BackgroundA self-reported life satisfaction question is routinely used as an indicator of societal well-being. Several studies support that mental illness is an important determinant for life satisfaction and improvement of mental healthcare access therefore could have beneficial effects on a population’s life satisfaction. However, only a few studies report the relationship between subjective mental health and life satisfaction. Subjective mental health is a broader concept than the presence or absence of psychopathology. In this study, we examine the strength of the association between a self-reported mental health question and self-reported life satisfaction, taking into account other relevant factors.MethodsWe conducted this analysis using successive waves of the Canadian Community Health Survey (CCHS) collected between 2003 and 2012. Respondents included more than 400,000 participants aged 12 and over. We extracted information on self-reported mental health, socio-demographic and other factors and examined correlation with self-reported life satisfaction using a proportional ordered logistic regression.ResultsLife satisfaction was strongly associated with self-reported mental health, even after simultaneously considering factors such as income, general health, and gender. The poor-self-reported mental health group had a particularly low life satisfaction. In the fair-self-reported mental health category, the odds of having a higher life satisfaction were 2.35 (95% CI 2.21 to 2.50) times higher than the odds in the poor category. In contrast, for the “between 60,000 CAD and 79,999 CAD” household income category, the odds of having a higher life satisfaction were only 1.96 (95% CI 1.90 to 2.01) times higher than the odds in the “less than 19,999 CAD” category.ConclusionsSubjective mental health contributes highly to life satisfaction, being more strongly associated than other selected previously known factors. Future studies could be useful to deepen our understanding of the interplay between subjective mental health, mental illness and life satisfaction. This may be beneficial for developing public health policies that optimize mental health promotion, illness prevention and treatment of mental disorders to enhance life satisfaction in the general population.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-5235-x) contains supplementary material, which is available to authorized users.

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Summary1. We present an empirical, analytical model that estimates both temperature and seasonal response functions for the growth of wild juvenile fish without the need for costly tank experiments in less realistic conditions. 2. Analysis of monthly recapture data on the lengths and weights of individual wild juvenile fish demonstrates that simple temperature-driven models of growth can be less informative than more realistic, empirical, models. 3. A case study of wild Atlantic salmon parr ( Salmo salar ) showed that: most growth took place in a 10-week period in spring, at temperatures below those that previous published models report as necessary for rapid growth and at faster rates than the maximum that previous models predicted. 4. Temperature and fish size allometry explained 45% of growth variation, but the effects of temperature were significantly and markedly different at different seasons. 5. Seasonal effects explained an additional 18% of the variation and were strongly associated with the abundance of potential 'drift' food. 6. The seasonal patterns for growth in length and weight were different, implying differential allocation of resources to structural and reserve tissues. 7. The growth patterns of sexually maturing male parr and emigrants also differed in comparison to other parr. 8. Condition factor, length at first capture and seasonal interactions with both early maturity and smolting explained another 7% of the variation. 9. However, individual fish did not grow consistently better, or worse, than the 'average' fish. 10. This study emphasizes the necessity to test the adequacy of laboratory-based physiological models with suitably detailed field data and to focus model refinement by identifying processes which otherwise confound interpretation.

Opioid use featured significant quantitative and qualitative differences between provinces in Canada and showed an overall increasing trend mainly driven by changes in "strong opioids" in the study period. Reasons for the observed differences are not clear yet require systematic examination to allow evidence-based interventions in the interest of equitable pain treatment as well as the reduction of high levels of opioid-related morbidity and mortality in Canada.

Summary 1.We report a modelling study of a data-set describing the growth of individual Atlantic salmon ( Salmo salar L.) parr in the Girnock Burn (Scotland). A development of the compensatory growth model due to Broekhusien et al . (1994) was fitted to these data by numerical optimization. 2. The model uses carbon mass as a surrogate for an energy currency. This mass is divided into structure and reserve components, so as to describe decoupled changes in length and wet-weight. 3. Using the same parameters for all fish, our model explained 83% of the variability in length and weight at age. Adding a single additional parameter for each individual enabled the model to explain over 96% of length and weight variability. 4. Weak negative correlation between size at first capture and within-study growth argues against genetic causality of observed growth variability. 5. The energetic basis of our model enables us to infer time-series of net assimilation and basal maintenance rates for the observed individuals. Maximal growth occurs early in the season when high assimilation is accompanied by low temperatures and maintenance rates. In late season, continuing high assimilation is balanced by high maintenance rates consequent on summer temperatures.