Mark P. Becker

This study tested the hypothesis that severe periodontitis in persons with non-insulin-dependent diabetes mellitus (NIDDM) increases the risk of poor glycemic control. Data from the longitudinal study of residents of the Gila River Indian Community were analyzed for dentate subjects aged 18 to 67, comprising all those: 1) diagnosed at baseline with NIDDM (at least 200 mg/dL plasma glucose after a 2-hour oral glucose tolerance test); 2) with baseline glycosylated hemoglobin (HbA1) less than 9%; and 3) who remained dentate during the 2-year follow-up period. Medical and dental examinations were conducted at 2-year intervals. Severe periodontitis was specified two ways for separate analyses: 1) as baseline periodontal attachment loss of 6 mm or more on at least one index tooth; and 2) baseline radiographic bone loss of 50% or more on at least one tooth. Clinical data for loss of periodontal attachment were available for 80 subjects who had at least one follow-up examination, 9 of whom had two follow-up examinations at 2-year intervals after baseline. Radiographic bone loss data were available for 88 subjects who had at least one follow-up examination, 17 of whom had two follow-up examinations. Poor glycemic control was specified as the presence of HbA, of 9% or more at follow-up. To increase the sample size, observations from baseline to second examination and from second to third examinations were combined. To control for non-independence of observations, generalized estimating equations (GEE) were used for regression modeling. Severe periodontitis at baseline was associated with increased risk of poor glycemic control at follow-up. Other statistically significant covariates in the GEE models were: 1) baseline age; 2) level of glycemic control at baseline; 3) having more severe NIDDM at baseline; 4) duration of NIDDM; and 5) smoking at baseline. These results support considering severe periodontitis as a risk factor for poor glycemic control and suggest that physicians treating patients with NIDDM should be alert to the signs of severe periodontitis in managing NIDDM.

This study tested the hypothesis that persons with non-insulin dependent diabetes mellitus (NIDDM) have greater risk of more severe alveolar bone loss progression over a 2-year period than those without NIDDM. Data from the longitudinal study of the oral health of residents of the Gila River Indian Community were analyzed for 362 subjects, aged 15 to 57, 338 of whom had less than 25% radiographic bone loss at baseline, and who did not develop NIDDM nor lose any teeth during the 2-year study period. The other 24 subjects had NIDDM at baseline, but met the other selection criteria. Bone scores (scale 0-4) from panoramic radiographs corresponded to bone loss of 0%, 1%-24%, 25%-49%, 50%-74%, or 75% and greater. Change in bone score category was computed as the change in worst bone score (WBS) reading after 2 years. Age, calculus, NIDDM status, time to follow-up examination, and baseline WBS were explanatory variables in regression models for ordinal categorical response variables. NIDDM was positively associated with the probability of a change in bone score when the covariates were controlled. The cumulative odds ratio for NIDDM at each threshold of the ordered response was 4.23 (95% C.I. = 1.80, 9.92). In addition to being associated with the incidence of alveolar bone loss (as demonstrated in previous studies), these results suggest an NIDDM-associated increased rate of alveolar bone loss progression.

This study tested the hypothesis that the risk for alveolar bone loss is greater, and bone loss progression more severe, for subjects with poorly controlled (PC) type 2 diabetes mellitus (type 2 DM) compared to those without type 2 DM or with better controlled (BC) type 2 DM. The PC group had glycosylated hemoglobin (HbA1) > or = 9%; the BC group had HbA1 < 9%. Data from the longitudinal study of the oral health of residents of the Gila River Indian Community were analyzed. Of the 359 subjects, aged 15 to 57 with less than 25% radiographic bone loss at baseline, 338 did not have type 2 DM, 14 were BC, and 7 were PC. Panoramic radiographs were used to assess interproximal bone level. Bone scores (scale 0-4) corresponding to bone loss of 0%, 1% to 24%, 25% to 49%, 50% to 74%, or > or = 75% were used to identify the worst bone score (WBS) in the dentition. Change in worst bone score at follow-up, the outcome, was specified on a 4-category ordinal scale as no change, or a 1-, 2-, 3-, or 4-category increase over baseline WBS (WBS1). Poorly controlled diabetes, age, calculus, time to follow-up examination, and WBS1 were statistically significant explanatory variables in ordinal logistic regression models. Poorly controlled type 2 DM was positively associated with greater risk for a change in bone score (compared to subjects without type 2 DM) when the covariates were included in the model. The cumulative odds ratio (COR) at each threshold of the ordered response was 11.4 (95% CI = 2.5, 53.3). When contrasted with subjects with BC type 2 DM, the COR for those in the PC group was 5.3 (95% CI = 0.8, 53.3). The COR for subjects with BC type 2 DM was 2.2 (95% CI = 0.7, 6.5), when contrasted to those without type 2 DM. These results suggest that poorer glycemic control leads to both an increased risk for alveolar bone loss and more severe progression over those without type 2 DM, and that there may be a gradient, with the risk for bone loss progression for those with better controlled type 2 DM intermediate to the other 2 groups.

Introduction Log-Linear Models and Latent Class Analysis Latent Class Measurement Models Latent Trait Models Discretized Latent Trait Models Estimation in Latent Trait Models

OBJECTIVE: To examine the association between the scope of quality improvement (QI) implementation in hospitals and hospital performance on selected indicators of clinical quality. DATA SOURCES: Secondary data from 1997 mailed survey of hospital QI practices, Medicare Inpatient Database, American Hospital Association's Annual Survey of Hospitals, the Bureau of Health Professions' Area Resource File, and two proprietary data sets compiled by Solucient Inc. containing data on managed care penetration and hospital financial performance. STUDY DESIGN: Cross-sectional study of 1,784 community hospitals to assess relationship between QI implementation approach and six hospital-level quality indicators. DATA COLLECTION/ABSTRACTION METHODS: Two-stage instrumental variables estimation in which predicted values (instruments) of four QI scope variables and control (exogenous) variables used to estimate hospital-level quality indicators. PRINCIPAL FINDINGS: Involvement by multiple hospital units in QI effort is associated with worse values on hospital-level quality indicators. Percentage of hospital staff and percentage of senior managers participating in formally organized QI teams are associated with better values on quality indicators. Percentage of physicians participating in QI teams is not associated with better values on the hospital-level quality indicators studied. CONCLUSIONS: Results supported the proposition that the scope of QI implementation in hospitals is significantly associated with hospital-level quality indicators. However, the direction of the association varied across different measures of QI implementation scope.