Evaluating risk factors associated with severe hypoglycaemia in epidiomology studies - What method should we use?

Diabetic Medicine

Volumn 21, Issue 8, 2004, Pages 914-919

  Bulsara, M K ^a,b   Holman, C D J ^a   Davis, E A ^b   Jones, T W ^b  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^b PRINCESS MARGARET HOSPITAL FOR CHILDREN   (Australia)

Author keywords

Poisson; Regression models; Severe hypoglycaemic; Type 1 diabetes; Zero inflated negative binomial

Indexed keywords

ADOLESCENT; ADULT; ANALYTIC METHOD; ARTICLE; BINOMIAL DISTRIBUTION; CHILD; CONTROLLED STUDY; DEMOGRAPHY; FEMALE; HUMAN; HYPOGLYCEMIA; INCIDENCE; INFANT; INSULIN DEPENDENT DIABETES MELLITUS; INTERMETHOD COMPARISON; MAJOR CLINICAL STUDY; MALE; POISSON DISTRIBUTION; RISK FACTOR; STATISTICAL MODEL;

AGE FACTORS; CHILD; CHILD, PRESCHOOL; COHORT STUDIES; FEMALE; HEMOGLOBIN A, GLYCOSYLATED; HUMANS; HYPOGLYCEMIA; INFANT; INFANT, NEWBORN; MALE; POISSON DISTRIBUTION; PROSPECTIVE STUDIES; REGRESSION ANALYSIS; RISK FACTORS;

EID: 3843148438     PISSN: 07423071     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1464-5491.2004.01250.x     Document Type: Article

References (25)

1. Rewers A, Chase HP, Mackenzie T, Walravens P, Roback M, Rewers M et al. Predictors of acute complications in children with Type 1 diabetes. J Am Med Assoc 2002; 287: 2511-2518.
2. Anonymous. Hypoglycemia in the Diabetes Control and Complications Trial. The Diabetes Control Complications Trial Research Group. Diabetes 1997; 46: 271-286.
3. Craig ME, Handelsman P, Donaghue KC, Chan A, Blades B, Laina R et al. Predictors of glycaemic control and hypoglycaemia in children and adolescents with type 1 diabetes from NSW and the ACT. Med J Australia 2002; 177: 235-238.
4. Bohning D, Dietz E, Schlattmann P. The zero-inflated Poisson model and the decayed, missing and filled teeth index in dental epidemiology. J Royal Statist Soc Series A 1999; 162: 195-209.
5. Lee AH, Stevenson MR, Wang K, Yau KKW. Modeling young driver motor vehicle crashes: data with extra zeros. Accident Anal Prevention 2002; 34: 515-521.
6. Hall DB. Zero-inflated Poisson and binomial regression with random effects: a case study. Biometrics 2000; 56: 1030-1039.
7. Ridout M. Models for count data with many zeros. Proceedings of the XIXth International Biometrics Conference 1998, Cape Town (Invited Papers) 1998; 179-192.
8. Greene WH. Accounting for excess zeros and sample selection in Poisson and negative binomial regression models. New York: Stern School of Business, New York University, Department of Economics, 1994, Working Paper Number EC-94-10.
9. Muhlhauser I, Overmann H, Bender R, Bon U, Berger M. Risk factors of severe hypoglycaemia in adult patients with Type I diabetes - a prospective population based study. Diabetologia 1998; 41: 1274-1282.
10. Rosilio M, Cotton JB, Wieliczko MC, Gendrault B, Carel JC, Couvaras O et al. Factors associated with glycemic control. A cross-sectional nationwide study in 2579 French children with type 1 diabetes. The French Pediatric Diabetes Group. Diabetes Care 1998; 21: 1146-1153.
11. Gupta PL, Gupta RC, Tripathi RC. Analysis of zero-adjusted count data. Computational Statistics Data Anal 1996; 23: 207-218.
12. Davis EA, Keating B, Byrne GC, Russell M, Jones TW. Impact of improved glycaemic control on rates of hypoglycaemia in insulin-dependent diabetes mellitus. Arch Dis Childhood 1998; 78: 111-115.
13. Davis EAF, Keating BB, Byrne GCF, Russell MM, Jones TWF. Hypoglycemia: incidence and clinical predictors in a large population-based sample of children and adolescents with IDDM. Diabetes Care 1997; 20: 22-25.
14. Long SJ, Freese J. Regression Models for Categorical Dependent Variables Using Stata. College Station, Texas: Stata Corporation, 2001.
15. Stata. STATA Release 8. College Station Texas: Stata Press, 2003.
16. Bohning D, Dietz E, Schlattmann P. Zero-inflated count models and their applications in public health and social science. In: Rost, J, Langeheine, R, eds. Applications of Latent Trait and Latent Class Models in the Social Sciences. 1st edn. Munster: Waxmann, 1997, 333-344.
17. Shankar V, Milton J, Mannering F. Modeling accident frequencies as zero-altered probability processes: an empirical inquiry. Accident Anal Prevention 1997; 29: 829-837.
18. Long SJ. Regression models for categorical and limited dependent variables. California: Sage; 1997.
19. Soltesz G. Round table on hypoglycaemia in diabetic children. Acta Paediatrica Suppl 1998; 425: 25-29.
20. Yau KKW, Lee AH. Zero-inflated Poisson regression with random effects to evaluate an occupational injury prevention programme. Statistics Med 2001; 20: 2907-2920.
21. Cheung YB. Zero-inflated models for regression analysis of count data, a study of growth and development. Statistics Med 2002; 21: 1461-1469.
22. Greene W. LIMDEP. 8th edn. Plainview, New York: Econometric Software Inc., 2002.
23. Bohning D. Zero-inflated Poisson models and C.A.MAN: A tutorial collection of evidence. Biometr J 1998; 40: 833-843.
24. Haughton D. Packages for estimating finite mixtures: a review. J Am Statist Assoc 1997; 51: 194-205.
25. Jones BL, Nagin DS, Roeder K. A SAS procedure based on mixture models for estimating development trajectories. Social Meth Res 2001; 29: 374-393.