scholarly journals A study of body measurements of sporty and not sporty persons living in Pärnu county

2020 ◽  
Vol 29 (2) ◽  
pp. 92-103
Author(s):  
Kandela Õun ◽  
Kaisa Kirikal
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Physical Fitness ◽  
Sport Activity ◽  
Well Being ◽  
Group Training ◽  
Body Measurements ◽  
Athletic Activity ◽  
Slight Tendency ◽  
Medium Weight

In 2019, a study was conducted on athletic activity among the inhabitants of Pärnu County. 1446 respondents aged 15–87 years participated in the study. The respondents were divided into two groups according to their athletic activity – respondents who are at least lightly active (named as SPORTY, n = 1244) and respondents with no sport activity (NOT SPORTY, n = 202). 41% of respondents had been engaged in physical activity for 10 years or more. A “not sporty” respondent is a person with a slight tendency to overweight, rather not satisfied with his/her health but quite satisfied with his/ her life and is short of time to work out but would like to engage in cycling, swimming or hiking. The “sporty” person’s body mass index is normal, and he/she has been engaged in sports for at least 10 years to achieve better physical fitness or well-being. He/she enjoys walking, cycling, or running. Women prefer group training; men prefer to train in the gym on their own. Respondents with more than five years of regular physical activity work out every week somewhat longer than others and, on average, a few hours more per week in summertime than in autumn and spring. Sporty respondents tend to be taller and of medium weight.

Environment factors associated with adolescents’ body mass index, physical activity and physical fitness in Kuching South City, Sarawak: a cross-sectional study

2012 ◽  
Vol 24 (4) ◽  
pp. 331-337 ◽  
Author(s):  
Whye L. Cheah ◽  
Ching T. Chang ◽  
Rosalia Saimon
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Physical Fitness ◽  
Body Mass ◽  
Well Being ◽  
Cross Sectional Study ◽  
Neighborhood Environment ◽  
Sectional Study ◽  
Cross Sectional ◽  
The Mean

Abstract This study examined the relationship between perceived built environment attributes and physical activity, physical fitness and body weight among adolescents aged 14–16 years in Sarawak. This was a cross-sectional study, using multi-stage sampling. A set of questionnaires consisting of socio-demographic information, a self-administered physical activity checklist and a Neighborhood Environment Walkability Scale-Youth (NEWS-Y) was used. Body mass index (BMI) was measured and physical fitness was tested using a maximal multistage 20 m shuttle run test. Data analysis was done using SPSS version 17.0. A total of 316 respondents participated. The mean BMI for boys was almost equal to the mean BMI for girls. Only 7.9% of the sampled population was found to be overweight or obese. The overall mean duration spent per day on physical activity was 128.4 min (SD 118.43), with mean of 56.1 min (SD 73.94) after school time. Girls reported to spend longer each day taking physical activity before and during school. Boys were found to have significantly higher VO2max of 27.79±5.91 mL/kg/min as compared to girls (t=11.22, p<0.000). Based on comparison with other countries, the NEWS-Y scores indicated a mixture of low and high walkability neighborhoods. Respondents who had lower BMIs reported living in lower residential density areas and less risk of crime, and respondents who had better physical fitness reported less suitable infrastructure for walking. Promotion of exercise at all levels should be continuously encouraged as it would lead to improvement in the well-being of an individual.

scholarly journals Physical Activity and Psychological Well-Being: Testing Alternative Sociological Interpretations

1990 ◽  
Vol 7 (4) ◽  
pp. 329-346 ◽  
Author(s):  
William McTeer ◽  
James E. Curtis
Keyword(s):  
Physical Activity ◽  
Socioeconomic Status ◽  
Social Interaction ◽  
Physical Fitness ◽  
Well Being ◽  
The Other ◽  
Positive Zero ◽  
Psychological Well Being ◽  
Relationship Of ◽  
The Relationship

This study examines the relationship between physical activity in sport and feelings of well-being, testing alternative interpretations of the relationship between these two variables. It was expected that there would be positive relationships between physical activity on the one hand and physical fitness, feelings of well-being, social interaction in the sport and exercise environment, and socioeconomic status on the other hand. It was also expected that physical fitness, social interaction, and socioeconomic status would be positively related to psychological well-being. Further, it was expected that any positive zero-order relationship of physical activity and well-being would be at least in part a result of the conjoint effects of the other variables. The analyses were conducted separately for the male and female subsamples of a large survey study of Canadian adults. The results, after controls, show a modest positive relationship of physical activity and well-being for males but no such relationship for females. The predicted independent effects of the control factors obtained for both males and females. Interpretations of the results are discussed.

Effect of Dietary Intake and Physical Activity on Body Mass Index Among the Students of University of Lahore

2020 ◽  
pp. 41-45
Author(s):  
OJS Admin
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Dietary Intake ◽  
Body Mass ◽  
Well Being ◽  
Good Health

Nutrition has fundamental role in the well-being of any individual. The intake of proper diet along with any kind of regular activity is essential for obtaining good health.

