Exploring causality between TV viewing and weight change in young and middle-aged adults. The Cardiovascular Risk in Young Finns study

Physical Activity, Sedentary Behavior, and Pancreatic Cancer Risk: A Mendelian Randomization Study

Pancreatic cancer is currently the seventh leading cause of cancer death worldwide. Understanding whether modifiable factors increase or decrease the risk of this disease is central to facilitating primary prevention. Several epidemiological studies have described the benefits of physical activity, and the risks associated with sedentary behavior, in relation to cancer. This study aimed to assess evidence of causal effects of physical activity and sedentary behavior on pancreatic cancer risk. We conducted a two-sample Mendelian randomization study using publicly available data for genetic variants associated with physical activity and sedentary behavior traits and genetic data from the Pancreatic Cancer Cohort Consortium (PanScan), the Pancreatic Cancer Case-Control Consortium (PanC4), and the FinnGen study for a total of 10 018 pancreatic cancer cases and 266 638 controls. We also investigated the role of body mass index (BMI) as a possible mediator between physical activity and sedentary traits and risk of developing pancreatic cancer. We found evidence of a causal association between genetically determined hours spent watching television (hours per day) and increased risk of pancreatic cancer for each hour increment (PanScan-PanC4 odds ratio = 1.52, 95% confidence interval 1.17-1.98, P = .002). Additionally, mediation analysis showed that genetically determined television-watching time was strongly associated with BMI, and the estimated proportion of the effect of television-watching time on pancreatic cancer risk mediated by BMI was 54%. This study reports the first Mendelian randomization-based evidence of a causal association between a measure of sedentary behavior (television-watching time) and risk of pancreatic cancer and that this is strongly mediated by BMI. Summary: Pancreatic cancer is a deadly disease that is predicted to become the second leading cause of cancer-related deaths by 2030. Physical activity and sedentary behaviors have been linked to cancer risk and survival. However, there is limited research on their correlation with pancreatic cancer. To investigate this, we used a Mendelian randomization approach to examine the genetic predisposition to physical activity and sedentariness and their relation to pancreatic cancer risk, while excluding external confounders. Our findings revealed a causal link between the time spent watching television and an increased risk of pancreatic cancer. Additionally, we determined that over half of the effect of watching television on pancreatic risk is mediated by the individual's BMI.

Physical Activity, Sedentary Behavior, and Osteoarthritis: A Two-Sample Mendelian Randomization Analysis

Background

Sedentary behavior and physical activity are still ambiguous in their effects on osteoarthritis. We aimed to evaluate the effects of physical activity and sedentary behavior on osteoarthritis to provide a reference for the prevention of osteoarthritis.

Methods

This study was conducted in Changchun, China in 2022. We used two-sample Mendelian randomization with the SNP as an instrumental variable to investigate the effect of physical activity and sedentary behavior on osteoarthritis. In addition, a two-step Mendelian randomization method was used to test whether mediating factors (BMI, smoking, Apolipoprotein B) were involved in mediating the effects of exposure factors on osteoarthritis.

Results

TV watching was causally related to knee osteoarthritis and spine osteoarthritis, and they were positively correlated (knee osteoarthritis: OR=1.162,95 %CI: 1.027-1.315, P=0.017; spine osteoarthritis: OR=1.208,95 %CI: 1.033-1.413, P=0.018). BMI played a mediating role in the process of TV watching with knee osteoarthritis and spine osteoarthritis. ((The proportion of BMI mediating effect: knee osteoarthritis: 47.1% (95% CI: 36.7%~63.2%); spine osteoarthritis: 29.5% (95% CI: 19.3%~40.8%)). The proportion of Smoking mediating effect in the process of TV watching with spine osteoarthritis was 16.1% (95% CI: 3.7% ~ 31.6%).

Conclusion

TV watching is a potential risk factor for osteoarthritis and plays a role through modifiable factors such as BMI and smoking, therefore, interventions on these factors have the potential to reduce the burden of osteoarthritis caused by longer TV watching times.

