Socio-economic, migrant and geographic differentials in coronary heart disease occurrence in New South Wales

Objective: This study examines the variation in coronary heart disease (CHD) mortality and acute myocardial infarction (AMI) by socio-economic status (SES), country of birth (COB) and geography (urban/rural) in the total population of New South Wales (Australia) in 1991-95. Method: CHD deaths and AMI are from complete enumerations of deaths and hospital admissions, respectively; and population denominators are from census information. Data are examined separately by sex, and comparisons of SES groups (based on municipalities), COB and region are analysed using Poisson regression, after adjustment for age. Results: The study identified higher risk for AMI admissions and CHD mortality in lower SES populations with significant linear trends, for both sexes, adjusted for age, region and COB. According to the population attributable fractions (PAF), 23-41% of the risk of CHD occurrence is due to SES lower than the highest quartile. The higher age-adjusted risk for CHD occurrence in rural and remote populations for both sexes, compared with urban communities, was lessened by adjustment for COB, and all but abolished when also adjusted for SES. COB analysis indicated significantly lower age-adjusted AMI admissions and CHD mortality compared with the Australian-born, Conclusions: Higher risks for CHD in rural populations compared with the capital city (Sydney) are due, in part, to lower SES, lesser migrant composition. Implications: Strategies for reducing CHD differentials should consider demographic factors and the fundamental need to reduce socio-economic inequalities, as well as targeting appropriate prevention measures.

Trends in the incidence, severity, and short-term outcome of stroke in Perth, Western Australia

Background and Purpose-This report describes trends in the key indices of cerebrovascular disease over 6 years from the end of the 1980s in a geographically defined segment of the city of Perth, Western Australia. Methods-Identical methods were used to find and assess all cases of suspected stroke in a population of approximately 134 000 residents in a triangular area of the northern suburbs of Perth. Case fatality was measured as vital status at 28 days after the onset of symptoms. Data for first-ever strokes and for all strokes for equivalent periods of 12 months in 1989-1990 and 1995-1996 were compared by age-standardized rates and proportions and Poisson regression. Results-There were 355 strokes in 328 patients and 251 first-ever strokes (71%) for 1989-1990 and 290 events in 281 patients and 213 first-ever strokes (73%) for 1995-1996. In Poisson models including age and period, overall trends in the incidence of both first-ever strokes (rate ratio = 0.75; 95% confidence limits, 0.63, 0.90) and all strokes (rate ratio = 0.73; 95% confidence limits, 0.62, 0.85) were obviously significant, but only the changes in men were independently significant. Case fatality did not change, and the balance between hemorrhagic and occlusive strokes in 1995-1996 was almost indistinguishable from that observed in 1989-1990. Conclusions-Our results, which are the only longitudinal population-based data available for Australia for key indices of stroke, suggest that it is a change in the frequency of stroke, rather than its outcome, that is chiefly responsible nationally for the fall in mortality from cerebrovascular disease.

Gender and age-at-first-admission for schizophrenia: Data from Australia and Brazil

In order to examine whether different populations show the same pattern of onset in the Southern Hemisphere, we examined the age-at-first-admission distribution for schizophrenia based on mental health registers from Australia and Brazil. Data on age-at-first-admission for individuals with schizophrenia were extracted from two names-linked registers, (1) the Queensland Mental Health Statistics System, Australia (N=7651, F= 3293, M=4358), and (2) a psychiatric hospital register in Pelotas, Brazil (N=4428, F=2220, M=2208). Age distributions were derived for males and females for both datasets. The general population structure tbr both countries was also obtained. There were significantly more males in the Queensland dataset (gz = 56.9, df3, p < 0.0001 ). Both dataset distributions were skewed to the right. Onset rose steeply after puberty to reach a modal age group of 20-29 for men and women, with a more gradual tail toward the older age groups. In Queensland 68% of women with schizophrenia had their first admissions after age 30, while the proportion from Brazil was 58%. Compared to the Australian dataset, the Brazilian dataset had a slightly greater proportion of first admissions under the age 30 and a slightly smaller proportion over the age of 60 years. This reflects the underlying age distributions of the two populations. This study confirms the wide age range and gender differences in age-at-first-admission distributions for schizophrenia and identified a significant difference in the gender ratio between the two datasets. Given widely differing health services, cultural practices, ethic variability, and the different underlying population distributions, the age-at-first-admission in Queensland and Brazil showed more similarities than differences. Acknowledgments: The Stanley Foundation supported this project.

