Development of rSs-NIE-1 and rSs-IR Recombinant Antigen-Based Immunoblot for Detection of Antibody to Strongyloides stercoralis.

Strongyloides stercoralis is a soil-transmitted nematode that can cause life-threatening conditions in immunocompromised persons. In the United States, strongyloidiasis should be considered mainly in immigrants, refugees, or travelers. The confirmatory laboratory diagnosis is usually performed by detecting larvae from the stool, duodenal material, and sputum. In persons who are immunocompromised with severe strongyloidiasis, adult worms and eggs can be detected from duodenal material. For serological diagnosis, most assays use crude antigens to detect anti-S. stercoralis IgG. Recently, recombinant proteins such as rSs-NIE-1 and rSs-IR have been used to detect IgG antibodies. We used rSs-NIE-1 and rSs-IR recombinant antigens to develop a biplex Western blot assay to detect the IgG4 antibody in individuals with strongyloidiasis. The sensitivities of rSs-NIE-1 and rSs-IR were 97.4% and 90.8%, respectively, whereas the specificities were 97.6% and 98%, respectively. In conclusion, the biplex rSs-NIE-1 and rSs-IR immunoblot performs well in detecting IgG4 antibody in S. stercoralis-infected persons.

Environmental temperatures and the incidence of food poisoning in England and Wales.

The incidence of food poisoning in England and Wales has been increasing for many years and it is now a major public health problem. Superimposed on this general rising trend is a well-established tendency for the number of cases of food poisoning to rise during the summer when warm weather favours the multiplication of pathogenic micro-organisms. This paper shows that weekly notifications of food poisoning in England and Wales are strongly associated with environmental temperatures, but that there are some important time lags in this relationship. The number of cases of food poisoning in a given week was only weakly correlated with the temperature of that week and the one preceding it. This suggests that factors operating close to the point of consumption within or outside the home are not the principal cause of the rise in food poisoning associated with warm summer conditions. There was a much stronger association with temperatures 2-5 weeks earlier, pointing to the importance of factors operating earlier in the food production or distribution system. The results of this study suggest that the food poisoning problem requires action by food producers and distributors as well as by consumers.

Public perceptions of health risks from polluted coastal bathing waters: a mixed methodological analysis using cultural theory.

This article explores public perceptions of, and attitudes toward, possible health risks from polluted coastal bathing waters in the United Kingdom. Cultural theory is applied in the present analysis, using a mixed methodology of quantitative analysis from interviews and qualitative interpretation of focus group discussions to provide insights into how different cultural solidarities view a number of issues. These include risks to health; attitudes toward regulation; public consultation and information provision; and trust, blame, and accountability applied to different stakeholders in the bathing-water-quality debate. The results show that individuals' standpoints can be represented on a number of dimensions, consistent with cultural theory, including perceptions of power and authority, beliefs in the efficacy of collective action, and acceptance or rejection of incremental change as opposed to radical solutions. The discussion focuses both on methodological and substantive issues related to the use of cultural theory as a research tool, and on policy recommendations arising from this research.

Multivariate spatial models for event data.

This paper describes how estimates made for event rates in small areas may be enhanced through spatial modelling of the data - taking the geographical location of each area into account - and through the addition of further information from each area. In particular we consider the use of spatial models to predict more than one outcome simultaneously. This is done by writing the spatial model as a multi-level model and subsequently enhancing this to encompass a multivariate data structure; estimates are obtained using iterative generalized least squares in the software package MLwiN. The example given considers mortality due to two causes--neoplasms and circulatory disease--in 143 postcode sectors in Greater Glasgow Health Board, Scotland. In addition, a measure of socio-economic deprivation is available for each area. Correlations between causes within areas, between areas within causes and between areas and causes are quantified, as are the relative contributions of the heterogeneous and spatial parts of the model. The results suggest a tendency for there to be pockets with high mortality rates due to neoplasms, whilst mortality due to circulatory disease follows a much smoother pattern. After taking deprivation into account, the spatial component accounts for just 19 per cent of the variation in the mortality due to neoplasms in Greater Glasgow but 66 per cent of the mortality due to circulatory disease.

