Physical inactivity, appetite regulation and obesity

In a consumerist society obsessed with body image and thinness, obesity levels have reached an all-time high. This multi-faceted book written by a range of experts, explores the social, cultural, clinical and psychological factors that lie behind the Obesity Epidemic . It is required reading for the many healthcare professionals dealing with the effects of obesity and for anyone who wants to know more about the causes of weight gain and the best ways of dealing with it. Fat Matters covers a range of issues from sociology through medicine to technology. This is not a book for the highly specialised expert. Rather it is a book that shows the diversity of approaches to the phenomenon of obesity, tailored to the reader who wants to be up-to-date and well-informed on a subject that is possibly as frequently discussed and as misunderstood as the weather.

Physical inactivity remains the greatest public health problem of the 21st century : evidence, improved methods and solutions using the '7 investments that work' as a framework

In 2009, BJSM's first editorial argued that ‘Physical inactivity is the greatest public health problem of the 21st century’.1 The data supporting that claim have not yet been challenged. Now, 5 years after BJSM published its first dedicated ‘Physical Activity is Medicine’ theme issue (http://bjsm.bmj.com/content/43/1.toc) we are pleased to highlight 23 new contributions from six countries. This issue contains an analysis of the cost of physical inactivity from the US Centre for Diseases Control.2 We also report the cost-effectiveness of one particular physical activity intervention for adults.3

Tracking of physical activity, physical inactivity, and health-related physical fitness in rural youth

This study examined the tracking of selected measures of physical activity, inactivity, and fitness in a cohort of rural youth. Students (N = 181, 54.7% female, 63.5% African American) completed test batteries during their fifth-(age = 10.7 +/- 0.7 years), sixth-, and seventh-grade years. The Previous Day Physical Activity Recall (PDPAR) was used to assess 30-min blocks of vigorous physical activity (VPA), moderate-to-vigorous physical activity (MVPA), TV watching and other sedentary activities, and estimated energy expenditure (EE). Fitness measures included the PWC 170 cycle ergometer test, strength tests, triceps skinfold thickness, and BMI. Intraclass correlation coefficients (ICCs) for VPA, MVPA, and after-school EE ranged from 0.63 to 0.78. ICCs ranged from 0.49 to 0.71 for measures of inactivity and from 0.78 to 0.82 for the fitness measures. These results indicate that measures of physical activity, inactivity, and physical fitness tend to track during the transition from elementary to middle school.

Age, physical inactivity, obesity, health conditions, and health-related quality of life among patients receiving conservative management for musculoskeletal disorders

Background Musculoskeletal conditions and insufficient physical activity have substantial personal and economic costs among contemporary aging societies. This study examined the age distribution, comorbid health conditions, body mass index (BMI), self-reported physical activity levels, and health-related quality of life of patients accessing ambulatory hospital clinics for musculoskeletal disorders. The study also investigated whether comorbidity, BMI, and self-reported physical activity were associated with patients’ health-related quality of life after adjusting for age as a potential confounder. Methods A cross-sectional survey was undertaken in three ambulatory hospital clinics for musculoskeletal disorders. Participants (n=224) reported their reason for referral, age, comorbid health conditions, BMI, physical activity levels (Active Australia Survey), and health-related quality of life (EQ-5D). Descriptive statistics and linear modeling were used to examine the associations between age, comorbidity, BMI, intensity and duration of physical activity, and health-related quality of life. Results The majority of patients (n=115, 51.3%) reported two or more comorbidities. In addition to other musculoskeletal conditions, common comorbidities included depression (n=41, 18.3%), hypertension (n=40, 17.9%), and diabetes (n=39, 17.4%). Approximately one-half of participants (n=110, 49.1%) self-reported insufficient physical activity to meet minimum recommended guidelines and 150 (67.0%) were overweight (n=56, 23.2%), obese (n=64, 28.6%), severely obese (n=16, 7.1%), or very severely obese (n=14, 6.3%), with a higher proportion of older patients affected. A generalized linear model indicated that, after adjusting for age, self-reported physical activity was positively associated (z=4.22, P<0.001), and comorbidities were negatively associated (z=-2.67, P<0.01) with patients’ health-related quality of life. Conclusion Older patients were more frequently affected by undesirable clinical attributes of comorbidity, obesity, and physical inactivity. However, findings from this investigation are compelling for the care of patients of all ages. Potential integration of physical activity behavior change or other effective lifestyle interventions into models of care for patients with musculoskeletal disorders is worthy of further investigation.

