Environment and Human Health in the Anthropocene: Interaction Between Natural and Social Systems in Coastal Tanzania
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».