Accidents to preschool children: comparing family and neighbourhood risk factors.

Accidental injury in young children is more common among poorer families and in deprived areas but little is known about how these factors interact. This paper describes a study to measure the contribution of individual family factors and area characteristics in determining risk of accidental injury among preschool children. We conducted a population based study of preschool accident and emergency attendances over two years in and around the city of Norwich, UK. Information on individual families was extracted from the district child health information system while "social areas" were constructed from adjacent census enumeration districts with homogeneous social and demographic characteristics. Statistical analysis was by multilevel modelling. Accidental injury rates were much higher in deprived urban neighbourhoods than in affluent areas but the multilevel analysis showed that, for all accidents, much of the variation in rates was accounted for by factors at the individual level i.e. male sex, young maternal age, number of elder siblings and distance from hospital, with a smaller, but independent, influence of living in a deprived neighbourhood. The model for more severe injuries was similar except single parenthood was now significant at the level of individuals and the effect of area deprivation was stronger. We conclude that preschool accidental injuries are influenced by factors operating at both the level of individual families and between areas. This evidence suggests that both social policy changes to improve child care among unsupported young families and targeting accident prevention measures at a local level towards deprived neighbourhoods would reduce accidents.

Multilevel modelling of the geographical distributions of diseases.

"Multilevel modelling is used on problems arising from the analysis of spatially distributed health data. We use three applications to demonstrate the use of multilevel modelling in this area. The first concerns small area all-cause mortality rates from Glasgow where spatial autocorrelation between residuals is examined. The second analysis is of prostate cancer cases in Scottish counties where we use a range of models to examine whether the incidence is higher in more rural areas. The third develops a multiple-cause model in which deaths from cancer and cardiovascular disease in Glasgow are examined simultaneously in a spatial model. We discuss some of the issues surrounding the use of complex spatial models and the potential for future developments."

Simultaneous analysis of individual and aggregate responses in psychometric data using multilevel modeling.

Psychometric data on risk perceptions are often collected using the method developed by Slovic, Fischhoff, and Lichtenstein, where an array of risk issues are evaluated with respect to a number of risk characteristics, such as how dreadful, catastrophic or involuntary exposure to each risk is. The analysis of these data has often been carried out at an aggregate level, where mean scores for all respondents are compared between risk issues. However, this approach may conceal important variation between individuals, and individual analyses have also been performed for single risk issues. This paper presents a new methodological approach using a technique called multilevel modelling for analysing individual and aggregated responses simultaneously, to produce unconditional and unbiased results at both individual and aggregate levels of the data. Two examples are given using previously published data sets on risk perceptions collected by the authors, and results between the traditional and new approaches compared. The discussion focuses on the implications of and possibilities provided by the new methodology.

A quantitative test of the cultural theory of risk perceptions: comparison with the psychometric paradigm.

This paper seeks to compare two frameworks which have been proposed to explain risk perceptions, namely, cultural theory and the psychometric paradigm. A structured questionnaire which incorporated elements from both approaches was administered to 129 residents of Norwich, England. The qualitative risk characteristics generated by the psychometric paradigm explained a far greater proportion of the variance in risk perceptions than cultural biases, though it should be borne in mind that the qualitative characteristics refer directly to risks whereas cultural biases are much more distant variables. Correlations between cultural biases and risk perceptions were very low, but the key point was that each cultural bias was associated with concern about distinct types of risks and that the pattern of responses was compatible with that predicted by cultural theory. The cultural approach also provided indicators for underlying beliefs regarding trust and the environment; beliefs which were consistent within each world view but divergent between them. An important drawback, however, was that the psychometric questionnaire could only allocate 32% of the respondents unequivocally to one of the four cultural types. The rest of the sample expressed several cultural biases simultaneously, or none at all. Cultural biases are therefore probably best interpreted as four extreme world views, and a mixture of qualitative and quantitative research methodologies would generate better insights into who might defend these views in what circumstances, whether there are only four mutually exclusive world views or not, and how these views are related to patterns of social solidarity, and judgments on institutional trust.

