229 resultados para MASLOV INDEX


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The Australian Unity Wellbeing Index monitors the subjective wellbeing of the Australian population. Our first survey was conducted in April 2001 and this report concerns the 30th survey, undertaken in August 2013. Our previous survey had been conducted four months earlier in April. This intervening period corresponded to the 6th year of the Labor Government, elected in November 2007. Shortly after data collection, on 7th September, an election took place at which Labor lost to the Liberal Party Coalition.
The share market had been stable for a couple of years, at a level well below its peak before the financial crisis. However, unemployment remained at about 5% and for those people with jobs, many were better-off financially due to cuts in interest rates, and so, in mortgage repayments.
Each survey involves a telephone interview with a new sample of 2,000 Australians, selected to represent the geographic distribution of the national population. These surveys comprise the Personal Wellbeing Index, which measures people’s satisfaction with their own lives, and the National Wellbeing Index, which measures how satisfied people are with life in Australia. Other items include a standard set of demographic questions and other survey-specific questions. The specific topics for Survey 30 are social media, personal achievement, and work conditions.

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Objective
Emerging evidence suggests that psychosocial stress may influence weight gain. The relationship between stress and weight change and whether this was influenced by demographic and behavioral factors was explored.

Design and Methods
A total of 5,118 participants of AusDiab were prospectively followed from 2000 to 2005. The relationship between stress at baseline and BMI change was assessed using linear regression.

Results
Among those who maintained/gained weight, individuals with high levels of perceived stress at baseline experienced a 0.20 kg/m2 (95% CI: 0.07-0.33) greater mean change in BMI compared with those with low stress. Additionally, individuals who experienced 2 or ≥3 stressful life events had a 0.13 kg/m2 (0.00-0.26) and 0.26 kg/m2 (0.14-0.38) greater increase in BMI compared with people with none. These relationships differed by age, smoking, and baseline BMI. Further, those with multiple sources of stressors were at the greatest risk of weight gain.

Conclusion
Psychosocial stress, including both perceived stress and life events stress, was positively associated with weight gain but not weight loss. These associations varied by age, smoking, obesity, and multiple sources of stressors. Future treatment and interventions for overweight and obese people should consider the psychosocial factors that may influence weight gain.

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Background The aim of the study was to examine the relationship between psychosocial and other working conditions and body-mass index (BMI) in a working population. This study contributes to the approximately dozen investigations of job stress, which have demonstrated mixed positive and negative results in relation to obesity, overweight and BMI. Methods A cross-sectional population-based survey was conducted among working Australians in the state of Victoria. Participants were contacted by telephone from a random sample of phone book listings. Information on body mass index was self-reported as were psychosocial work conditions assessed using the demand/control and effort/reward imbalance models. Other working conditions measured included working hours, shift work, and physical demand. Separate linear regression analyses were undertaken for males and females, with adjustment for potential confounders. Results A total of 1101 interviews (526 men and 575 women) were completed. Multivariate models (adjusted for socio-demographics) demonstrated no associations between job strain, as measured using the demand/control model, or ERI using the effort/reward imbalance model (after further adjustment for over commitment) and BMI among men and women. Multivariate models demonstrated a negative association between low reward and BMI among women. Among men, multivariate models demonstrated positive associations between high effort, high psychological demand, long working hours and BMI and a negative association between high physical demand and BMI. After controlling for the effort/reward imbalance or the demand/control model, the association between physical demand and working longer hours and BMI remained. Conclusion Among men and women the were differing patterns of both exposures to psychosocial working conditions and associations with BMI. Among men, working long hours was positively associated with higher BMI and this association was partly independent of job stress. Among men physical demand was negatively associated with BMI and this association was independent of job stress.

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This study aimed to (1) determine preliminary validity of the Developmental Behaviour Checklist-Hyperactivity Index (DBC-HI) as a screening measure of combined-type ADHD in autism and ADHD, and (2) compare emotional-behavioural disturbance using the DBC in autism, ADHD and autism + ADHD. Forty-nine age- and PIQ-matched young people [6-18 years; 12 autism, 13 ADHD, 12 autism + ADHD, 12 typically developing] were recruited. Parents completed the Conners-Revised Rating Scale and DBC. The DBC-HI displayed strong internal consistency and good external validity, reliably measuring combined-type ADHD. The DBC-HI distinguished autism from autism + ADHD with fair sensitivity and specificity. Individuals with autism + ADHD exhibited a more severe profile of emotional-behavioural disturbance than autism or ADHD alone. The DBC may be a useful 'all-in-one' screening tool to (1) identify comorbidity and (2) determine the severity of emotional-behavioural disturbance in autism and/or ADHD. © 2014 Elsevier Ltd.

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To investigate the effect of low glycemic index (LGI) carbohydrate meal on subjective, metabolic and physiological responses, and endurance performance in the Ramadan fasted state.

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There is a robust comorbidity between mood disorders and cardiovascular disorder (CVD). The atherogenic index of plasma (AIP) and the atherogenic coefficient (AC) are important atherogenic indexes. The aims of this study were to delineate whether AIP and AC are increased in mood disorders especially when comorbid with tobacco use disorder (TUD).