Age-at-first-admission of schizophrenia, bipolar disorder and major depression: Implications of heterogeneity

Age of onset is an important variable when considering the cause and course of mental illnesses. Given the debate about the relationship between psychotic disorders it would be useful to compare age-at-first-admission for ICD schizophrenia and for affective psychoses when the latter is differentiated into 'major depression' and 'bipolar disorder'. Data on age-at-first-admission for Australian-born individuals diagnosed with schizophrenia (ICD 295) or affective psychosis (ICD 296) were extracted from the Queensland Mental Health Statistics System -- a comprehensive, namelinked mental health register. Because the ICD 9 category 296.1 was used to code what is now called "major depressive episode', this group was differentiated from other 296 categorieswhich were considered bipolar disorders. Those receiving more than one diagnoses within these categories were excluded. All distributions show a wide age range of onset from early adolescence into the seventies and eighties. However the modal age-group for major depression ('60-69' for both sexes) is clearly different from bipolar disorder ('20-29' for males; '30- 39' for females), the latter distribution being more similar to the SCZ distribution (which had a model age-group of '20-29' for both sexes). While these distributions were similar for males and females, there were sex differences in the proportions within each diagnostic group: more males with schizophrenia, and more females with bipolar disorder and with major depression. Our results suggest heterogeneity within the affective psychoses as categorised by ICD 9, with bipolar disorder having an age-at-first-admission distribution more similar to schizophrenia than major depression. The Stanley Foundation supported this project.

Predictors of genital warts among women attending two family planning clinics

Objectives: To establish the prevalence and predictors of genital warts among healthy women presenting for contraceptive advice at two family planning clinics, one in a major Australian city and one in a country town in the same state. Methods: Consecutive consenting attendees (n = 1218)at two family planning clinics in Queensland completed a questionnaire and were examined for genital warts. Results: The point prevalence of visible genital warts was 3.3 per cent in the city clinic and 14.4 per cent in the country town. For half of these clients a finding of warts was unexpected, in that the client was unaware of their presence and presentation to the family planning clinic was not specifically for advice about sexually transmitted infections. The major predictor of a finding of warts was client age, with the highest prevalence in 20- to 25-year-olds. Warts were also commoner amongst smokers in the country town but not in Brisbane. However, no analysed sociodemographic variable predicted a finding of warts of which the client was not aware. Conclusions: Genital warts are common among young women presenting for contraceptive advice. Such women are often unaware that they have warts. Examination for genital warts should be a part of any routine examination of sexually active women, and medical practitioners should be aware of appropriate advice for patients who are found to have genital warts on routine examination.

Age-related differences in physical activity levels of young adults

Purpose: To examine age-related differences in the physical activity behaviors of young adults. Methods: We examined rates of participation in vigorous- and moderate-intensity leisure-time activity and walking, as well as an index of physical activity sufficient for health benefits in three Australian cross-sectional samples, for the age ranges of 18-19, 20-24, and 25-29 yr. Data were collected in 1991, 1996, and 1997/8. Results: There was at least a 15% difference in vigorous-intensity leisure-time physical activity from the 18-19 yr to the 25-29 yr age groups, and at least a 10% difference in moderate-intensity leisure-time physical activity. For the index of sufficient activity there was a difference between 9 and 21% across age groups. Differences in rates of walking were less than 8%. For all age groups, males had higher rates of participation for vigorous and moderate-intensity activity than did females, bur females had much higher rates of participation in walking than males. Age-associated differences in activity levels were more apparent for males. Conclusions: Promoting walking and various forms of moderate-intensity physical activities to young adult males, and encouraging young adult females to adopt other forms of moderate-intensity activity to complement walking may help to ameliorate decreases in physical activity over the adult lifespan.

Estimating HIV incidence rates from age prevalence data in epidemic situations

We present a method of estimating HIV incidence rates in epidemic situations from data on age-specific prevalence and changes in the overall prevalence over time. The method is applied to women attending antenatal clinics in Hlabisa, a rural district of KwaZulu/Natal, South Africa, where transmission of HIV is overwhelmingly through heterosexual contact. A model which gives age-specific prevalence rates in the presence of a progressing epidemic is fitted to prevalence data for 1998 using maximum likelihood methods and used to derive the age-specific incidence. Error estimates are obtained using a Monte Carlo procedure. Although the method is quite general some simplifying assumptions are made concerning the form of the risk function and sensitivity analyses are performed to explore the importance of these assumptions. The analysis shows that in 1998 the annual incidence of infection per susceptible woman increased from 5.4 per cent (3.3-8.5 per cent; here and elsewhere ranges give 95 per cent confidence limits) at age 15 years to 24.5 per cent (20.6-29.1 per cent) at age 22 years and declined to 1.3 per cent (0.5-2.9 per cent) at age 50 years; standardized to a uniform age distribution, the overall incidence per susceptible woman aged 15 to 59 was 11.4 per cent (10.0-13.1 per cent); per women in the population it was 8.4 per cent (7.3-9.5 per cent). Standardized to the age distribution of the female population the average incidence per woman was 9.6 per cent (8.4-11.0 per cent); standardized to the age distribution of women attending antenatal clinics, it was 11.3 per cent (9.8-13.3 per cent). The estimated incidence depends on the values used for the epidemic growth rate and the AIDS related mortality. To ensure that, for this population, errors in these two parameters change the age specific estimates of the annual incidence by less than the standard deviation of the estimates of the age specific incidence, the AIDS related mortality should be known to within +/-50 per cent and the epidemic growth rate to within +/-25 per cent, both of which conditions are met. In the absence of cohort studies to measure the incidence of HIV infection directly, useful estimates of the age-specific incidence can be obtained from cross-sectional, age-specific prevalence data and repeat cross-sectional data on the overall prevalence of HIV infection. Several assumptions were made because of the lack of data but sensitivity analyses show that they are unlikely to affect the overall estimates significantly. These estimates are important in assessing the magnitude of the public health problem, for designing vaccine trials and for evaluating the impact of interventions. Copyright (C) 2001 John Wiley & Sons, Ltd.