Agroecosystem engineering extended from plant-microbe interactions revealed by multi-omics data

In an agroecosystem, plants and microbes coexist and interact with environmental factors such as climate, soil, and pests. However, agricultural practices that depend on chemical fertilizers, pesticides, and frequent tillage often disrupt the beneficial interactions in the agroecosystem. To reconcile the improvement of crop performance and reduction in environmental impacts in agriculture, we need to understand the functions of the complex interactions and develop an agricultural system that can maximize the potential benefits of the agroecosystem. Therefore, we are developing a system called the agroecosystem engineering system, which aims to optimize the interactions between crops, microbes, and environmental factors, using multi-omics analysis. This review first summarizes the progress and examples of omics approaches, including multi-omics analysis, to reveal complex interactions in the agroecosystem. The latter half of this review discusses the prospects of data analysis approaches in the agroecosystem engineering system, including causal network analysis and predictive modeling.

Multiple trajectories of any intensities of physical activity are better than sustained sedentary time on improving waist circumference and body mass index among Chinese adults: China Health and Nutrition Survey, 2004-2018

Higher levels of physical activity (PA) may be associated with more favorable measures of adiposity, and sedentary time (ST) is associated with adverse health outcomes independent of PA. We hypothesized that multiple routes of different PA intensities PA combined with ST would be associated with coexisting latent waist circumference (WC) and body mass index (BMI) trajectories among Chinese adults. Thus, we aimed to determine multiple routes of PA and ST and their associations with trajectories of WC and BMI. We used data from 13 137 adults in the China Health and Nutrition Survey between 2004 and 2018. Using group-based multitrajectory modeling, we determined multiple trajectories of light-, moderate-, and vigorous-intensity PA (LPA, MPA) and ST (PA trajectories) and concurrent WC and BMI trajectories. Then, we explored logit regressions between them. We identified 4 PA trajectories. The majority (high LPA, 43.5%) exhibited decreasing high LPA levels. The rest were high ST (9.0%), decreased MPA (15.8%), and high vigorous-intensity PA (31.7%). People with high ST showed higher odds of having abdominal obesity (odds ratio [OR] = 2.23) or severe abdominal obesity (OR = 1.73) than those with decreased MPA (OR = 1.85 and 1.71) and high LPA (OR = 1.43 for abdominal obesity). They also showed higher odds of being overweight (OR = 1.73) than those with decreased MPA (OR = 1.58) and high LPA (OR = 1.39). Any level of PA is better than sustained ST for improving adiposity indicators among Chinese adults.

Consuming media, consuming food: investigating concurrent TV viewing and eating using a 7-d time use diary survey

OBJECTIVE

One explanation for the relationship between TV viewing and obesity is that people may (over)eat while watching TV. The current study investigated associations between TV viewing and the time spent on (concurrent) eating in a naturalistic setting among a general population sample.

DESIGN

Preregistered secondary data analyses were performed of a diary survey in which respondents reported their time use in 10-min blocks for 7 d.

SETTING

Concurrent TV viewing and eating was operationalised as all blocks in which TV viewing and eating occurred simultaneously. Furthermore, the TV content respondents watched was coded as food-related (i.e. culinary content) or non-food related.

PARTICIPANTS

The sample composed of 2292 adults (58·9 % female) in the Netherlands, aged ≥ 20 years, from all educational levels (18·1 % low, 29·8 % middle and 51·4 % high).

RESULTS

More than half of the respondents (51·3 %) reported concurrent TV viewing and eating at least once during the 7-d diary period. The average eating occasion was longer in duration while watching TV (v. without media use), and the total time spent on eating was longer on days of concurrent TV viewing and eating (v. days of eating without media use). The percentage of TV viewing time spent on concurrent eating did not differ between food-related and non-food-related TV content.

CONCLUSIONS

Eating while watching TV was related to an increased time spent on eating. Even though energy intake was not assessed, these findings from a naturalistic setting provide further evidence that concurrent TV viewing and eating may contribute to overeating.

