Environment and Human Health in the Anthropocene: Interaction Between Natural and Social Systems in Coastal Tanzania
Bibliographic record
Abstract
Coastal Tanzania, a region of historical and geopolitical importance in the western Indian Ocean, is a place where the problem of rapid environmental change is inextricably entwined with the challenges of development. In this region, although the fingerprint of the anthropocene has been discernible over the last century, there is paucity of research on how the population has interacted with the changing environment to generate disparities in perceptions of climate change and human health outcomes. The objectives of this thesis are four-fold: to assess barriers to climate change adaptation based on context (place), to explain group disparities in barriers to climate change adaptation based on relative well-being (income poverty), to evaluate description-based and experienced-based perceptions of environmental change, and to analyse the relationship between subjective and objective health status, on the one hand, and public perception of human health risks associated with climate change, on the other hand. Cross-sectional survey data on 1253 individuals (606 males and 647 females) were collected during March and September 2013 to make inferences about the population in this region. This was complemented with 50-year (1960-2009) meteorological data on rainfall and temperature. Multivariate regression, counterfactual decomposition, multinomial regression and time-series were used in the quantitative analyses. The results show that barriers to adaptation to climate change mainly reflect strong place-specific differences among the population. Disparities in barriers to climate adaptation between poor and nonpoor residents are mainly attributable to group differences in the magnitudes of the determinants (endowments) rather than group differences in the effects of the determinants (coefficients). There is agreement between respondents’ perceptions of temperature change and available scientific climatic evidence over the 50-year period although results on perception of rainfall patterns were varied. Generally, higher ratings on subjective health status were associated with lower scores on perceived human health risks of climate change. Concerning objective health status, the results were varied. Individuals who indicated that they had been previously diagnosed with hepatitis, skin conditions or tuberculosis had lower scores on perceived health risks of climate change unlike their counterparts who stated that they had been previously diagnosed with malaria in the past 12 months or had been diagnosed with HIV/AIDS. These relationships persist even when biosocial and sociocultural attributes are taken into consideration. The results underscore the complex ways in which objective and subjective health interact with biosocial, sociocultural and contextual factors to shape public perception on health risks associated with climate change. At least two policy implications originate from the findings of this dissertation. First, disentangling the complex indirect pathways among barriers to climate change adaptation, place-based attributes and relative well-being is a challenging research endeavour that requires the development of new partnerships to provide more accurate data. Given the complex mechanism by which experiential climate change acts, collectively, with compositional and contextual factors to influence public perception of climate change-related human health risks, it is probably apt to approach the study of environmental change and human health using integrative frameworks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".