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  5.     <title>UTas ePrints - Where the dust settles: a spatial investigation of respiratory disease and particulate air pollution in the Tamar Valley (1992-2006)</title>
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  13.     <meta content="Jabbour, Samya" name="eprints.creators_name" />
  14. <meta content="Samya.Jabbour@utas.edu.au" name="eprints.creators_id" />
  15. <meta content="thesis" name="eprints.type" />
  16. <meta content="2008-01-11 01:57:51" name="eprints.datestamp" />
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  19. <meta content="Where the dust settles: a spatial investigation of respiratory disease and particulate air pollution in the
  20. Tamar Valley (1992-2006)" name="eprints.title" />
  21. <meta content="unpub" name="eprints.ispublished" />
  22. <meta content="300800" name="eprints.subjects" />
  23. <meta content="public" name="eprints.full_text_status" />
  24. <meta content="spatial investigation, respiratory disease, particulate air pollution, Tamar Valley, Tasmania" name="eprints.keywords" />
  25. <meta content="The detrimental health effects of particulate air pollution have been well established
  26. through environmental health research worldwide. Fine or ‘respirable’ particulate
  27. matter derived from combustion sources has been linked to both acute and chronic
  28. respiratory and cardiovascular conditions, and premature death in the most susceptible
  29. of a population. The Tamar Valley in northern Tasmania has a significant winter air
  30. pollution problem. Launceston is the largest population centre in the valley (population
  31. approx. 67,000) and despite its size this small city has regularly recorded the highest
  32. levels of particulate pollution levels of any city in Australia. This is due largely to
  33. complex geographic and climatic processes that support cold air drainage and the
  34. formation of night-time temperature inversions in the valley over winter months.
  35. Under these conditions ground temperature drops and air pollution becomes trapped at
  36. ground level under a layer of dense cold air. Fine particulate matter from domestic
  37. wood heating contributes to around 88% of particulate load in Launceston compared to
  38. 65% in other Australian cities. Concern has therefore been raised for the respiratory
  39. health of Tamar Valley residents in recent years. Previous studies have assumed
  40. homogeneity of pollution exposure, and disease risk, across the landscape. This
  41. assumption is unrealistic, as recent research indicates that both the distribution of
  42. disease and the dispersal of particulate air pollution exhibit considerable spatial
  43. variation.
  44. This is the first study to look in detail at the spatial relationships between particulate
  45. air pollution and respiratory disease distribution in the Tamar Valley. Disease clustering
  46. was investigated and various environmental processes were explored in detail to
  47. explain the spatial disparity of disease distribution. Patterns of respiratory disease
  48. occurrence in the Tamar Valley were investigated through spatial analysis of 15 years
  49. (1992-2006) of de-identified hospital admissions records. Issues of confidentiality and
  50. geoprivacy in spatial public health studies were discussed in detail. Spatial distributions
  51. of Asthma, Bronchiolitis, Bronchitis and Chronic Obstructive Pulmonary Disease (COPD)
  52. were explored individually and in combined form. Data were explored for annual
  53. variations in disease distribution. This revealed that, while disease incidence generally
  54. declined over the study period, this decline was most noticeable around George Town
  55. in the north of the valley. Further analysis revealed little spatial variation in seasonal
  56. spatial patterns of disease occurrence across the valley, though disease cases
  57. generally were more numerous in winter. COPD incidence was found to be highly
  58. clustered in a small number of address locations thought to correspond to nursing
  59. homes and aged care facilities across the valley. It was therefore believed that COPD was more closely correlated with the locations of these facilities than with any
  60. geographic or climatic processes. Three techniques for the detection of disease clusters
  61. were applied (kernel density function, Getis Ord Gi* statistic and Kulldorff’s spatial
  62. scan statistic). Areas around George Town and the North Esk valley east of Launceston
  63. consistently showed elevated disease levels. However, considerable variation in the
  64. reporting of ‘significant’ clusters was noted between methods, and also with the same
  65. method at different spatial scales. Issues of statistical inference were therefore
  66. discussed.
