Increased cardio-metabolic risk is associated with increased TV viewing time

Purpose: Television viewing time, independent of leisure-time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and five-year changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardio-metabolic risk (waist circumference, triglycerides, high density lipoprotein cholesterol, systolic and diastolic blood pressure, fasting plasma glucose; and a clustered cardio-metabolic risk score) in Australian adults. Methods: AusDiab is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999–2000 and 2004–2005. Non-institutionalized adults aged ≥ 25 years were measured at baseline (11,247; 55% of those completing an initial household interview); 6,400 took part in the five-year follow-up biomedical examination, and 3,846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used and unstandardized B coefficients (95% CI) are provided. Results: Baseline television viewing time (10 hours/week unit) was not significantly associated with change in any of the biomarkers of cardio-metabolic risk. Increases in television viewing time over five years (10 hours/week unit) were associated with increases in: waist circumference (cm) (men: 0.43 (0.08, 0.78), P = 0.02; women: 0.68 (0.30, 1.05), P <0.001), diastolic blood pressure (mmHg) (women: 0.47 (0.02, 0.92), P = 0.04), and the clustered cardio-metabolic risk score (women: 0.03 (0.01, 0.05), P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. Conclusion: These findings indicate that an increase in television viewing time is associated with adverse cardio-metabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.

Socioeconomic inequalities in weight status among mid-aged adults : the contribution of perceptions of weight status and weight-control behaviours

Background Socioeconomically-disadvantaged adults in developed countries experience a higher prevalence of a number of chronic diseases, such as cardiovascular disease, type 2 diabetes, osteoarthritis and some forms of cancer. Overweight and obesity are major risk factors for these diseases. Lower socioeconomic groups have a greater prevalence of overweight and obesity and this may contribute to their higher morbidity and mortality. International studies suggest that socioeconomic groups may differ in their self-perceptions of weight status and their engagement in weightcontrol behaviours (WCBs). Research has shown that lower socioeconomic adults are more likely to underestimate their weight status, and are less likely to engage in WCBs. This may contribute (in part) to the marked inequalities in weight status observed at the population level. There are few, and somewhat limited, Australian studies that have examined the types of weight-control strategies people adopt, the barriers to their weight control, the determinants of their perceived weight status and WCBs. Furthermore, there are no known Australian studies that have examined socioeconomic differences in these factors to better understand the reasons for socioeconomic inequalities in weight status. Hence, the overall aim of this Thesis is to examine why socioeconomically-disadvantaged group experience a greater prevalence of overweight and obesity than their more-advantaged counterparts. Methods This Thesis used data from two sources. Men and women aged 45 to 60 years were examined from both data source. First, the longitudinal Australian Diabetes, Obesity and Lifestyle (AusDiab) Study were used to advance our knowledge and understanding of socioeconomic differences in weight change, perceived weight status and WCBs. A total of 2753 participants with measured weights at both baseline (1999-2000) and follow-up (2004-2005) were included in the analyses. Percent weight change over the five-year interval was calculated and perceived weight status, WCBs and highest attained education were collected at baseline. Second, the Candidate conducted a postal questionnaire from 1013 Brisbane residents (69.8 % response rate) to investigate the relationship between socioeconomic position, determinants of perceived weight status, WCBs, and barriers and reasons to weight control. A test-retest reliability study was conducted to determine the reliability of the new measures used in the questionnaire. Most new measures had substantial to almost perfect reliability when considering either kappa coefficient or crude agreement. Results The findings from the AusDiab Study (accepted for publication in the Australian and New Zealand Journal of Public Health) showed that low-educated men and women were more likely to be obese at baseline compared to their higheducated respondents (O.R. = 1.97, 95 % C.I. = 1.30-2.98 and O.R. = 1.52, 95 % C.I. = 1.03-2.25, respectively). Over the five year follow-up period (1999-2000 to 2004- 05) there were no socioeconomic differences in weight change among men, however socioeconomically-disadvantaged women had greater weight gains. Participants perceiving themselves as overweight gained less weight than those who saw themselves as underweight or normal weight. There was no relationship between engaging in WCBs and five-year weight change. The postal questionnaire data showed that socioeconomically-disadvantaged groups were less likely to engage in WCBs. If they did engage in weight control, they were less likely to adopt exercise strategies, including moderate and vigorous physical activities but were more likely to decrease their sitting time to control their weight. Socioeconomically-disadvantaged adults reported more barriers to weight control; such as perceiving weight loss as expensive, requiring a lot of cooking skills, not being a high priority and eating differently from other people in the household. These results have been accepted for publication in Public Health Nutrition. The third manuscript (under review in Social Science and Medicine) examined socioeconomic differences in determinants of perceived weight status and reasons for weight control. The results showed that lower socioeconomic adults were more likely to specify the following reasons for weight control: they considered themselves to be too heavy, for occupational requirements, on recommendation from their doctor, family members or friends. Conversely, high-income adults were more likely to report weight control to improve their physical condition or to look more attractive compared with those on lower-incomes. There were few socioeconomic differences in the determinants of perceived weight status. Conclusions Education inequalities in overweight/obesity among men and women may be due to mis-perceptions of weight status; overweight or obese individuals in loweducated groups may not perceive their weight as problematic and therefore may not pay attention to their energy-balance behaviours. Socioeconomic groups differ in WCBs, and their reasons and perceived barriers to weight control. Health promotion programs should encourage weight control among lower socioeconomic groups. More specifically, they should encourage the engagement of physical activity or exercise and dietary strategies among disadvantaged groups. Furthermore, such programs should address potential barriers for weight control that disadvantaged groups may encounter. For example, disadvantaged groups perceive that weight control is expensive, requires cooking skills, not a high priority and eating differently from other people in the household. Lastly, health promotion programs and policies aimed at reducing overweight and obesity should be tailored to the different reasons and motivations to weight control experienced by different socioeconomic groups. Weight-control interventions targeted at higher socioeconomic groups should use improving physical condition and attractiveness as motivational goals; while, utilising social support may be more effective for encouraging weight control among lower socioeconomic groups.