Estimating the burden of disease attributable to physical inactivity in South Africa in 2000

Objectives. To quantify the burden of disease attributable to physical inactivity in persons 15 years or older, by age group and sex, in South Africa for 2000. Design. The global comparative risk assessment (CRA) methodology of the World Health Organization was followed to estimate the disease burden attributable to physical inactivity. Levels of physical activity for South Africa were obtained from the World Health Survey 2003. A theoretical minimum risk exposure of zero, associated outcomes, relative risks, and revised burden of disease estimates were used to calculate population-attributable fractions and the burden attributed to physical inactivity. Monte Carlo simulation-modelling techniques were used for the uncertainty analysis. Setting. South Africa. Subjects. Adults ≥ 15 years. Outcome measures. Deaths and disability-adjusted life years (DALYs) from ischaemic heart disease, ischaemic stroke, breast cancer, colon cancer, and type 2 diabetes mellitus. Results. Overall in adults ≥ 15 years in 2000, 30% of ischaemic heart disease, 27% of colon cancer, 22% of ischaemic stroke, 20% of type 2 diabetes, and 17% of breast cancer were attributable to physical inactivity. Physical inactivity was estimated to have caused 17 037 (95% uncertainty interval 11 394 - 20 407), or 3.3% (95% uncertainty interval 2.2 - 3.9%) of all deaths in 2000, and 176 252 (95% uncertainty interval 133 733 - 203 628) DALYs, or 1.1% (95% uncertainty interval 0.8 - 1.3%) of all DALYs in 2000. Conclusions. Compared with other regions and the global average, South African adults have a particularly high prevalence of physical inactivity. In terms of attributable deaths, physical inactivity ranked 9th compared with other risk factors, and 12th in terms of DALYs. There is a clear need to assess why South Africans are particularly inactive, and to ensure that physical activity/inactivity is addressed as a national health priority.

Sedentariness and physical inactivity in diabetes: a case for home-based exercise prescription

Increasing proportions of the global population are being diagnosed with diabetes. It is anticipated that by 2030, 10% of the adult population worldwide will be living with this condition. Lifestyle factors can impact on the development, management and progression of diabetes. Obesity and sedentary living are contributory factors to the increased volume of diabetes. Physical activity offers those living with diabetes the opportunities to keep well and attain potentially more stable blood glucose control reducing the level of medical intervention required and delaying or preventing some of the life-changing complications that can derive from a diabetes diagnosis. Exercise interventions are effective in preventing and treating type-II diabetes. However, maintaining regular exercise routines, especially home-based exercises may provide a key for sustaining the health benefits.

Job Strain as a Risk Factor for Leisure-Time Physical Inactivity: An Individual-Participant Meta-Analysis of Up to 170,000 Men and Women

Unfavorable work characteristics, such as low job control and too high or too low job demands, have been suggested to increase the likelihood of physical inactivity during leisure time, but this has not been verified in large-scale studies. The authors combined individual-level data from 14 European cohort studies (baseline years from 19851988 to 20062008) to examine the association between unfavorable work characteristics and leisure-time physical inactivity in a total of 170,162 employees (50 women; mean age, 43.5 years). Of these employees, 56,735 were reexamined after 29 years. In cross-sectional analyses, the odds for physical inactivity were 26 higher (odds ratio 1.26, 95 confidence interval: 1.15, 1.38) for employees with high-strain jobs (low control/high demands) and 21 higher (odds ratio 1.21, 95 confidence interval: 1.11, 1.31) for those with passive jobs (low control/low demands) compared with employees in low-strain jobs (high control/low demands). In prospective analyses restricted to physically active participants, the odds of becoming physically inactive during follow-up were 21 and 20 higher for those with high-strain (odds ratio 1.21, 95 confidence interval: 1.11, 1.32) and passive (odds ratio 1.20, 95 confidence interval: 1.11, 1.30) jobs at baseline. These data suggest that unfavorable work characteristics may have a spillover effect on leisure-time physical activity.

