The Relative Influences of Climate and Competition on Tree Growth along Montane Ecotones in the Rocky Mountains

Distribution shifts of tree species are likely to be highly dependent upon population performance at distribution edges. Understanding the drivers of aspects of performance, such as growth, at distribution edges is thus crucial to accurately predicting responses of tree species to climate change. Here, we use a Bayesian model and sensitivity analysis to partition the effects of climate and crowding, as a metric of competition, on radial growth of three dominant conifer species along montane ecotones in the Rocky Mountains. These ecotones represent upper and lower distribution edges of two species, and span the distribution interior of the third species. Our results indicate a greater influence of climate (i.e., temperature and precipitation) than crowding on radial growth. Competition importance appears to increase towards regions of more favorable growing conditions, and precise responses to crowding and climate vary across species. Overall, our results suggest that climate will likely be the most important determinant of changes in tree growth at distribution edges of these montane conifers in the future

The Effect of Isoleucine Supplementation of Peripheral Blood Mononuclear Cell Metabolism in Subjects With Type 2 Diabetes

Type 2 diabetes (T2D) is an increasing health concern as 425 million people are diagnosed with it worldwide. It is associated with chronic systemic inflammation and increased oxidative stress; individuals with these inflammatory conditions have altered metabolic pathways and mitochondrial function including changes in mitochondrial respiration values in peripheral blood mononuclear cells (PBMCs). Mitochondrial respiratory capacity is vital to produce cellular energy in the form of adenosine triphosphate (ATP) via the tricarboxylic acid (TCA) cycle and mitochondrial electron transport chain (ETC). Metabolic dysfunction associated with systemic inflammation can lead to limited production of tricarboxylic acid (TCA) cycle intermediates which are vital for metabolism. It has previously been shown that providing anaplerotic TCA cycle precursors, specifically isoleucine and valine, can replenish TCA cycle intermediates. The purpose of this study was to assess the mitochondrial function in PBMCs from eight control subjects and seven T2D subjects using high resolution respirometry. Subjects with T2D received ten days of treatment with three grams daily of supplemental isoleucine. PBMC respiration was compared between control and T2D at baseline, and T2D subjects were assessed for changes over the treatment duration. Subjects with T2D had significantly lower leak respiration and leak-related coupling control ratio than healthy control subjects. There was no significant change in measures of PBMC respiration from T2D subjects before and after treatment. Although there appears to be minor differences in PBMC respiratory rate between subjects with T2D and healthy controls, 10 days of isoleucine supplementation was not effective at recovering altered PBMC respiration in T2D subjects

How weight change is modelled in population studies can affect research findings: empirical results from a large-scale cohort study

Objectives: To investigate how results of the association between education and weight change vary when weight change is defined and modelled in different ways. Design: Longitudinal cohort study. Participants: 60 404 men and women participating in the Social, Environmental and Economic Factors (SEEF) subcomponent of the 45 and Up Study—a population-based cohort study of people aged 45 years or older, residing in New South Wales, Australia. Outcome measures: The main exposure was selfreported education, categorised into four groups. The outcome was annual weight change, based on change in self-reported weight between the 45 and Up Study baseline questionnaire and SEEF questionnaire (completed an average of 3.3 years later). Weight change was modelled in four different ways: absolute change (kg) modelled as (1) a continuous variable and (2) a categorical variable (loss, maintenance and gain), and relative (%) change modelled as (3) a continuous variable and (4) a categorical variable. Different cutpoints for defining weight-change categories were also tested. Results: When weight change was measured categorically, people with higher levels of education (compared with no school certificate) were less likely to lose or to gain weight. When weight change was measured as the average of a continuous measure, a null relationship between education and annual weight change was observed. No material differences in the education and weight-change relationship were found when comparing weight change defined as an absolute (kg) versus a relative (%) measure. Results of the logistic regression were sensitive to different cut-points for defining weight-change categories. Conclusions: Using average weight change can obscure important directional relationship information and, where possible, categorical outcome measurements should be included in analyses

