Effects of a health advocacy program to promote physical activity and nutrition behaviors among adolescents: An evaluation of the Young Leaders for Healthy Change program

Background. This study was designed to evaluate the effects of the Young Leaders for Healthy Change program, an internet-delivered program in the school setting that emphasized health advocacy skills-development, on nutrition and physical activity behaviors among older adolescents (13–18 years). The program consisted of online curricular modules, training modules, social media, peer and parental support, and a community service project. Module content was developed based on Social Cognitive Theory and known determinants of behavior for older adolescents. ^ Methods. Of the 283 students who participated in the fall 2011 YL program, 38 students participated in at least ten of the 12 weeks and were eligible for this study. This study used a single group-only pretest/posttest evaluation design. Participants were 68% female, 58% white/Caucasian, 74% 10th or 11th graders, and 89% mostly A and/or B students. The primary behavioral outcomes for this analysis were participation in 60-minutes of physical activity per day, 20-minutes of vigorous- or moderate- intensity physical activity (MVPA) participation per day, television and computer time, fruit and vegetable (FV) intake, sugar-sweetened beverage intake, and consumption of breakfast, home-cooked meals, and fast food. Other outcomes included knowledge, beliefs, and attitudes related to healthy eating, physical activity, and advocacy skills. ^ Findings. Among the 38 participants, no significant changes in any variables were observed. However, among those who did not previously meet behavioral goals there was an 89% increase in students who participated in more than 20 minutes of MVPA per day and a 58% increase in students who ate home-cooked meals 5–7 days per week. The majority of participants met program goals related to knowledge, beliefs, and attitudes prior to the start of the program. Participants reported either maintaining or improving to the goal at posttest for all items except FV intake knowledge, taste and affordability of healthy foods, interest in teaching others about being healthy, and ease of finding ways to advocate in the community. ^ Conclusions. The results of this evaluation indicated that promoting healthy behaviors requires different strategies than maintaining healthy behaviors among high school students. In the school setting, programs need to target the promotion and maintenance of health behaviors to engage all students who participate in the program as part of a class or club activity. Tailoring the program using screening and modifying strategies to meet the needs of all students may increase the potential reach of the program. The Transtheoretical Model may provide information on how to develop a tailored program. Additional research on how to utilize the constructs of TTM effectively among high school students needs to be conducted. Further evaluation studies should employ a more expansive evaluation to assess the long-term effectiveness of health advocacy programming.^

Bioactive Compounds in Some Culinary Aromatic Herbs and Their Effects on Human Health

Culinary herbs are herbaceous (leafy) plants that add flavour and colour to all types of meals. There is a wide variety of herbs that are used for culinary purposes worldwide, which are also recognized for their beneficial health effects, and thus have also been used in folk medicine. Besides their nutritional value herbs are rich in many phytochemical components with bioactive effects, thus improving human health. The aim of the present work was to make a general overview of some of these herbs, including their gastronomic usage, their chemical composition in bioactive components and their reported health effects. This work showed that the health effects are very diverse and differ according to the herb in question. However, some of the most frequently citted biological activities include antioxidant, antimicrobial, and antiviral effects.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Incorporating an economic model in the health impact assessment approach

The current policy decision making in Australia regarding non-health public investments (for example, transport/housing/social welfare programmes) does not quantify health benefits and costs systematically. To address this knowledge gap, this study proposes an economic model for quantifying health impacts of public policies in terms of dollar value. The intention is to enable policy-makers in conducting economic evaluation of health effects of non-health policies and in implementing policies those reduce health inequalities as well as enhance positive health gains of the target population. Health Impact Assessment (HIA) provides an appropriate framework for this study since HIA assesses the beneficial and adverse effects of a programme/policy on public health and on health inequalities through the distribution of those effects. However, HIA usually tries to influence the decision making process using its scientific findings, mostly epidemiological and toxicological evidence. In reality, this evidence can not establish causal links between policy and health impacts since it can not explain how an individual or a community reacts to changing circumstances. The proposed economic model addresses this health-policy linkage using a consumer choice approach that can explain changes in group and individual behaviour in a given economic set up. The economic model suggested in this paper links epidemiological findings with economic analysis to estimate the health costs and benefits of public investment policies. That is, estimating dollar impacts when health status of the exposed population group changes by public programmes – for example, transport initiatives to reduce congestion by building new roads/ highways/ tunnels etc. or by imposing congestion taxes. For policy evaluation purposes, the model is incorporated in the HIA framework by establishing association among identified factors, which drive changes in the behaviour of target population group and in turn, in the health outcomes. The economic variables identified to estimate the health inequality and health costs are levels of income, unemployment, education, age groups, disadvantaged population groups, mortality/morbidity etc. However, though the model validation using case studies and/or available database from Australian non-health policy (say, transport) arena is in the future tasks agenda, it is beyond the scope of this current paper.

