lecture 5-understanding and changing physical activity behaviour Flashcards
What are the UK recommendations around exercise?
Either 150 minutes ofmoderate aerobic activityevery week (e.g.cycling orbrisk walking)
Or 75 minutesofvigorous aerobicactivity every week
(e.g. running or tennis)
And strength exercises on2 or more days aweek thatworkall the major muscles (legs, hips, back, abdomen, chest, shoulders and arms)e.g. weight lifting, yoga, or heavy gardening
+ Minimize the amount of time spent being sedentary (sitting) for extended periods
Define Physical activity
Any bodily movement produced by skeletal muscles that requires energy expenditure, e.g. walking, gardening, fidgeting (WHO, 2017)
Define exercise
An activity that is planned, structured, and repetitive and has a final or an intermediate objective to improve or maintain physical fitness (Caspersen et al., 1985)
Define sport
An activity involving physical exertion, skill and/or hand-eye coordination as the primary focus of the activity, with elements of competition where rules and patterns of behaviour governing the activity exist (Australian Bureau of Statistics, 2008)
Benefits of PA
1. Physical well-being
PA a main modifiable risk factor for non-communicable diseases (NCD) mortality (Oguma et al., 2002; Savela et al., 2010)
High triglycerides; b) High LDL (low density lipoprotein); c) Low HDL (high density lipoprotein); d) High blood glucose; e) High blood pressure; f) Central adiposity
Reduced risks of diabetes, stroke, cancer (Warburton, Nicol & Bredin, 2006; Pedersen & Saltin, 2015)
Overweight/obesityObstructive sleep apnoea (Daniels, 2009)Bone health (lower bone density as young as 6yo) (Cole et al., 2012)
Prospective studies show physical activity is positively associated with positive health outcomes:
Diabetes: Fretts et al 2012
OBJECTIVE To examine the association of objectively measured participation in low levels of physical activity with incident type 2 diabetes.
RESEARCH DESIGN AND METHODS
The study population included participants free of diabetes and cardiovascular disease at baseline (n = 1,826) who participated in a follow-up examination. Generalized estimating equations were used to examine the association of steps per day with incident diabetes.
RESULTS During 5 years of follow-up, 243 incident cases of diabetes were identified. When compared with participants in the lowest quartile of steps per day (<3,500 steps), participants in the upper three quartiles of steps per day had lower odds for diabetes, consistent with a threshold effect. Contrasting the three upper quartiles with the lowest quartile, the odds ratio of diabetes was 0.71 (95% CI 0.51–0.98).
CONCLUSIONS Modest levels of physical activity are associated with a lower risk of incident diabetes, compared with lower levels of activity.
Cardiovascular disease: Li & Siegrist. Int J Environmental Research & Public Health 2012, 9, 391-407
In order to update and improve available evidence on associations of physical activity (PA) with cardiovascular disease (CVD) by applying meta-analytic random effects modeling to data from prospective cohort studies, using high quality criteria of study selection, we searched the PubMed database from January 1980 to December 2010 for prospective cohort studies of PA and incident CVD, distinguishing occupational PA and leisure time PA, coronary heart disease (CHD) and stroke, respectively. Inclusion criteria were peer-reviewed English papers with original data, studies with large sample size (n ≥ 1,000) and substantial follow-up (≥ 5 years), available data on major confounders and on estimates of relative risk (RR) or hazard ratio (HR), with 95% confidence intervals (CI). We included 21 prospective studies in the overall analysis, with a sample size of more than 650,000 adults who were initially free from CVD, and with some 20,000 incident cases documented during follow-up. Among men, RR of overall CVD in the group with the high level of leisure time PA was 0.76 (95% CI 0.70-0.82, p < 0.001), compared to the reference group with low leisure time PA, with obvious dose-response relationship. A similar effect was observed among women (RR = 0.73, 95% CI 0.68-0.78, p < 0.001). A strong protective effect of occupational PA was observed for moderate level in both men (RR = 0.89, 95% CI 0.82-0.97, p = 0.008) and women (RR = 0.83, 95% CI 0.67-1.03, p = 0.089). No publication bias was observed. Our findings suggest that high level of leisure time PA and moderate level of occupational PA have a beneficial effect on cardiovascular health by reducing the overall risk of incident coronary heart disease and stroke among men and women by 20 to 30 percent and 10 to 20 percent, respectively.
Obesity: Banks et al. BMC Public Health, 2011, 11, 762
Background
Patterns of physical activity (PA), domestic activity and sedentary behaviours are changing rapidly in Asia. Little is known about their relationship with obesity in this context. This study investigates in detail the relationship between obesity, physical activity, domestic activity and sedentary behaviours in a Thai population.
