Chronic diseases are among the leading causes of death globally, and as much as 80% of these deaths are reported to be preventable with proper diet and lifestyle. Although extensive research has demonstrated that the increased consumption of fruits and vegetables offers protective health effects from many chronic illnesses, populations in both developed and developing nations consistently fall short of the recommended intake of 5 or more servings a day. This study investigated the effects of daily consumption of Green Smoothies for 4 consecutive weeks on blood pressure and health-related quality of life. Green Smoothies are a blended drink consisting of fruit, leafy greens and water. The study was a randomized controlled trial with a final sample of 29 volunteer participants. Data were collected at baseline and post-intervention and included anthropometric and physiologic measures, as well as a nutrition survey. The treatment group demonstrated trends toward improvements in waist circumference (p = 0.026), waist-to-hip ratio (p = 0.05), and symptoms of burden linked to diet (p = 0.04), small intestine (p = 0.04), large intestine (p = 0.05), and mineral needs (p = 0.04). Despite the lack of statistically significant reductions in blood pressure, the trend toward improvements in waist circumference and waist-to-hip ratio are considered to be useful and informative of health risk. Thus, the results of this study provide preliminary support for the consumption of Green Smoothies as a possible primary prevention effort for chronic conditions. It may also help to reduce health risks or even reverse the effects of chronic conditions.

Cardiovascular disease is one of the leading causes of death in industrialized nations. Research indicates that job strain may be significantly related to cardiovascular disease in employees with little to no social support. Using the JDC-S model developed by Karasek (1979) and elaborated upon by Johnson and Hall (1988), the family-supportive supervisory behaviors (FSSB) measure created by Hammer et al., (2009), and the blood pressure wrist monitor device Omron317T, this study examined FSSB as a moderator of the relationship between job strain, job demands, job control and workers' blood pressure on work and non-work days. Sixty-nine grocery store workers from a Midwest grocery store chain participated in this study, fifty-six of which were included in the analyses. Though none of the interactions were significant at the .05 level, results indicate that FSSB is significantly related to a number of blood pressure readings at the grand centered mean of job strain, job control, and job demands.

Indiana University-Purdue University Indianapolis (IUPUI) / Objective: "The purpose of this research is: Study the use of Moderate Resolution Imaging Spectroradiometer (MODIS) data in retrieving the aerosol optical depth (AOD) over Indiana State at high resolution of 500 meters. Examine the potential of using the resulted AOD data as an indicator of particulate air pollution by comparing the satellite derived AOD data with the ground measurements (provided from the continuous air monitors available over the study area). If an association should be found, AOD data would be used to map particulate matter (PM) concentration. Assess current and future ambient concentrations of air pollutants in the State of Indiana using the AOD."

Existing research on health disparities in breast cancer is heavily focused on outcomes for poor or low-income women. Little is known about the experience of privately insured Black breast cancer patients that have moderate to high SES. As a result, the present study was conducted to learn more about their experiences. It examines differences in physician prescribing of two breast cancer pain treatments, peripheral nerve block (PNB) and opioids, for Black and White women with like levels of health insurance coverage and socioeconomic status (SES). Three specific questions are addressed: 1. What, if any, race-based disparities exist in usage of PNBs at time of total mastectomy? 2. What, if any, race based disparities exist in the prescription of opioids for postoperative pain following total mastectomy? 3. What, if any, changes have occurred in the frequency of orders placed for PNBs and prescription opioids over time, to treat postoperative pain resulting from mastectomy? A cross-sectional designed was used relying on an existing national dataset, Optum Clinformatics Data Mart. The study period was January 1, 2012, through December 31, 2019. Study results revealed that while moderate to higher SES Black women have equitable access to PNB and opioids - a kind of shield from long established physician bias against Black women – this protection is quite porous. They still do not have open and ready access to PNB as a more advanced pain treatment. Nor do they have assurance that they are protected from the overprescribing of opioids, a class of drugs with serious and well-known safety risks. Therefore, on the surface, it appears that equity and racial inclusion are hallmarks of physician prescribing of postoperative breast cancer pain treatment. However, further interrogation reveals that ‘separate and somewhat equal’ is a more accurate characterization of their prescribing practices, based both on race and SES.