  67. Several ‘exposure surfaces’ were created to approximate the winter dispersion of
  68. particulate air pollution in Launceston. Modelled air pollution concentrations were
  69. derived from TAPM (The Air Pollution Model), a prognostic air pollution dispersion
  70. model currently in use in Tasmania for environmental monitoring purposes. A digital
  71. elevation model was also classified into terrain features that are known to accumulate
  72. high levels of particulate pollution through the process of cold air drainage (i.e. lowlying
  73. channels and river flats). Spatial relationships between disease incidence and
  74. these air pollution ‘proxies’ were then explored in detail. Weak relationships were
  75. found between disease incidence and terrain features representing small channel and
  76. valleys. A ‘significant’ relationship was found between disease incidence and the valley
  77. floor, though issues of statistical inference were again discussed in this context. Spatial
  78. non-stationarity was detected in all relationships, indicating that global statistics
  79. inadequately define these relationships. A strong inverse relationship was found
  80. between modelled air pollution concentrations and disease incidence, indicating that
  81. disease rates were generally higher in areas outside the modelled air pollution plume
  82. derived by TAPM. TAPM concentrations were also found to closely mirror the underlying
  83. population distribution. The inability of TAPM to adequately predict pollution levels in
  84. areas outside major population centres, and various issues of socioeconomic
  85. confounding were discussed as possible explanations for this finding.
  86. Results generally revealed considerable variation in the spatial relationships between
  87. disease incidence and air pollution proxies used in this study. These results argue
  88. strongly for the spatial analysis of air pollution relationships to health outcomes, and
  89. the continued refinement of methods. None of these findings could have resulted from
  90. a purely temporal (non-spatial) investigation." name="eprints.abstract" />
  91. <meta content="2007-10" name="eprints.date" />
  92. <meta content="published" name="eprints.date_type" />
  93. <meta content="94" name="eprints.pages" />
  94. <meta content="University of Tasmania" name="eprints.institution" />
  95. <meta content="School of Geography and Environmental Studies" name="eprints.department" />
  96. <meta content="honours" name="eprints.thesis_type" />
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  472. 426." name="eprints.referencetext" />
  473. <meta content="Jabbour, Samya (2007) Where the dust settles: a spatial investigation of respiratory disease and particulate air pollution in the Tamar Valley (1992-2006). Honours thesis, University of Tasmania." name="eprints.citation" />
  474. <meta content="http://eprints.utas.edu.au/2992/1/1_Frontispiece.pdf" name="eprints.document_url" />
  475. <meta content="http://eprints.utas.edu.au/2992/2/2_Chapter_1.pdf" name="eprints.document_url" />
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  481. <meta content="http://eprints.utas.edu.au/2992/8/8_References.pdf" name="eprints.document_url" />
  482. <link rel="schema.DC" href="http://purl.org/DC/elements/1.0/" />
  483. <meta content="Where the dust settles: a spatial investigation of respiratory disease and particulate air pollution in the
  484. Tamar Valley (1992-2006)" name="DC.title" />
  485. <meta content="Jabbour, Samya" name="DC.creator" />
  486. <meta content="300800 Environmental Sciences" name="DC.subject" />
  487. <meta content="The detrimental health effects of particulate air pollution have been well established
  488. through environmental health research worldwide. Fine or ‘respirable’ particulate
  489. matter derived from combustion sources has been linked to both acute and chronic
  490. respiratory and cardiovascular conditions, and premature death in the most susceptible
  491. of a population. The Tamar Valley in northern Tasmania has a significant winter air
  492. pollution problem. Launceston is the largest population centre in the valley (population
  493. approx. 67,000) and despite its size this small city has regularly recorded the highest
  494. levels of particulate pollution levels of any city in Australia. This is due largely to
  495. complex geographic and climatic processes that support cold air drainage and the
  496. formation of night-time temperature inversions in the valley over winter months.
  497. Under these conditions ground temperature drops and air pollution becomes trapped at
  498. ground level under a layer of dense cold air. Fine particulate matter from domestic
  499. wood heating contributes to around 88% of particulate load in Launceston compared to
  500. 65% in other Australian cities. Concern has therefore been raised for the respiratory
  501. health of Tamar Valley residents in recent years. Previous studies have assumed
  502. homogeneity of pollution exposure, and disease risk, across the landscape. This
  503. assumption is unrealistic, as recent research indicates that both the distribution of
  504. disease and the dispersal of particulate air pollution exhibit considerable spatial
  505. variation.
