Issues in the statistical analysis of small area health data
1999; Wiley; Volume: 18; Issue: 17-18 Linguagem: Inglês
10.1002/(sici)1097-0258(19990915/30)18
ISSN1097-0258
Autores Tópico(s)Nutritional Studies and Diet
ResumoStatistics in MedicineVolume 18, Issue 17-18 p. 2377-2399 Research Article Issues in the statistical analysis of small area health data Jon Wakefield, Corresponding Author Jon Wakefield Small Area Health Statistics Unit, Department of Epidemiology and Public Health, Imperial College School of Medicine, St Mary's Campus, Norfolk Place, London W2 1PG, U.K.Small Area Health Statistics Unit, Department of Epidemiology and Public Health, Imperial College School of Medicine, St Mary's Campus, Norfolk Place, London W2 1PG, U.K.Search for more papers by this authorPaul Elliott, Paul Elliott Small Area Health Statistics Unit, Department of Epidemiology and Public Health, Imperial College School of Medicine, St Mary's Campus, Norfolk Place, London W2 1PG, U.K.Search for more papers by this author Jon Wakefield, Corresponding Author Jon Wakefield Small Area Health Statistics Unit, Department of Epidemiology and Public Health, Imperial College School of Medicine, St Mary's Campus, Norfolk Place, London W2 1PG, U.K.Small Area Health Statistics Unit, Department of Epidemiology and Public Health, Imperial College School of Medicine, St Mary's Campus, Norfolk Place, London W2 1PG, U.K.Search for more papers by this authorPaul Elliott, Paul Elliott Small Area Health Statistics Unit, Department of Epidemiology and Public Health, Imperial College School of Medicine, St Mary's Campus, Norfolk Place, London W2 1PG, U.K.Search for more papers by this author First published: 31 August 1999 https://doi.org/10.1002/(SICI)1097-0258(19990915/30)18:17/18 3.0.CO;2-GCitations: 51AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract The availability of geographically indexed health and population data, with advances in computing, geographical information systems and statistical methodology, have opened the way for serious exploration of small area health statistics based on routine data. Such analyses may be used to address specific questions concerning health in relation to sources of pollution, to investigate clustering of disease or for hypothesis generation. We distinguish four types of analysis: disease mapping; geographic correlation studies; the assessment of risk in relation to a prespecified point or line source, and cluster detection and disease clustering. A general framework for the statistical analysis of small area studies will be considered. This framework assumes that populations at risk arise from inhomogeneous Poisson processes. Disease cases are then realizations of a thinned Poisson process where the risk of disease depends on the characteristics of the person, time and spatial location. Difficulties of analysis and interpretation due to data inaccuracies and aggregation will be addressed with particular reference to ecological bias and confounding. The use of errors-in-variables modelling in small area analyses will be discussed. Copyright © 1999 John Wiley & Sons, Ltd. REFERENCES 1 Clayton, D. G., Bernardinelli, L. and Montomoli, C. 'Spatial correlation in ecological analysis', International Journal of Epidemiology, 22, 1193–1202 (1993).Medline 10.1093/ije/22.6.1193 CASPubMedWeb of Science®Google Scholar 2 Alexander, F. E., Williams, J., Cartwright, R. A. and Ricketts, T. J. 