Heat stress illnesses, including heat stroke and heat exhaustion, represent a serious, persistent, and growing public health threat to military and civilian populations. Global climate change, due primarily to increased greenhouse gas concentrations in the atmosphere, has resulted in measured increases in temperature and humidity. Climate models project warming trends to continue in the future with very high confidence, resulting in more dangerous mean and extreme heat conditions. The associations between environmental heat indicators and observed adverse health outcomes have been increasingly studied for mortality endpoints and among elderly populations. This dissertation aimed to expand this investigation to heat illness morbidity outcomes among active-duty military servicemembers while assessing a range of heat indices. This is an assumed healthy, working-age population that is regularly exposed to outdoor heat in combination with high levels of exertion. Comparable civilian populations, in some respects, include athletes and outdoor laborers such as construction workers or farmers. In Chapter 2, we assessed annual rates of ambulatory encounters, hospitalizations, and reportable events among active-duty soldiers at ten US Army installations from 1991 to 2018 to produce rate ratios for estimation of future climate change impacts. In this chapter, we identified positive long-term associations between annual heat indices and heat stress illness hospitalization and reportable event outcomes. Chapter 3 assessed incident active-duty US military heat stress illness cases at 24 installations between 1998 and 2019 on a daily-scale, resulting in odds ratio exposure-lag-response curves applicable to near-term risk assessment. The daily-scale relationships betweenheat indices and case-defined heat stress illnesses were non-linear, with increasing odds ratios starting from mild temperature ranges, and displayed short-term delayed effects. Finally, Chapter 4 described demographic and body composition risk factor trends in the US military from 1998 to 2019. In this assessment, we identified a null trend for body mass index among heat stress illness subjects over the study period. Overall, our findings demonstrate a connection between temperature and humidity indicators and observed heat stress illness morbidity outcomes among multiple sets of indices and timescales. This dissertation highlights an urgent need for vigilant heat stress prevention and control measures to protect health and maintain performance in hot and humid environments.

Exposure to environmental chemicals has been shown to affect health status throughout the life course. Quantifying the joint effect of environmental mixtures over time is crucial to determine optimal intervention timing. Establishing causal relationships from environmental mixture data can be challenging due to various factors, including multicollinearity, complex functional form of exposure-response relationships, and residual unmeasured confounding. These issues can lead to biased estimates of treatment effects and pose significant obstacles in accurately identifying the true relationship between the pollutants and outcome variables. Causal interpretation of longitudinal environmental mixture studies encounters challenges. This dissertation explores the use of causal inference in environmental mixture studies, with a particular emphasis on addressing three key challenges. First, there is currently no statistical approach that allows simultaneous consideration of time-varying confounding, flexible modeling, and variable selection when examining the effect of multiple, correlated, and time-varying exposures. Second, the violation of a critical assumption that underpins all causal inference methods - namely, the absence of unmeasured confounding - poses a significant problem, as models that incorporate multiple environmental exposures may exacerbate the degree of bias depending on the nature of unmeasured confounding. Finally, there is a lack of computational resources that facilitate the application of newly developed causal inference methods for analyzing environmental mixtures. In Chapter 2, we introduce a causal inference method, g-BKMR, which enables to estimate nonlinear, non-additive effects of time-varying exposures and time-varying confounders, while also allowing for variable selection. An extensive simulation study shows that g-BKMR outperforms approaches that rely on correct model specification or do not account for time-dependent confounding, especially when correlation across time-varying exposures is high or the exposure-outcome relationship is nonlinear. We apply g-BKMR to quantify the contribution of metal mixtures to blood glucose in the Strong Heart Study, a prospective cohort study of American Indians. Chapter 3, we address the issue of time-varying unmeasured confounding when estimating time-varying effects of exposure to environmental chemicals. We review the Bayesian g-formula under the assumption of no unmeasured confounding, and then introduce a Bayesian probabilistic sensitivity analysis approach that can account for multiple, potentially time-varying, unmeasured confounders and continuous exposures. Through a simulation study, we demonstrate that the proposed algorithm outperforms the naive method, which fails to consider the influence of confounding. Chapter 4, introduces causalbkmr, a novel R package and can be currently be accessed on Github. causalbkmr is designed to support the implementation of g-BKMR, BKMR Causal Mediation Analysis, and Multiple Imputation BKMR, thereby offering a user-friendly and effective platform for executing these state-of-the-art methods in practice in the context of complex mixtures analysis. While the package bkmr is available, the novel package causalbkmr expands upon bkmr by enabling its application specifically to environmental mixture data within a causal inference framework. The implementation of these novel methodologies within causalbkmr allows for the extraction of causal interpretations, thus enhancing the analytical capabilities provided by the package. Chapter 5 concludes with a discussion and outlines potential future directions for investigation.