Age gelation of UHT milk - A review

Gelation of UHT milk during storage (age gelation) is a major factor limiting its shelf-life. The gel which forms is a three-dimensional protein matrix initiated by interactions between the whey protein beta -lactoglobulin and the kappa -casein of the casein micelle during the high heat treatment. These interactions lead to the formation of a beta -lactoglobulin-kappa -casein complex (beta kappa -complex). A feasible mechanism of age gelation is based on a two-step process; in the first step, the beta kappa -complexes dissociate from the casein micelles due to the breakdown of multiple anchor sites on kappa -casein, and in the second step, these complexes aggregate into a three-dimensional matrix. When a critical volume concentration of the beta kappa -complex is attained, a gel of custard-like consistency is formed. Significant factors which influence the onset of gelation include the nature of the heat treatment, proteolysis during storage, milk composition and quality, seasonal milk production factors and storage temperature. In this review, age gelation is discussed in terms of these factors, causative mechanisms and procedures for controlling it.

Paternal age as a risk factor for psychosis and schizophrenia: Findings from Denmark, Sweden and Australia

The offspringof older fathers have an increased risk of various disorders that may be due to the accumulation of DNA mutations during spermatogenesis. Previous studies have suggested increased paternal age may be a risk factor for schizophrenia. The aim of the current study was to examine paternal age as a risk factor for schizophrenia andror psychosis. We used data from three sources: a population-based cohort studyŽDenmark., and two case-control studiesŽSweden and Australia.. In the Danish and Australian studies, we examined both psychosis and schizophrenia. In the Swedish study we examined psychosis only. After controllingfor the effect of maternal age, increased paternal age was significantly associated with increased risk of both psychosis and schizophrenia in the Danish study and of psychosis in the Swedish study. The Australian study found no association between paternal age and risk of psychosis or schizophrenia. In all three studies the relationship between paternal age and risk of disorder in the offspring was AUB-shaped. In addition to an increased risk for the offspringof older father Ž)35 years., there was a non-significant increase for the offspringof fathers aged less than 20 years. The possible role of paternally derived DNA mutations andror other psychosocial factors associated with older paternal age warrants further research. The ‘U’-shaped relationship suggests that factors other than DNA mutations may warrant consideration in this research. The Stanley Foundation supported this project.

Influence of patient age and implantation technique on the probability of re-replacement of the homograft aortic valve

Background and aim of the study: Results of valve re-replacement (reoperation) in 898 patients undergoing aortic valve replacement with cryopreserved homograft valves between 1975 and 1998 are reported. The study aim was to provide estimates of unconditional probability of valve reoperation and cumulative incidence function (actual risk) of reoperation. Methods: Valves were implanted by subcoronary insertion (n = 500), inclusion cylinder (n = 46), and aortic root replacement (n = 352). Probability of reoperation was estimated by adopting a mixture model framework within which estimates were adjusted for two risk factors: patient age at initial replacement, and implantation technique. Results: For a patient aged 50 years, the probability of reoperation in his/her lifetime was estimated as 44% and 56% for non-root and root replacement techniques, respectively. For a patient aged 70 years, estimated probability of reoperation was 16% and 25%, respectively. Given that a reoperation is required, patients with non-root replacement have a higher hazard rate than those with root replacement (hazards ratio = 1.4), indicating that non-root replacement patients tend to undergo reoperation earlier before death than root replacement patients. Conclusion: Younger patient age and root versus non-root replacement are risk factors for reoperation. Valve durability is much less in younger patients, while root replacement patients appear more likely to live longer and hence are more likely to require reoperation.

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advancesin information technology has the potential to radically transformimmunology in the postgenomics era. Not only do we now have readyaccess to vast quantities of existing data, but new data with relevanceto immunology are being accumulated at an exponential rate. Resourcesfor computational immunology include biological databases and methodsfor data extraction, comparison, analysis and interpretation. Publiclyaccessible biological databases of relevance to immunologists numberin the hundreds and are growing daily. The ability to efficientlyextract and analyse information from these databases is vital forefficient immunology research. Most importantly, a new generationof computational immunology tools enables modelling of peptide transportby the transporter associated with antigen processing (TAP), modellingof antibody binding sites, identification of allergenic motifs andmodelling of T-cell receptor serial triggering.