Understanding causal relationships between the built and social environment, health and associated behaviours and risk factors

Introduction: Built environment interventions designed to reduce non-communicable diseases and health inequity, complement urban planning agendas focused on creating more ‘liveable’, compact, pedestrian-friendly, less automobile dependent and more socially inclusive cities.However, what constitutes a ‘liveable’ community is not well defined. Moreover, there appears to be a gap between the concept and delivery of ‘liveable’ communities. The recently funded NHMRC Centre of Research Excellence (CRE) in Healthy Liveable Communities established in early 2014, has defined ‘liveability’ from a social determinants of health perspective. Using purpose-designed multilevel longitudinal data sets, it addresses five themes that address key evidence-base gaps for building healthy and liveable communities. The CRE in Healthy Liveable Communities seeks to generate and exchange new knowledge about: 1) measurement of policy-relevant built environment features associated with leading non-communicable disease risk factors (physical activity, obesity) and health outcomes (cardiovascular disease, diabetes) and mental health; 2) causal relationships and thresholds for built environment interventions using data from longitudinal studies and natural experiments; 3) thresholds for built environment interventions; 4) economic benefits of built environment interventions designed to influence health and wellbeing outcomes; and 5) factors, tools, and interventions that facilitate the translation of research into policy and practice. This evidence is critical to inform future policy and practice in health, land use, and transport planning. Moreover, to ensure policy-relevance and facilitate research translation, the CRE in Healthy Liveable Communities builds upon ongoing, and has established new, multi-sector collaborations with national and state policy-makers and practitioners. The symposium will commence with a brief introduction to embed the research within an Australian health and urban planning context, as well as providing an overall outline of the CRE in Healthy Liveable Communities, its structure and team. Next, an overview of the five research themes will be presented. Following these presentations, the Discussant will consider the implications of the research and opportunities for translation and knowledge exchange. Theme 2 will establish whether and to what extent the neighbourhood environment (built and social) is causally related to physical and mental health and associated behaviours and risk factors. In particular, research conducted as part of this theme will use data from large-scale, longitudinal-multilevel studies (HABITAT, RESIDE, AusDiab) to examine relationships that meet causality criteria via statistical methods such as longitudinal mixed-effect and fixed-effect models, multilevel and structural equation models; analyse data on residential preferences to investigate confounding due to neighbourhood self-selection and to use measurement and analysis tools such as propensity score matching and ‘within-person’ change modelling to address confounding; analyse data about individual-level factors that might confound, mediate or modify relationships between the neighbourhood environment and health and well-being (e.g., psychosocial factors, knowledge, perceptions, attitudes, functional status), and; analyse data on both objective neighbourhood characteristics and residents’ perceptions of these objective features to more accurately assess the relative contribution of objective and perceptual factors to outcomes such as health and well-being, physical activity, active transport, obesity, and sedentary behaviour. At the completion of the Theme 2, we will have demonstrated and applied statistical methods appropriate for determining causality and generated evidence about causal relationships between the neighbourhood environment, health, and related outcomes. This will provide planners and policy makers with a more robust (valid and reliable) basis on which to design healthy communities.

How does Australian diabetic foot screening rate on an international Stage?

