Preventing obesity in infants: the growing healthy feasibility trial protocol

INTRODUCTION: Early childhood is an important period for establishing behaviours that will affect weight gain and health across the life course. Early feeding choices, including breast and/or formula, timing of introduction of solids, physical activity and electronic media use among infants and young children are considered likely determinants of childhood obesity. Parents play a primary role in shaping these behaviours through parental modelling, feeding styles, and the food and physical activity environments provided. Children from low socio-economic backgrounds have higher rates of obesity, making early intervention particularly important. However, such families are often more difficult to reach and may be less likely to participate in traditional programs that support healthy behaviours. Parents across all socio-demographic groups frequently access primary health care (PHC) services, including nurses in community health services and general medical practices, providing unparalleled opportunity for engagement to influence family behaviours. One emerging and promising area that might maximise engagement at a low cost is the provision of support for healthy parenting through electronic media such as the Internet or smart phones. The Growing healthy study explores the feasibility of delivering such support via primary health care services.

METHODS: This paper describes the Growing healthy study, a non-randomised quasi experimental study examining the feasibility of an intervention delivered via a smartphone app (or website) for parents living in socioeconomically disadvantaged areas, for promoting infant feeding and parenting behaviours that promote healthy rather than excessive weight gain. Participants will be recruited via their primary health care practitioner and followed until their infant is 9 months old. Data will be collected via web-based questionnaires and the data collected inherently by the app itself.

ETHICS AND DISSEMINATION: This study received approval from the University of Technology Sydney Ethics committee and will be disseminated via peer-reviewed publications and conference presentations.

How calls from carers, friends and family members of someone affected by cancer differ from those made by people diagnosed with cancer; analysis of 4 years of South Australian Cancer Council Helpline data

PURPOSE: The purpose of this study is to determine how people diagnosed with cancer who call the Cancer Council Helpline in South Australia differ from carers/family/friends (caregivers) who call. METHOD: Descriptive, retrospective audit of calls from people who contacted Cancer Council Helpline in South Australia between 16 April 2009 and 16 April 2013 who were diagnosed with cancer (n = 5766) or were the caregivers (n = 5174) of a person with cancer. RESULTS: Caregivers were more likely to be female (p < 0.001); younger in age (p < 0.001); call regarding cancer that was metastasised/widespread/advanced, terminal or at an unknown stage (p < 0.001) and phone requesting general cancer information or emotional support (p < 0.001). This group was more distressed (p < 0.001) but less likely (p = 0.02) to be offered and/or accept referrals to counselling than people diagnosed with cancer who called. Follow-up care was required by 63.5 % of caregivers and 73.1 % of people with cancer according to distress management guidelines; 8.5 and 15.3 %, respectively, accepted referrals to internal services. The most frequently discussed topic for both groups was emotional/psychological concerns. There were no differences in remoteness of residence or call length between groups. CONCLUSIONS: Caregivers represented different demographic groups than people diagnosed with cancer who called this helpline. The two groups phoned for different issues, at different stages of disease progression, displayed different levels of distress and, therefore, may benefit from services being tailored to meet their unique needs. These results also demonstrate the capacity of helplines to complement other health services and confirm that callers to cancer helplines exhibit high levels of distress.

It's not just the television: survey analysis of sedentary behaviour in New Zealand young people

BACKGROUND: Sedentary behaviour has been linked with adverse health outcomes in young people; however, the nature and context of being sedentary is poorly understood. Accurate quantification and description of sedentary behaviour using population-level data is required. The aim of this research was to describe sedentary behaviour among New Zealand (NZ) youth and examine whether sedentary behaviour differs by Body Mass Index (BMI) status in this population.

METHODS: A national representative cross-sectional survey of young people aged 5-24 years (n = 2,503) was conducted in 2008-2009. Data from this survey, which included subjectively (recall diary; n = 1,309) and objectively (accelerometry; n = 960) measured sedentary behaviour for participants aged 10-18 years were analysed using survey weighted methods.

