An environmental gap analysis at a university campus.

The environmental quality of the learning environment is a critical element for good health and well-being among beneficiaries of tertiary institutions, ultimately influencing staff productivity and learning performance of students. High population densities, inefficient resource use and unique microenvironments within tertiary institutions can result in myriad environmental challenges which require targeted solutions. An environmental gap analysis is a pragmatic and evidence-based approach that can be used to evaluate the environmental quality of institutions through the provision of baseline data and comparison to relevant environmental standards. In this study, an environmental gap analysis was conducted at university campus, where air, noise, water and soil data were collected for 12 weeks at indoor and outdoor sites. The data obtained were averaged, graphed and benchmarked using relevant local and international guidelines to identify gaps. Additionally, the data were tested using two-way analysis of variance (ANOVA). Generally, the levels of parameters monitored were acceptable and within respective local and international guidelines; however, air temperature and relative humidity of the indoor cafeteria as well as turbidity of tap water were not in conformance with guidelines. Improvements in maintenance of ventilation systems and water distribution infrastructure are recommended along with further investigations of drinking water and indoor air quality at the campus. The insight obtained in this study provided important baseline data, in an area where there is a dearth of information, from which deficiencies can be identified and evidence-based recommendations can be made.

Evaluating Cardiovascular Disease (CVD) risk scores for participants with known CVD and non-CVD in a multiracial/ethnic Caribbean sample.

BACKGROUND: Cardiovascular Disease (CVD) risk prediction models have been useful in estimating if individuals are at low, intermediate, or high risk, of experiencing a CVD event within some established time frame, usually 10 years. Central to this is the concern in Trinidad and Tobago of using pre-existing CVD risk prediction methods, based on populations in the developed world (e.g. ASSIGN, Framingham and QRISK®2), to establish risk for its multiracial/ethnic Caribbean population. The aim of this study was to determine which pre-existing CVD risk method is best suited for predicting CVD risk for individuals in this population. METHOD: A survey was completed by 778 participants, 526 persons with no prior CVD, and 252 who previously reported a CVD event. Lifestyle and biometric data was collected from non-CVD participants, while for CVD participants, medical records were used to collect data at the first instance of CVD. The performances of three CVD risk prediction models (ASSIGN, Framingham and QRISK®2) were evaluated using their calculated risk scores. RESULTS: All three models (ASSIGN, Framingham and QRISK®2) identified less than 62% of cases (CVD participants) with a high proportion of false-positive predictions to true predictions as can be seen by positive predictabilities ranging from 78% (ASSIGN and Framingham) to 87% (QRISK®2). Further, for all three models, individuals whose scores fell into the misclassification range were 2X more likely to be individuals who had experienced a prior CVD event as opposed to healthy individuals. CONCLUSION: The ASSIGN, Framingham and QRISK®2 models should be utilised with caution on a Trinidad and Tobago population of intermediate and high risk for CVD since these models were found to have underestimated the risk for individuals with CVD up to 2.5 times more often than they overestimated the risk for healthy persons.

Health Dynamics in the Built Environment: An Urban Intensity Perspective - An Exploratory Study in Trinidad and Tobago.

The built environment encompasses the physical components of the environment, inclusive of infrastructure, households, buildings, streets, and open spaces, within which individuals reside and carry out their daily activities. It affects both indirectly and directly on the outdoor and indoor physical environment as well as the socio-economic environment. The elements which comprise the built environment and those of the physical and socio-economic environments, which are affected by it, are recognised as key determinants of health. In this study, health dynamics in the built environment are explored along the urban-rural gradient in Trinidad and Tobago. The gradient is measured by a statistically validated Urban Intensity Index developed previously, using physical data from the built environment. Published physical health data from National Surveys as well as data collected on perceptions of health care access and environmental quality are utilised in conjunction with the Urban Intensity Index values to model chronic illness. Multivariate statistical analysis and maps are used to explore and illustrate these dynamics. Ultimately, the outputs of this study can potentially support efforts to diminish the gap between rhetoric and reality, through provision of critical information for policy and decision making, as the global development agenda moves towards evidence-based policy making.