Methods
74,981 adult students aged 20-50 from all regions of Thailand attending the Sukhothai Thammathirat Open University in 2005-2006 completed a self-administered questionnaire, including providing appropriate self-reported data on height, weight and PA. We conducted cross-sectional analyses of the relationship between obesity, defined according to Asian criteria (Body Mass Index (BMI) ≥25), and measures of physical activity and sedentary behaviours (exercise-related PA; leisure-related computer use and television watching (“screen-time”); housework and gardening; and sitting-time) adjusted for age, sex, income and education and compared according to a range of personal characteristics.
Results
Overall, 15.6% of participants were obese, with a substantially greater prevalence in men (22.4%) than women (9.9%). Inverse associations between being obese and total weekly sessions of exercise-related PA were observed in men, with a significantly weaker association seen in women (p(interaction) < 0.0001). Increasing obesity with increasing screen-time was seen in all population groups examined; there was an overall 18% (15-21%) increase in obesity with every two hours of additional daily screen-time. There were 33% (26-39%) and 33% (21-43%) reductions in the adjusted risk of being obese in men and women, respectively, reporting housework/gardening daily versus seldom or never. Exercise-related PA, screen-time and housework/gardening each had independent associations with obesity.
Interventions show
improvements in:
CVD risk factors: Buchan et al. 2011
The purpose of this study was to examine the effects of exercising at different intensities over 7 weeks on components of physical fitness and CVD risk factors. Forty-seven boys and 10 girls, (16.4±0.7 years of age) were divided into a moderate, high intensity, or a control group. All participants had indices of obesity and blood pressure recorded in addition to four physical performance measures pre- and post-intervention. In addition, the intervention groups repeated the physical performance measures at the 4th week phase of the intervention. Following the intervention, significant improvements (P<0.05) in the high-intensity group were found in the 20 MSFT, agility, CMJ and 10 m sprint post-intervention. Participants in the moderate intensity group displayed significant improvements (P<0.05) in both the CMJ and 20 MSFT post-intervention. Body fat % significantly improved (P<0.01) in the moderate group only post-intervention. Interestingly, Systolic blood pressure significantly improved post-intervention (112±10 vs 106±11 mmHg) (P=0.017) in the high intensity group. In conclusion, high-intensity exercise over 7 weeks is a very time efficient means of improving important components of physical fitness in adolescents.
Obesity: Gourlan et al. 2011
As the benefits that regular physical activity (PA) have on obesity are well known, many interventions promote active lifestyle adoption among obese populations. This meta-analysis aims to determine (i) the global effect that interventions promoting PA among obese populations have on their PA behaviour; (ii) varia- tions in the effect of interventions depending on the PA indicator used; (iii) the programme’s dose characteristics and (iv) maintenance of the intervention effects after the intervention has ended. A comprehensive search through databases and review articles was completed. Forty-six studies met the inclusion criteria. Calcu- lations of effect size (Cohen’s d) and a moderator analysis were conducted. The meta-analysis showed that interventions globally have an impact on the PA behaviour of obese populations (d = 0.44; 95% CI = 0.31, 0.57). The moderator analysis revealed that interventions of less than 6 months reported significantly larger effects than longer interventions. Moreover, the interventions had a stron- ger impact on the number of steps and the PA indexes (i.e. composite scores reflecting PA practice) than on other PA indicators. Finally, the analysis revealed that interventions succeed in maintaining PA behaviour after the intervention is over. However, relatively few studies addressed this issue (n = 9).
Pain in arthritis sufferers: Conn et al. 2008
OBJECTIVE:
Due to reduced physical activity, adults with arthritis experience significant disability and comorbidities including cardiovascular disease. This meta-analytic review integrates results from primary research studies testing interventions to increase physical activity in arthritis patients.
METHODS:
Extensive literature searching strategies were employed to locate published and unpublished empirical studies testing physical activity interventions. Results were coded for studies that had at least 5 participants. Effect sizes (ESs) were calculated for measures of physical activity, pain, and objective and subjective measures of functional ability.
RESULTS:
Twenty-eight research studies with 4111 subjects were synthesized. The mean ES for 2-group comparisons (treatment versus control) was 0.69 for physical activity, 0.21 for pain, 0.49 for objectively measured function, and 0.14 for subjectively measured function. This average effect on subjective function is consistent with a Health Assessment Questionnaire mean of 0.64 for treatment subjects as compared with 0.70 for control subjects. For pain assessed using the 0 to 10 visual analog scale, the average effect amounts to a mean of 3.78 for treatment subjects versus 4.33 for control subjects. Control group subjects experienced statistically significant improvements in pain and, to a lesser extent, objectively measured functional ability during study participation.
