Prospective study of individual, social, and environmental predictors of physical activity: women's leisure running

Background: Understanding and influencing the determinants of physical activity is an important public health challenge. We used prospective data to examine the influence of individual, social, and environmental factors on physical activity behaviour, using regular running as the behavioural model. Methods: Over 500 middle-aged women completed two consecutive questionnaires in 2000 and 2002. Logistic regression analyses were used to examine factors predicting adoption of and regression from regular leisure-time running during the follow-up. Results: Women who frequently used behavioural change skills were more likely to adopt regular running (OR=4.0, CI=1.7-9.5). There was an interaction between the enjoyment of running and family support: those who rated enjoyment of running high and reported high family support were less likely to adopt running (OR= 0.2, CI = 0.1-0.5). Women who reported infrequent use of motives were more likely (OR = 3.3, CI = 1.6-6.9) to regress from regular running. There was an interaction between perceived health and the neighbourhood environment: those who perceived themselves to be in poor health and had an unattractive neighbourhood were more likely (OR = 2.7, CI = 0.9-8.3) to regress from regular running. Conclusions: Behavioural skills and enjoyment may be of particular importance for the adoption of regular activity; social support and an aesthetically attractive neighbourhood are likely to have a key role in encouraging maintenance. (c) 2004 Elsevier Ltd. All rights reserved.

Modeling the age of tropical moist forest fragments in heavily-cleared lowland landscapes of Colombia

Increasingly, large areas of native tropical forests are being transformed into a mosaic of human dominated land uses with scattered mature remnants and secondary forests. In general, at the end of the land clearing process, the landscape will have two forest components: a stable component of surviving mature forests, and a dynamic component of secondary forests of different ages. As the proportion of mature forests continues to decline, secondary forests play an increasing role in the conservation and restoration of biodiversity. This paper aims to predict and explain spatial and temporal patterns in the age of remnant mature and secondary forests in lowland Colombian landscapes. We analyse the age distributions of forest fragments, using detailed temporal land cover data derived from aerial photographs. Ordinal logistic regression analysis was applied to model the spatial dynamics of mature and secondary forest patches. In particular, the effect of soil fertility, accessibility and auto-correlated neighbourhood terms on forest age and time of isolation of remnant patches was assessed. In heavily transformed landscapes, forests account for approximately 8% of the total landscape area, of which three quarters are comprised of secondary forests. Secondary forest growth adjacent to mature forest patches increases mean patch size and core area, and therefore plays an important ecological role in maintaining landscape structure. The regression models show that forest age is positively associated with the amount of neighbouring forest, and negatively associated with the amount of neighbouring secondary vegetation, so the older the forest is the less secondary vegetation there is adjacent to it. Accessibility and soil fertility also have a negative but variable influence on the age of forest remnants. The probability of future clearing if current conditions hold is higher for regenerated than mature forests. The challenge of biodiversity conservation and restoration in dynamic and spatially heterogeneous landscape mosaics composed of mature and secondary forests is discussed. (c) 2004 Elsevier B.V. All rights reserved.

Development and evaluation of a youth mental health community awareness campaign - The Compass Strategy

Background: Early detection and treatment of mental disorders in adolescents and young adults can lead to better health outcomes. Mental health literacy is a key to early recognition and help seeking. Whilst a number of population health initiatives have attempted to improve mental health literacy, none to date have specifically targeted young people nor have they applied the rigorous standards of population health models now accepted as best practice in other health areas. This paper describes the outcomes from the application of a health promotion model to the development, implementation and evaluation of a community awareness campaign designed to improve mental health literacy and early help seeking amongst young people. Method: The Compass Strategy was implemented in the western metropolitan Melbourne and Barwon regions of Victoria, Australia. The Precede-Proceed Model guided the population assessment, campaign strategy development and evaluation. The campaign included the use of multimedia, a website, and an information telephone service. Multiple levels of evaluation were conducted. This included a cross-sectional telephone survey of mental health literacy undertaken before and after 14 months of the campaign using a quasi-experimental design. Randomly selected independent samples of 600 young people aged 12 - 25 years from the experimental region and another 600 from a comparison region were interviewed at each time point. A series of binary logistic regression analyses were used to measure the association between a range of campaign outcome variables and the predictor variables of region and time. Results: The program was judged to have an impact on the following variables, as indicated by significant region-by-time interaction effects ( p < 0.05): awareness of mental health campaigns, self-identified depression, help for depression sought in the previous year, correct estimate of prevalence of mental health problems, increased awareness of suicide risk, and a reduction in perceived barriers to help seeking. These effects may be underestimated because media distribution error resulted in a small amount of print material leaking into the comparison region. Conclusion: We believe this is the first study to apply the rigorous standards of a health promotion model including the use of a control region to a mental health population intervention. The program achieved many of its aims despite the relatively short duration and moderate intensity of the campaign.