'A specialist leukaemia/lymphoma registry in the UK. Part 2: clustering of Hodgkin's disease', British Journal of Cancer, 60, 948–952 (1989).Medline 10.1038/bjc.1989.396 CASPubMedWeb of Science®Google Scholar 3 Baris, Y. I., Simonato, L., Atrinli, M., Pooley, S., Saracci, R., Skidmore, J. and Wagner, C. 'Epidemiological and environmental evidence of the health effects of exposure to erionite fibres: a four year study in the Cappodocian region of Turkey', International Journal of Cancer, 39, 10–17 (1987).Medline 10.1002/ijc.2910390104 CASPubMedWeb of Science®Google Scholar 4 Marshall, R. 'A review of methods for the statistical analysis of spatial patterns of disease', Journal of the Royal Statistical Society, Series A, 154, 421–441 (1991). 10.2307/2983152 Web of Science®Google Scholar 5 Alexander, F. and Cuzick, J. ' Methods for the assessment of disease clusters', in P. Elliott, J. Cuzick, D. English and R. Stern (eds), Geographical and Environmental Epidemiology: Methods for Small-area Studies, Oxford University Press, Oxford, 1992, pp. 238–250. Web of Science®Google Scholar 6 Clayton, D. G. and Bernardinelli, L. ' Bayesian methods for mapping disease risk', in P. Elliott, J. Cuzick, D. English and R. Stern (eds), Geographical and Environmental Epidemiology: Methods for Small-area Studies, Oxford University Press, Oxford, 1992, pp. 205–220. Google Scholar 7 Elliott, P., Martuzzi, M. and Shaddick, G. 'Spatial statistical methods in environmental epidemiology: a critique', Statistical Methods in Medical Research, 4, 149–161 (1995). 10.1177/096228029500400204 CASGoogle Scholar 8 Alexander, F. E. and Boyle, P. Methods for Investigating Localised Clustering of Disease, International Agency for Research on Cancer Scientific Publications, No. 135, 1996. Google Scholar 9 Diamond, I. ' Population counts in small areas', in P. Elliott, J. Cuzick, D. English and R. Stern (eds), Geographical and Environmental Epidemiology: Methods for Small-area Studies, Oxford University Press, Oxford, 1992, pp. 96–105. Google Scholar 10 Simpson, S., Tye, R. and Diamond, I. ' What was the real population of local areas in mid-1991', Estimating with Confidence Project Working Paper 10, 1995. Google Scholar 11 Cressie, N. A. C. Statistics for Spatial Data, Wiley, New York, 1991. Google Scholar 12 Briggs, D. J., Collins, S., Elliott, P., Fischer, P., Kingham, S., Lebret, E., Pryl, K., Van Reeuwijk, H., Smallbone, K. and Van Der Veen, A. 'Mapping urban air pollution using GIS: a regression-based approach', International Journal of Geographical Information Systems, 11, 699–718 (1997). 10.1080/136588197242158 Web of Science®Google Scholar 13 Elliott, P., Shaddick, G., Kleinschmidt, I., Jolley, D., Walls, P., Beresford, J. and Grundy, C. 'Cancer incidence near municipal solid waste incinerators in Great Britain', British Journal of Cancer, 73, 702–707 (1996).Medline 10.1038/bjc.1996.122 CASPubMedWeb of Science®Google Scholar 14 Whittemore, A. S. and Gong, G. 'Poisson regression with misclassified counts: application to cervical cancer mortality rates', Applied Statistics, 40, 81–93 (1991). 10.2307/2347906 CASPubMedWeb of Science®Google Scholar 15 Wakefield, J. C. and Morris, S. E. ' Spatial dependence and errors-in-variables in environmental epidemiology', in J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith (eds), Proceedings of the Sixth Valencia Meeting on Bayesian Statistics, Wiley, 1999, pp. 657–684. Web of Science®Google Scholar 16 Carstairs, V. and Morris, R. Deprivation and Health in Scotland, Aberdeen University Press, Aberdeen, 1991. Google Scholar 17 Richardson, S. ' Statistical methods for geographical correlation studies', in P. Elliott, J. Cuzick, D. English and R. Stern (eds), Geographical and Environmental Epidemiology: Methods for Small-area Studies, Oxford University Press, Oxford, 1992, pp. 181–204. Web of Science®Google Scholar 18 Richardson, S., Stucker, I. and Hémon, D. 