CONCLUSIONS:
Physical activity interventions resulted in moderate positive effects on physical activity behavior and small positive effects on pain and physical function outcomes. Future research should examine specific intervention characteristics that result in optimal results, such as frequency, type, and intensity of exercise.
Physical Fitness
Physical fitness is positively associated with positive health outcomes:
Balducci et al. Diabetes Care, 2012 Jun, 35, 1347-54:
606 adults, Improvements in physical fitness associated reduced BMI, CVD risk, and improvements in HDL cholesterol
Lee et al. British Journal Of Sports Medicine, 2011, 45, 504-10:
31818 men and 10555 women
Self report leisure time PA and maximal treadmill test
Treadmill test results predict all cause mortality better than PA
OBJECTIVE:
To examine the combined associations and relative contributions of leisure-time physical activity (PA) and cardiorespiratory fitness (CRF) with all-cause mortality.
DESIGN:
Prospective cohort study. Setting Aerobics centre longitudinal study.
PARTICIPANTS:
31,818 men and 10 555 women who received a medical examination during 1978-2002. Assessment of risk factors Leisure-time PA assessed by self-reported questionnaire; CRF assessed by maximal treadmill test. Main outcome measures All-cause mortality until 31 December 2003.
RESULTS:
There were 1492 (469 per 10,000) and 230 (218 per 10,000) deaths in men and women, respectively. PA and CRF were positively correlated in men (r = 0.49) and women (r = 0.47) controlling for age (p < 0.001 for both). PA was inversely associated with mortality in multivariable Cox regression analysis among men, but the association was eliminated after further adjustment for CRF. No significant association of PA with mortality was observed in women. CRF was inversely associated with mortality in men and women, and the associations remained significant after further adjustment for PA.
Physical Fitness improvements occur as a result of:
- increased activity of heart muscles
- increased electrical activity
- increased heart regularity
- impacts on other disease risk factors as a result of increases in energy expenditure
Physical Activity Improvements occur as a result of:
- improved cardiovascular strength
- reduction in blood pressure
- reduction in weight and obesity
- improved muscle and bone health
- improved glycaemic control
Psychological well-being
Prospective studies show physical activity is positively associated with positive health outcomes:
This study investigated lung cancer stigma, anxiety, depression and quality of life (QOL), and validated variable similarities between ever and never smokers. Patients took online self-report surveys. Variable contributions to QOL were investigated using hierarchical multiple regression.
Patients were primarily Caucasian females with smoking experience. Strong negative relationships emerged between QOL and anxiety, depression and lung cancer stigma. Lung cancer stigma provided significant explanation of the variance in QOL beyond covariates. No difference emerged between smoker groups for study variables. Stigma may play a role in predicting QOL. Interventions promoting social and psychological QOL may enhance stigma resistance skills.
Depression and Anxiety Disorders: Pasco et al. 2011
Although it has been hypothesized that the association of physical activity with depressive and anxiety symptoms is bidirectional, few studies have examined this issue in a prospective setting. We studied this bidirectional association using data on physical activity and symptoms of anxiety and depression at three points in time over 8 years. A total of 9,309 participants of the British Whitehall II prospective cohort study provided data on physical activity, anxiety and depression symptoms and 10 covariates at baseline in 1985. We analysed the associations of physical activity with anxiety and/or depression symptoms using multinomial logistic regression (with anxiety and depression symptoms as dependent variables) and binary logistic regression (with physical activity as the dependent variable). There was a cross-sectional inverse association between physical activity and anxiety and/or depressive symptoms at baseline (ORs between 0.63 and 0.72). In cumulative analyses, regular physical activity across all three data waves, but not irregular physical activity, was associated with reduced likelihood of depressive symptoms at follow-up (OR = 0.71, 95 % CI 0.54, 0.99). In a converse analysis, participants with anxiety and depression symptoms at baseline had higher odds of not meeting the recommended levels of physical activity at follow-up (OR = 1.79, 95 % CI 1.17, 2.74). This was also the case in individuals with anxiety and/or depression symptoms at both baseline and follow-up (OR = 1.70, 95 % CI 1.10, 2.63). The association between physical activity and symptoms of anxiety and/or depression appears to be bidirectional.