Assessment of Health Impacts of Heatwaves in Brisbane, Australia : How to Best Define A Heatwave?

Background and Objective: As global warming continues, the frequency, intensity and duration of heatwaves are likely to increase. However, a heatwave is unlikely to be defined uniformly because acclimatisation plays a significant role in determining the heat-related impact. This study investigated how to best define a heatwave in Brisbane, Australia. Methods: Computerised datasets on daily weather, air pollution and health outcomes between 1996 and 2005 were obtained from pertinent government agencies. Paired t-tests and case-crossover analyses were performed to assess the relationship between heatwaves and health outcomes using different heatwave definitions. Results: The maximum temperature was as high as 41.5°C with a mean maximum daily temperature of 26.3°C. None of the five commonly-used heatwave definitions suited Brisbane well on the basis of the health effects of heatwaves. Additionally, there were pros and cons when locally-defined definitions were attempted using either a relative or absolute definition for extreme temperatures. Conclusion: The issue of how to best define a heatwave is complex. It is important to identify an appropriate definition of heatwave locally and to understand its health effects.

The role of social capital in reducing negative health outcomes among police officers

This paper investigates the role of social capital on the reduction of short and long run negative health effects associated with stress, as well as indicators of burnout among police officers. Despite the large volume of research on either social capital or the health effects of stress, the interaction of these factors remains an underexplored topic. In this empirical analysis we aim to reduce such a shortcoming focusing on a highly stressful and emotionally draining work environment, namely law enforcement agents who perform as an essential part of maintaining modern society. Using a multivariate regression analysis focusing on three different proxies of health and three proxies for social capital conducting also several robustness checks, we find strong evidence that increased levels of social capital is highly correlated with better health outcomes. Additionally we observe that while social capital at work is very important, social capital in the home environment and work-life balance are even more important. From a policy perspective, our findings suggest that work and stress programs should actively encourage employees to build stronger social networks as well as incorporate better working/home life arrangements.

Airborne particles and health

Much has been written about airborne particulate matter, and countless meetings, workshops and conferences have been held, both nationally and internationally, to address the many scientific challenges which they present, especially when one considers their effects on human health. Particles are a complex airborne pollutant, because of their many different characteristics and the many different ways in which they can be measured and detected. This article summarises the current state of knowledge on the effects of particulate matter and health, based primarily on epidemiological studies which focused on exposure to particle mass, and more recently, on particle number concentration.

Assessment of heat-related health impacts in Brisbane, Australia : comparison of different heatwave definitions

Background: There is no global definition of a heatwave because local acclimatisation and adaptation influence the impact of extreme heat. Even at a local level there can be multiple heatwave definitions, based on varying temperature levels or time periods. We investigated the relationship between heatwaves and health outcomes using ten different heatwave definitions in Brisbane, Australia. ---------- Methodology/Principal Findings: We used daily data on climate, air pollution, and emergency hospital admissions in Brisbane between January 1996 and December 2005; and mortality between January 1996 and November 2004. Case-crossover analyses were used to assess the relationship between each of the ten heatwave definitions and health outcomes. During heatwaves there was a statistically significant increase in emergency hospital admissions for all ten definitions, with odds ratios ranging from 1.03 to 1.18. A statistically significant increase in the odds ratios of mortality was also found for eight definitions. The size of the heat-related impact varied between definitions.---------- Conclusions/Significance Even a small change in the heatwave definition had an appreciable effect on the estimated health impact. It is important to identify an appropriate definition of heatwave locally and to understand its health effects in order to develop appropriate public health intervention strategies to prevent and mitigate the impact of heatwaves.