'Comparison of relative risks obtained in ecological and individual studies: some methodological considerations', International Journal of Epidemiology, 16, 111–119 (1987).Medline 10.1093/ije/16.1.111 CASPubMedWeb of Science®Google Scholar 19 Piantadosi, S., Byar, D. P. and Green, S. B. 'The ecological fallacy', American Journal of Epidemiology, 127, 893–904 (1988).Medline 10.1093/oxfordjournals.aje.a114892 CASPubMedWeb of Science®Google Scholar 20 Greenland, S. and Robins, J. 'Ecological studies: biases, misconceptions and counterexamples', American Journal of Epidemiology, 139, 747–760 (1994).Medline 10.1093/oxfordjournals.aje.a117069 CASPubMedWeb of Science®Google Scholar 21 Diggle, P. 'A point process modelling approach to raised incidence of a rare phenomenon in the vicinity of a prespecified point', Journal of the Royal Statistical Society, Series A, 153, 340–362 (1990). 10.2307/2982977 Google Scholar 22 Diggle, P. and Elliott, P. 'Disease risk near point sources: Statistical analyses for analyses using individually or spatially aggregated data', Journal of Epidemiology and Community Health, 49, S20–S27 (1995).Medline 10.1136/jech.49.Suppl_2.S20 PubMedWeb of Science®Google Scholar 23 Diggle, P. J. and Rowlingson, B. S. 'A conditional approach to point process modelling of raised incidence', Journal of the Royal Statistical Society, Series A, 157, 433–440 (1994). 10.2307/2983529 PubMedWeb of Science®Google Scholar 24 Bithell, J. F. 'An application of density estimation to geographical epidemiology', Statistics in Medicine, 9, 691–701 (1990).Medline 10.1002/sim.4780090616 CASPubMedWeb of Science®Google Scholar 25 Lawson, A. B. and Williams, F. L. R. 'Applications of extraction mapping in environmental epidemiology', Statistics in Medicine, 12, 1249–1258 (1993).Medline 10.1002/sim.4780121306 CASPubMedWeb of Science®Google Scholar 26 Kelsall, J. E. and Diggle, P. J. 'Kernel estimation of relative risk', Bernoulli, 1, 3–16 (1995). 10.2307/3318678 Google Scholar 27 Kelsall, J. E. and Diggle, P. J. 'Non-parametric estimation of spatial variation in relative risk', Statistics in Medicine, 14, 2335–2342 (1995).Medline 10.1002/sim.4780142106 CASPubMedWeb of Science®Google Scholar 28 Kelsall, J. E. and Diggle, P. J. 'Spatial variation in risk: a nonparametric binary regression approach', Applied Statistics, 47, 559–573 (1998). 10.1111/1467-9876.00128 Web of Science®Google Scholar 29 Hastie, T. J. and Tibshirani, R. J. Generalized Additive Models, Chapman and Hall, London, 1990. Web of Science®Google Scholar 30 Cook-Mozaffari, P., Darby, S., Doll, R., Forman, D., Hermon, C., Pike, M. C. and Vincent, T. 'Geographical variation in mortality from leukaemia and other cancers in England and Wales in relation to proximity to nuclear installations, 1967–78', British Journal of Cancer, 59, 476–485 (1989).Medline 10.1038/bjc.1989.99 CASPubMedWeb of Science®Google Scholar 31 Waller, L. A., Turnbull, B. W., Clark, L. C. and Nasca, P. ' Spatial pattern analyses to detect rare disease clusters', in L. Lange, L. Ryan, L. Billard, D. Brillinger, L. Conquest and J. Greenhouse (eds), Case Studies in Biometry, Wiley, New York, 1994, pp. 3–23. Google Scholar 32 Openshaw, S., Craft, A. W., Charlton, M. and Birch, J. M. 'Investigation of leukaemia clusters by use of a geographical analysis machine', Lancet, i, 272–273 (1988).Medline 10.1016/S0140-6736(88)90352-2 CASGoogle Scholar 33 Turnbull, B. W., Iwano, E. J., Burnett, W. S., Howe, H. L. and Clark, L. C. 