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The objective of our study was identification and molecular characterization of piroplasms and rickettsias occurring in brown (Parahyaena brunnea) and spotted hyaenas (Crocuta crocuta) from various localities in Namibia and South Africa. Whole blood (n = 59) and skin (n = 3) specimens from brown (n = 15) and spotted hyaenas (n = 47) were screened for the presence of Babesia, Theileria, Ehrlichia and Anaplasma species using the reverse line blot (RLB) hybridization technique. PCR products of 52/62 (83.9%) of the specimens hybridized only with the Theileria/Babesia genus-specific probes and not with any of the species-specific probes, suggesting the presence of a novel species or variant of a species. No Ehrlichia and/or Anaplasma species DNA could be detected. A parasite 18S ribosomal RNA gene of brown (n = 3) and spotted hyaena (n = 6) specimens was subsequently amplified and cloned, and the recombinants were sequenced. Homologous sequence searches of databases indicated that the obtained sequences were most closely related to Babesia lengau, originally described from cheetahs (Acinonyx jubatus). Observed sequence similarities were subsequently confirmed by phylogenetic analyses which showed that the obtained hyaena sequences formed a monophyletic group with B. lengau, B abesia conradae and sequences previously isolated from humans and wildlife in the western USA. Within the B. lengau clade, the obtained sequences and the published B. lengau sequences were grouped into six distinct groups, of which groups I to V represented novel B. lengau genotypes and/or gene variants. We suggest that these genotypes cannot be classified as new Babesia species, but rather as variants of B. lengau. This is the first report of occurrence of piroplasms in brown hyaenas.

We conducted a survival analysis to determine the effect of poverty on mortality in a national sample of blacks and whites 25-74 years of age (in the First National Health and Nutrition Examination Survey and National Health Examination Follow-up Survey). We estimated the proportion of mortality associated with poverty from 1973 through 1984 and in 1991 by calculating the population attributable risk. We assessed confounding by major known risk factors, such as smoking, serum total cholesterol, and inactivity. In 1973, 16.1% of U.S. mortality among black and white persons 25-74 years of age was attributable to poverty; in 1991, the proportion increased to 17.7%. In 1991, the population attributable risk of poverty on mortality was lowest for white women, 1.7 times higher for white men, 2.6 times higher for black women, and 3.6 times higher for black men. Potential confounders explained 40% of the effect of poverty on mortality among women. The proportion of mortality attributable to poverty among U.S. black and white adults has increased in recent decades and is comparable to that attributable to cigarette smoking. The effect of poverty on mortality must be explained by conditions other than commonly recognized risk factors.

In the previous lesson on Measures of Effect, we focused exclusively on ratio measures of effect. In this lesson, we consider difference measures of effect and other related measures that allow the investigator to consider the potential public health impact of the results obtained from an epidemiologic study.

This lesson considers how the assessment of confounding gets somewhat more complicated when controlling for more than one risk factor. In particular, when several risk factors are being controlled, we may find that considering all risk factors simultaneously may not lead to the same conclusion as when considering risk factors separately. We have previously (Lesson 10) argued that the assessment of confounding is not appropriate for variables that are effect modifiers of the exposure-disease relationship under study. Consequently, throughout this lesson, our discussion of confounding will assume that none of the variables being considered for control are effect modifiers (i.e., there is no interaction between exposure and any variable being controlled).

The field of epidemiology was initially concerned with providing a methodological basis for the study and control of population epidemics. Now, however, epidemiology has a much broader scope, including the study of both acute and chronic diseases, the quality of health care, and mental health problems. As the focus of epidemiologic inquiry has broadened, so has the methodology. In this overview lesson, we describe examples of epidemiologic research and introduce several important methodologic issues typically considered in such research.

Suppose we are studying whether there is a link between exposure to a toxic chemical and the development of lung cancer in a chemical industry. To answer this question properly, we would want to isolate the effect of the chemical from the possible influence of other variables, particularly age and smoking status, two known risk factors for lung cancer. That is, our goal is to determine whether or not exposure to the chemical contributes anything over and above the effects of age and smoking to the development of lung cancer.

This study examined the dominant factors that predict the utilization of services by 129 identified elder abuse victims who reside in the community. Utilizing the Andersen Model, services accepted or rejected were analyzed from individual, family and environmental perspectives. Results indicated that service utilization is related to three "need" factors: (1) Victim has cognitive and ADL impairments, (2) Victim has poor health status (self rated), and (3) The abuser is financially dependent on the victim and is also the primary caregiver of the victim. "Enabling" factor (1) Victim lives alone. "Predisposing" factors (1) Abuser is substance abuser and (2) Abuser is female. A great proportion of the elder abuse victims in this study accepted services from an agency that provided a single entry point into the service system and had highly trained personnel utilizing a case management approach.

We examined consistency in the classification of ancestry by self, proxy, interviewer, and funeral director (on a death certificate) in a sample of the U.S. population--the First National Health and Nutrition Examination Survey and Epidemiologic Follow-up. Among study subjects for whom comparable ethnic identity options were available at both interviews, 58% of subjects specified the same identity at two times. Persons who specified four different ethnic backgrounds were 3.4 times as likely to change their identity over time as persons specifying only one background. Self-classification of ancestry at initial interview was consistent with proxy reports at follow-up for 55% of subjects for whom proxy information was available. Comparison of the self-classification of ancestry with the classification of race by interviewers and by funeral directors indicates high consistency for Whites and Blacks and low consistency for American Indians. The "measurement" of ancestry (that is, race or ethnicity) is critical to the understanding and elimination of differences in health status among racial/ethnic populations, but the low reliability of these measures over time and across observers complicates the analysis and interpretation of health statistics by ancestry, particularly for populations other than White or Black.

From January to April, 1990, 695 measles cases were reported to the Puerto Rico Health Department; there were 12 measles-associated deaths (case fatality ratio, 17/1000), more than in any year since 1967. We conducted a case-control study of risk factors for severe measles. We identified 16 children (ages 5 to 34 months) with severe measles and selected children with nonsevere measles as controls (39 hospitalized and 38 nonhospitalized). Controls were frequency matched to severe measles cases by region of residence. One case and two controls had been vaccinated. An underlying illness was present in 50% of cases and 16% of nonhospitalized controls (Mantel-Haenszel weighted odds ratio 5.3; 95% confidence interval 1.4, 20.2). In a multivariate analysis cases were significantly more likely than hospitalized controls to be from families with an annual income of$5000 (odds ratio (OR), 26.9), to have a mother without a high school degree (OR 11.1), to be anemic (hemoglobin10 g/dl) (OR 15.9) and have an underlying illness (OR 18.3). During measles outbreaks preventing severe illness requires aggressive control measures and strategies to increase vaccine coverage of children with underlying illnesses and of low socioeconomic status.