scholarly journals Telomere Shortening Unrelated to Smoking, Body Weight, Physical Activity, and Alcohol Intake: 4,576 General Population Individuals with Repeat Measurements 10 Years Apart

PLoS Genetics ◽  
2014 ◽  
Vol 10 (3) ◽  
pp. e1004191 ◽  
Author(s):  
Maren Weischer ◽  
Stig E. Bojesen ◽  
Børge G. Nordestgaard
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
General Population ◽  
Alcohol Intake ◽  
Telomere Shortening

scholarly journals Alcohol energy intake and habitual physical activity in older adults

2004 ◽  
Vol 91 (1) ◽  
pp. 149-152 ◽  
Author(s):  
Klaas R. Westerterp ◽  
Erwin P. Meijer ◽  
Annelies H. C. Goris ◽  
Arnold D. M. Kester
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Alcohol Consumption ◽  
Energy Intake ◽  
Alcohol Intake ◽  
Activity Level ◽  
Habitual Physical Activity ◽  
Additional Energy ◽  
Higher Alcohol ◽  
Dietary Record

Alcohol forms a significant component of many diets and it supplements rather than displaces daily energy intake. Surprisingly, alcohol intake does not systematically increase body weight. The present study assessed whether a higher level of habitual physical activity in the daily environment is associated with a higher alcohol intake. Alcohol intake as part of total food intake was measured with a 7 d dietary record while at the same time physical activity was monitored with a tri-axial accelerometer for movement registration. Subjects were twenty women and twenty-four men, aged 61±5 years, of BMI 27·1±4·6 kg/m2. Between subjects, there was a positive association between the level of habitual physical activity and alcohol intake (r 0·41; P<0·01). The subjects with higher alcohol intake had a higher activity level. On days with and days without alcohol consumption there was no difference in physical activity within subjects. In conclusion, it was shown that subjects with higher alcohol consumption are habitually more active. This may explain the lack of increasing body weight through additional energy intake from alcohol.

scholarly journals Characteristics of Victims of Fall-Related Accidents during Mountain Hiking

2020 ◽  
Vol 17 (3) ◽  
pp. 1115
Author(s):  
Martin Faulhaber ◽  
Gerhard Ruedl ◽  
Friedemann Schneider ◽  
Dagmar Walter ◽  
Regina Sterr ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
General Population ◽  
Alcohol Intake ◽  
Muscle Soreness ◽  
Fluid Intake ◽  
Demographic Data ◽  
Average Weight ◽  
Subjective Level ◽  
Defective Vision

The study evaluated characteristics of non-fatal mountain hiking accidents caused by falls. Questionnaires were sent to mountain hikers who suffered a fall-related accident in Tyrol (Austria) during a 3-year period. The questionnaire included details of socio-demographic data, physical activity, medication intake, defective vision, breaks, fluid intake, level of fatigue, muscle soreness, use of backpacks, use of hiking sticks, and type of shoes. Data of 405 individuals (57% females and 43% males) were included in the analyses. Victims were 56 ± 15 years of age, had a body mass index of 24.8 ± 3.5, and indicated 4.2 ± 3.9 h/week regular physical activity. A defective vision was reported by 70% of the victims, breaks were frequent (in 80%), and alcohol intake was rare (4%) among the interviewed hikers. Subjective level of fatigue was low and only 5% reported muscle soreness. A backpack was carried by 83% of the victims and the average weight was higher in males compared to females. The majority (61%) of the victims wore ankle-height hiking shoes with a profiled sole. Victims of non-fatal falls in mountain hiking are older than the general population of mountain hikers and are often afflicted with defective vision.

scholarly journals Resting Energy Expenditure of Master Athletes: Accuracy of Predictive Equations and Primary Determinants

2021 ◽  
Vol 12 ◽  
Author(s):  
Petra Frings-Meuthen ◽  
Sara Henkel ◽  
Michael Boschmann ◽  
Philip D. Chilibeck ◽  
José Ramón Alvero Cruz ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
General Population ◽  
Energy Expenditure ◽  
Ambient Temperature ◽  
Resting Energy Expenditure ◽  
Fat Free Mass ◽  
World Health ◽  
Master Athletes ◽  
Resting Energy

