Reliability and prevalence of physical performance examination assessing mobility and balance in older persons in the US: data from the Third National Health and Nutrition Examination Survey.

OBJECTIVE: This report provides reliability and prevalence estimates by sex, age, and race/ethnicity of an observed physical performance examination (PPE) assessing mobility and balance. SETTING: The Third National Health and Nutrition Examination Survey (NHANES III) 1988-1994. DESIGN: A cross-sectional nationally representative survey. PARTICIPANTS: All persons aged 60 and older (n = 5,403) who performed the PPE either in the mobile examination center (MEC) or in the home during NHANES III (conducted 1988-1994). MEASUREMENTS: The PPE included timed chair stand, full tandem stand, and timed 8-foot walk. RESULTS: Timed chair stand and 8-foot timed walk were reliable measurements (Intraclass Correlations > 0.5). Women were significantly slower (P < .001) than men for both timed chair stands and timed walk. Non-Hispanic white men and women did the maneuvers in significantly less time than non-Hispanic black men and women and Mexican Americans women (P < .001). CONCLUSIONS: Lower extremity functions measured by timed chair stand and walk are reliable. Women at every age group were more physically limited than men.

Adjustment of provisional mortality series: the dynamic linear model with structured measurement errors.

The authors "consider the problem of adjusting provisional time series using a bivariate structural model with correlated measurement errors. Maximum likelihood estimators and a minimum mean squared error adjustment procedure are derived for a provisional and final series containing common trend and seasonal components. The model also includes measurement errors common to both series and errors that are specific to the provisional series. [The authors] illustrate the technique by using provisional data to forecast ischemic heart disease mortality."

Hospital characteristics and mortality rates.

The Health Care Financing Administration (HCFA) publishes hospital mortality rates each year. We undertook a study to identify characteristics of hospitals associated with variations in these rates. To do so, we obtained data on 3100 hospitals from the 1986 HCFA mortality study and the American Hospital Association's 1986 annual survey of hospitals. The mortality rates were adjusted for each hospital's case mix and other characteristics of its patients. The mortality rate for all hospitalizations was 116 per 1000 patients. Adjusted mortality rates were significantly higher for for-profit hospitals (121 per 1000) and public hospitals (120 per 1000) than for private not-for-profit hospitals (114 per 1000; P less than 0.0001 for both comparisons). Osteopathic hospitals also had an adjusted mortality rate that was significantly higher than average (129 per 1000; P less than 0.0001). Private teaching hospitals had a significantly lower adjusted mortality rate (108 per 1000) than private nonteaching hospitals (116 per 1000; P less than 0.0001). Adjusted mortality rates were also compared for hospitals in the upper and lower fourths of the sample in terms of certain hospital characteristics. The mortality rates were 112 and 121 per 1000 for the hospitals in the upper and lower fourths, respectively, in terms of the percentage of physicians who were board-certified specialists (P less than 0.0001), 112 and 120 per 1000 for occupancy rate (P less than 0.0001), 113 and 120 per 1000 for payroll expenses per hospital bed (P less than 0.0001), and 113 and 119 per 1000 for the percentage of nurses who were registered (P less than 0.0001).

The application of time series forecasting methods to an estimation problem using provisional mortality statistics.

Provisional estimates of mortality for selected causes of death are published each month by the National Center for Health Statistics. These estimates are based upon a ten per cent sample of death certificates in the United States. Final mortality results, based upon all the death certificates for a calendar year, are available one to two years after publication of the provisional estimates. This paper explores the potential of time series forecasting techniques for improving mortality estimates by using the correlation structure between the provisional and final series to obtain mortality estimates that are expected to be closer to final values than currently used provisional estimates.