'Monitoring for clusters of disease: application to leukaemia incidence in upstate New York', American Journal of Epidemiology, Supplement 1, S136–S143 (1990).Medline CASPubMedGoogle Scholar 34 Besag, J. and Newell, J. 'The detection of clusters in rare diseases', Journal of the Royal Statistical Society, Series A, 154, 143–155 (1991). 10.2307/2982708 Web of Science®Google Scholar 35 Cuzick, J. and Edwards, R. 'Spatial clustering for inhomogeneous populations', Journal of the Royal Statistical Society, Series B, 52, 73–104 (1990). 10.1111/j.2517-6161.1990.tb01773.x Web of Science®Google Scholar 36 Diggle, P. and Chetwynd, A. 'Second-order analysis of spatial clustering for inhomogeneous populations', Biometrics, 47, 1155–1163 (1991).Medline 10.2307/2532668 CASPubMedWeb of Science®Google Scholar 37 Schulman, J., Selvin, S. and Merrill, D. W. 'Density equalised map projections: a method for analysing clustering around a fixed point', Statistics in Medicine, 7, 491–505 (1988).Medline 10.1002/sim.4780070406 CASPubMedWeb of Science®Google Scholar 38 Clayton, D. G. and Kaldor, J. 'Empirical Bayes estimates of age-standardized relative risks for use in disease mapping', Biometrics, 43, 671–682 (1987).Medline 10.2307/2532003 CASPubMedWeb of Science®Google Scholar 39 Eaton, N., Shaddick, G., Dolk, H. and Elliott, P. 'Small-area study of the incidence of neoplasms of the brain and central nervous system among adults in the West Midlands', British Journal of Cancer, 75, 1080–1083 (1997).Medline 10.1038/bjc.1997.184 CASPubMedWeb of Science®Google Scholar 40 Besag, J. and Kooperberg, C. 'On conditional and intrinsic autoregressions', Biometrika, 82, 733–746 (1995). Web of Science®Google Scholar 41 Besag, J., York, J. and Mollié, A. 'Bayesian image restoration with two applications in spatial statistics', Annals of the Institute of Statistics and Mathematics, 43, 1–59 (1991). 10.1007/BF00116466 PubMedWeb of Science®Google Scholar 42 Wolpert, R. L. and Ickstadt, K. 'Poisson/gamma random field models for spatial statistics', Biometrika, 85, 251–267 (1998). 10.1093/biomet/85.2.251 Web of Science®Google Scholar 43 Stone, R. 'Investigations of excess environmental risks around putative source: statistical problems and a proposed test', Statistics in Medicine, 7, 649–660 (1988).Medline 10.1002/sim.4780070604 CASPubMedWeb of Science®Google Scholar 44 Morton-Jones, T., Diggle, P. and Elliott, P. 'Investigation of excess environmental risk around putative sources: Stone's test with covariate adjustment', Statistics in Medicine, 18, 189–197 (1999).Medline 10.1002/(SICI)1097-0258(19990130)18:2 3.0.CO;2-Y CASPubMedWeb of Science®Google Scholar 45 Lawson, A. 'On the analysis of mortality events associated with a prespecified fixed point', Journal of the Royal Statistical Society, Series A, 156, 363–377 (1993). 10.2307/2983063 CASPubMedWeb of Science®Google Scholar 46 Diggle, P. J., Morris, S. E. Elliott, P. and Shaddick, G. 'Regression modelling of disease risk in relation to point sources', Journal of the Royal Statistical Society, Series A, 160, 491–505 (1997). 10.1111/j.1467-985X.1997.00076.x PubMedWeb of Science®Google Scholar 47 Potthoff, R. F. and Whittinghill, M. 'Testing for homogeneity: I. The binomial and multinomial distributions', Biometrika, 53, 167–182 (1996). 10.1093/biomet/53.1-2.167 Google Scholar 48 Potthoff, R. F. and Whittinghill, M. 