  506. This is the first study to look in detail at the spatial relationships between particulate
  507. air pollution and respiratory disease distribution in the Tamar Valley. Disease clustering
  508. was investigated and various environmental processes were explored in detail to
  509. explain the spatial disparity of disease distribution. Patterns of respiratory disease
  510. occurrence in the Tamar Valley were investigated through spatial analysis of 15 years
  511. (1992-2006) of de-identified hospital admissions records. Issues of confidentiality and
  512. geoprivacy in spatial public health studies were discussed in detail. Spatial distributions
  513. of Asthma, Bronchiolitis, Bronchitis and Chronic Obstructive Pulmonary Disease (COPD)
  514. were explored individually and in combined form. Data were explored for annual
  515. variations in disease distribution. This revealed that, while disease incidence generally
  516. declined over the study period, this decline was most noticeable around George Town
  517. in the north of the valley. Further analysis revealed little spatial variation in seasonal
  518. spatial patterns of disease occurrence across the valley, though disease cases
  519. generally were more numerous in winter. COPD incidence was found to be highly
  520. clustered in a small number of address locations thought to correspond to nursing
  521. homes and aged care facilities across the valley. It was therefore believed that COPD was more closely correlated with the locations of these facilities than with any
  522. geographic or climatic processes. Three techniques for the detection of disease clusters
  523. were applied (kernel density function, Getis Ord Gi* statistic and Kulldorff’s spatial
  524. scan statistic). Areas around George Town and the North Esk valley east of Launceston
  525. consistently showed elevated disease levels. However, considerable variation in the
  526. reporting of ‘significant’ clusters was noted between methods, and also with the same
  527. method at different spatial scales. Issues of statistical inference were therefore
  528. discussed.
  529. Several ‘exposure surfaces’ were created to approximate the winter dispersion of
  530. particulate air pollution in Launceston. Modelled air pollution concentrations were
  531. derived from TAPM (The Air Pollution Model), a prognostic air pollution dispersion
  532. model currently in use in Tasmania for environmental monitoring purposes. A digital
  533. elevation model was also classified into terrain features that are known to accumulate
  534. high levels of particulate pollution through the process of cold air drainage (i.e. lowlying
  535. channels and river flats). Spatial relationships between disease incidence and
  536. these air pollution ‘proxies’ were then explored in detail. Weak relationships were
  537. found between disease incidence and terrain features representing small channel and
  538. valleys. A ‘significant’ relationship was found between disease incidence and the valley
  539. floor, though issues of statistical inference were again discussed in this context. Spatial
  540. non-stationarity was detected in all relationships, indicating that global statistics
  541. inadequately define these relationships. A strong inverse relationship was found
  542. between modelled air pollution concentrations and disease incidence, indicating that
  543. disease rates were generally higher in areas outside the modelled air pollution plume
  544. derived by TAPM. TAPM concentrations were also found to closely mirror the underlying
  545. population distribution. The inability of TAPM to adequately predict pollution levels in
  546. areas outside major population centres, and various issues of socioeconomic
  547. confounding were discussed as possible explanations for this finding.
  548. Results generally revealed considerable variation in the spatial relationships between
  549. disease incidence and air pollution proxies used in this study. These results argue
  550. strongly for the spatial analysis of air pollution relationships to health outcomes, and
  551. the continued refinement of methods. None of these findings could have resulted from
  552. a purely temporal (non-spatial) investigation." name="DC.description" />
  553. <meta content="2007-10" name="DC.date" />
  554. <meta content="Thesis" name="DC.type" />
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  679.     <h1 class="ep_tm_pagetitle">Where the dust settles: a spatial investigation of respiratory disease and particulate air pollution in the Tamar Valley (1992-2006)</h1>