RESULTS: Participants self-reported spending on average 521 minutes per day (standard error [SE] 5.29) in total sedentary behaviour, 181 minutes per day (SE 3.91) in screen-based sedentary activities (e.g., television and video games), and 340 minutes per day (SE 5.22) in other non-screen sedentary behaviours (e.g., school, passive transport and self-care). Accelerometer-measured total sedentary behaviour was on average 420 minutes per day (SE 4.26), or 53% (SE 0.42%) of monitored time. There were no statistically significant differences in time spent in sedentary behaviour among overweight, obese and healthy/underweight young people.

CONCLUSIONS: Both subjective and objective methods indicate that NZ youth spend much of their waking time being sedentary. No relationships were found between sedentary behaviour and BMI status. These findings extend previous research by describing engagement in specific sedentary activities, as well as quantifying the behaviour using an objective method. Differences in what aspects of sedentary behaviour the two methods are capturing are discussed. This research highlights the potential for future interventions to target specific sedentary behaviours or demographic groups.

Special report : the wellbeing of Australians : groups with the highest and lowest wellbeing in Australia

Overview and Aim
1. This report concerns an analysis of the cumulative data from 15 surveys using the Personal Wellbeing Index to measure Subjective Wellbeing. The total number of respondents is about 30,000 but not all data were available for all analyses due to changing variables between
surveys.
2. The aim of this analysis is to determine those sub-groups with the highest and the lowest wellbeing.
Method
3. The definition of sub-groups is through the demographic variables of Income, Gender, Age, Household Composition, Relationship Status and Employment Status. Index domains are also included. While not every combination of demographic variables has been tested, the total number of combinations analysed was 3,277.
4. Extreme group mean scores are defined as lying above 79 points and below 70 points. These values are at least five standard deviations beyond the total sample mean score and are, therefore, extreme outliers. The minimum number of responses that could form such a group is
one. Data are accumulated across surveys for corresponding groups.
Results
5. The initial search for the most extreme groups identified the 20 highest and the 20 lowest groups with a minimum N=10. These are termed the ‘Exclusive’ groups since they were based only on the previously identified extreme scores. In order to determine the true mean of each of these groups, a further analysis incorporated all respondents who met the definition of group membership. For example, an Exclusive group defined as [male, 76+ years] would contain only the accumulation of scores from individual surveys that met the extreme score criterion (<70 or >79). The Inclusive group included the scores from all survey respondents who matched the group definition of male, 76+ years.
6. The results revealed a dominance by the domains of the Personal Wellbeing Index. The extreme high groups were predicted by high scores on all domains except safety and relationships. The low groups were defined by low scores on all seven domains.
7. A further search for extreme groups was undertaken that was restricted to the demographic descriptors. The 20 highest and 20 lowest groups were identified based on a minimum cell content of N=10. The corresponding Inclusive group means were then calculated as before.
8. In order to increase the reliability of the final groups, a minimum cell content of N=20 cases was imposed.
9. Six extreme high groups were identified. These are dominated by high income and the presence of a partner. Five extreme low groups were identified. These are dominated by very low income, the absence of a partner, and unemployment.
Conclusions
10. The conclusions drawn from these analyses are as follows:
10.1 The central defining characteristics of people forming the extreme high wellbeing groups is high household income and living with a partner.
10.2 The central defining risk factors for people forming the extreme low wellbeing groups are very low household income, not living with a partner, and unemployment.
10.3 None of these five demographic characteristics are sufficient to define extreme wellbeing groups on their own. They all act in combinations of at least two risk factors together.

Socio-demographic constraints to travel behavior

Purpose – This study aims to ascertain the effect of socio-demographic constraints on dimension of travel choice. This study also seeks to derive personal ecological explanations for variation in travel preference, travel intention and travel choice behavior of a wide range of destinations.

Design/methodology/approach – A large representative sample of 49,105 Australian respondents is utilized. Binary logistic regression is used to determine the impact of constraint variables.