Resting energy expenditure (REE) is determined mainly by fat-free mass (FFM). FFM depends also on daily physical activity. REE normally decreases with increased age due to decreases in FFM and physical activity. Measuring REE is essential for estimating total energy expenditure. As such, there are a number of different equations in use to predict REE. In recent years, an increasing number of older adults continue to participate in competitive sports creating the surge of master athletes. It is currently unclear if these equations developed primarily for the general population are also valid for highly active, older master athletes. Therefore, we tested the validity of six commonly-used equations for predicting REE in master athletes. In conjunction with the World Masters Athletic Championship in Malaga, Spain, we measured REE in 113 master athletes by indirect calorimetry. The most commonly used equations to predict REE [Harris &amp; Benedict (H&amp;B), World Health Organization (WHO), Müller (MÜL), Müller-FFM (MÜL-FFM), Cunningham (CUN), and De Lorenzo (LOR)] were tested for their accuracies. The influences of age, sex, height, body weight, FFM, training hours per week, phase angle, ambient temperature, and athletic specialization on REE were determined. All estimated REEs for the general population differed significantly from the measured ones (H&amp;B, WHO, MÜL, MÜL-FFM, CUN, all p &lt; 0.005). The equation put forward by De Lorenzo provided the most accurate prediction of REE for master athletes, closely followed by FFM-based Cunningham’s equation. The accuracy of the remaining commonly-used prediction equations to estimate REE in master athletes are less accurate. Body weight (p &lt; 0.001), FFM (p &lt; 0.001), FM (p = 0.007), sex (p = 0.045) and interestingly temperature (p = 0.004) are the significant predictors of REE. We conclude that REE in master athletes is primarily determined by body composition and ambient temperature. Our study provides a first estimate of energy requirements for master athletes in order to cover adequately athletes’ energy and nutrient requirements to maintain their health status and physical performance.

How to Maintain a Healthy Body Weight

2006 ◽  
Vol 76 (4) ◽  
pp. 208-215 ◽  
Author(s):  
Astrup
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Weight Loss ◽  
Body Weight ◽  
Glycemic Index ◽  
Dairy Products ◽  
Weight Control ◽  
Healthy Body Weight ◽  
Healthy Body

The epidemic of both obesity and type 2 diabetes is due to environmental factors, but the individuals developing the conditions possess a strong genetic predisposition. Observational surveys and intervention studies have shown that excess body fatness is the major environmental cause of type 2 diabetes, and that even a minor weight loss can prevent its development in high-risk subjects. Maintenance of a healthy body weight in susceptible individuals requires 45–60 minutes physical activity daily, a fat-reduced diet with plenty of fruit, vegetables, whole grain, and lean meat and dairy products, and moderate consumption of calorie containing beverages. The use of table values to predict the glycemic index of meals is of little – if any – value, and the role of a low-glycemic index diet for body weight control is controversial. The replacement of starchy carbohydrates with protein from lean meat and lean dairy products enhances satiety, and facilitate weight control. It is possible that dairy calcium also promotes weight loss, although the mechanism of action remains unclear. A weight loss of 5–10% can be induced in almost all obese patients providing treatment is offered by a professional team consisting of a physician and dieticians or nurses trained to focus on weight loss and maintenance. Whereas increasing daily physical activity and regular exercise does not significantly effect the rate of weight loss in the induction phase, it plays an important role in the weight maintenance phase due to an impact on daily energy expenditure and also to a direct enhancement of insulin sensitivity.