No description available.

Fine particulate matter (PM2.5) exposure is associated with increased risk of adverse cardiovascular health outcomes. Prior research shows that PM2.5 is disproportionately concentrated in communities of low socioeconomic status and with higher proportions of underrepresented ethnic and racial groups. However, little is known about the levels and trends in PM2.5 in American Indian (AI) communities. Prior work has estimated the risk of CVD outcomes from exposure to total PM2.5 and PM2.5 constituents in white, Black, Asian, and Hispanic populations; however, AI populations have been historically excluded from many of these studies. While certain behavioral and environmental CVD risk factors have been extensively studied in AI populations, the CVD health impacts of air pollution have not been previously characterized. In Chapter 2, we aimed to compare PM2.5 concentrations in AI- vs. non-AI-populated counties over time (2000 – 2018) in the contiguous US. We used a multi-criteria approach to classify counties as AI- or non-AI-populated. We ran linear mixed-effects models to estimate the difference in county-wide annual PM2.5 concentrations from monitoring sites and well-validated prediction models (measured and modeled PM2.5, respectively) in AI- vs. non-AI-populated counties, adjusting for population density and median household income. We estimated whether differences in AI- vs. non-AI-populated counties varied over time using interaction terms with calendar year. On average, adjusted measured PM2.5 concentrations in AI-populated counties were 0.79 μg/m3 (95%CI: 0.33, 1.26) lower than in non-AI-populated counties. However, this association was not constant over time; while in 2000, adjusted concentrations in AI-populated counties were 1.83 μg/m3 (95%CI: 1.53, 2.13) lower, by 2018, they were 0.84 μg/m3 (95%CI: 0.53, 1.15) higher than in non-AI-populated counties. Over the study period, measured PM2.5 mean concentrations in AI-populated counties decreased by 2.49 vs. 5.18 μg/m3 in non-AI-populated counties. Results were similar for satellite-based, modeled PM2.5. This study highlights disparities in PM2.5 trends between AI- and non-AI-populated counties over time, underscoring the need to strengthen air pollution regulations in tribal territories and areas where AI populations live. In Chapter 3, we further interrogate what components of PM2.5 could be contributing to the trends in total PM2.5. We estimated that adjusted concentrations of all six PM2.5 components in AI-populated counties were significantly lower than in non-AI-populated counties. However, component-specific trends varied over time. Sulfate and ammonium levels were significantly lower in AI- vs. non-AI-populated counties in 2000 but higher after 2011. Nitrate levels were consistently lower in AI- counties, while black carbon, organic matter, and soil levels showed inconsistent differences in AI- vs. non-AI-populated counties. This study highlights how differences in time trends of certain components by AI-populated county type, namely sulfate and ammonium, are driving steeper declines in total PM2.5 in non-AI vs. AI-populated counties, providing potential directives for air pollution regulations of key emissions sources on tribal and AI-populated lands. In Chapter 4, we estimated the effects of long-term PM2.5 exposure on CVD incidence, CVD mortality, and all-cause mortality in the Strong Heart Study (SHS), a longitudinal cohort of American Indian adults enrolled from centers in Arizona, Oklahoma, and North Dakota and South Dakota. We followed 2,115 participants from 2000–2019. Adjusted hazard ratios (95%CI) per 1μg/m3 increase in PM2.5 with CVD incidence, CVD mortality, and all-cause mortality were 1.09 (0.91, 1.30), 1.11 (0.91, 1.36), and 1.10 (0.96, 1.25), respectively. Center-specific models identified positive associations between PM2.5 and incident CHD (2.24 (1.40, 3.56)) and CVD (1.55 (1.05, 2.31)) in Arizona, marginally positive association between PM2.5 and CVD mortality in Oklahoma (1.29 (0.99, 1.68)), and null associations in North Dakota and South Dakota. This study assesses PM2.5 exposure and cardiovascular health effects in American Indian communities—addressing a critical gap in the representation of evidence in air pollution regulation. Further research on underlying mechanisms driving the unique associations observed across regions is needed.

