Complexity of management and health outcomes in a prospective cohort study of 573 heart failure patients in Australia : does more equal less?

Aims and objectives : To compare the efficacy of chronic heart failure management programmes (CHF-MPs) according to a scoring algorithm used to quantify the level of applied interventions–the Heart Failure Intervention Score (HF-IS).

Background : The overall efficacy of heart failure programmes has been proven in several meta-analyses. However, the debate continues as to which components are essential in a heart failure programme to improve patient outcomes.

Design : Prospective cohort study of patients participating in heart failure programmes.

Method : Forty-eight of 62 (77%) programmes in Australia participating in a national register of CHF-MPs were evaluated using the HF-IS: derived from a summed and weighted score of each intervention applied by the CHF-MP (27 interventions overall). The CHF-MPs were prospectively categorised as relatively low (HF-IS < 190 – n = 39 programmes & 407 patients) or high (HF-IS ≥ 190 – n = 9 programmes & 166 patients) in complexity. Six-month morbidity and mortality rates in 573 consecutively recruited patients with systolic dysfunction and in New York Heart Association Class II–IV were prospectively examined.

Results : Patients exposed to CHF-MPs with a high HF-IS had a lower rate of unplanned, all-cause hospitalisation (n = 24, 14% vs. n = 102, 25%) compared with CHF-MPs with a low HF-IS within six months. On an adjusted basis, CHF-MPs with a high HF-IS were associated with a reduced risk of unplanned hospitalisation and/or death within six months and remained event-free longer.

Conclusion : High complexity CHF-MPs applying more evidence-based interventions are associated with a higher event-free survival over six months.

Relevance to clinical practice : The HF-IS is an easy-to-use evidence-based tool to assist programme coordinators to improve the quality of their heart failure programme which may also improve patient outcomes.

Statistical approaches to testing the relationships of the built environment with resident-level physical activity behavior and health outcomes in cross-sectional studies with cluster sampling

To achieve valid conclusions, studies exploring associations of the built environment with residents' physical activity and health-related outcomes need to employ statistical approaches accounting for clustered data. This article discusses the following main statistical approaches: analysis of covariance, regression models with robust standard errors, generalized estimating equations, and multilevel generalized linear models. The choice of a statistical method depends on the characteristics of the study and research questions. While the first three approaches are employed to account for clustering in the data, multilevel models can also help unravel more substantive issues within a social ecological theoretical framework of health behavior.

The stress of fire fighting - implications for long term health outcomes

Fire and rescue staff routinely endure significant psychological and environmental stress exposure on the job. While much has been done to improve understanding of the physiological effects of exposure to these conditions, little has been done to quantify the inflammatory stress response that firefighters are exposed to during wildfire suppression. Therefore the aim of the present study was to explore whether firefighters experienced a change in inflammatory markers following one day, and across two days of wildfire suppression tasks. Twelve male fire-fighters participated in two consecutive days of live-fire prescribed burn operations in Ngarkat National Park, South Australia. Typical work tasks included lighting burns, patrolling containment lines, supressing spot fires, and operating vehicles. A number of the inflammatory markers changed significantly across the course of a shift and several presented with an attenuated response across the second day. This finding implies that there was a compounding effect of repeated exposure to these stressors which could have considerable implications for managing fire-fighters health and wellbeing over a multi-day campaign. Further research is required to see which fire ground stressor, or combination of stressors is causing these changes in the inflammatory markers across consecutive work shifts.

Experiences of racism, racial/ethnic attitudes, motivated fairness and mental health outcomes among primary and secondary school students

While studies investigating the health effects of racial discrimination for children and youth have examined a range of effect modifiers, to date, relationships between experiences of racial discrimination, student attitudes, and health outcomes remain unexplored. This study uniquely demonstrates the moderating effects of vicarious racism and motivated fairness on the association between direct experiences of racism and mental health outcomes, specifically depressive symptoms and loneliness, among primary and secondary school students. Across seven schools, 263 students (54.4% female), ranging from 8 to 17 years old (M = 11.2, SD = 2.2) reported attitudes about other racial/ethnic groups and experiences of racism. Students from minority ethnic groups (determined by country of birth) reported higher levels of loneliness and more racist experiences relative to the majority group students. Students from the majority racial/ethnic group reported higher levels of loneliness and depressive symptoms if they had more friends from different racial/ethnic groups, whereas the number of friends from different groups had no effect on minority students' loneliness or depressive symptoms. Direct experiences of racism were robustly related to higher loneliness and depressive symptoms in multivariate regression models. However, the association with depressive symptoms was reduced to marginal significance when students reported low motivated fairness. Elaborating on the negative health effects of racism in primary and secondary school students provides an impetus for future research and the development of appropriate interventions.

Housing strategies that improve indigenous health outcomes

Housing is a key social determinant of health. The relationship between housing outcomes and health outcomes is bi-directional: housing affects healthoutcomes, and health affects housing outcomes. There are clear links between the quality and location of housing and health outcomes. The impacts of housing on health vary between geographic and climatic locations and contexts. There is a wide range of housing interventions that positively impact Indigenous health. One way of categorisingthese is: infrastructure improvements; addressing behavioural factors; and adjustments to policy environments.