Electronic Media Device Usage and Its Associations With BMI and Obesity in a Rapidly Developing City in South China

Objective: This study aimed to evaluate the television (TV) viewing and computer and mobile phone usage duration in a community sample of Chinese adults and examine their associations with BMI and obesity. Methods: We conducted a community-based health needs assessment study from February to December 2018 among 2,873 Chinese adults in Nanshan District of Shenzhen, China. We used self-administered questionnaires to collect the data from 24 community health service centers in Nanshan District. The participants individually recorded the time they spent watching TV and using computers and mobile phones. They also answered questions about their sociodemographic and lifestyle factors. We measured their height and weight by using ultrasonic height and weight scales. Then, we calculated and categorized their BMI in accordance with the standards prescribed by the World Health Organization for Asians. Results: Most of the participants were young adults (aged 18-44 years, 74.2%). The overall prevalence of obesity was 15.30%. The prevalence of TV, computer, and mobile phone usage was 75.5, 71.2, and 93.8% in females and 71.1, 75.7, and 94.2% in males, respectively. The youth (18-24 years) and the elderly (65 years or older) had the longest time using mobile phones (3.78 ± 2.51 h) and watching TV programs (2.12 ± 1.38 h), respectively. Longer usage of computers and mobile phones was evident in males (p < 0.05) and participants with a high education level (p < 0.01). The univariate analysis results showed an association between high BMI and obesity and short duration of using computers and mobile phones (all p < 0.05). By contrast, no significant associations were found between the length of TV program viewing and mobile phone usage and BMI (p > 0.05). After we adjusted for potential confounders, we found that computer usage time and the overall usage time of the three electronic devices had an inverse association with BMI (p < 0.05). Conclusions: Mobile phones were the most popular electronic device in Nanshan residents of Shenzhen. Unlike most previous studies, we found an inverse association between screen time and BMI. Nevertheless, scholars should conduct further studies to explore this association. Overall, we strongly encourage the appropriate use of electronic devices.

Physical inactivity, television time and chronic diseases in Brazilian adults and older adults

This study aimed to investigate the association between simultaneity of leisure-time physical inactivity and high television time with the presence of chronic diseases in adults and older adults in Brazil. We analyzed secondary data from Vigitel 2013 database, a cross-sectional national survey. It was included 37 947 adults (18-59 years) and 14 982 older adults (≥60 years) living in Brazilian state capitals. The association was between simultaneity of risk behaviors considering leisure-time physical inactivity (<10 min/day) and high television time (≥2 h/day), with the presence of chronic diseases (diabetes, dyslipidemia, hypertension and obesity), measured according to the age group. We performed a binary logistic regression, crude and adjusted analysis, using weighted to reflect population estimates. In adults, there was an association between leisure-time physical inactivity and television time with the presence of diseases. In practice, the simultaneity of risk behaviors when compared with those without risk behavior had higher odds for diabetes (OR = 1.83), dyslipidemia (OR = 1.17), hypertension (OR = 1.54) and obesity (OR = 1.60). In older adults, the simultaneity was associated with diabetes (OR = 1.61), hypertension (OR = 1.33) and obesity (OR = 1.81). We concluded that for adults and older adults the simultaneity of leisure-time physical inactivity and high television time increased the odds for the presence of chronic disease, especially for diabetes and obesity.

Does prolonged television viewing affect Body Mass Index? A case of the Kingdom of Saudi Arabia

BACKGROUND

The rising prevalence of overweight and obesity and their health implications is a major public health concern worldwide. This study set out to understand the relationship between the number of hours spent watching television and Body Mass Index (BMI) in the Kingdom of Saudi Arabia using data from the Saudi Health Interview Survey.

METHODS

The study employed both ordinary least squares and quantile regressions to estimate the mean and distributional association of prolonged television watching and BMI.

RESULTS

The findings showed that prolonged television viewing is associated with larger BMI values. Additionally, the relationship was found to be greater towards the lower and upper tails of the BMI range and insignificant in the middle of the BMI distribution. Furthermore, the findings also showed that there is a gender gap in BMI levels, where females are likely to have higher BMI values than males.

CONCLUSIONS

The creation of more proactive recreational programs that can act as substitutes to television watching is recommended in order to reduce the amount of time that individuals spend watching television. It is also recommended that such interventions are tailored towards improving females' levels of physical activity. The inclusion of television programs aimed at encouraging physical exercise and healthy diets is also imperative.