  680.     <p style="margin-bottom: 1em" class="not_ep_block"><span class="person_name">Jabbour, Samya</span> (2007) <xhtml:em>Where the dust settles: a spatial investigation of respiratory disease and particulate air pollution in the Tamar Valley (1992-2006).</xhtml:em> Honours thesis, University of Tasmania.</p><p style="margin-bottom: 1em" class="not_ep_block"></p><table style="margin-bottom: 1em" class="not_ep_block"><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4043' );" href="http://eprints.utas.edu.au/2992/1/1_Frontispiece.pdf" onmouseout="EPJS_HidePreview( event, 'doc_preview_4043' );"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" class="ep_doc_icon" border="0" /></a><div class="ep_preview" id="doc_preview_4043"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/2992/thumbnails/1/preview.png" class="ep_preview_image" border="0" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/2992/1/1_Frontispiece.pdf"><span class="ep_document_citation">PDF (Front Matter)</span></a> - 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Requires a PDF viewer<br />1251Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4048' );" href="http://eprints.utas.edu.au/2992/6/6_Chapter_5.pdf" onmouseout="EPJS_HidePreview( event, 'doc_preview_4048' );"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" class="ep_doc_icon" border="0" /></a><div class="ep_preview" id="doc_preview_4048"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/2992/thumbnails/6/preview.png" class="ep_preview_image" border="0" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/2992/6/6_Chapter_5.pdf"><span class="ep_document_citation">PDF (Chapter 5)</span></a> - Requires a PDF viewer<br />1166Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4049' );" href="http://eprints.utas.edu.au/2992/7/7_Conclusion.pdf" onmouseout="EPJS_HidePreview( event, 'doc_preview_4049' );"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" class="ep_doc_icon" border="0" /></a><div class="ep_preview" id="doc_preview_4049"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/2992/thumbnails/7/preview.png" class="ep_preview_image" border="0" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/2992/7/7_Conclusion.pdf"><span class="ep_document_citation">PDF (Conclusion)</span></a> - Requires a PDF viewer<br />59Kb</td></tr><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_4050' );" href="http://eprints.utas.edu.au/2992/8/8_References.pdf" onmouseout="EPJS_HidePreview( event, 'doc_preview_4050' );"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" class="ep_doc_icon" border="0" /></a><div class="ep_preview" id="doc_preview_4050"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/2992/thumbnails/8/preview.png" class="ep_preview_image" border="0" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/2992/8/8_References.pdf"><span class="ep_document_citation">PDF (References)</span></a> - Requires a PDF viewer<br />75Kb</td></tr></table><div class="not_ep_block"><h2>Abstract</h2><p style="padding-bottom: 16px; text-align: left; margin: 1em auto 0em auto">The detrimental health effects of particulate air pollution have been well established&#13;
  681. through environmental health research worldwide. Fine or ‘respirable’ particulate&#13;
  682. matter derived from combustion sources has been linked to both acute and chronic&#13;
  683. respiratory and cardiovascular conditions, and premature death in the most susceptible&#13;
  684. of a population. The Tamar Valley in northern Tasmania has a significant winter air&#13;
  685. pollution problem. Launceston is the largest population centre in the valley (population&#13;
  686. approx. 67,000) and despite its size this small city has regularly recorded the highest&#13;
  687. levels of particulate pollution levels of any city in Australia. This is due largely to&#13;
  688. complex geographic and climatic processes that support cold air drainage and the&#13;
  689. formation of night-time temperature inversions in the valley over winter months.&#13;
  690. Under these conditions ground temperature drops and air pollution becomes trapped at&#13;
  691. ground level under a layer of dense cold air. Fine particulate matter from domestic&#13;
  692. wood heating contributes to around 88% of particulate load in Launceston compared to&#13;
  693. 65% in other Australian cities. Concern has therefore been raised for the respiratory&#13;
  694. health of Tamar Valley residents in recent years. Previous studies have assumed&#13;
  695. homogeneity of pollution exposure, and disease risk, across the landscape. This&#13;
  696. assumption is unrealistic, as recent research indicates that both the distribution of&#13;
  697. disease and the dispersal of particulate air pollution exhibit considerable spatial&#13;
  698. variation.&#13;
  699. This is the first study to look in detail at the spatial relationships between particulate&#13;
  700. air pollution and respiratory disease distribution in the Tamar Valley. Disease clustering&#13;
  701. was investigated and various environmental processes were explored in detail to&#13;
  702. explain the spatial disparity of disease distribution. Patterns of respiratory disease&#13;
  703. occurrence in the Tamar Valley were investigated through spatial analysis of 15 years&#13;
  704. (1992-2006) of de-identified hospital admissions records. Issues of confidentiality and&#13;
  705. geoprivacy in spatial public health studies were discussed in detail. Spatial distributions&#13;
  706. of Asthma, Bronchiolitis, Bronchitis and Chronic Obstructive Pulmonary Disease (COPD)&#13;
  707. were explored individually and in combined form. Data were explored for annual&#13;