Background From the conservative estimates of registrants with the National Diabetes Supply Scheme, we will be soon passing 1.1 Million Australians affected by all types of diabetes. The diabetes complications of foot ulceration and amputation are costly to all. These costs can be reduced with appropriate prevention strategies, starting with identifying people at risk through primary care diabetic foot screening. However, levels of diabetic foot screening in Australia are difficult to quantify. Methods This presentation reports on foot screening rates as recorded in the academic literature, national health surveys and national database reports. The focus is on type 1 and type 2 diabetes in adults, and not gestational diabetes or children. Literature searches included diabetic foot screening that occurred in the primary care setting for populations over 2000 people from 2002 to 2014. Searches were performed using Medline and CINAHL as well as internet searches of OECD health databases. The primary outcome measure was foot -screening rates as a percentage of adult diabetic population. Results The lack of a national diabetes database and register hampers efforts to analyse diabetic foot screening levels. The most recent and accurate level for Australian population review was in the AUSDIAB (Australian Diabetes and lifestyle survey) from 2004. This survey reported screening in primary care to be as low as 50%. Countries such as the United Kingdom and United States of America report much higher rates of foot screening (67-88%) using national databases and web based initiatives that involve patients and clinicians. Conclusions Australian rates of diabetic foot screening in primary care centres is ambiguous. Uptake of national registers, incentives and web based systems improve levels of diabetic foot assessment which are the first steps to a healthier diabetic population.

Is there a relationship between screening for diabetes related foot complications and limb amputation?

Background From the conservative estimates of registrants with the National Diabetes Supply Scheme, we will be soon passing 1.1 Million Australians affected by all types of diabetes. The diabetes complications of foot ulceration and amputation are costly to all. These costs can be reduced with appropriate prevention strategies, starting with identifying people at risk through primary care diabetic foot screening. Yet levels of diabetic foot screening in Australia are difficult to quantify. This presentation aims to report on foot screening rates as recorded in existing academic literature, national health surveys and national database reports. Methods Literature searches included diabetic foot screening that occurred in the primary care setting for populations over 2000 people from 2002 to 2014. Searches were performed using Medline and CINAHL as well as internet searches of Organisations for Economic Co-operation and Development (OECD) countries health databases. The focus is on type 1 and type 2 diabetes in adults, and not gestational diabetes or children. The two primary outcome measures were foot -screening rates as a percentage of adult diabetic population and major lower limb amputation incidence rates from standardised OECD data. Results The most recent and accurate level for Australian population review was in the AUSDIAB (Australian Diabetes and lifestyle survey) from 2004. This survey reported screening in primary care to be as low as 50%. Countries such as the United Kingdom and United States of America have much higher reported rates of foot screening (67-86%) recorded using national databases and web based initiatives that involve patients and clinicians. By comparison major amputation rates for Australia were similar to the United Kingdom at 6.5 versus 5.1 per 100,000 population, but dis-similar to the United States of America at 17 per 100,000 population. Conclusions Australian rates of diabetic foot screening in primary care centres is ambiguous. There is no direct relationship between foot screening levels in a primary care environment and major lower limb amputation, based on national health survey's and OECD data. Uptake of national registers, incentives and web-based systems improve levels of diabetic foot assessment, which are the first steps to a healthier diabetic population.

Niveles de actividad física, condición física y tiempo en pantallas en escolares de Bogotá, Colombia: Estudio FUPRECOL

Examina la relación entre los niveles de actividad física (AF) de forma objetiva, la condición física (CF) y el tiempo de exposición a pantallas en niños y adolescentes de Bogotá, Colombia.

Beneficial associations of physical activity with 2-h but not fasting blood glucose in Australian adults

OBJECTIVE - We examined the associations of physical activity with fasting plasma glucose (FPG) and with 2-h postload plasma glucose (2-h PG) in men and women with low, moderate, and high waist circumference. RESEARCH DESIGN AND METHODS - The Australian Diabetes, Obesity and Lifestyle (AusDiab) study provided data on a population-based cross-sectional sample of 4,108 men and 5,106 women aged >= 25 years without known diabetes or health conditions that could affect physical activity. FPG and 2-h PG were obtained from an oral glucose tolerance test. Self-reported physical activity level was defined according to the current public health guidelines as active (>= 150 min/week across five or more sessions) or inactive (< 150 min/week and/or less than five sessions). Sex-specific quintiles of physical activity time were used to ascertain dose response. RESULTS - Being physically active and total physical activity time were independently and negatively associated with 2-h PG. When physical activity level was considered within each waist circumference category, 2-h PG was significantly lower in active high-waist circumference women (beta-0.30 [95% CI -0.59 to -0.01], P = 0.044) and active low-waist circumference men(beta-0.25 [-0.49 to -0.02],P = 0.036) compared with their inactive counterparts. Considered across physical activity and waist circumference categories, 2-h PG levels were not significantly different between active moderate-waist circumference participants and active low-waist circumference participants. Associations between physical activity and FPG were nonsignificant. CONCLUSIONS - There are important differences between 2-h PG and FPG related to physical activity. It appears that 2-h PG is more sensitive to the beneficial effects of physical activity, and these benefits occur across the waist circumference spectrum.