What is Machine Learning? A Primer for the Epidemiologist

Machine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problems for which classical methods are not well-suited. In order to critically evaluate the value of integrating machine learning algorithms and existing methods, however, it is essential to address language and technical barriers between the two fields that can make it difficult for epidemiologists to read and assess machine learning studies. Here, we provide an overview of the concepts and terminology used in machine learning literature, which encompasses a diverse set of tools with goals ranging from prediction to classification to clustering. We provide a brief introduction to 5 common machine learning algorithms and 4 ensemble-based approaches. We then summarize epidemiologic applications of machine learning techniques in the published literature. We recommend approaches to incorporate machine learning in epidemiologic research and discuss opportunities and challenges for integrating machine learning and existing epidemiologic research methods.

Associations Between Trajectories of Leisure-Time Physical Activity and Television Viewing Time Across Adulthood: The Cardiovascular Risk in Young Finns Study

BACKGROUND

The purpose of this study was to examine trajectories of leisure-time physical activity (LTPA) and television-viewing (TV) time and their associations in adults over 10 years.

METHODS

The sample comprised 2934 participants (men, 46.0%) aged 24-39 years in 2001 and they were followed up for 10 years. LTPA and TV time were assessed using self-report questionnaires in 2001, 2007, and 2011. Longitudinal LTPA and TV-time trajectories and their interactions were analyzed with mixture modeling.

RESULTS

Three LTPA (persistently highly active, 15.8%; persistently moderately active, 60.8%; and persistently low active, 23.5%) and 4 TV time (consistently low, 38.6%; consistently moderate, 48.2%; consistently high, 11.7%; and consistently very high, 1.5%) trajectory classes were identified. Persistently highly active women had a lower probability of consistently high TV time than persistently low-active women (P = .02), whereas men who were persistently highly active had a higher probability of consistently moderate TV time and a lower probability of consistently low TV time than their persistently low-active counterparts (P = .03 and P = .01, respectively).

CONCLUSIONS

Maintaining high LTPA levels were accompanied by less TV over time in women, but not in men. The associations were partially explained by education, body mass index, and smoking.

Associations of Sedentary Time with Energy Expenditure and Anthropometric Measures

PURPOSE

To investigate associations between accelerometer-determined sedentary time (ST) in prolonged (≥30 min) and nonprolonged (<30 min) bouts with physical activity energy expenditure (PAEE) from doubly labeled water. Additionally, associations between ST and body mass index (BMI) and waist circumference were examined.

METHODS

Data from 736 women and 655 men age 43 to 82 yr were analyzed. Participants wore the Actigraph GT3X for 7 d on two occasions approximately 6 months apart, and the average of the measurements was used. Physical activity energy expenditure was estimated by subtracting resting metabolic rate and the thermic effect of food from doubly labeled water estimates of total daily energy expenditure. Cross-sectional associations were analyzed using isotemporal substitution modeling.

RESULTS

Reallocation of prolonged ST to nonprolonged was not associated with increased PAEE and only significantly associated with lower BMI (β = -0.57 kg·m; 95% confidence interval, -0.94 to -0.20) and waist circumference (β = -1.61 cm; 95% confidence interval, -2.61 to -0.60) in men. Replacing either type of ST with light or moderate-to-vigorous physical activity was significantly associated with higher PAEE, and lower BMI and waist circumference in both women and men.

CONCLUSIONS

Limiting time spent sedentary as well as decreasing ST accumulated in prolonged bouts may have beneficial effects on BMI and waist circumference. Replacing any type of ST with activities of light or higher intensity may also have a substantial impact on PAEE.

Long-term determinants of changes in television viewing time in adults: Prospective analyses from the Young Finns Study

PURPOSE

The long-term effects of sociodemographic and health characteristics on television viewing (TV) time changes have not been identified in adulthood. We aimed to examine the modifiable and non-modifiable determinants of changes in TV-time in young adults over 10 years.

METHODS

Participants (N = 2929) aged 24-39 years were recruited between 2001 and 2011 from the Cardiovascular Risk in Young Finns Study. Data were collected using questionnaires and a medical examination. The determinants of changes in TV-time were estimated using latent growth modeling for men and women separately.