  708. variations in disease distribution. This revealed that, while disease incidence generally&#13;
  709. declined over the study period, this decline was most noticeable around George Town&#13;
  710. in the north of the valley. Further analysis revealed little spatial variation in seasonal&#13;
  711. spatial patterns of disease occurrence across the valley, though disease cases&#13;
  712. generally were more numerous in winter. COPD incidence was found to be highly&#13;
  713. clustered in a small number of address locations thought to correspond to nursing&#13;
  714. homes and aged care facilities across the valley. It was therefore believed that COPD was more closely correlated with the locations of these facilities than with any&#13;
  715. geographic or climatic processes. Three techniques for the detection of disease clusters&#13;
  716. were applied (kernel density function, Getis Ord Gi* statistic and Kulldorff’s spatial&#13;
  717. scan statistic). Areas around George Town and the North Esk valley east of Launceston&#13;
  718. consistently showed elevated disease levels. However, considerable variation in the&#13;
  719. reporting of ‘significant’ clusters was noted between methods, and also with the same&#13;
  720. method at different spatial scales. Issues of statistical inference were therefore&#13;
  721. discussed.&#13;
  722. Several ‘exposure surfaces’ were created to approximate the winter dispersion of&#13;
  723. particulate air pollution in Launceston. Modelled air pollution concentrations were&#13;
  724. derived from TAPM (The Air Pollution Model), a prognostic air pollution dispersion&#13;
  725. model currently in use in Tasmania for environmental monitoring purposes. A digital&#13;
  726. elevation model was also classified into terrain features that are known to accumulate&#13;
  727. high levels of particulate pollution through the process of cold air drainage (i.e. lowlying&#13;
  728. channels and river flats). Spatial relationships between disease incidence and&#13;
  729. these air pollution ‘proxies’ were then explored in detail. Weak relationships were&#13;
  730. found between disease incidence and terrain features representing small channel and&#13;
  731. valleys. A ‘significant’ relationship was found between disease incidence and the valley&#13;
  732. floor, though issues of statistical inference were again discussed in this context. Spatial&#13;
  733. non-stationarity was detected in all relationships, indicating that global statistics&#13;
  734. inadequately define these relationships. A strong inverse relationship was found&#13;
  735. between modelled air pollution concentrations and disease incidence, indicating that&#13;
  736. disease rates were generally higher in areas outside the modelled air pollution plume&#13;
  737. derived by TAPM. TAPM concentrations were also found to closely mirror the underlying&#13;
  738. population distribution. The inability of TAPM to adequately predict pollution levels in&#13;
  739. areas outside major population centres, and various issues of socioeconomic&#13;
  740. confounding were discussed as possible explanations for this finding.&#13;
  741. Results generally revealed considerable variation in the spatial relationships between&#13;
  742. disease incidence and air pollution proxies used in this study. These results argue&#13;
  743. strongly for the spatial analysis of air pollution relationships to health outcomes, and&#13;
  744. the continued refinement of methods. None of these findings could have resulted from&#13;
  745. a purely temporal (non-spatial) investigation.</p></div><table style="margin-bottom: 1em" cellpadding="3" class="not_ep_block" border="0"><tr><th valign="top" class="ep_row">Item Type:</th><td valign="top" class="ep_row">Thesis (Honours)</td></tr><tr><th valign="top" class="ep_row">Keywords:</th><td valign="top" class="ep_row">spatial investigation, respiratory disease, particulate air pollution, Tamar Valley, Tasmania</td></tr><tr><th valign="top" class="ep_row">Subjects:</th><td valign="top" class="ep_row"><a href="http://eprints.utas.edu.au/view/subjects/300800.html">300000 Agricultural, Veterinary and Environmental Sciences &gt; 300800 Environmental Sciences</a></td></tr><tr><th valign="top" class="ep_row">ID Code:</th><td valign="top" class="ep_row">2992</td></tr><tr><th valign="top" class="ep_row">Deposited By:</th><td valign="top" class="ep_row"><span class="ep_name_citation"><span class="person_name">Ms Sandy von Allmen</span></span></td></tr><tr><th valign="top" class="ep_row">Deposited On:</th><td valign="top" class="ep_row">11 Jan 2008 12:57</td></tr><tr><th valign="top" class="ep_row">Last Modified:</th><td valign="top" class="ep_row">11 Jan 2008 12:57</td></tr><tr><th valign="top" class="ep_row">ePrint Statistics:</th><td valign="top" class="ep_row"><a target="ePrintStats" href="/es/index.php?action=show_detail_eprint;id=2992;">View statistics for this ePrint</a></td></tr></table><p align="right">Repository Staff Only: <a href="http://eprints.utas.edu.au/cgi/users/home?screen=EPrint::View&amp;eprintid=2992">item control page</a></p>
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