Sex-differences in reasons for non-participation at recruitment : Geelong Osteoporosis Study

Background : Understanding reasons for non-participation in health studies can help guide recruitment strategies and inform researchers about potential sources of bias in their study sample. Whilst there is a paucity of literature regarding this issue, it remains highly plausible that men and women may have varied reasons for declining an invitation to participate in research. We aimed to investigate sex-differences in the reasons for non-participation at baseline of the Geelong Osteoporosis Study (GOS).

Methods : The GOS, a prospective cohort study, randomly recruited men and women aged 20 years and over from a region in south-eastern Australia using Commonwealth electoral rolls (2001–06 and 1993–97, respectively). Reasons for non-participation (n=1,200) were documented during the two recruitment periods. We used the Pearson’s chi squared test to explore differences in the reasons for non-participation between men and women.

Results : Non-participation in the male cohort was greater than in the female cohort (32.9% vs. 22.9%; p<0.001). Overall, there were sex-differences in the reasons provided for non-participation (p<0.001); apparent differences related to time constraints (men 26.3% vs. women 10.4%), frailty/inability to cope with or understand the study (men 18.7% vs. women 30.6%), and reluctance over medical testing (men 1.1% vs women 9.9%). No sex-differences were observed for non-participation related to personal reason/disinterest, and language- or travel-related reasons.

Conclusions : Improving participation rates in epidemiological studies may require different recruitment strategies for men and women in order to address sex-specific concerns about participating in research.

The cost-effectiveness of a successful community-based obesity prevention program: the Be Active Eat Well program

Objective: 

Prevalence and community variation in harmful levels of family conflict witnessed by children: implications for prevention

 Abstract
Children’s reports of high family conflict consistently predict poor outcomes. The study identified criteria for high family conflict based on prospective prediction of increased risk for childhood depression. These criteria were subsequently used to establish the prevalence of high family conflict in Australian communities and to identify community correlates suitable for targeting prevention programs. Study 1 utilised a longitudinal design. Grade 6 and 8 students completed a family conflict scale (from the widely used Communities That Care survey) in 2003 and depression symptomotology were evaluated at a 1-year follow-up (International Youth Development Study, N = 1,798). Receiver-operating characteristic analysis yielded a cut-off point on a family conflict score with depression symptomatology as a criterion variable. A cut-off score of 2.5 or more (on a scale of 1 to 4) correctly identified 69 % with depression symptomology, with a specificity of 77.2 % and sensitivity at 44.3 %. Study 2 used data from an Australian national survey of Grade 6 and 8 children (Healthy Neighbourhoods Study, N = 8,256). Prevalence estimates were calculated, and multivariate logistic regression with multi-level modelling was used to establish factors associated with community variation in family conflict levels. Thirty-three percent of Australian children in 2006 were exposed to levels of family conflict that are likely to increase their future risk for depression. Significant community correlates for elevated family conflict included Indigenous Australian identification, socioeconomic disadvantage, urban and state location, maternal absence and paternal unemployment. The analysis provides indicators for targeting family-level mental health promotion programs.

Prevention of common mental disorders: what can we learn from those who have gone before and where do we go next?

Objective:

Using social network analysis to identify key child care center staff for obesity prevention interventions: a pilot study

Introduction. Interest has grown in how systems thinking could be used in obesity prevention. Relationships between key actors, represented by social networks, are an important focus for considering intervention in systems. Method. Two long day care centers were selected in which previous obesity prevention programs had been implemented. Measures showed ways in which physical activity and dietary policy are conversations and actions transacted through social networks (interrelationships) within centers, via an eight item closed-ended social network questionnaire. Questionnaire data were collected from (17/20; response rate 85%) long day care center staff. Social network density and centrality statistics were calculated, using UCINET social network software, to examine the role of networks in obesity prevention. Results. “Degree” (influence) and “betweeness” (gatekeeper) centrality measures of staff inter-relationships about physical activity, dietary, and policy information identified key players in each center. Network density was similar and high on some relationship networks in both centers but markedly different in others, suggesting that the network tool identified unique center social dynamics. These differences could potentially be the focus of future team capacity building. Conclusion. Social network analysis is a feasible and useful method to identify existing obesity prevention networks and key personnel in long day care centers.