RESULTS

For men, inverse associations with initial levels of TV-time were observed for students becoming employed and already has children, and direct associations were observed for both those who stayed a smoker and those who stayed overweight/obese. Increasing attention to health habits was inversely associated with a slope of TV-time, whereas age and becoming unemployed were positively associated with the slope of TV-time. For women, inverse associations with the levels of TV-time were found for age, staying in non-manual work, and paying consistently high and increasing attention to health habits, and direct associations were found for staying unemployed, smoking and overweight/obese, and becoming employed, single and non-smoking. Increasing physical activity, becoming employed, motherhood, and normal weight were inversely associated with the slope of TV-time, whereas age and staying in non-manual work were positively associated with the slope of TV-time.

CONCLUSIONS

This suggests several gender-specific determinants of changes in TV-time that can help identify potential targets for interventions to prevent excessive TV-time in adulthood.

Longitudinal associations between TV viewing and BMI not explained by the 'mindless eating' or 'physical activity displacement' hypotheses among adults

BACKGROUND

The mechanisms explaining the positive relationship between television (TV) viewing and body mass index (BMI) are unclear. 'Mindless eating' and 'physical activity displacement' theories have been suggested, but have not been tested longitudinally among young adults. This study aimed to determine whether longitudinal associations between young adults' TV viewing and BMI are explained by changes in TV-related food and beverage consumption (FBC) and/or leisure-time physical activity (LTPA) over 5 years among young adults.

METHODS

A cohort of young Australian adults (n = 1068) was assessed in 2004-6 (T1) and 2009-2011 (T2), height and weight were measured (T1) or self-reported (T2), and participants self-reported TV viewing time (hours/day), weekly TV-related FBC and LTPA (mins/week). Linear regression was used to examine direct pathways between TV viewing and BMI, adjusting for TV-related FBC and LTPA to examine indirect pathways.

RESULTS

The association between TV viewing time and BMI (β: 0.41, 95% CI 0.03, 0.78 for > 1-h increase in TV viewing/day) was not explained by TV-related FBC (β: 0.37, 95% CI -0.18, 0.91) or LTPA (β: 0.38, 95% CI -0.17, 0.93) hypotheses. Increased TV-related FBC was associated with increased TV viewing (0.39 ± 1.54 h/day) and greater increases in BMI (0.92 ± 2.28 kg/m², p = 0.16). LTPA increases were not associated with changes in TV viewing (- 0.07 ± 1.42 h/day), and increases in BMI were smallest when LTPA increased (0.44 ± 2.25 kg/m²) and greatest when LTPA decreased (0.82 ± 2.30 kg/m²) (p = 0.13).

CONCLUSIONS

Factors other than changes in TV-related FBC or LTPA may explain the longitudinal relationship between TV viewing and increasing BMI among young adults. Findings confirm that TV viewing is a risk factor for weight gain in young adults but the underlying causal mechanisms remain unclear.

Does Childhood Temperamental Activity Predict Physical Activity and Sedentary Behavior over a 30-Year Period? Evidence from the Young Finns Study

PURPOSE

We examined associations between childhood temperamental activity, physical activity (PA), and television (TV) viewing over a 30-year period.

METHOD

The participants (1220 boys and 1237 girls) were aged 3, 6, 9, and 12 years in 1980 and were followed until 2011. Temperamental activity was evaluated by participants' mothers at baseline. The PA was assessed based on maternal ratings of the child from ages 3 to 6 and via self-report age from the age of 9 across all measurements. TV viewing was assessed using self-reports taken from 2001 to 2011. The associations between temperamental activity and the level and change of PA and TV viewing were determined using linear growth modeling stratified by gender and age group.

RESULTS

High temperamental activity assessed from ages 9 to 12 was associated with high levels of childhood PA in both genders, but with a steeper decline in PA levels during the first 9 years of follow-up in boys. High temperamental activity assessed from ages 3 to 6 was associated with the decline of PA from childhood to youth in girls. High childhood temperamental activity was associated with decreased levels of PA in adulthood in men, but not in women. The associations between childhood temperamental activity and TV viewing during adulthood seemed to be positive but not consistently significant in all age and gender groups.