Findings – Age, income and life stage have significant differential and interactive effects on travel behavior. Socio-demographic variables act in different ways to constrain/free different types of travel behavior. However there are significant levels of travel by even the most constrained groups as well as significant amounts of non-travel by the least constrained sectors of our society. These impacts are country specific.

Research limitations/implications – The travel motivations of constraint groups need to be considered to order better understand travel behavior. Investigation of psychological and ecological facilitators and constraints to travel is needed.

Practical implications – This information is most useful for market segmentation and the development of constraint group destination marketing plans. Managers can use utilize such results to minimize the barriers to travel by particular groups.

Originality/value – This paper utilizes a large database to provide insights into the personal ecological constraints to travel.

A practitioner's report on the interactive effects of socio-demographic barriers to travel

Researchers have viewed constraints as a subset of reasons for not engaging in a particular behavior. This study investigates the impact of two-way interactions between age, income, and life stage (forming groups of more and less constrained respondents) on dependent variables comprising intentions held by Australian residents to travel intrastate, interstate or overseas for a vacation. A representative sample of 49,105 Australian respondents is utilized. Binary logistic regression is used to profile respondents who intend to take a domestic or an overseas holiday of more than three days duration. This paper finds that the interactions between the constraint variables of age, income and life stage are important in explaining travel preferences. Constraint groups are then formed by combining the important constraint variables. There are significant levels of vacation travel by even the most constrained groups as well as significant amounts of non-travel by the least constrained sectors of our society. Marketing insights and recommendations are provided for the most constrained travel group and the least constrained travel group.

Role of age, sex, and obesity in the higher prevalence of arthritis among lower socioeconomic groups: a population-based survey

Objective: To compare the prevalence of arthritis among population groups based on demographic, socioeconomic, and body mass index (BMI) characteristics; to investigate the combined influence of these factors on arthritis; and to assess the relationship between self-reported health and psychological distress and arthritis.

Methods: Data from the Victorian Population Health Survey (n = 7,500) were used in the study. Psychological distress was assessed using the Kessler Psychological Distress scale, and self-reported health was assessed by a single item. Multiple logistic regression was used to investigate the combined influence of demographic and socioeconomic factors and BMI on arthritis.

Results: Overall, 23% of Victorian adults (20% men and 26% women) reported having arthritis. The presence of arthritis was associated with high psychological distress (odds ratio [OR] 1.2; 95% confidence interval [95% CI] 1.1-1.4) and poor self-reported health (OR 1.9; 95% CI 1.7-2.1). Increased prevalence of arthritis was found in older age groups, lower education and income groups, and in people who were overweight or obese. Women had higher risk of arthritis, even after adjustment for age, residence, education, occupation, income, and BMI. Age and BMI independently predicted arthritis for men and women. For men, higher risk of arthritis was also associated with lower income.

Conclusion: Arthritis is a highly prevalent condition associated with poor health and high psychological distress. Prevalence of arthritis is disproportionately high among women and individuals from lower socioeconomic backgrounds. As the prevalence of arthritis is predicted to increase, careful consideration of causal factors, and setting priorities for resource allocation for the treatment and prevention of arthritis are required.

Clinical and demographic differences between sexually violent predators and other commitment types in a state forensic hospital

Sexual offenders who are involuntarily civilly committed to a secure state hospital as Sexually Violent Predators (SVPs) appear to differ significantly from other current patient populations. Demographically, SVPs are older and more predominantly Caucasian than other patients. They are less frequently psychotic than patients committed under other state statutes such as those found incompetent to stand trial, not guilty by reason of insanity and mentally ill prison transfers. Another salient dimension which distinguishes SVPs is the degree of psychopathy observed in these patients. As a group, SVPs display only slightly higher levels of psychopathy than other patient groups as measured by the revised Psychopathy Checklist. Yet when considered by offender type, rapists are found to have significantly higher average psychopathy scores than other patients, while child molesters are assessed as having lower average psychopathy scores than most other patient commitment categories.