Urban-rural variations in suicides and undetermined deaths in England and Wales.

BACKGROUND: Given that a high proportion of undetermined deaths are thought to be suicides, the objective of the study was to compare the geography of the two verdicts, with emphasis on urban-rural differences, to determine whether the likelihood of a death being classified as suicide varies according to location. METHODS: Standardized mortality ratios (SMRs) were mapped for the local authority districts of England and Wales, using data aggregated over the period 1989-1992. Districts were classified according to population density, and SMRs calculated for each quartile. Finally, regression equations were obtained to model the relationship of suicide and undetermined death with a series of risk factors. RESULTS: Both male and female undetermined deaths showed a significant deficit in the most sparsely populated districts and a significant excess in the most densely populated districts. Female suicides were also significantly high in densely populated districts, but male suicides were highest in the most rural areas (SMR 110, 95 per cent confidence intervals 105-115). District variations in both verdicts were associated with the proportion of single-person households for both sexes, but male suicides and male undetermined deaths were associated with additional predictors, consistent with their distinct geographical distributions. CONCLUSIONS: Differences in suicide methods, the likelihood of communicating suicidal intent and, perhaps, variations in access to psychiatric services might be contributory factors to the observed differences between the verdicts. The results suggest that recorded suicides are a biased subset of actual suicides, particularly for males, and that the study of suicide verdicts alone is potentially misleading.

Tuberculosis mortality in England and Wales during 1982-1992: its association with poverty, ethnicity and AIDS.

This paper seeks to establish the strength of association between contemporary tuberculosis (TB) in England and Wales and several potential aetiological factors. It presents an ecological analysis of standardised annual TB mortality rates for the 403 local authority districts between 1982 and 1992, disaggregated by age and sex. Social, demographic and ethnicity measures from the 1981 and 1991 censuses and standardised annual AIDS-related mortality rates for young men are used to calculate Poisson regression models. A strong association was found between all TB mortality groups and overcrowding at the household level. For women, no other measures improved the explanatory power of the models. In multiple regressions, both poverty and AIDS-related mortality explained additional variation in the model for younger men. The link between ethnicity and tuberculosis notifications was not reflected in this analysis of mortality. For all groups no evidence of a positive relationship with ethnicity was found, once overcrowding had been accounted for. The significance of household as opposed to district level crowding suggests that prolonged contact is required for disease transmission. Regression analysis indicates that it is the overcrowding and poverty among ethnic populations that is significant for their tuberculosis mortality. The fact that the relationship between AIDS and TB is confined to the group most typical of AIDS patients provides evidence that AIDS has little influence on the level of tuberculosis mortality in the wider population. Explanations for the observed relationship include preferential certification, migration for treatment and shortcomings in health care provision.

Multi-level modelling of geographically aggregated health data: a case study on malignant melanoma mortality and UV exposure in the European Community.

A multi-level modelling approach is used to examine the variance in mortality rates from malignant melanoma at different geographical scales within nine European nations with reference to exposure to ultraviolet light (UVB). For males and females, the greatest variations in the relationship between UVB exposure and mortality are seen between nations, rather than regions and sub-regions within nations. This suggests that factors and characteristics acting at a national scale, such as genetic and behavioural differences, are of importance. Multi-level modelling is used to show how a previous suggestion of a quadratic association between UVB exposure and malignant melanoma across Europe is unlikely to be true. The general usefulness of multi-level modelling in the analysis of disease data which is structured in a hierarchy is discussed, with particular reference to geographical analyses of small area data.

Mortality from non-Hodgkin lymphoma and UV exposure in the European Community.