Akt Expression is Diminished by Physical Inactivity in Early Stages of Development in Soleus Muscle of Rats

Metabolic Syndrome is a group of conditions related to obesity and physical inactivity. Little is known about the role of physical inactivity, in early stages of development, in the susceptibility to insulin resistant phenotype induced by high fat diet. Akt plays a key role in protein synthesis and glucose transport in skeletal muscle and has been regulated by muscle activity. The objective of present study was to determine the effect of early physical inactivity on muscle growth and susceptibility to acquire a diabetic phenotype and to assess its relationship with Akt expression. Forty Wistar male rats were distributed in two groups (standard group, Std) and movement restriction (RM). Between days 23 and 70 after birth, RM group was kept in small cages that did not allow them to perform relevant motor activity. From day 71 to 102 after birth, 10 rats of each group were fed with hyperlipidic diet (groups Std-DAG and RM-DAG). No differences were observed in total body weight although DAG increased epididymal fat pad weight. RM decreased significantly the soleus weight. Insulin-mediated glucose uptake was lower in RM-DAG group. Akt protein levels were lower in RM groups. Real time RT-PCR analysis showed that movement restriction decreased mRNA levels of AKT1 in soleus muscle, regardless of supplied diet. These findings suggest that early physical inactivity limits muscle`s growth and contributes to instauration of insulin resistant phenotype, which can be partly explained by dysregulation of Akt expression.

Personal, social and environmental correlates of resilience to physical inactivity among women from socio-economically disadvantaged backgrounds

While sex and socio-economic disparities in physical activity have been well documented, not all disadvantaged women are inactive. This study aimed to examine correlates of achieving recommended levels of physical activity among women of low socio-economic position. In 2005, a population-based sample of 291 women with low educational attainment provided survey data on leisure time physical activity (LTPA). Participants reported potential personal (enjoyment and self-efficacy; barriers; intentions; guilt and priorities; routines and scheduling; occupational physical activity; television viewing), social (support from family/friends; social participation; sport/recreation club membership; dog ownership) and environmental (aesthetics; safety; local access; footpaths; interesting walks; busy roads to cross; heavy traffic) correlates of physical activity. Nearly 40% of participants achieved recommended LTPA (150 min week–1). Multivariable analyses revealed that higher levels of self-efficacy for walking [prevalence ratio (PR) 2.05, 95% confidence interval (CI) 1.19–3.53], higher enjoyment of walking (PR 1.48, 95% CI 1.04–2.12), greater intentions to be active (PR 1.97, 95% CI 1.12–3.45) and having set routines for physical activity (PR 1.91, 95% CI 1.18–3.09) were significantly associated with achieving recommended LTPA. Personal factors were the characteristics most strongly associated with achieving recommended levels of LTPA among women from socio-economically disadvantaged backgrounds.

The economic burden of ill health due to diet, physical inactivity, smoking, alcohol and obesity in the UK : an update to 2006-07 NHS costs

Background: Estimates of the economic cost of risk factors for chronic disease to the NHS provide evidence for prioritization of resources for prevention and public health. Previous comparable estimates of the economic costs of poor diet, physical inactivity, smoking, alcohol and overweight/obesity were based on economic data from 1992–93.

Methods: Diseases associated with poor diet, physical inactivity, smoking, alcohol and overweight/obesity were identified. Risk factor-specific population attributable fractions for these diseases were applied to disease-specific estimates of the economic cost to the NHS in the UK in 2006–07.

Results: In 2006–07, poor diet-related ill health cost the NHS in the UK £5.8 billion. The cost of physical inactivity was £0.9 billion. Smoking cost was £3.3 billion, alcohol cost £3.3 billion, overweight and obesity cost £5.1 billion.