Disorders of breathing and continence have a stronger association with back pain than obesity and physical activity

Although obesity and physical activity have been argued to predict back pain, these factors are also related to incontinence and breathing difficulties. Breathing and continence mechanisms may interfere with the physiology of spinal control, and may provide a link to back pain. The aim of this study was to establish the association between back pain and disorders of continence and respiration in women. We conducted a cross-sectional analysis of self-report, postal survey data from the Australian Longitudinal Study on Women's Health. We used multinomial logistic regression to model four levels of back pain in relation to both the traditional risk factors of body mass index and activity level, and the potential risk factors of incontinence, breathing difficulties, and allergy. A total of 38 050 women were included from three age-cohorts. When incontinence and breathing difficulties were considered, obesity and physical activity were not consistently associated with back pain. In contrast, odds ratios (OR) for often having back pain were higher for women often having incontinence compared to women without incontinence (OR were 2.5, 2.3 and 2.3 for young, mid-age! and older women, respectively). Similarly, mid-aged and older women had higher odds of having back pain often when they experienced breathing difficulties often compared to women with no breathing problems (OR of 2.0 and 1.9, respectively). Unlike obesity and physical activity, disorders of continence and respiration were strongly related to frequent back pain. This relationship may be explained by physiological limitations of co-ordination of postural, respiratory and continence functions of trunk muscles.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Regional patterns of agricultural land use and deforestation in Colombia

An expanding human population and associated demands for goods and services continues to exert an increasing pressure on ecological systems. Although the rate of expansion of agricultural lands has slowed since 1960, rapid deforestation still occurs in many tropical countries, including Colombia. However, the location and extent of deforestation and associated ecological impacts within tropical countries is often not well known. The primary aim of this study was to obtain an understanding of the spatial patterns of forest conversion for agricultural land uses in Colombia. We modeled native forest conversion in Colombia at regional and national-levels using logistic regression and classification trees. We investigated the impact of ignoring the regional variability of model parameters, and identified biophysical and socioeconomic factors that best explain the current spatial pattern and inter-regional variation in forest cover. We validated our predictions for the Amazon region using MODIS satellite imagery. The regional-level classification tree that accounted for regional heterogeneity had the greatest discrimination ability. Factors related to accessibility (distance to roads and towns) were related to the presence of forest cover, although this relationship varied regionally. In order to identify areas with a high risk of deforestation, we used predictions from the best model, refined by areas with rural population growth rates of > 2%. We ranked forest ecosystem types in terms of levels of threat of conversion. Our results provide useful inputs to planning for biodiversity conservation in Colombia, by identifying areas and ecosystem types that are vulnerable to deforestation. Several of the predicted deforestation hotspots coincide with areas that are outstanding in terms of biodiversity value.

Subtypes of Illicit Drug Users: A Latent Class Analysis of Data From an Australian Twin Sample

This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a 'self-medicating' subgroup is needed.