'Testing for homogeneity: II. The Poisson distribution', Biometrika, 53, 183–190 (1966).Medline 10.1093/biomet/53.1-2.183 CASPubMedWeb of Science®Google Scholar 49 Muirhead, C. R. and Butland, B. K. ' Testing for over-dispersion using an adapted form of the Potthoff-Whittinghill method', in F. E. Alexander and P. Boyle (eds), Methods for Investigating Localized Clustering of Disease, International Agency for Research on Cancer, 1996, pp. 40–52. Google Scholar 50 Fuller, W. A. Measurement Error Models, Wiley, 1987. 10.1002/9780470316665 Google Scholar 51 Carroll, R. J., Ruppert, D. and Stefanski, L. A. Measurement Error in Nonlinear Models, Chapman and Hall, London, 1995. 10.1007/978-1-4899-4477-1 Google Scholar 52 Richardson, S. ' Measurement error', in W. R. Gilks, S. Richardson and D. J. Spiegelhalter (eds), Markov Chain Monte Carlo in Practice, Chapman and Hall, New York, 1996, pp. 401–417. 10.1007/978-1-4899-4485-6_22 Web of Science®Google Scholar 53 Wakefield, J. C. and Stephens, D. A. ' Bayesian errors-in-variables modeling', in D. K. Dey, S. K. Ghosh and B. K. Mallick (eds), Generalized Linear Models: A Bayesian Perspective, Marcel-Dekker, New York, 1999. Google Scholar 54 Jordan, P., Brubacher, D., Tsugane, S., Tsubono, Y., Gey, K. F. and Moser, U. 'Modelling of mortality data from a multi-centre study in Japan by means of Poisson regression with errors in variables', International Journal of Epidemiology, 26, 501–507 (1997).Medline 10.1093/ije/26.3.501 CASPubMedWeb of Science®Google Scholar 55 Bernardinelli, L., Pascutto, C., Best, N. G. and Gilks, W. R. 'Disease mapping with errors in covariates', Statistics in Medicine, 16, 741–752 (1997).Medline 10.1002/(SICI)1097-0258(19970415)16:7 3.0.CO;2-1 CASPubMedWeb of Science®Google Scholar 56 Diggle, P. J., Tawn, J. A. and Moyeed, R. A. 'Model-based geostatistics (with discussion)', Applied Statistics, 47, 299–350 (1998). 10.1111/1467-9876.00113 Web of Science®Google Scholar 57 Currie, J. ' On the analysis of spatial point process data with inaccurately observed covariate information', in V. Barnett and K. F. Turkman (eds), Statistics for the Environment 4: Health and the Environment, Wiley, 1998. Google Scholar 58 Richardson, S. and Gilks, W. R. 'A Bayesian approach to measurement error problems in epidemiology using conditional independence models', American Journal of Epidemiology, 138, 430–442 (1993).Medline 10.1093/oxfordjournals.aje.a116875 CASPubMedWeb of Science®Google Scholar 59 Clayton, D. G. ' Models for the analysis of cohort and case-control studies with inaccurately measured exposures', in J. H. Dwyer, F. Manning, P. Lippert and P. Hoflmeister (eds), Statistical Models for Longitudinal Studies of Health, Oxford University Press, New York, 1992, pp. 301–331. Google Scholar 60 Spiegelhalter, D. J. 'Bayesian graphical modelling: a case study in monitoring health outcomes', Applied Statistics, 47, 115–133 (1998). 10.1111/1467-9876.00101 Web of Science®Google Scholar 61 Dellaportas, P. and Stephens, D. A. 'Bayesian analysis of errors-in-variables regression models', Biometrics, 51, 1085–1095 (1995). 10.2307/2533007 Web of Science®Google Scholar 62 Spiegelman, D. and Casella, M. 'Fully parametric and semiparametric regression models for common events with covariate measurement error, in main study/validation study designs', Biometrics, 53, 395–409 (1997).Medline 10.2307/2533945 CASPubMedWeb of Science®Google Scholar 63 Doll, R. and Peto, R. The Causes of Cancer, Oxford Medical Publications, Oxford, 1981. Google Scholar Citing Literature Volume18, Issue17-18Special Issue: BURNING ISSUES IN MEDICAL STATISTICS15 ‐ 30 September 1999Pages 2377-2399 ReferencesRelatedInformation
Referência(s)