Conclusion: The estimates of the economic cost of risk factors for chronic disease presented here are based on recent financial data and are directly comparable. They suggest that poor diet is a behavioural risk factor that has the highest impact on the budget of the NHS, followed by alcohol consumption, smoking and physical inactivity.

The economic benefits of reducing physical inactivity : an Australian example

Background: Physical inactivity has major impacts on health and productivity. Our aim was to estimate the health and economic benefits of reducing the prevalence of physical inactivity in the 2008 Australian adult population. The economic benefits were estimated as ‘opportunity cost savings’, which represent resources utilized in the treatment of preventable disease that are potentially available for re-direction to another purpose from fewer incident cases of disease occurring in communities.
Methods: Simulation models were developed to show the effect of a 10% feasible, reduction target for physical inactivity from current Australian levels (70%). Lifetime cohort health benefits were estimated as fewer incident cases of inactivity-related diseases; deaths; and Disability Adjusted Life Years (DALYs) by age and sex. Opportunity costs were estimated as health sector cost impacts, as well as paid and unpaid production gains and leisure impacts from fewer disease events associated with reduced physical inactivity. Workforce production gains were estimated by comparing surveyed participation and absenteeism rates of physically active and inactive adults, and valued using the friction cost approach. The impact of an improvement in health status on unpaid household production and leisure time were modeled from time use survey data, as applied to the exposed and non-exposed population subgroups and valued by suitable proxy. Potential costs associated with interventions to increase physical activity were not included. Multivariable uncertainty analyses and univariate sensitivity analyses were undertaken to provide information on the strength of the conclusions.
Results: A 10% reduction in physical inactivity would result in 6,000 fewer incident cases of disease, 2,000 fewer deaths, 25,000 fewer DALYs and provide gains in working days (114,000), days of home-based production (180,000) while conferring a AUD96 million reduction in health sector costs. Lifetime potential opportunity cost savings in workforce production (AUD12 million), home-based production (AUD71 million) and leisure-based production (AUD79 million) was estimated (total AUD162 million 95% uncertainty interval AUD136 million, AUD196 million).
Conclusions: Opportunity cost savings and health benefits conservatively estimated from a reduction in population-level physical inactivity may be substantial. The largest savings will benefit individuals in the form of unpaid production and leisure gains, followed by the health sector, business and government.

Physical inactivity and other health risks among Australian males in less-skilled occupations

Male workers in less-skilled occupations have higher rates of cardiovascular disease, compared with higher-skilled workers. A representative population sample of Australian male workers was used to compare physical activity levels and selected cardiovascular disease risk factors in less-skilled versus professional and skilled workers. Workers in the less-skilled occupational categories reported significantly more vigorous work and home-based activity than did those in the professional and skilled categories. In multivariate comparisons, cigarette smoking was the only factor that discriminated between the less-skilled versus the professional and skilled employees. Although worksites can potentially provide health-promoting physical activity options for higher-risk groups, our findings suggest that smoking and possibly overweight are risk factors that are more strongly present in less-skilled occupations.

Preferential deposition of visceral adipose tissue occurs due to physical inactivity.

We hypothesised that strict inactivity (bed rest) would lead to regional differences in fat deposition. Twenty-four male subjects underwent 60 d bed rest and remained inactive (n = 9), performed resistance exercise plus whole-body vibration (RVE; n = 7) or resistance exercise only (RE; n = 8). Fat mass was assessed via dual X-ray absorptiometry. In the inactive subjects, fat deposition differed between body regions (P = 0.0005) with android region visceral adipose tissue increasing the most (+29% at the end of bed rest), followed by remainder of the trunk (from chin to the iliac crest; +10%) and the arms and legs (both +7%). Insulin sensitivity reduced in the inactive subjects at the end of bed rest (P = 0.036). RE did not have a significant impact on regional fat mass changes (P ⩾ 0.055). In RVE, increases in visceral adipose tissue (-14%; P = 0.028 vs inactive subjects) and in the arms (arms -8%, P = 0.011 vs inactive) were not seen. We conclude that inactivity leads to a preferential increase in visceral adipose tissue.