Landmark models for optimizing the use of repeated measurements of risk factors in electronic health records to predict future disease risk

The benefits of using electronic health records for disease risk screening and personalized heathcare decisions are becoming increasingly recognized. We present a computationally feasible statistical approach to address the methodological challenges in utilizing historical repeat measures of multiple risk factors recorded in electronic health records to systematically identify patients at high risk of future disease. The approach is principally based on a two-stage dynamic landmark model. The first stage estimates current risk factor values from all available historical repeat risk factor measurements by landmark-age-specific multivariate linear mixed-effects models with correlated random-intercepts, which account for sporadically recorded repeat measures, unobserved data and measurements errors. The second stage predicts future disease risk from a sex-stratified Cox proportional hazards model, with estimated current risk factor values from the first stage. Methods are exemplified by developing and validating a dynamic 10-year cardiovascular disease risk prediction model using electronic primary care records for age, diabetes status, hypertension treatment, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol from 41,373 individuals in 10 primary care practices in England and Wales contributing to The Health Improvement Network (1997-2016). Using cross-validation, the model was well-calibrated (Brier score = 0.041 [95%CI: 0.039, 0.042]) and had good discrimination (C-index = 0.768 [95%CI: 0.759, 0.777]).This work was funded by the Medical Research Council (MRC) (grant MR/K014811/1). J.B. was supported by an MRC fellowship (grant G0902100) and the MRC Unit Program (grant MC_UU_00002/5). R.H.K. was supported by an MRC Methodology Fellowship (grant MR/M014827/1)

Characteristics of antidepressant medication users in a cohort of mid-age and older Australians

OBJECTIVES: We aimed to investigate antidepressant use, including the class of antidepressant, in mid-age and older Australians according to sociodemographic, lifestyle and physical and mental health-related factors. METHODS: Baseline questionnaire data on 111,705 concession card holders aged ⩾45 years from the 45 and Up Study—a population-based cohort study from New South Wales, Australia—were linked to administrative pharmaceutical data. Current- and any-antidepressant users were those dispensed medications with Anatomical Therapeutic Chemical classification codes beginning N06A, within ⩽6 months and ⩽19 months before baseline, respectively; non-users had no antidepressants dispensed ⩽19 months before baseline. Multinomial logistic regression was used to calculate adjusted relative risk ratios (aRRRs) for predominantly self-reported factors in relation to antidepressant use. RESULTS: Some 19% of the study population (15% of males and 23% of females) were dispensed at least one antidepressant during the study period; 40% of participants used selective serotonin reuptake inhibitors (SSRIs) only and 32% used tricyclic antidepressants (TCAs) only. Current antidepressant use was markedly higher in those reporting: severe versus no physical impairment (aRRR 3.86(95%CI 3.67–4.06)); fair/poor versus excellent/very good self-rated health (4.04(3.83–4.25)); high/very high versus low psychological distress (7.22(6.81–7.66)); ever- versus never-diagnosis of depression by a doctor (18.85(17.95–19.79)); low-dose antipsychotic use versus no antipsychotic use (12.26(9.85–15.27)); and dispensing of ⩾10 versus <5 other medications (5.97(5.62–6.34)). Sociodemographic and lifestyle factors were also associated with use, although to a lesser extent. Females, older people, those with lower education and those with poorer health were more likely to be current antidepressant users than non-users and were also more likely to use TCAs-only versus SSRIs-only. CONCLUSIONS: Use of antidepressants is substantially higher in those with physical ill-health and in those reporting a range of adverse mental health measures. In addition, sociodemographic factors, including sex, age and education were also associated with antidepressant use and the class of antidepressant used.Emily Banks and Bryan Rodgers are supported by the NHMRC (Fellowship No. 1042717 and 471429, respectively). This project was supported by the Study of Economic and Environmental Factors in health project, funded by the National Health and Medical Research Council of Australia (NHMRC) (grant reference: 402810) and NHMRC project grant 1024450