Cognitive functioning: Fozard. 1999
Less healthful lifestyles also tend to aggregate among individuals with lower levels of education and may, in part, explain previously noted associations between low education and/or socioeconomic status and poorer cognitive function (Kilander et al., 1997). Examples of such lifestyle factors include smoking, excessive alcohol consumption, illicit drug use, dietary factors, and physical inactivity.
With respect to health-compromising behaviors, several studies have revealed poorer cognitive performance among individuals who smoke tobacco products (M.F. Elias et al., in press; Galanis et al., 1997; Hill, 1989; Launer et al., 1996). Heavy alcohol consumption also has known deleterious effects on cognition (Rourke and Løberg, 1996; Tarter and Van Thiel, 1985). However, across a range of habitual drinking, several investigations have noted an inverted U-or J-shaped relation between alcohol consumption and cognitive function (Dufouil et al., 1997; M.F. Elias et al., in press; P.K. Elias et al., in press; Launer et al., 1996). Drugs of abuse (e.g., opiates, cocaine) have been associated with poorer cognitive performance (Carlin and O’Malley, 1996; Strickland and Stein, 1995). In addition, several dietary insufficiencies, such as vitamin B6, vitamin B12, thiamine, folate, and zinc, have been related to cognitive difficulties (Lester and Fishbein, 1988; Riggs et al., 1996; Whitehouse et al., 1993). Greater caloric consumption in middle age has been shown to predict poorer mental status in old age (Fraser et al., 1996), and a proportionally greater intake of dietary refined carbohydrates has predicted lower IQ scores in children (Lester et al., 1982).
Health-enhancing behaviors have been associated with better cognitive functioning. For example, greater intake of vitamin C, an antioxidant, has been related to enhanced cognitive test performance and/or a lower prevalence of cognitive impairment (Gale et al., 1996; Jama et al., 1996; Paleologos et al., 1998). Greater levels of physical fitness (or physical activity) have also been associated with higher levels of cognitive functioning (Dustman et al., 1994). In addition, several investigations have revealed improvements in cognitive performance with aerobic exercise training (Emery and Blumenthal, 1991; Kramer et al., 1998).
psychological wellbeing interventions:
Villaverde et al. Journal Clinical Nursing, 2012, 21, 923-8:
60 post-menopausal women with depression and anxiety
6 months mixed exercises vs. Control
improvements in depression and anxiety with exercise
Chalder et al. Health Technology Assessment, 2012, 16, 1-164
361 depressives –
3 f2f, 10 telephone by trained facilitator, or control
no effects of physical activity intervention on depression
Short term studies demonstrate positive effects on:
Mood and self esteem: Barton et al. 2012
AIMS:
This study evaluated two existing group-based health promotion initiatives (a social club and a swimming group) and compared these to a new green exercise programme (weekly countryside and urban park walks).
METHODS:
Participants represented a clinical population (N = 53) and were all experiencing a range of mental health problems. They only attended one of the three programmes and sessions were held once a week for six weeks in all initiatives. Composite questionnaires incorporating two standardized measures to analyse changes in self-esteem and mood were completed before and after all sessions.
RESULTS:
A significant main effect for self-esteem and mood pre and post activity (p < 0.001) was reported after participating in a single session. The change in self-esteem was significantly greater in the green exercise group compared with the social activities club (p < 0.001). Dose responses showed that both self-esteem and mood levels improved over the six-week period and improvements were related to attendance in the green exercise group.
CONCLUSIONS:
Green exercise as a health-promoting initiative for people experiencing mental ill health is equally as effective as existing programmes. Combining exercise, nature and social components in future initiatives may play a key role in managing and supporting recovery from mental ill health, suggesting a potential ‘green’ approach to mental healthcare and promotion.
Self efficacy: Annesi et al. 2012
This study investigated associations between pre-school children’s time spent playing electronic games and their fundamental movement skills. In 2009, 53 children had physical activity (Actigraph accelerometer counts per minute), parent proxy-report of child’s time in interactive and non-interactive electronic games (min./week), and movement skill (Test of Gross Motor Development-2) assessed. Hierarchical linear regression, adjusting for age (range = 3-6 years), sex (Step 1), and physical activity (cpm; M=687, SD=175.42; Step 2), examined the relationship between time in (a) non-interactive and (b) interactive electronic games and locomotor and object control skill. More than half (59%, n=31) of the children were female. Adjusted time in interactive game use was associated with object control but not locomotor skill. Adjusted time in non-interactive game use had no association with object control or locomotor skill. Greater time spent playing interactive electronic games is associated with higher object control skill proficiency in these young children. Longitudinal and experimental research is required to determine if playing these games improves object control skills or if children with greater object control skill proficiency prefer and play these games.