Can social dancing prevent falls in older adults? a protocol of the Dance, Aging, Cognition,Economics (DAnCE) fall prevention randomised controlled trial

Background:  Falls are one of the most common health problems among older people and pose a major economic burden on health care systems. Exercise is an accepted stand-alone fall prevention strategy particularly if it is balance training or regular participation in Tai chi. Dance shares the ‘holistic’ approach of practices such as Tai chi. It is a complex sensorimotor rhythmic activity integrating multiple physical, cognitive and social elements. Small-scale randomised controlled trials have indicated that diverse dance styles can improve measures of balance and mobility in older people, but none of these studies has examined the effect of dance on falls or cognition. This study aims to determine whether participation in social dancing: i) reduces the number of falls; and ii) improves cognitive functions associated with fall risk in older people.

Methods/design: A single-blind, cluster randomised controlled trial of 12 months duration will be conducted. Approximately 450 participants will be recruited from 24 self-care retirement villages that house at least 60 residents each in Sydney, Australia. Village residents without cognitive impairment and obtain medical clearance will be eligible. After comprehensive baseline measurements including physiological and cognitive tests and self-completed questionnaires, villages will be randomised to intervention sites (ballroom or folk dance) or to a wait-listed control using a computer randomisation method that minimises imbalances between villages based on two baseline fall risk measures. Main outcome measures are falls, prospectively measured, and the Trail Making cognitive function test. Cost-effectiveness and cost-utility analyses will be performed.

Discussion: This study offers a novel approach to balance training for older people. As a community-based approach to fall prevention, dance offers older people an opportunity for greater social engagement, thereby making a major contribution to healthy ageing. Providing diversity in exercise programs targeting seniors recognises the heterogeneity of multicultural populations and may further increase the number of taking part in exercise.

Socioeconomic status and quality of life in population-based Australian men: data from the Geelong Osteoporosis Study

Objective : To investigate the relationship between socioeconomic status (SES) and reported perceptions of quality of life (QOL) in a cross-sectional population-based analysis of a representative sample of Australian men.

Associations between measures of adiposity over 10 years and patella cartilage in population-based asymptomatic women

Objective: Osteoarthritis (OA) most commonly affects the patellofemoral compartment of the knee, and is a major cause of pain and disability. Structural changes that evolve prior to the onset of symptoms can be visualised using magnetic resonance imaging (MRI). There is little known information about the role of adiposity on the early structural changes in the patella cartilage in younger, asymptomatic adult females.

Methods: One hundred and sixty asymptomatic women (20–49 years) participating in the Geelong Osteoporosis Study underwent knee MRI (2006–8). Weight and body mass index (BMI) were measured 10 years prior (1994–7, baseline) and at the time of MRI (current), with change over the period calculated (current–baseline). Relationships between measures of adiposity and patella cartilage volume and defects were examined.

Results: After adjustment for age and patella bone volume, there was a reduction of 13 ml (95% confidence interval (95% CI), −25.7, −0.55) in patella cartilage volume for every 1 unit increase in current BMI, and a reduction of 27 ml (95% CI −52.6, −1.5) per BMI unit increase over 10 years (P=0.04 for both). No significant association was observed between baseline BMI and patella cartilage volume (P=0.16). Increased baseline and current weight and BMI were associated with increased prevalence of patella cartilage defects (all P<0.001).

Conclusions: Adiposity and weight gain during midlife are associated with detrimental structural change at the patella in young to middle-aged healthy non-osteoarthritic women. Maintaining a healthy weight and avoiding weight gain in younger asymptomatic women may be important in the prevention of patellofemoral OA.

Malware detection and prevention in RFID systems

The threat that malware poses to RFID systems was identified only recently. Fortunately, all currently known RFID malware is based on SQLIA. Therefore, in this chapter we propose a dual pronged, tag based SQLIA detection and prevention method optimized for RFID systems. The first technique is a SQL query matching approach that uses simple string comparisons and provides strong security against a majority of the SQLIA types possible on RFID systems. To provide security against second order SQLIA, which is a major gap in the current literature, we also propose a tag data validation and sanitization technique. The preliminary evaluation of our query matching technique is very promising, showing 100% detection rates and 0% false positives for all attacks other than second order injection.