There has been a large, unexplained rise in the incidence of non-Hodgkin's lymphoma (NHL) in many countries. It has been hypothesised that increased exposure to solar ultraviolet (UV) radiation may have been a factor in this increase. The hypothesis that exposure to ultraviolet radiation is a factor in NHL can be tested by examining whether geographical variations in UV and in the incidence of the disease are positively correlated. Previous studies have given mixed results but some of these have failed to take into account confounding by socio-economic factors and the multilevel structure of data derived from several different countries. It was therefore decided to carry out a study using data on NHL mortality for the period 1971-80 for level II administrative units in 9 countries in the European Community. Estimated levels of solar UV and per capita GDP were also derived. Poisson regression models of the relationship between NHL mortality, UV and per capita GDP, taking into account the multilevel structure of the data, were fitted using the MLn package. Simple models that did not adjust for the effects of variations in per capita GDP or account adequately for the structure of the data produced apparent negative or quadratic associations between NHL and UV. However, further models show that there is a highly significant positive association between NHL and per capita GDP. Once this is included in the fixed and random parts of the multilevel model the association between NHL and UV becomes positive although non-significant (p = 0.081) at the conventional 0.05 level. These results underline the need to control for socio-economic factors and to take into account the multilevel structure of the data. Studies using international data that do not do this run the risk of producing misleading results.

The future of community nursing in the United Kingdom: district nursing, health visiting and school nursing.

This paper examines the future of community nursing, within the wider framework of a rapidly changing National Health Service. The research was commissioned by the Community Performance Review Network, as part of a series of comparative studies between community healthcare NHS trusts. Three questionnaires were sent to 24 trusts, covering three of the community nursing services; district nursing, health visiting and school nursing. Of the 24 trusts involved in the network, 22 responded to some or all of the questionnaires. A wide range of management structures and working practices were found between trusts, but several common themes and issues of concern emerged. For district nurses, these included the shift from secondary to primary care and the changing demands of the client population served, with increasing numbers of elderly and chronically disabled patients. This led to anxiety over the communication between different providers of care, such as community, acute and social services, and the skills mix and training requirements for nurses. Health visitors and school nurses were concerned about being marginalized in the move towards integrated primary health care teams. As the emphasis changes from treating illness to health promotion, concern was expressed about how performance could be measured on the less quantifiable outcomes of preventative care, and hence how jobs could be justified to purchasers of health care. A central theme was the potential role of the nurse practitioner in provision of primary care, and this formed a focus for other anxieties concerning both the current situation and future of community nursing services.

Exploring the "psychometric paradigm": comparisons between aggregate and individual analyses.

The "psychometric paradigm" developed by Slovic, Fischhoff, and Lichtenstein was a landmark in research about public attitudes toward risks. One problem with work, however, was that (at least initially) it did not attempt to distinguish between individuals or groups of people, except "experts" vs. "lay people." This paradigm produced a "cognitive map" of hazards, and the assumption seemed to be that the characteristics identified were inherent attributes of risk. This paper examines the validity of this assumption. A questionnaire survey similar to those designed by Slovic et al. was conducted, but the data were analyzed at both the aggregate level, using mean scores, and at the level of individuals (N = 131 Norwich residents). The results reported here demonstrate that (1) individuals vary in their perception of the same risk issue; (2) individuals vary in their rating of the same risks characteristics on the same risk issue; and (3) some of the strong intercorrelations observed between risk characteristics at the aggregate level are not supported when the same data are analysed at the level of individuals. Despite these findings, the relationship between risk characteristics and risk perceptions inferred by the psychometric paradigm did hold true at the level of individuals, for most--but not all--of the characteristics. In particular, the relationship between "lack of knowledge to those exposed" and risk perceptions appears to be a complex one, a finding which has important implications for risk communication strategies.

A multilevel model of sudden infant death syndrome in England and Wales.

The relationship between migration and sudden infant death syndrome (SIDS) in England and Wales is analyzed using official data for the period 1979-1983. "In this paper, multilevel modelling is used to examine the variability in SIDS deaths at different geographical scales, namely district, county, and regional levels. Given the population-mixing hypothesis, it is possible that high levels of population mixing in one district will have an effect on the spread of infections in an adjacent district, and the rates for individual districts will not be spatially independent of each other. Factors such as climate varying at regional scale may also be important. A log-linear multilevel model is developed to examine these issues, and the discussion focuses on the methodological issues raised by the analysis such as appropriate multilevel structure, methods of estimation, dispersion of residuals, and significance of parameter estimates."