Income-related inequalities in chronic conditions, physical functioning and psychological distress among older people in Australia: cross-sectional findings from the 45 and up study

BACKGROUND: The burden of chronic disease continues to rise as populations age. There is relatively little published on the socioeconomic distribution of this burden in older people. This study quantifies absolute and relative income-related inequalities in prevalence of chronic diseases, severe physical functioning limitation and high psychological distress in mid-age and older people in Australia. METHODS: Cross-sectional study of 208,450 participants in the 45 and Up Study, a population-based cohort of men and women aged 45–106 years from New South Wales, Australia. Chronic conditions included self-reported heart disease, diabetes, Parkinson’s disease, cancer and osteoarthritis; physical functioning limitation (severe/not) was measured using Medical Outcomes Study measures and psychological distress (high/not) using the Kessler Psychological Distress Scale. For each outcome, prevalence was estimated in relation to annual household income (6 categories). Prevalence differences (PDs) and ratios (PRs) were generated, comparing the lowest income category (<$20,000) to the highest (≥$70,000), using Poisson regression with robust standard errors, weighted for age, sex and region of residence. Analyses were stratified by age group (45–64, 65–79 and ≥80 years) and sex and adjusted for age and country of birth. RESULTS: With few exceptions, there were income gradients in the prevalence of chronic conditions among all age-sex groups, with prevalence decreasing with increasing income. Of the chronic diseases, PDs were highest for diabetes (ranging between 5.69% and 10.36% across age-sex groups) and in women, also for osteoarthritis (5.72% to 8.14%); PRs were highest for osteoarthritis in men aged 45–64 years (4.01), otherwise they were highest for diabetes (1.78 to 3.43). Inequalities were very high for both physical functioning limitation and psychological distress, particularly among those aged 45–64 (PDs between 18.67% and 29.23% and PRs between 4.63 and 16.51). Absolute and relative inequalities tended to decrease with age, but remained relatively high for diabetes and physical functioning in the elderly (≥80 years). CONCLUSIONS: Significant inequalities in the prevalence of chronic conditions, physical functioning and psychological distress persist into old age. The additional health burden placed on those who are already disadvantaged is likely to become an increasingly important issue in an ageing population

Socioeconomic variation in absolute cardiovascular disease risk and treatment in the Australian population

Cardiovascular disease (CVD), preventable through appropriate management of absolute CVD risk, disproportionately affects socioeconomically disadvantaged individuals. The aim of this study was to estimate absolute and relative socioeconomic inequalities in absolute CVD risk and treatment in the Australian population using cross-sectional representative data on 4,751 people aged 45-74 from the 2011-12 Australian Health Survey. Poisson regression was used to calculate prevalence differences (PD) and ratios (PR) for prior CVD, high 5-year absolute risk of a primary CVD event and guideline-recommended medication use, in relation to socioeconomic position (SEP, measured by education). After adjusting for age and sex, the prevalence of high absolute risk of a primary CVD event among those of low, intermediate and high SEP was 12.6%, 10.9% and 7.7% (PD, low vs. high=5.0 [95% CI: 2.3, 7.7], PR=1.6 [1.2, 2.2]) and for prior CVD was 10.7%, 9.1% and 6.7% (PD=4.0 [1.4, 6.6], PR=1.6 [1.1, 2.2]). The proportions using preventive medication use among those with high primary risk were 21.3%, 19.5% and 29.4% for low, intermediate and high SEP and for prior CVD, were 37.8%, 35.7% and 17.7% (PD=20.1 [9.7, 30.5], PR=2.1 [1.3, 3.5]). Proportions at high primary risk and not using medications among those of low, intermediate and high SEP were 10.6%, 8.8% and 4.7% and with prior CVD not using medications were 8.5%, 6.3% and 4.1%. Findings indicate substantial potential to prevent CVD and reduce inequalities through appropriate management of high absolute risk in the population.This work was supported by a National Health and Medical Research Council of Australia (NHMRC) Partnership Project (reference 1092674) and the NHMRC Centre for Research Excellence in Medicines and Ageing (reference 1060407). Emily Banks is supported by the NHMRC (reference 1042717)