Testing alternative models for the conservation of koalas in fragmented rural-urban landscapes

Predicting the various responses of different species to changes in landscape structure is a formidable challenge to landscape ecology. Based on expert knowledge and landscape ecological theory, we develop five competing a priori models for predicting the presence/absence of the Koala (Phascolarctos cinereus) in Noosa Shire, south-east Queensland (Australia). A priori predictions were nested within three levels of ecological organization: in situ (site level) habitat (< 1 ha), patch level (100 ha) and landscape level (100-1000 ha). To test the models, Koala surveys and habitat surveys (n = 245) were conducted across the habitat mosaic. After taking into account tree species preferences, the patch and landscape context, and the neighbourhood effect of adjacent present sites, we applied logistic regression and hierarchical partitioning analyses to rank the alternative models and the explanatory variables. The strongest support was for a multilevel model, with Koala presence best predicted by the proportion of the landscape occupied by high quality habitat, the neighbourhood effect, the mean nearest neighbour distance between forest patches, the density of forest patches and the density of sealed roads. When tested against independent data (n = 105) using a receiver operator characteristic curve, the multilevel model performed moderately well. The study is consistent with recent assertions that habitat loss is the major driver of population decline, however, landscape configuration and roads have an important effect that needs to be incorporated into Koala conservation strategies.

The importance of forest area and configuration relative to local habitat factors for conserving forest mammals: A case study of koalas in Queensland, Australia

The loss and fragmentation of forest habitats by human land use are recognised as important factors influencing the decline of forest-dependent fauna. Mammal species that are dependent upon forest habitats are particularly sensitive to habitat loss and fragmentation because they have highly specific habitat requirements, and in many cases have limited ability to move through and utilise the land use matrix. We addressed this problem using a case study of the koala (Phascolarctos cinereus) surveyed in a fragmented rural-urban landscape in southeast Queensland, Australia. We applied a logistic modelling and hierarchical partitioning analysis to determine the importance of forest area and its configuration relative to site (local) and patch-level habitat variables. After taking into account spatial auto-correlation and the year of survey, we found koala occurrence increased with the area of all forest habitats, habitat patch size and the proportion of primary Eucalyptus tree species; and decreased with mean nearest neighbour distance between forest patches, the density of forest patches, and the density of sealed roads. The difference between the effect of habitat area and configuration was not as strong as theory predicts, with the configuration of remnant forest becoming increasingly important as the area of forest habitat declines. We conclude that the area of forest, its configuration across the landscape, as well as the land use matrix, are important determinants of koala occurrence, and that habitat configuration should not be overlooked in the conservation of forest-dependent mammals, such as the koala. We highlight the implications of these findings for koala conservation. (c) 2006 Elsevier Ltd. All rights reserved.

Modelling the conversion of Colombian lowland ecosystems since 1940: Drivers, patterns and rates

In biologically mega-diverse countries that are undergoing rapid human landscape transformation, it is important to understand and model the patterns of land cover change. This problem is particularly acute in Colombia, where lowland forests are being rapidly cleared for cropping and ranching. We apply a conceptual model with a nested set of a priori predictions to analyse the spatial and temporal patterns of land cover change for six 50-100 km(2) case study areas in lowland ecosystems of Colombia. Our analysis included soil fertility, a cost-distance function, and neighbourhood of forest and secondary vegetation cover as independent variables. Deforestation and forest regrowth are tested using logistic regression analysis and an information criterion approach to rank the models and predictor variables. The results show that: (a) overall the process of deforestation is better predicted by the full model containing all variables, while for regrowth the model containing only the auto-correlated neighbourhood terms is a better predictor; (b) overall consistent patterns emerge, although there are variations across regions and time; and (c) during the transformation process, both the order of importance and significance of the drivers change. Forest cover follows a consistent logistic decline pattern across regions, with introduced pastures being the major replacement land cover type. Forest stabilizes at 2-10% of the original cover, with an average patch size of 15.4 (+/- 9.2) ha. We discuss the implications of the observed patterns and rates of land cover change for conservation planning in countries with high rates of deforestation. (c) 2005 Elsevier Ltd. All rights reserved.