A study of the geographical distribution of suicide rates in England and Wales 1989-92 using empirical bayes estimates.

In order to achieve the suicide reduction targets proposed by the U.K. Government's The Health of the Nation document, it is necessary to determine its geographical distribution. This objective is approached using district level data for England and Wales, aggregated for 1989-92. Two techniques are used, and compared. The first is the traditional method of mapping Standardized Mortality Ratios (SMR), expressed as relative risks. The second technique employed is the relatively new method of empirical Bayes estimates (EBE). It is shown that this is a superior measure for an initial investigation of the distribution of suicide, as relative risks for this comparatively rare condition are highly dependent on the population size of the areas studied. Discernible trends of high risk are shown in high population density, urban areas for both sexes, and in economically depressed agricultural, rural areas for men. The effects of economic hardship, unemployment and social disintegration are suggested as contributing to this distribution in an initiatory or exacerbatory capacity, for those suffering from psychiatric vulnerability or existing mental illness. Suggestions are made for more detailed analyses of high risk areas.

The application of K-function analysis to the geographical distribution of road traffic accident outcomes in Norfolk, England.

One method applicable to the examination of spatial point patterns of disease, the calculation of K-functions, is presented. The technique is used to determine the degree of clustering exhibited by the residuals from a spatially referenced logit model constructed to ascertain the factors influencing the likelihood of death in a road traffic accident. This was done to test if there was some systematic geographical factor influencing outcome not adequately controlled for in the model. K-functions are extremely versatile, overcoming many of the problems of incorporating the notion of scale associated with traditional methods of spatial autocorrelation. Recently software has become available which allows their calculation in an easy to use Geographical Information System style environment. This study illustrates the relevance of the method, not only to the analysis of data on mortality and morbidity, but also to the examination of the residuals from any spatial regression.

Regional variations in mortality rates in England and Wales: an analysis using multi-level modelling.

Mortality rates in England and Wales display a persistent regional pattern indicating generally poorer health in the North and West. Some of this is simply a reflection of regional differences in the extent of social deprivation which is known to exert a profound influence on health. Part of the pattern may also be the result of regional differences in urbanization which also affect mortality rates. However, there may be important regional differences over and above these compositional effects. This study attempts to establish the magnitude of such independent regional differences in mortality rates by using the techniques of multi-level modelling. Standardized mortality rates (SMRs) for males and females under 65 for 1989-91 in local authority districts are grouped into categories using the ACORN classification scheme. The Townsend Index is included as a measure of social deprivation. Using a cross-classified multi-level model, it is shown that region accounts for approximately four times more variation in SMRs than is explained by the ACORN classification. Analysis of diagnostic residuals show a clear North-South divide in excess mortality when both regional and socio-economic classification of districts are modelled simultaneously, a possibility allowed for by the use of a multi-level model.

Climate change and the incidence of food poisoning in England and Wales.

In recent years there have been several spells of high temperatures providing analogues for the conditions that might become more common as a result of the enhanced greenhouse effect. Statistical models were developed of the relationship between the monthly incidence of food poisoning and temperatures and these were then used to provide estimates of the possible effects of future warmer summers. Routinely collected data on the number of reported cases of food poisoning were analysed for the years 1982-1991. Regression analysis was used to establish the relationship between the monthly of food poisoning and temperatures of the same and the previous month. Published scenarios for future temperatures were applied to these statistical models to provide estimates of the possible impacts of warmer conditions. The monthly incidence of food poisoning was found to be significantly associated with the temperature of the same and of the previous month with the latter having the stronger effect. Using published data on the relationship between reported and actual numbers of cases of food poisoning, it is estimated that annually there might be an additional 179 000 cases of food poisoning by the year 2050 as a result of climate change. The observed relationship with the same month's temperature underlies the need for improvements in storage, preparation and hygiene close to the point of consumption. However, there was a much stronger relationship with the temperature of the previous month, indicating the importance of conditions earlier in the food production process. Improvements in areas such as animal husbandry and slaughtering may also be necessary to avoid the adverse effects of a warmer climate.