Canada's Health Status: A Public Health Perspective1

Health status assessment and disease surveillance are essential to identify and priorize health issues, to evaluate intervention programs and to plan to meet future needs for health services. Canadians currently benefit by having among the highest life expectancies at birth in the world (81 for females, 74 for males). Disability-free life expectancies for females and males, respectively, were 10.1 and 11.3 years lower for the lowest income quintile compared to the highest. Canada's infant mortality rate in 1990 (7/1000 live births) was one of the lowest in the world but within Canada, the rate in the lowest income quintile (10.5/1000 live births) was almost double that in the highest income quintile (5.8/1000 live births). Fair or poor health was reported by 36% of adult Canadians in the lowest income category in 1990 compared to only 5% in the highest income group. The leading causes of premature death for females in 1991 were breast cancer, coronary heart disease, lung cancer, car crashes, birth defects and suicide; those for males were coronary heart disease, suicide, car crashes, lung cancer, birth defects, and AIDS. Lowest income quintile males had mortality rates at least double those for the highest income quintile for alcohol-related conditions, violence, injuries and emphysema. Cardiovascular diseases, cancer, musculoskeletal diseases, injuries and respiratory diseases imposed the highest direct and indirect economic costs in Canada in 1986. For all of these conditions, improved prevention is possible. For example, the forecasted tobacco-related deaths before age 70 among current male smokers age 15 will far exceed those due to car crashes, suicide, murder, AIDS, and drug abuse combined. Population aging will aggravate trends for many chronic conditions especially those with increasing incidence rates; there will be large increases in the numbers of persons with aging-related cancers, dementias and other conditions. There is an urgent need for Canadian health jurisdictions to ensure that rational priorities, goals/objectives, strategies, and programs are in place to enhance prevention and disease control.     

Estimated Distributions for Average Daily Consumption of Total and Self-Caught Fish for Adults in Michigan Angler Households

Fish consumption rates play a critical role in the assessment of human health risks posed by the consumption of fish from chemically contaminated water bodies. Based on data from the 1989 Michigan Sport Anglers Fish Consumption Survey, we examined total fish consumption, consumption of self-caught fish, and consumption of Great Lakes fish for all adults, men, women, and certain higher risk subgroups such as anglers. We present average daily consumption rates as compound probability distributions consisting of a Bernoulli trial (to distinguish those who ate fish from those who did not) combined with a distribution (both empirical and parametric) for those who ate fish. We found that the average daily consumption rates for adults who ate fish are reasonably well fit by lognormal distributions. The compound distributions may be used as input variables for Monte Carlo simulations in public health risk assessments.     

Toward overcoming problems in evaluation research: A beginning perspective on power

An information feedback model and an ideology of evaluation is posed. The authors' experiences in actually doing evaluation research are then contrasted with the model and ideology. Suggestions are made for closing the gap between reality and the model, primarily by altering the structural constraints that present obstacles to achieving the model. The authors assume that impact on policy is the appropriate criterion for the success of an evlauation, and they conclude that political constraints are primary in preventing evaluation research from having this impact. It is proposed that evaluators need to develop more explicitly political ways of acquiring power of their own in order to maximize such impact. Some ways social researchers might conceptualize and construct an appropriate base of power are considered.     

Statistical Matching Using File Concatenation With Adjusted Weights and Multiple Imputations

Statistically matched files are created in an attempt to solve the practical problem that exists when no single file has the full set of variables needed for drawing important inferences. Previous methods of file matching are reviewed, and the method of file concatenation with adjusted weights and multiple imputations is described and illustrated on an artificial example. A major benefit of this approach is the ability to display sensitivity of inference to untestable assumptions being made when creating the matched file.