Haematocrit: Relationships with Blood Lipids, Blood Pressure and other Cardiovascular Risk Factors

1994 ◽  
Vol 72 (01) ◽  
pp. 058-064 ◽  
Author(s):  
Goya Wannamethee ◽  
A Gerald Shaper
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Alcohol Intake ◽  
Blood Lipids ◽  
The Other ◽  
The Relationship

SummaryThe relationship between haematocrit and cardiovascular risk factors, particularly blood pressure and blood lipids, has been examined in detail in a large prospective study of 7735 middle-aged men drawn from general practices in 24 British towns. The analyses are restricted to the 5494 men free of any evidence of ischaemic heart disease at screening.Smoking, body mass index, physical activity, alcohol intake and lung function (FEV1) were factors strongly associated with haematocrit levels independent of each other. Age showed a significant but small independent association with haematocrit. Non-manual workers had slightly higher haematocrit levels than manual workers; this difference increased considerably and became significant after adjustment for the other risk factors. Diabetics showed significantly lower levels of haematocrit than non-diabetics. In the univariate analysis, haematocrit was significantly associated with total serum protein (r = 0*18), cholesterol (r = 0.16), triglyceride (r = 0.15), diastolic blood pressure (r = 0.17) and heart rate (r = 0.14); all at p <0.0001. A weaker but significant association was seen with systolic blood pressure (r = 0.09, p <0.001). These relationships remained significant even after adjustment for age, smoking, body mass index, physical activity, alcohol intake, lung function, presence of diabetes, social class and for each of the other biological variables; the relationship with systolic blood pressure was considerably weakened. No association was seen with blood glucose and HDL-cholesterol. This study has shown significant associations between several lifestyle characteristics and the haematocrit and supports the findings of a significant relationship between the haematocrit and blood lipids and blood pressure. It emphasises the role of the haematocrit in assessing the risk of ischaemic heart disease and stroke in individuals, and the need to take haematocrit levels into account in determining the importance of other cardiovascular risk factors.

Mental distress and its associations with behavioral outcomes during the COVID-19: A national survey of Chinese adults (Preprint)

2020 ◽  
Author(s):  
Lu Ma ◽  
Liwang Gao ◽  
Joseph Tak-Fai Lau ◽  
Rahman Atif ◽  
Blair T. Johnson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Educational Attainment ◽  
Structural Equation ◽  
Online Survey ◽  
Mental Distress ◽  
Structural Equation Models ◽  
Behavioral Outcomes ◽  
National Sample ◽  
Negative Consequences

BACKGROUND This study primarily aimed to evaluate the associations between mental distress and COVID-19-related changes in behavioral outcomes, and potential modifiers (age, gender, and educational attainment) of such associations. OBJECTIVE The COVID -19 pandemic has led to elevated levels of mental distress attributed to prolonged lockdowns, business closures, and social isolation. Its impact on behavioral outcomes is however less known. This study is designed to primarily evaluate the associations between mental distress and COVID-19-related changes in drinking, smoking, physical activity and body weight, and potential modifiers of such associations including age, gender, and educational attainment. METHODS An online survey using anonymous network sampling was conducted in China during April-May, 2020 using a 74-item questionnaire distributed through social media. A national sample of 10,545 adults in 31 provinces provided data on socio-demographic characteristics, COVID-19-related mental distress, and changes in behavioral outcomes. Structural equation models were used for data analyses. RESULTS About 13% of adults reported experiencing at least one symptom of mental distress. After adjusting for age, education, gender, ethnicity, marital status, residence, and number of chronic conditions, greater mental distress was associated with increased smoking and alcohol consumption (among current smokers and drinkers) and with both increased and decreased physical activity. Underweight adults were more likely to lose body weight (≥1 kg) whereas overweight adults were more likely to gain weight by the same amount. The association between mental distress and change in physical activity was stronger in adults aged 40 and above and those with high education. Mental distress was significantly associated with an increase in smoking in males but not females. CONCLUSIONS Mental distress was associated with increased smoking in males but not females. These findings inform the design of tailored public health interventions aimed to mitigate long-term negative consequences of mental distress on outcomes.

scholarly journals Annual rhythms in adults’ lifestyle and health (ARIA): protocol for a 12-month longitudinal study examining temporal patterns in weight, activity, diet, and wellbeing in Australian adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rachel G. Curtis ◽  
Timothy Olds ◽  
François Fraysse ◽  
Dorothea Dumuid ◽  
Gilly A. Hendrie ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Weight Gain ◽  
Repeated Measures ◽  
Vigorous Physical Activity ◽  
Activity Patterns ◽  
Intervention Strategy ◽  
Temporal Patterns ◽  
Trial Registration ◽  
Multi Level