The effects of the 2009 dust storm on emergency admissions to a hospital in Brisbane, Australia

In September 2009 an enormous dust storm swept across eastern Australia. Dust is potentially hazardous to health as it interferes with breathing, and previous dust storms have been linked to increased risks of asthma and even death. We examined whether the 2009 Australian dust storm changed the volume or characteristics of emergency admissions to hospital. We used an observational study design, using time series analyses to examine changes in the number of admissions, and case-only analyses to examine changes in the characteristics of admissions. The admission data were from the Prince Charles Hospital, Brisbane, between 1 January 2009 and 31 October 2009. There was a 39% increase in emergency admissions associated with the storm (95% confidence interval: 5, 81%), which lasted for just one day. The health effects of the storm could not be detected using particulate matter levels. We found no significant change in the characteristics of admissions during the storm, specifically there was no increase in respiratory admissions. The dust storm had a short-lived impact on emergency hospital admissions. This may be because the public took effective avoidance measures, or because the dust was simply not toxic, being mainly composed of soil. Emergency departments should be prepared for a short-term increase in admissions during dust storms.

Floods and human health : a systematic review

Floods are the most common type of disaster globally, responsible for almost 53,000 deaths in the last decade alone (23:1 low- versus high-income countries). This review assessed recent epidemiological evidence on the impacts of floods on human health. Published articles (2004–2011) on the quantitative relationship between floods and health were systematically reviewed. 35 relevant epidemiological studies were identified. Health outcomes were categorized into short- and long-term and were found to depend on the flood characteristics and people's vulnerability. It was found that long-term health effects are currently not well understood. Mortality rates were found to increase by up to 50% in the first year post-flood. After floods, it was found there is an increased risk of disease outbreaks such as hepatitis E, gastrointestinal disease and leptospirosis, particularly in areas with poor hygiene and displaced populations. Psychological distress in survivors (prevalence 8.6% to 53% two years post-flood) can also exacerbate their physical illness. There is a need for effective policies to reduce and prevent flood-related morbidity and mortality. Such steps are contingent upon the improved understanding of potential health impacts of floods. Global trends in urbanization, burden of disease, malnutrition and maternal and child health must be better reflected in flood preparedness and mitigation programs.

Methodological challenges when estimating the effects of season and seasonal exposures on birth outcomes

Background Many previous studies have found seasonal patterns in birth outcomes, but with little agreement about which season poses the highest risk. Some of the heterogeneity between studies may be explained by a previously unknown bias. The bias occurs in retrospective cohorts which include all births occurring within a fixed start and end date, which means shorter pregnancies are missed at the start of the study, and longer pregnancies are missed at the end. Our objective was to show the potential size of this bias and how to avoid it. Methods To demonstrate the bias we simulated a retrospective birth cohort with no seasonal pattern in gestation and used a range of cohort end dates. As a real example, we used a cohort of 114,063 singleton births in Brisbane between 1 July 2005 and 30 June 2009 and examined the bias when estimating changes in gestation length associated with season (using month of conception) and a seasonal exposure (temperature). We used survival analyses with temperature as a time-dependent variable. Results We found strong artificial seasonal patterns in gestation length by month of conception, which depended on the end date of the study. The bias was avoided when the day and month of the start date was just before the day and month of the end date (regardless of year), so that the longer gestations at the start of the study were balanced by the shorter gestations at the end. After removing the fixed cohort bias there was a noticeable change in the effect of temperature on gestation length. The adjusted hazard ratios were flatter at the extremes of temperature but steeper between 15 and 25°C. Conclusions Studies using retrospective birth cohorts should account for the fixed cohort bias by removing selected births to get unbiased estimates of seasonal health effects.

Estimating the effects of environmental exposures using a weighted mean of monitoring stations

The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.

Changes in health profiles of participants in an Australian police department’s Wellness program

Background: Little is known about the health effects of worksite wellness programs on police department staff. Objective: To examine 1-2 year changes in health profiles of participants in the Queensland Police Service’s wellness program. Methods: Participants underwent yearly physical assessments. Health profile data collected during assessments from 2008 to 2012 were included in the analysis. Data Analysis: Repeated-measures ANOVA was used for continuous outcome variables, related-samples Wilcoxon Signed Rank test for non-normally continuous variables, and McNemar’s test for binary variables. Results: Significant changes in physical measures included decreases in waist circumference and percent body fat, and increases in cardiorespiratory fitness and flexibility (p<0.01). Changes in serum cholesterol, haemoglobin, total cholesterol ratios, HDL, LDL and Triglyceride levels were also significant (p<0.01). Conclusion: Participants’ health profiles mostly improved between cycles although most changes were not clinically significant. As this evaluation used a single-group pre-test post-test design, it provides initial indications that wellness programs can benefit staff in police departments.