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.

Cross-sectional study of 24-hour urinary electrolyte excretion and associated health outcomes in a convenience sample of Australian primary schoolchildren: the salt and other nutrients in children (SONIC) study protocol

BACKGROUND: Dietary sodium and potassium are involved in the pathogenesis of cardiovascular disease. Data exploring the cardiovascular outcomes associated with these electrolytes within Australian children is sparse. Furthermore, an objective measure of sodium and potassium intake within this group is lacking. OBJECTIVE: The primary aim of the Salt and Other Nutrient Intakes in Children ("SONIC") study was to measure sodium and potassium intakes in a sample of primary schoolchildren located in Victoria, Australia, using 24-hour urine collections. Secondary aims were to identify the dietary sources of sodium and potassium, examine the association between these electrolytes and cardiovascular risk factors, and assess children's taste preferences and saltiness perception of manufactured foods. METHODS: A cross-sectional study was conducted in a convenience sample of schoolchildren attending primary schools in Victoria, Australia. Participants completed one 24-hour urine collection, which was analyzed for sodium, potassium, and creatinine. Completeness of collections was assessed using collection time, total volume, and urinary creatinine. One 24-hour dietary recall was completed to assess dietary intake. Other data collected included blood pressure, body weight, height, waist and hip circumference. Children were also presented with high and low sodium variants of food products and asked to discriminate salt level and choose their preferred variant. Parents provided demographic information and information on use of discretionary salt. Descriptive statistics will be used to describe sodium and potassium intakes. Linear and logistic regression models with clustered robust standard errors will be used to assess the association between electrolyte intake and health outcomes (blood pressure and body mass index/BMI z-score and waist circumference) and to assess differences in taste preference and discrimination between high and low sodium foods, and correlations between preference, sodium intake, and covariates. RESULTS: A total of 780 children across 43 schools participated. The results from this study are expected at the end of 2015. CONCLUSIONS: This study will provide the first objective measure of sodium and potassium intake in Australian schoolchildren and improve our understanding of the relationship of these electrolytes to cardiovascular risk factors. Furthermore, this study will provide insight into child taste preferences and explore related factors. Given the cardiovascular implications of consuming too much sodium and too little potassium, monitoring of these nutrients during childhood is an important public health initiative.

Sleep disturbances and associated health outcomes: an epidemiological study

 This series of 8 peer-reviewed published studies provided novel evidence demonstrating a strong, independent association between daytime sleepiness, disturbed nocturnal sleep and pathological sleep disorders (sleep apnoea and insomnia) and deleterious health outcomes across several critical age-related developmental periods among three representative, population-based samples from Australia, Norway and the USA.

Environmental contributions to social and mental health outcomes following pediatric stroke

Mental health and social outcomes following acquired brain injury (ABI) in children are often considered to be due to brain insult, but other factors, such as environment, may also play a role. We assessed mental health and social function in children with chronic illness, with and without stroke (a form of ABI), and typically developing (TD) controls to examine environmental influences on these outcomes. We recruited 36 children diagnosed with stroke, 15 with chronic asthma, and 43 TD controls. Children and parents completed questionnaires rating child mental health and social function and distal and proximal environment. TD children had significantly less internalizing and social problems than stroke and asthma groups, and engaged in more social activities than children with stroke. Poorer parent mental health predicted more internalizing and social problems and lower social participation. Family dysfunction was associated with internalizing problems. Lower parent education contributed to children's social function. Children with chronic illness are at elevated risk of poorer mental health and social function. Addition of brain insult leads to poorer social participation. Quality of home environment contributes to children's outcomes, suggesting that supporting parent and family function provides an opportunity to optimize child mental health and social outcomes.

The role of dietary choices and medical expenditures on health outcomes when health shocks are endogenous

This paper presents a theoretical framework that incorporates both a role for preventive actions (through food choices) and treatment (through medical services) to improve health outcomes. In particular, we allow for an agent's calorie decision to alter the distribution of future health shocks. Once a shock is realized, medical care can be used to improve health outcomes. Thus this model can help us determine the role of the preventive actions and treatments in producing better health outcomes and study the links between an agent's choice of medical services and her diet. This framework suggests that wealthier individuals, on average, have lower morbidity rates and lead a healthier lifestyle than lower income agents. Finally, our numerical exercise captures U.S. cross-sectional facts regarding the choice of diet, medical expenditures as well as health and non-food expenditures.

Estimating the proportion of metabolic health outcomes attributable to obesity: a cross-sectional exploration of body mass index and waist circumference combinations

BACKGROUND: Recent evidence suggests that a substantial subgroup of the population who have a high-risk waist circumference (WC) do not have an obese body mass index (BMI). This study aimed to explore whether including those with a non-obese BMI but high risk WC as 'obese' improves prediction of adiposity-related metabolic outcomes.

METHODS: Eleven thousand, two hundred forty-seven participants were recruited. Height, weight and WC were measured. Ten thousand, six hundred fifty-nine participants with complete data were included. Adiposity categories were defined as: BMI(N)/WC(N), BMI(N)/WC(O), BMI(O)/WC(N), and BMI(O)/WC(O) (N = non-obese and O = obese). Population attributable fraction, area under the receiver operating characteristic curve (AUC), and odds ratios (OR) were calculated.