Interaction of psychosocial risk factors explain increased neck problems among female office workers

This study investigated the relationship between psychosocial risk factors and (1) neck symptoms and (2) neck pain and disability as measured by the neck disability index (NDI). Female office workers employed in local private and public organizations were invited to participate, with 333 completing a questionnaire. Data were collected on various risk factors including age, negative affectivity, history of previous neck trauma, physical work environment, and task demands. Sixty-one percent of the sample reported neck symptoms lasting greater than 8 days in the last 12 months. The mean NDI of the sample was 15.5 out of 100, indicating mild neck pain and disability. In a hierarchical multivariate logistic regression, low supervisor support was the only psychosocial risk factor identified with the presence of neck symptoms. Similarly, low supervisor support was the only factor associated with the score on the NDI. These associations remained after adjustment for potential confounders of age, negative affectivity, and physical risk factors. The interaction of job demands, decision authority, and supervisor support was significantly associated with the NDI in the final model and this association increased when those with previous trauma were excluded. Interestingly, and somewhat contrary to initial expectations, as job demands increased, high decision authority had an increasing effect on the NDI when supervisor support was low. Crown copyright (c) 2006 Published by Elsevier B.V. All rights reserved.

Predictors of osteoarthritis(OA) improvement in patients treated with Hylan G-F for knee OA.

Aim of study: Different criteria for treatment response were explored to identify predictors of OA improvement. Analyses were based on data from a previously reported 1-year randomized controlled trial of appropriate care with or without hylan G-F 20 in patients with knee OA. Methods: Five definitions of ‘‘patient responder’’ from baseline to month 12 were examined: at least 20% reduction in WOMAC pain score; at least 20% reduction in WOMAC pain score and at least 20% reduction in either the WOMAC stiffness or function score; OARSI responder criteria (Propositions A and B) for intra-articular drugs; and OMERACT-OARSI responder criteria (Proposition D). As an a posteriori analysis, multivariable logistic regression models for each definition of patient responder were developed using a forward selection method. The following variables were defined prior to modeling and considered in the model along with two-way interactions: age (O65 years), BMI, gender, X-ray grade (0, I, II vs III, IV), co-morbidity (1 or 2 conditions vs 3 or more), duration of OA in study knee (years), previous surgery of study knee, hylan G-F 20 injection technique, WOMAC pain, stiffness and function, and treatment group. Results: Hylan G-F 20 was a predictor of improvement for all patient responder definitions P ! 0.001; odds of improvement were 2.7 or higher for patients in the hylan G-F 20 group compared to appropriate care without hylan G-F 20. For three of the five patient responder definitions, X-ray grade was a predictor of improvement (P ! 0.10; lower X-ray grade increased the odds of improvement). For four of the five patient responder definitions, duration of OA was a predictor of improvement (P ! 0.10; shorter duration of OA increased the odds of improvement). Conclusion: Analyses showed that appropriate care with hylan G-F 20 is the dominant predictor of patient improvement. While high grade structural damage does not preclude a response, patients who are targeted early in the disease process when less structural damage has occurred, may have a greater chance of improvement.

The impact of target board recommendations in Australian takeovers

This paper examines the impact of targe board recommendations on the probability of the bid being successful in the Australian takeovers context. Specifically, we model the success rate of the bid as a binary dependent variable and target board recommendations or the board hostility as our key independent variable by using logistic regression framework. Our model also includes bid structures and conditions variables (such as initial bid premium, bid conditions, toehold, and interlocking relationship) and bid events (such as panel and bid duration) as our control variables. Overall, we find board hostility has statistically significant negative effect on the success rate of the bid and almost all control variables (except for the initial bid premium) are statistically significant with the correct sign. That is, we find toehold, the percentage of share required to make the bid becomes successful, and the unconditional bid have positive impact on the success rate of the bid, at least as predictive determinants prior to the release of any hostile recommendation. Consistent with Craswell (2004), we also find the negative relation between interlocking relationship and the success rate of the bid. Our finding supports that from target investors’ point of view, interlock is consistent with the negative story of self interest by directors. Finally, like Walking (1985), we find that the initial bid premium does not have influence on the success rate of the bid. Hence our results reinstate Walking’s bid premium puzzle in Australian context.