CONCLUSION

High temperamental activity may contribute to the development of a physically inactive lifestyle. More evidence is needed with regard to gender differences among participants in similar study settings.

Lifestyle behaviours associated with 5-year weight gain in a prospective cohort of Australian adults aged 26-36 years at baseline

Background

Whether not meeting common guidelines for lifestyle behaviours is associated with weight gain is uncertain. This study examined whether 5-year weight gain was predicted by not meeting guidelines for: breakfast consumption (eating between 6 and 9 am), takeaway food consumption (<2 times/week), television viewing (<2 h/day) and daily steps (≥10,000 steps/day).

Methods

One thousand one hundred and fifty-five Australian participants (43% men, 26–36 years) completed questionnaires and wore a pedometer at baseline (2004-06) and follow-up (2009-11). Weight was measured or self-reported, with a correction factor applied. For each behaviour, participants were classified according to whether they met the guideline: consistently met at baseline and follow-up (reference group); not met at baseline but met at follow-up; met at baseline but not met at follow-up; consistently not met at baseline and follow-up. For each behaviour, weight gain was calculated using linear regression. Weight gain by number of guidelines met was also examined.

Results

Mean 5-year weight gain was 2.0 kg (SD:6.3). Compared to the reference group, additional weight (mean, 95% CI) was gained among those who did not meet the guideline at follow-up, or consistently did not meet the guideline, for breakfast (1.8 kg, 0.7–2.9; 1.5 kg, 0.1–2.8); takeaway food (2.2 kg, 0.7–3.6; 1.9 kg, 0.7–3.1); watching television (1.9 kg, 0.9–2.9; 1.4 kg, 0.4–2.3); and daily steps (2.6 kg, 1.1–4.04; 1.6 kg, 0.5–2.7). Those who met ≤1 guideline at follow-up gained 3.8 kg (95% CI 2.3–5.3) more than those meeting all guidelines.

Conclusion

Individuals who adopted healthier behaviours between baseline and follow-up had similar weight gain to those who met the guidelines at both time points. Encouraging young adults to meet these simple guidelines may reduce weight gain.

Electronic supplementary material

The online version of this article (doi:10.1186/s12889-016-3931-y) contains supplementary material, which is available to authorized users.

What is the metabolic and energy cost of sitting, standing and sit/stand transitions?

PURPOSE

Modern lifestyles require people to spend prolonged periods of sitting, and public health messages recommend replacing sitting with as much standing as is feasible. The metabolic/energy cost (MEC) of sitting and standing is poorly understood, and MEC associated with a transition from sitting to standing has not been reported. Thus, we carefully quantified the MEC for sitting, standing and sit/stand transitions, adjusting for age and fat-free mass (FFM) in a sample of adults with no known disease.

METHODS

Participants (N = 50; 25 women), 20–64 years, randomly performed three conditions for 10 min each (sitting, standing, 1 sit/stand transition min(−1) and then sitting back down). MEC was measured by indirect calorimetry and FFM by dual-energy X-ray absorptiometry.

RESULTS

V̇O2 (ml kg(−1) min(−1)) for sitting (2.93 ± 0.61; 2.87 ± 0.37 in men and women respectively), standing (3.16 ± 0.63; 3.03 ± 0.40), and steady-state cost of repeated sit/stand transitions (1 min(−1)) (3.86 ± 0.75; 3.79 ± 0.57) were significantly different regardless of sex and weight (p < 0.001). EE (kcal min(−1)) also differed from sitting (1.14 ± 0.18; 0.88 ± 0.11), to standing (1.23 ± 0.19; 0.92 ± 0.13), and sit/stand transitions (1 min(−1)) (1.49 ± 0.25; 1.16 ± 0.16). Heart-rate increased from sitting to standing (~13 bpm; p < 0.001). Neither sex nor FFM influenced the results (p ≥ 0.05).