RESULTS: Participants were on average 48 years old and 50 % were men. The proportions of BMI(N)/WC(N), BMI(N)/WC(O), BMI(O)/WC(N) and BMI(O)/WC(O) were 68, 12, 2 and 18 %, respectively. A lower proportion of diabetes was attributable to obesity defined using BMI alone compared to BMI and WC combined (32 % vs 47 %). AUC for diabetes was also lower when obesity was defined using BMI alone (0.62 vs 0.66). Similar results were observed for all outcomes. The odds for hypertension, dyslipidaemia, diabetes and CVD were increased for those with BMI(N)/WC(O) (OR range 1.8-2.7) and BMI(O)/WC(O) (OR 1.9-4.9) compared to those with BMI(N)/WC(N).

CONCLUSIONS: Current population monitoring, assessing obesity by BMI only, misses a proportion of the population who are at increased health risk through excess adiposity. Improved identification of those at increased health risk needs to be considered for better prioritisation of policy and resources.

Assessing mediators between discrimination, health behaviours and physical health outcomes: a representative cross-sectional study

PURPOSE: Discrimination is a social determinant of health; however, the pathways linking discrimination to ill-health are under-researched. This study investigated the mediators through which discrimination affects health behaviours and physical health outcomes, as well as assessed whether sex moderated these mechanisms. METHODS: Data from a representative survey (n = 1023) of undergraduate students enrolled in a Brazilian university in 2012 were used. Structural equation models were applied to assess the following mediation mechanisms--(1) discrimination influences self-rated health and body mass index via anxiety/depression; (2) discrimination affects behaviours (alcohol consumption, problem drinking, smoking, fruit/vegetable consumption, and physical activity) through discomfort associated with discriminatory experiences. The potential of sex to act as an effect-modifying variable was also explored in each of the postulated pathways. RESULTS: The effect of discrimination on self-rated poor health was totally (100.0%) mediated by anxiety/depression, while body mass index was not correlated with discrimination. Self-reported discrimination was associated with some behaviours via discomfort. Particularly, discomfort partially mediated the positive association between discrimination, leisure time physical activity (43.3%), and fruit/vegetable consumption (52.2%). Sex modified the association between discrimination, discomfort and physical activity in that such mechanism (more discrimination → more discomfort → more physical activity) was statistically significant in the entire sample and among females, but not among males. CONCLUSIONS: This is one of the first studies to demonstrate that discrimination is associated with physical health outcomes and behaviours via distinct pathways. Future investigations should further explicate the mediational pathways between discrimination and key health outcomes.

Air pollution and health: bridging the gap from sources to health outcomes: conference summary

Air Pollution and Health: Bridging the Gap from Sources to Health Outcomes, an international specialty conference sponsored by the American Association for Aerosol Research, was held to address key uncertainties in our understanding of adverse health effects related to air pollution and to integrate and disseminate results from recent scientific studies that cut across a range of air pollution-related disciplines. The Conference addressed the science of air pollution and health within a multipollutant framework (herein "multipollutant" refers to gases and particulate matter mass, components, and physical properties), focusing on five key science areas: sources, atmospheric sciences, exposure, dose, and health effects. Eight key policy-relevant science questions integrated across various parts of the five science areas and a ninth question regarding findings that provide policy-relevant insights served as the framework for the meeting. Results synthesized from this Conference provide new evidence, reaffirm past findings, and offer guidance for future research efforts that will continue to incrementally advance the science required for reducing uncertainties in linking sources, air pollutants, human exposure, and health effects. This paper summarizes the Conference findings organized around the science questions. A number of key points emerged from the Conference findings. First, there is a need for greater focus on multipollutant science and management approaches that include more direct studies of the mixture of pollutants from sources with an emphasis on health studies at ambient concentrations. Further, a number of research groups reaffirmed a need for better understanding of biological mechanisms and apparent associations of various health effects with components of particulate matter (PM), such as elemental carbon, certain organic species, ultrafine particles, and certain trace elements such as Ni, V, and Fe(II), as well as some gaseous pollutants. Although much debate continues in this area, generation of reactive oxygen species induced by these and other species present in air pollution and the resulting oxidative stress and inflammation were reiterated as key pathways leading to respiratory and cardiovascular outcomes. The Conference also underscored significant advances in understanding the susceptibility of populations, including the role of genetics and epigenetics and the influence of socioeconomic and other confounding factors and their synergistic interactions with air pollutants. Participants also pointed out that short-and long-term intervention episodes that reduce pollution from sources and improve air quality continue to indicate that when pollution decreases so do reported adverse health effects. In the limited number of cases where specific sources or PM2.5 species were included in investigations, specific species are often associated with the decrease in effects. Other recent advances for improved exposure estimates for epidemiological studies included using new technologies such as microsensors combined with cell phone and integrated into real-time communications, hybrid air quality modeling such as combined receptor-and emission-based models, and surface observations used with remote sensing such as satellite data.