Adolescent to Adult Health.

METHODS

We classified screen time continuously as self-reported total hours per week of television, videos, and video/computer games at baseline and categorical as extended screen time (≥14 h per week). We fit cross-classified multilevel models (CCMM) to examine to examine the individual-, school- and neighborhood-level demographic and socioeconomic factors associated with screen time. Models were fit using MLwiN with Bayesian estimation procedures.

RESULTS

AYAs reported an average of 22.8 (SD = 19.4) and 21.9 (SD = 20.3) hours of screen time, respectively. At the individual level, younger age, male sex, Black/multiracial race, receipt of public assistance, and lower parental education were associated with higher screen time. At the school level, being out of session (i.e., school and national holidays including summer), having a higher proportion of non-White students, and having a lower proportion of parents with a college education were associated with higher individual screen time.

CONCLUSIONS

We found that individual-level factors most influence youth screen time, with smaller contributions from school factors.

The impact of social distancing and self-isolation in the last corona COVID-19 outbreak on the body weight in Sulaimani governorate- Kurdistan/Iraq, a prospective case series study

BACKGROUND

Our area, corona (COVID-19) quarantine was applied from March 14 to April 23, 2020. It was in all forms, including curfew, social distancing, self-quarantine, area quarantine, self-monitoring, and isolation. Due to their concerns about their safety and families, friends, colleagues, and society, everybody was feeling upset, fearful, and anxious. Several studies have reported an association between prolonged sitting time and weight gain. As a way to relieve the tension during that period, people started stocking up on unhealthy foods like over-salted snacks and over-sweetened sugars. People stayed at home, feeling bored, anxious, and stressed and sought relief by eating. Also, there was a rise in emotional eating when the stress of isolation increased by the closure of gyms, casinos, and movie theaters. Moreover, restaurants were allowed to serve the only takeout. Besides, unemployment was skyrocketing, hospitals were overflowing (or were preparing for the possibility), many people were struggling to meet their basic needs, and no one knows when or how it would end.

OBJECTIVE

The study aimed to figure out whether social isolation during the COVID-19 quarantine is consistent and associated with emotional eating and gaining weight or not.

METHODS

A prospective cross-sectional case series study was conducted on 765 patients who have visited the bariatric clinic in Sulaimani city, Kurdistan-Iraq, from April 23 to June 23, 2020. An individual face-to-face interview was conducted with each participant to obtain signed informed consent, provide them with information about the type and the subject of the work, and ask them the study's questions. Each interview lasted between 30 and 45 min and was conducted in a closed session by two Kurdistan Board trainees.

RESULTS

No patient who was quarantined for the COVID-19 was included in the work, but all other patients were included. The selected patients were those who had undergone social distancing (n = 568, 82.48%) by the local law and did self-isolation (n = 134, 17.51%) at home for reasons like having comorbidity, being prone to contamination due to their jobs (health, police, and media workers), having some family members at home with comorbidity (n = 23, 03.00%), and having comorbidity and having undergone social distancing because of their other family members' need to do so for their physical disability (n = 25, 03.27%). Almost all patients (n = 741, 96.86%), even, those with comorbidity (n = 136, 17.78%), were emotionally stable before the outbreak. Seventy-three female patients (09.54%) and138 males (20.65%) sustain their weight during and two months after the outbreak, while the rest (n = 554, 72.41%) gained different amounts of weight.

CONCLUSION

Social distancing and self-isolation in the last COVID-19 outbreak influenced weight gain, but weight gain of less than 2 kg was observed among almost all patients who gained weight (98.05%). The patients who were gain more than 3 kg were mostly females or/and from the center of large cities.

Training Load, Immune Status, and Clinical Outcomes in Young Athletes: A Controlled, Prospective, Longitudinal Study

Introduction: Beside positive effects on athlete's health, competitive sport can be linked with an increased risk of illness and injury. Because of high relative increases in training, additional physical and psychological strains, and an earlier specialization and professionalization, adolescent athletes needs an increased attention. Training can alter the immune system by inducing a temporary immunosuppression, finally developing infection symptoms. Previous studies identified Epstein Barr Virus (EBV) as potential indicator for the immune status. In addition to the identification of triggering risk factors for recurrent infections, the aim was to determine the interaction between training load, stress sense, immunological parameters, and clinical symptoms.

Methods: A controlled, prospective, longitudinal study on young athletes (n = 274, mean age: 13.8 ± 1.5 yrs) was conducted between 2010 and 2014. Also 285 controls (students, who did not perform competitive sports, mean age: 14.5 ± 1.9 yrs) were recruited. Athletes were examined 3 times each year to determine the effects of stress factors (training load: training hours per week [Th/w]) on selected outcome parameters (clinical [susceptibility to infection, WURSS-21: 21-item Wisconsin Upper Respiratory Symptom Survey], immunological, psychological end points). As part of each visit, EBV serostatus and EBV-specific IgG tiers were studied longitudinally as potential immune markers.

Results: Athletes (A) trained 14.9 ± 5.6 h weekly. Controls (C) showed no lower stress levels compared to athletes (p = 0.387). Twelve percent of athletes reported recurrent infections (C: 8.5%, p = 0.153), the presence of an upper respiratory tract infection (URTI) was achieved in 30.7%. EBV seroprevalence of athletes was 60.3% (C: 56.6%, p = 0.339). Mean EBV-specific IgG titer of athletes was 166 ± 115 U/ml (C: 137 ± 112 U/ml, p = 0.030). With increasing Th/w, higher stress levels were observed (p < 0.001). Analyzes of WURSS-21 data revealed no relationship to training load (p = 0.323). Also, training load had no relation to EBV serostatus (p = 0.057) or the level of EBV-specific IgG titers (p = 0.364).

Discussion: Young elite athletes showed no increased sense of stress, no higher prevalence of recurrent infections, and no different EBV-specific serological parameters compared to controls. Also, no direct relationship between training loads, clinical complaints, and EBV-specific immune responses was found. With increasing training loads athletes felt more stressed, but significant associations to EBV-specific serological parameters were absent. In summary, EBV serostatus and EBV-specific IgG titers do not allow risk stratification for impaired health. Further investigations are needed to identify additional risk factors and immune markers, with the aim to avoid inappropriate strains by early detection and following intervention.