CONCLUSIONS

This study found in a sample of adults with no known disease that continuous standing raised MEC 0.07 kcal min(−1) above normal sitting. The transition from sitting to standing (and return to sitting) had a metabolic cost of 0.32 kcal min(−1) above sitting. Therefore, public health messages recommending to interrupt sitting frequently should be informed of the modest energetic costs regardless of sex and body composition.

Tracking of Television Viewing Time during Adulthood: The Young Finns Study

PURPOSE

The aim of this study was to investigate the tracking of television viewing (TV) time as an indicator of sedentary behavior among adults for a period of 25 yr.

METHODS

A random sample of 1601 subjects (740 men) age 18, 21, and 24 yr participated in the Cardiovascular Risk in Young Finns Study in 1986. TV time during leisure time was measured with a single self-report question at baseline and in 2001, 2007, and 2011. Tracking of TV time was analyzed using Spearman rank correlations and simplex models. Level and change of TV time were examined using linear growth modeling.

RESULTS

The 4- and 6-yr integrated TV time stability coefficients, adjusted for measurement errors, were ≥0.60 in adulthood and quite similar for both men and women. The stability coefficients tended to decline as the time interval increased. The stability of the indirect estimation of TV time for a 25-yr period was moderately or highly significant for both genders in most age groups. Younger age, but not gender, was found to be associated with a higher initial level of TV time. Male gender and older age were found to be significantly associated with the slope of TV time.

CONCLUSION

The stability of TV time is predominantly moderate to high during adulthood and varies somewhat by age and gender.

The mysterious case of the public health guideline that is (almost) entirely ignored: call for a research agenda on the causes of the extreme avoidance of physical activity in obesity

Physical activity and exercise guidelines for weight management call for at least 60 min of daily activity. However, these documents fail to acknowledge that almost no obese adults meet this target and that non-adherence and dropout are even higher among obese individuals than the general population. The reasons for this level of activity avoidance among obese individuals remain poorly understood, and there are no evidence-based methods for addressing the problem. Opinions among exercise scientists are polarized. Some advocate moderate intensity and long duration, whereas others call for high intensity and shorter duration. The latter approach attributes the inactivity and high dropout to limited discretionary time and the slow accrual of visible benefits. However, higher intensity has been associated with non-adherence and dropout, whereas longer duration has not. A conceptual model is then proposed, according to which obesity interacts with intensity, causing physical activity and exercise to be associated with reduced pleasure among obese individuals. We theorize that, in turn, repeated experiences of reduced pleasure lead to avoidance. On this basis, we call for a research agenda aimed at identifying the causes of activity-associated and exercise-associated displeasure in obesity and, by extension, the causes of the extreme physical inactivity among obese individuals.

Television viewing and fatty liver in early midlife. The Cardiovascular Risk in Young Finns Study

INTRODUCTION

Both sedentary behaviour and fatty liver are associated with increased risk of obesity and non-communicable diseases, but their relationship remains unknown. We investigated the relationship of television (TV) viewing time with serum gamma-glutamyltransferase (GGT) and Fatty Liver Index (FLI), and ultrasonographically assessed liver fat.

METHODS

A total of 1,367 adults of the population-based Cardiovascular Risk in Young Finns study (748 women, 619 men, aged 34-49 years) had fasting serum GGT, triglycerides, weight, height, and waist circumference, and self-reported TV time data from 2001, 2007, and 2011. Changes in GGT and FLI, and liver ultrasound images in 2011 were studied in groups with constantly low (≤ 1 h/d), moderate (1-3 h/d), or high (≥ 3 h/d) daily TV time, and in groups with ≥ 1 hour increase/decrease in daily TV time between 2001 and 2011.

RESULTS

Constantly high TV time was associated with higher GGT and FLI (P < 0.02 in both), and 2.3-fold (95% CI 1.2-4.5) increased risk of fatty liver regardless of age, sex, leisure-time and occupational physical activity, energy intake, diet composition, alcohol use, sleep duration, socioeconomic status, and smoking. Adjustment for BMI partly attenuated the associations.

CONCLUSIONS

High TV viewing increases fatty liver risk. It may be one mechanism linking sedentary behaviour with increased cardiometabolic disease risks.