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BACKGROUND: Physical activity (PA) has been consistently implicated in the etiology of obesity, whereas recent evidence on the importance of sedentary time remains inconsistent. Understanding of dose-response associations of PA and sedentary time with overweight and obesity in adults can be improved with large-scale studies using objective measures of PA and sedentary time. The purpose of this study was to examine the strength, direction and shape of dose-response associations of accelerometer-based PA and sedentary time with body mass index (BMI) and weight status in 10 countries, and the moderating effects of study site and gender. METHODS: Data from the International Physical activity and the Environment Network (IPEN) Adult study were used. IPEN Adult is an observational multi-country cross-sectional study, and 12 sites in 10 countries are included. Participants wore an accelerometer for seven consecutive days, completed a socio-demographic questionnaire and reported height and weight. In total, 5712 adults (18-65 years) were included in the analyses. Generalized additive mixed models, conducted in R, were used to estimate the strength and shape of the associations. RESULTS: A curvilinear relationship of accelerometer-based moderate-to-vigorous PA and total counts per minute with BMI and the probability of being overweight/obese was identified. The associations were negative, but weakened at higher levels of moderate-to-vigorous PA (>50 min per day) and higher counts per minute. No associations between sedentary time and weight outcomes were found. Complex site- and gender-specific findings were revealed for BMI, but not for weight status. CONCLUSIONS: On the basis of these results, the current Institute of Medicine recommendation of 60 min per day of moderate-to-vigorous PA to prevent weight gain in normal-weight adults was supported. No relationship between sedentary time and the weight outcomes was present, calling for further examination. If moderator findings are confirmed, the relationship between PA and BMI may be country- and gender-dependent, which could have important implications for country-specific health guidelines. © 2015 Macmillan Publishers Limited All rights reserved.

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Bipolar disorder (BD) is a serious and recurring condition that affects approximately 2.4% of the global population. About half of BD sufferers have an illness course characterized by either a manic or a depressive predominance. This predominant polarity in BD may be differentially associated with several clinical correlates. The concept of a polarity index (PI) has been recently proposed as an index of the antimanic versus antidepressive efficacy of various maintenance treatments for BD. Notwithstanding its potential clinical utility, predominant polarity was not included in the DSM-5 as a BD course specifier.

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BackgroundWe have previously demonstrated that between the years 1980 and 2000, the mean body mass index (BMI) of the urban Australian population increased, with greater increases observed with increasing BMI. The current study aimed to quantify trends over time in BMI according to education between 1980 and 2007.MethodsWe compared data from the 1980, 1983 and 1989 National Heart Foundation Risk Factor Prevalence Studies, 1995 National Nutrition Survey, 2000 Australian Diabetes, Obesity and Lifestyle Study and the 2007 National Health Survey. For survey comparability, analyses were restricted to urban Australian residents aged 25-64 years. BMI was calculated from measured height and weight. The education variable was dichotomised at completion of secondary school. Four age-standardised BMI indicators were compared over time by sex and education: mean BMI, mean BMI of the top five percent of the BMI distribution, prevalence of obesity (BMI⩾30 kg/m(2)), prevalence of class II(+) obesity (BMI⩾35 kg/m(2)).ResultsBetween 1980 and 2007, the mean BMI among men increased by 2.5 kg/m(2) and 1.7 kg/m(2) for those with low and high education levels, respectively, corresponding to increases in obesity prevalence of 20(from 12% to 32%) and 11(10% to 21%) %-points. Among women mean BMI increased by 2.9 kg/m(2) and 2.4 kg/m(2) for those with low and high education levels respectively, corresponding to increases in obesity prevalence of 16(12% to 28%) and 12(7% to 19%) %-points. The prevalence of class II(+) obesity among men increased by 9(1% to 10%) and 4(1% to 5%) %-points for those with low and high education levels, and among women increased by 8(4% to 12%) and 4(2% to 6%) %-points. Absolute and relative differences between education groups generally increased over time.ConclusionsEducational differences in BMI have persisted among urban Australian adults since 1980 without improvement. Obesity prevention policies will need to be effective in those with greatest socio-economic disadvantage if we are to equitably and effectively address the population burden of obesity and its corollaries.International Journal of Obesity accepted article preview online, 16 March 2015. doi:10.1038/ijo.2015.27.

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A search in the literature reveals that mathematical conditions (usually sufficient conditions) for the Fuzzy Inference System (FIS) models to satisfy the monotonicity property have been developed. A monotonically-ordered fuzzy rule base is important to maintain the monotonicity property of an FIS. However, it may difficult to obtain a monotonically-ordered fuzzy rule base in practice. We have previously introduced the idea of fuzzy rule relabeling to tackle this problem. In this paper, we further propose a monotonicity index for the FIS system, which serves as a metric to indicate the degree of a fuzzy rule base fulfilling the monotonicity property. The index is useful to provide an indication whether a fuzzy rule base should (or should not) be used in practice, even with fuzzy rule relabeling. To illustrate the idea, the zero-order Sugeno FIS model is exemplified. We add noise as errors into the fuzzy rule base to formulate a set of non-monotone fuzzy rules. As such, the metric also acts as a measure of noise in the fuzzy rule base. The results show that the proposed metric is useful to indicate the degree of a fuzzy rule base fulfilling the monotonicity property.