Physical Activity, Physical Fitness And Body Mass Index As Predictors Of Future Obesity In Canada

2005 ◽  
Vol 37 (Supplement) ◽  
pp. S172
Author(s):  
Susan E. Brien ◽  
Peter T. Katzmarzyk ◽  
Cora L. Craig ◽  
Lise Gauvin
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Physical Fitness ◽  
Body Mass

A comparison of physical activity, physical fitness levels, BMI and blood pressure of adults with intellectual disability, who do and do not take part in Special Olympics Ireland programmes: Results from the SOPHIE study

2017 ◽  
Vol 22 (2) ◽  
pp. 154-170 ◽  
Author(s):  
Denise Walsh ◽  
Sarahjane Belton ◽  
Sarah Meegan ◽  
Kirsty Bowers ◽  
Deidre Corby ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Intellectual Disability ◽  
Physical Fitness ◽  
Vigorous Physical Activity ◽  
Well Being ◽  
Self Report ◽  
Special Olympics ◽  
The Impact ◽  
Fitness Levels

People with an intellectual disability are less physically active, live more sedentary lives, have lower fitness levels and are more likely to be overweight or obese than the general population. No evidence exists on the impact of participation in Special Olympics Ireland (SOI) on physical activity and physical fitness levels. Adults with intellectual disabilities (16–64 years) were recruited from services and SOI clubs. Physical measures included waist circumference, height, weight, blood pressure, heart rate and 6-min walking test. Self-report questionnaires gathered data on physical activity levels. Actigraph (GT3X) accelerometers were used to gain an objective measure of physical activity. SOI participants accumulated more moderate to vigorous physical activity per day, had higher fitness levels and more positive health profile scores than those not taking part in SOI. SOI has the potential to make a positive difference to people’s physical health and subsequently their overall health and well-being.

scholarly journals Clinical Measures of Physical Fitness Predict Insulin Resistance in People at Risk for Diabetes

2008 ◽  
Vol 88 (11) ◽  
pp. 1355-1364 ◽  
Author(s):  
Chiao-Nan Chen ◽  
Lee-Ming Chuang ◽  
Ying-Tai Wu
Keyword(s):  
Physical Activity ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Body Mass Index ◽  
At Risk ◽  
Risk Factor ◽  
Waist Circumference ◽  
Physical Fitness ◽  
Clinical Measures

Background and Purpose Physical inactivity has been well documented as a risk factor for type 2 diabetes. Previous studies measured the level of physical activity either with questionnaires or with direct measurements of maximum oxygen uptake. However, questionnaires are patient-report measures, and methods for obtaining direct maximum oxygen uptake measurements often are not available clinically. The purpose of this study was to investigate whether clinical measurement of health-related physical fitness with a simple test battery can predict insulin resistance, a precursor of type 2 diabetes, in people at risk for diabetes. Subjects and Methods A total of 151 volunteers with at least one diabetes risk factor (overweight, hypertension, dyslipidemia, family history, impaired glucose tolerance, gestational diabetes, or delivering a baby weighing more than 4.0 kg) were recruited. Insulin resistance (as determined with the homeostasis model assessment of insulin resistance [HOMA-IR]), physical fitness (including body composition, as determined with the body mass index and waist circumference), muscle strength (handgrip strength [force-generating capacity]), muscle endurance (sit-up test), flexibility (sit-and-reach test), and cardiorespiratory endurance (step test) were measured, and a physical activity questionnaire was administered. Backward regression analysis was used to build the prediction models for insulin resistance from components of physical fitness and physical activity. Results Body mass index, muscle strength, and cardiorespiratory fitness predicted HOMA-IR in men (adjusted R2=.264). In women, age, waist circumference, and cardiorespiratory fitness were the predictors of HOMA-IR (adjusted R2=.438). Discussion and Conclusion Clinical measures of physical fitness can predict insulin resistance in people at risk for diabetes. The findings support the validity of clinical measures of physical fitness for predicting insulin resistance in people at risk for diabetes.

scholarly journals Characteristics of Adopters of an Online Social Networking Physical Activity Mobile Phone App: Cluster Analysis (Preprint)

2018 ◽  
Author(s):  
Ilea Sanders ◽  
Camille E Short ◽  
Svetlana Bogomolova ◽  
Tyman Stanford ◽  
Ronald Plotnikoff ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Cluster Analysis ◽  
Social Networking ◽  
Cost Effective ◽  
Well Being ◽  
Health Promotion Program ◽  
Research Translation ◽  
Activity Levels ◽  
Market Segments

