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Andy Sloggett

Publications and source records attributed to Andy Sloggett.

3 recordsLinked to original sources

Fertility in Kenya and Uganda: a comparative study of trends and determinants.

Between 1980 and 2000 total fertility in Kenya fell by about 40 per cent, from some eight births per woman to around five. During the same period, fertility in Uganda declined by less than 10 per cent. An analysis of the proximate determinants shows that the difference was due primarily to greater contraceptive use in Kenya, though in Uganda there was also a reduction in pathological sterility. The Demographic and Health Surveys show that women in Kenya wanted fewer children than those in Uganda, but that in Uganda there was also a greater unmet need for contraception. We suggest that these differences may be attributed, in part at least, first, to the divergent paths of economic development followed by the two countries after Independence; and, second, to the Kenya Government's active promotion of family planning through the health services, which the Uganda Government did not promote until 1995.

Contraception↗

Regression models for relative survival.

Four approaches to estimating a regression model for relative survival using the method of maximum likelihood are described and compared. The underlying model is an additive hazards model where the total hazard is written as the sum of the known baseline hazard and the excess hazard associated with a diagnosis of cancer. The excess hazards are assumed to be constant within pre-specified bands of follow-up. The likelihood can be maximized directly or in the framework of generalized linear models. Minor differences exist due to, for example, the way the data are presented (individual, aggregated or grouped), and in some assumptions (e.g. distributional assumptions). The four approaches are applied to two real data sets and produce very similar estimates even when the assumption of proportional excess hazards is violated. The choice of approach to use in practice can, therefore, be guided by ease of use and availability of software. We recommend using a generalized linear model with a Poisson error structure based on collapsed data using exact survival times. The model can be estimated in any software package that estimates GLMs with user-defined link functions (including SAS, Stata, S-plus, and R) and utilizes the theory of generalized linear models for assessing goodness-of-fit and studying regression diagnostics.

Adolescent↗

Health inequalities in the older population: the role of personal capital, social resources and socio-economic circumstances.

Older people now constitute the majority of those with health problems in developed countries so an understanding of health variations in later life is increasingly important. In this paper, we use data from three rounds of the Health Survey for England, a large nationally representative sample, to analyse variations in the health of adults aged 65-84 by indicators of attributes acquired in childhood and young adulthood, termed personal capital; and by current social resources and current socio-economic circumstances, while controlling for smoking behaviour and age. We used six indicators of health status in the analysis, four based on self-reports and two based on nurse collected data, which we hypothesised would identify different dimensions of health. Results showed that socio-economic indicators, particularly receipt of income support (a marker of poverty) were most consistently associated with raised odds of poor health outcomes. Associations between marital status and health were in some cases not in the expected direction. This may reflect bias arising from exclusion of the institutional population (although among those under 85 the proportion in institutions is very low) but merits further investigation, especially as the marital status composition of the older population is changing. Analysis of deviance showed that social resources (marital status and social support) had the greatest effect on the indicator of psychological health (GHQ) and also contributed significantly to variation in self-rated health, but among women not to variation in taking three or more medicines and among men not to self-reported long-standing illnesses. Smoking, in contrast, was much more strongly associated with these indicators than with self-rated health. These results are consistent with the view that self-rated health may provide a holistic indicator of health in the sense of well-being, whereas measures such as taking prescribed medications may be more indicative of specific morbidities. The results emphasise again the need to consider both socio-economic and socio-psychological influences on later life health.

Aged↗