Thesis (D. Tech. (Environmental Health)) -- Central University of technology, Free State, 2013 / Some epidemiological studies suggest that exposure to high levels of electromagnetic fields (EMFs) may be linked with the development of adverse health effects. However there is still controversy on this matter. Due to rapid technological growth in the modern society, employees in the welding and electrical industries are highly exposed to electromagnetic fields and may be at a high risk for developing occupational diseases. The health effects which may result from exposure to electromagnetic fields are related to the strength and frequency of the fields. This study was conducted to (i) assess the exposure levels to EMFs in the welding industry, (ii) determine the possible health risks associated with exposure levels, and (iii) develop a health and safety model to guide the industry on how to reduce exposure to EMFs. The study was conducted in one mega welding company in the Mangaung Metropolitan Municipality. Welders, fitters and office workers (88 in total) gave consent to participate in the study and completed questionnaires (ethical clearance attached). Measurements of extremely low frequency EMFs were taken in workshop A, workshop B and working offices. Measurements for magnetic fields were taken at distances of 1, 2 and 3 meters (m) from the EMFs sources. The exposure levels of magnetic fields were very high in the workshops, with welders and fitters exposed to about 7.6 microtesla (μT). Electric fields were relatively low in all workstations. Participants in the study were experiencing symptoms of ill health such as headaches, sleep disorders, fatigue and distress. The symptoms reported by the workers were similar in the both groups (exposed and control). There is no clear relationship between recorded exposure levels and the development of the reported symptoms. The health and safety model was developed to guide the industry to reduce exposure to electromagnetic fields. The model describes the implementation of engineering and administrative control measures in an effort to reduce exposure to EMFs. The model also highlights the importance of wearing personal protective equipment to shield against EMFs amongst others. This study suggests that occupational exposure to high levels of extremely low frequency EMFs may increase the risk for development of chronic diseases such as leukaemia, brain and breast cancer and other diseases among highly exposed employees. Implementation of safety measures is necessary to reduce exposure to EMFs.

Thesis (M. Tech. (Biomedical Technology)) -- Central University of technology, Free State, 2013 / Electromagnetic fields are present wherever electricity is created. The frequency range of these electromagnetic fields is from extremely low to extremely high. The fields present in domestic areas fall within the extremely low frequency range. These fields are created by domestic electrical appliances and telecommunication. There has been much debate on the effect of exposure to these fields on human health. Research has not yet been able to prove adverse effect of these fields on human health. In fact, the benefits of magneto therapy has been recognized and used for several decades. Recently a specific electromagnetic signal has been under investigation for its ability to stimulate the immune response. This signal is produced by a patented generator, called Immunent Activator. Studies performed with the Immunent Activator signal on farm animals revealed increased feed conversion and decreased intestinal lesions of animals with intestinal infections. Most of the research was performed on fish and fowls and evidence of similar findings in mammals is lacking. In the current study, mice were exposed to the Immunent BV signal for seven days, after which immune cell counts were performed and compared to the immune cell counts of a control group of mice which received no electromagnetic exposure. It was found that the T-lymphocyte population of immune cells in the exposed group of mice was statistically significantly higher than that of the control group. The neutrophil count was statistically significantly lower in the exposed group compared to the control group. These findings revealed evidence of immune stimulation in the mice which were exposed to the Immunent Activator signal. Suggestions for further research could be made with regard to specific mechanisms of immune stimulation. The findings of this and other related studies hold benefits for the farming and health industry.