BACKGROUND To date, many online health behavior programs developed by researchers have not been translated at scale. To inform translational efforts, health researchers must work with marketing experts to design cost-effective marketing campaigns. It is important to understand the characteristics of end users of a given health promotion program and identify key market segments. OBJECTIVE This study aimed to describe the characteristics of the adopters of Active Team, a gamified online social networking physical activity app, and identify potential market segments to inform future research translation efforts. METHODS Participants (N=545) were Australian adults aged 18 to 65 years who responded to general advertisements to join a randomized controlled trial (RCT) evaluating the Active Team app. At baseline they provided demographic (age, sex, education, marital status, body mass index, location of residence, and country of birth), behavioral (sleep, assessed by the Pittsburgh Quality Sleep Index) and physical activity (assessed by the Active Australia Survey), psychographic information (health and well-being, assessed by the PERMA [Positive Emotion, Engagement, Relationships, Meaning, Achievement] Profile; depression, anxiety and stress, assessed by the Depression, Anxiety, and Stress Scale [DASS-21]; and quality of life, assessed by the 12-Item Short Form Health Survey [SF-12]). Descriptive analyses and a k-medoids cluster analysis were performed using the software R 3.3.0 (The R Foundation) to identify key characteristics of the sample. RESULTS Cluster analyses revealed four clusters: (1) younger inactive women with poor well-being (218/545), characterized by a higher score on the DASS-21, low mental component summary score on the SF-12, and relatively young age; (2) older, active women (153/545), characterized by a lower score on DASS-21, a higher overall score on the SF-12, and relatively older age; (3) young, active but stressed men (58/545) with a higher score on DASS-21 and higher activity levels; and (4) older, low active and obese men (30/545), characterized by a high body mass index and lower activity levels. CONCLUSIONS Understanding the characteristics of population segments attracted to a health promotion program will guide the development of cost-effective research translation campaigns. CLINICALTRIAL Australian New Zealand Clinical Trial Registry ACTRN12617000113358; https://www.anzctr.org .au/Trial/Registration/TrialReview.aspx?id=371463 INTERNATIONAL REGISTERED REPOR RR2-10.1186/s12889-017-4882-7

scholarly journals Physical fitness, nutritional habits and daily locomotive action of 12-year-old children with different body mass index

2008 ◽  
Vol 20 (1) ◽  
pp. 32 ◽  
Author(s):  
S Kamtsios
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Physical Fitness ◽  
Body Mass ◽  
Sports Medicine ◽  
School Design ◽  
Nutritional Habits ◽  
And Gender ◽  
Tv Watching ◽  
Limited Physical Activity

Objective. The purpose of this study was to examine the differences in physical fitness, daily nutritional habits and locomotive behaviour among pupils with varying body mass index (BMI) in the 5th and 6th grades of primary school. Design. The sample consisted of 480 pupils (229 boys and 251 girls), who participated in specific Eurofit tests and completed questionnaires probing their physical activity and nutritional habits. They were divided according to their BMI into normal, overweight or obese children. Main outcome measures. 18% and 8% of the pupils were categorised as overweight and obese, respectively. Results. From the data analysis (two-way ANOVA), with BMI and gender as independent variables, it was found that the obese and overweight pupils had lower performance in long jump, in 30-m speed and in 20-m shuttle run. They adopted sedentary daily habits, such as many hours of TV watching and unhealthly nutritional habits. Conclusions. The results of this study support the need for intervention at school through physical education and health education lessons, to inform pupils about the health risks associated with limited physical activity and unhealthy nutritional habits. Another goal should be to motivate and create behaviours that are conducive to better lifestyle habits. South African Journal of Sports Medicine Vol. 20 (1) 2008: pp. 32-36

scholarly journals Effect of Physical Activity on Body Mass Index and some Physical Fitness Factors in Addicted Women

2017 ◽  
Vol 6 (4) ◽  
pp. 43-49
Author(s):  
Behrouz Ghorbanzadeh ◽  
Bohlol Ghorbanian ◽  
Yosef Yavari ◽  
Maryam Lotfi ◽  
Mehrnoosh Shamiry ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Physical Fitness ◽  
Body Mass

scholarly journals HUBUNGAN STATUS GIZI DAN AKTIVITAS FISIK DENGAN KEBUGARAN JASMANI REMAJA

2018 ◽  
Vol 2 (2) ◽  
pp. 133-142
Author(s):  
Ihda Nur Kasyifa ◽  
Mohammad Zen Rahfiludin ◽  
Suroto Suroto
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Physical Fitness ◽  
Body Mass ◽  
Research Method ◽  
Statistic Analysis ◽  
Cross Sectional ◽  
Tenth Graders ◽  
Kolmogorov Smirnov ◽  
The Relationship

Physical fitness is one of the most important things especially for teens due to their highactivities. Factors that affect physical fitness such as physical activity and BMI/Age. This study aimsto find out the relationship between body mass index based on age (BMI/Age) and physical activitywith physical fitness of SMKN Jawa Tengah Semarang students. This study use quantitative approachwith cross sectional research method. Population used in this study are 118 tenth graders and thesampel are 55 students. Statistic analysis in this study use Kolmogorov-Smirnov and Rank Spearmantest. The result shows that most of 16-year-olds participants are 39 students (70,9%) and 45 studentsare male. Fourty nine students (81,8%) have normal BMI/Age which 28 participants have kind ofheavy activities and the physical fitness of 31 participants count as good categoy. This study showthere is no relationship between IMT/U with physical fitness (p = 0,252 and r = 0,160) and there isa relationship between physical activity with physical fitness (p = 0,003 and r = 0,391).

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