Tobacco smoking and all-cause mortality in a large Australian cohort study: findings from a mature epidemic with current low smoking prevalence

This study finds that up to two-thirds of deaths in current smokers&nbsp; in Australia can be attributed to smoking. Abstract Background The smoking epidemic in Australia is characterised by historic levels of prolonged smoking, heavy smoking, very high levels of long-term cessation, and low current smoking prevalence, with 13% of adults reporting that they smoked daily in 2013. Large-scale quantitative evidence on the relationship of tobacco smoking to mortality in Australia is not available despite the potential to provide independent international evidence about the contemporary risks of smoking. Methods This is a prospective study of 204,953 individuals aged ≥45&nbsp;years sampled from the general population of New South Wales, Australia, who joined the 45 and Up Study from 2006–2009, with linked questionnaire, hospitalisation, and mortality data to mid-2012 and with no history of cancer (other than melanoma and non-melanoma skin cancer), heart disease, stroke, or thrombosis. Hazard ratios (described here as relative risks, RRs) for all-cause mortality among current and past smokers compared to never-smokers were estimated, adjusting for age, education, income, region of residence, alcohol, and body mass index. Results Overall, 5,593 deaths accrued during follow-up (874,120 person-years; mean: 4.26&nbsp;years); 7.7% of participants were current smokers and 34.1% past smokers at baseline. Compared to never-smokers, the adjusted RR (95% CI) of mortality was 2.96 (2.69–3.25) in current smokers and was similar in men (2.82 (2.49–3.19)) and women (3.08 (2.63–3.60)) and according to birth cohort. Mortality RRs increased with increasing smoking intensity, with around two- and four-fold increases in mortality in current smokers of ≤14 (mean 10/day) and ≥25 cigarettes/day, respectively, compared to never-smokers. Among past smokers, mortality diminished gradually with increasing time since cessation and did not differ significantly from never-smokers in those quitting prior to age 45. Current smokers are estimated to die an average of 10&nbsp;years earlier than non-smokers. Conclusions In Australia, up to two-thirds of deaths in current smokers can be attributed to smoking. Cessation reduces mortality compared with continuing to smoke, with cessation earlier in life resulting in greater reductions

Landmark Models for Optimizing the Use of Repeated Measurements of Risk Factors in Electronic Health Records to Predict Future Disease Risk.

The benefits of using electronic health records (EHRs) for disease risk screening and personalized health-care decisions are being increasingly recognized. Here we present a computationally feasible statistical approach with which to address the methodological challenges involved in utilizing historical repeat measures of multiple risk factors recorded in EHRs to systematically identify patients at high risk of future disease. The approach is principally based on a 2-stage dynamic landmark model. The first stage estimates current risk factor values from all available historical repeat risk factor measurements via landmark-age-specific multivariate linear mixed-effects models with correlated random intercepts, which account for sporadically recorded repeat measures, unobserved data, and measurement errors. The second stage predicts future disease risk from a sex-stratified Cox proportional hazards model, with estimated current risk factor values from the first stage. We exemplify these methods by developing and validating a dynamic 10-year cardiovascular disease risk prediction model using primary-care EHRs for age, diabetes status, hypertension treatment, smoking status, systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol in 41,373 persons from 10 primary-care practices in England and Wales contributing to The Health Improvement Network (1997-2016). Using cross-validation, the model was well-calibrated (Brier score = 0.041, 95% confidence interval: 0.039, 0.042) and had good discrimination (C-index = 0.768, 95% confidence interval: 0.759, 0.777)