Spatial interdependencies in population distributions: a study in univariate map analysis. 1. Rural population densities. 2. Urban population distributions.

PIP: The author uses univariate map techniques to study the pattern properties of population distribution. In Part 1 methods for analyzing statistically homogeneous maps are discussed, and the results of rural population density studies are reviewed. The methodology of map analysis to be adopted is considered. In Part 2, the relationship between process and map structure is explored with respect to the nature of certain types of geographical spaces. Urban population distributions are discussed, and statistical techniques different from those used in Part 1 are presented. The study is based on U.S. census data for Iowa and Wisconsin for every 10 years from 1930 and 1970^ieng

Statistical analysis of spatial data in the presence of missing observations: a methodological guide and an application to urban census data.

"In this paper a simple introduction and guide to a widely applicable method for estimating missing data in fields of enquiry such as census maps or LANDSAT images are presented. The method given is a maximum likelihood procedure.... The algorithm is presented in the form of a simple tutorial guide. An example, of median income levels in Houston [Texas], is worked through in detail for missing cells in census data. The example is characterised by a variable mean and a general variance-covariance matrix."

Hitting the target: the equitable distribution of health visitors across caseloads.

BACKGROUND: Health visitors in the United Kingdom work mainly with pre-school children and their mothers. Their distribution across the population is largely historical, highly variable and relates poorly to indicators of population need. METHODS: A range of largely routine data sources were used to describe the nature, variation and statistical determinants of the workload of individual health visitors in Sheffield, England, in 1996-1997. Regression models were tested relating measures of need and deprivation to the total number of client contacts. RESULTS: Caseloads were smaller in the most deprived areas, with wide variation. Most (93 per cent) contacts were with mothers and young children. Health visitors visited the clients designated as highest priority on average 4.7 times more often than routine clients. The main reasons for high priority ratings were child protection concerns, maternal mental health problems, child development and health concerns, and first-time mothers in the postnatal period. Half of all client contacts were with low-priority families for routine child health surveillance or were client initiated. Models based on the number of children under five and any one of a range of measures of social deprivation account for 57-59 per cent of variation in workload and could be used to allocate resources more equitably. CONCLUSIONS: Although most health visitors apparently subscribe to the principle of targeting, the extent varies widely. Constraints on targeting are routine child health surveillance reviews, and client demands. More equitable allocation of health visitors and more explicit targeting policies might increase the effectiveness of the health visiting service.

Levels of satisfaction of 'low-risk' mothers with their current health visiting service.

AIMS AND OBJECTIVES: To assess the expressed levels of satisfaction of 'low-risk' mothers with the current health visiting service. Setting Sheffield, England, Autumn 1997. METHODOLOGY: Self-completion, postal questionnaire (initial postcard reminder followed by a second letter and questionnaire) to a sample of 403 mothers assessed as 'low priority' by their health visitor. Questions largely related to maternal opinion of the adequacy of the health visiting service delivered during the first 9-12 months. The local research ethics committee approved the study. RESULTS: A corrected response rate of 75% with little evidence of significant bias. A high proportion (86%) of women stated that they were either 'fairly' or 'very' satisfied with the service they had received from their health visitor with regard to their baby. A lower proportion (72%) was equally satisfied with the service they had received in respect of their own health. Despite an average number of approximately 10 contacts in relation to infant health with the health visitor during the first year of life, some 6% of women wanted more frequent contacts, particularly in the first few weeks. Study limitations The questionnaire was designed specifically for the study and validation was limited. The study population comprised a selected, 'low-risk' group. CONCLUSIONS: The number of reported contacts with the health visitor seemed to greatly exceed those indicated by a basic child health surveillance programme. The overall level of maternal satisfaction is high, though a minority of women would like more support. Dissatisfaction was expressed with the lack of an appointment system for clinics, poor punctuality in home visits, and inappropriate or inadequate advice.

Errors in postcode to enumeration district mapping and their effect on small area analyses of health data.

BACKGROUND: Health research often seeks to associate individuals to their socio-economic circumstances by linking an individual's postcode to their Census enumeration district (ED). As part of a study into health visitor resource allocation the objective here is to quantify the errors that arise in attaching ED level deprivation scores to records and counts of records by ED when records are matched to EDs via their postcodes rather than their exact address. METHODS: The result of routine matching of postcodes to EDs was compared with the more accurate method of matching addresses to EDs. Townsend scores were then attributed to records according to the two different methods and the results compared. A sample of 4013 births registered in Sheffield in 1996 was used. RESULTS: The comparative work showed that the mismatching of individual addresses arising from matching postcodes to EDs was 16.4 per cent. (The 95 per cent confidence interval is 15.1-17.7 per cent.) Over one-third of mismatched records (about 6 per cent of the total records) were found to have Townsend scores greater than +/- 2 compared with the score obtained through the more accurate process of address matching. CONCLUSIONS: The evidence of the study is that it is important to recognize there are errors inherent in matching individual addresses to EDs via the address postcode. For problems involving resource allocation and for research into relationships between health outcomes or service uptake and deprivation it may be necessary to seek to quantify the level of error introduced through using postcode to ED matching.