Abstract Background Almost one in three Australian adults are now obese, and the rate continues to rise. The causes of obesity are multifaceted and include environmental, cultural and lifestyle factors. Emerging evidence suggests there may be temporal patterns in weight gain related, for example, to season and major festivals such as Christmas, potentially due to changes in diet, daily activity patterns or both. The aim of this study is to track the annual rhythm in body weight, 24 h activity patterns, dietary patterns, and wellbeing in a cohort of Australian adults. In addition, through data linkage with a concurrent children’s cohort study, we aim to examine whether changes in children’s body mass index, activity and diet are related to those of their parents. Methods A community-based sample of 375 parents aged 18 to 65 years old, residing in or near Adelaide, Australia, and who have access to a Bluetooth-enabled mobile device or a computer and home internet, will be recruited. Across a full year, daily activities (minutes of moderate to vigorous physical activity, light physical activity, sedentary behaviour and sleep) will be measured using wrist-worn accelerometry (Fitbit Charge 3). Body weight will be measured daily using Fitbit wifi scales. Self-reported dietary intake (Dietary Questionnaire for Epidemiological Studies V3.2), and psychological wellbeing (WHOQOL-BREF and DASS-21) will be assessed eight times throughout the 12-month period. Annual patterns in weight will be examined using Lowess curves. Associations between changes in weight and changes in activity and diet compositions will be examined using repeated measures multi-level models. The associations between parent’s and children’s weight, activity and diet will be investigated using multi-level models. Discussion Temporal factors, such as day type (weekday or weekend day), cultural celebrations and season, may play a key role in weight gain. The aim is to identify critical opportunities for intervention to assist the prevention of weight gain. Family-based interventions may be an important intervention strategy. Trial registration Australia New Zealand Clinical Trials Registry, identifier ACTRN12619001430123. Prospectively registered on 16 October 2019.

scholarly journals Body weight trends in adolescents of Central Italy across 13 years: social, behavioural, and psychological correlates

2021 ◽  
Author(s):  
Giovanni Castellini ◽  
Giulio D’Anna ◽  
Eleonora Rossi ◽  
Emanuele Cassioli ◽  
Fabio Voller ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Psychological Distress ◽  
Sexual Activity ◽  
Family Relationships ◽  
Parental Education ◽  
Central Italy ◽  
Eating Behaviour ◽  
Soft Drinks ◽  
Bullying Victimisation

Abstract Aim The study aimed to determine trends in the prevalence of underweight, overweight, obesity and their putative risk factors in different cohorts from a representative population of adolescents in Central Italy. Subject and methods After random sampling, five cohorts of adolescents attending public high schools – aged 14 to 18 years – were evaluated from 2005 to 2018 (n: 25,174). Collected information included self-reported body mass index (BMI), descriptors of family environment, eating behaviour, physical activity, screen use, bullying victimisation, sexual behaviour (age at first intercourse, number of partners) and perceived psychological distress. For these data, between-cohort prevalence differences were used to esteem prevalence variations across time. In the 2018 cohort, the association between these factors and body weight was evaluated through multinomial regressions with sex-specific crude relative risk ratios for different BMI categories. Results An increased prevalence of overweight was observed for both boys and girls. The study outlined a transition towards higher parental education and unemployment, reduced soft drinks consumption and higher psychological distress. Sex-specific changes were observed for physical and sexual activity, and a rising percentage of girls reported being bullied and distressing family relationships. Parental education and employment, together with physical activity, confirmed to be protective factors against pathological weight. The latter clustered with reduced soft drinks consumption, bullying victimisation, early sexual activity, worse family relationships and higher distress. Conclusion An increased prevalence of both overweight and underweight was observed across time. Economic factors associated with unemployment and changes in behavioural patterns may have contributed to this trend.

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