Gender inequality, poverty and human development in Kenya: Main indicators, trends and limitations

Indicators of gender inequality, poverty and human development in Kenya are examined. Significant and rising incidence of absolute poverty occurs in Kenya and women are more likely to be in poverty than men. Female/male ratios in Kenyan decision-making institutions are highly skewed against women and they experience unfavourable enrolment ratios in primary, secondary and tertiary institutions. The share of income earned by women is much lower than men's share. General Kenyan indicators highlight declining GDP per capita, increased poverty rates especially for women, reduced life expectancy, a narrowing of the difference in female/male life expectancy rates, increased child mortality rates and an increase in the female child mortality rates. This deterioration results in an increased socio-economic burden on women, not adequately captured in the HPI, HDI, GDI and GEM. This paper advocates the use of household level gender disaggregated data because much gender inequality occurs in and emanates from the household level where culture plays a very important role in allocation of resources and decision-making. Because most human development indicators are aggregates or averages, they can be misleading. They need to be supplemented by distributional and disaggregated data as demonstrated in the Kenyan case. The importance is emphasised of studying coping mechanisms of household/families for dealing with economic hardship and other misfortunes, such AIDS.

Urbanization, population transition, and growth

This paper analyzes a dual economy consisting of urban market areas and less developed rural areas with or without local markets. Urban areas have better opportunities for earnings and education than rural areas. Rural families choose whether to move to urban areas at costs that differ from location to location. As per capita output grows relative to the moving cost, urbanization proceeds, leading to lower fertility, more investments in human and physical capital per child relative to output per worker, and faster economic growth. These impacts are stronger if rural areas have no access to markets.

Application of spatial analysis techniques to adjust for fertility trends and identify interplot competition in early stage sugarcane selection trials

Most sugarcane breeding programs in Australia use large unreplicated trials to evaluate clones in the early stages of selection. Commercial varieties that are replicated provide a method of local control of soil fertility. Although such methods may be useful in detecting broad trends in the field, variation often occurs on a much smaller scale. Methods such as spatial analysis adjust a plot for variability by using information from immediate neighbours. These techniques are routinely used to analyse cereal data in Australia and have resulted in increased accuracy and precision in the estimates of variety effects. In this paper, spatial analyses in which the variability is decomposed into local, natural, and extraneous components are applied to early selection trials in sugarcane. Interplot competition in cane yield and trend in sugar content were substantial in many of the trials and there were often large differences in the selections between the spatial and current method used by the Bureau of Sugar Experiment Stations. A joint modelling approach for tonnes sugar per hectare in response to fertility trends and interplot competition is recommended.

Toward better outcomes with tacrolimus therapy: Population pharmacokinetics and individualized dosage prediction in adult liver transplantation

Patient outcomes in transplantation would improve if dosing of immunosuppressive agents was individualized. The aim of this study is to develop a population pharmacokinetic model of tacrolimus in adult liver transplant recipients and test this model in individualizing therapy. Population analysis was performed on data from 68 patients. Estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F) using the nonlinear mixed effects model program (NONMEM). Factors screened for influence on these parameters were weight, age, sex, transplant type, biliary reconstructive procedure, postoperative day, days of therapy, liver function test results, creatinine clearance, hematocrit, corticosteroid dose, and interacting drugs. The predictive performance of the developed model was evaluated through Bayesian forecasting in an independent cohort of 36 patients. No linear correlation existed between tacrolimus dosage and trough concentration (r(2) = 0.005). Mean individual Bayesian estimates for CL/F and V/F were 26.5 8.2 (SD) L/hr and 399 +/- 185 L, respectively. CL/F was greater in patients with normal liver function. V/F increased with patient weight. CL/F decreased with increasing hematocrit. Based on the derived model, a 70-kg patient with an aspartate aminotransferase (AST) level less than 70 U/L would require a tacrolimus dose of 4.7 mg twice daily to achieve a steady-state trough concentration of 10 ng/mL. A 50-kg patient with an AST level greater than 70 U/L would require a dose of 2.6 mg. Marked interindividual variability (43% to 93%) and residual random error (3.3 ng/mL) were observed. Predictions made using the final model were reasonably nonbiased (0.56 ng/mL), but imprecise (4.8 ng/mL). Pharmacokinetic information obtained will assist in tacrolimus dosing; however, further investigation into reasons for the pharmacokinetic variability of tacrolimus is required.

Estimating trends and seasonality in coronary heart disease

We present two methods of estimating the trend, seasonality and noise in time series of coronary heart disease events. In contrast to previous work we use a non-linear trend, allow multiple seasonal components, and carefully examine the residuals from the fitted model. We show the importance of estimating these three aspects of the observed data to aid insight of the underlying process, although our major focus is on the seasonal components. For one method we allow the seasonal effects to vary over time and show how this helps the understanding of the association between coronary heart disease and varying temperature patterns. Copyright (C) 2004 John Wiley Sons, Ltd.

Genetic population structure and call variation in a passerine bird, the satin bowerbird, Ptilonorhynchus violaceus

Geographic variation in vocalizations is widespread in passerine birds, but its origins and maintenance remain unclear. One hypothesis to explain this variation is that it is associated with geographic isolation among populations and therefore should follow a vicariant pattern similar to that typically found in neutral genetic markers. Alternatively, if environmental selection strongly influences vocalizations, then genetic divergence and vocal divergence may be disassociated. This study compared genetic divergence derived from 11 microsatellite markers with a metric of phenotypic divergence derived from male bower advertisement calls. Data were obtained from 16 populations throughout the entire distribution of the satin bowerbird, an Australian wet-forest-restricted passerine. There was no relationship between call divergence and genetic divergence, similar to most other studies on birds with learned vocalizations. Genetic divergence followed a vicariant model of evolution, with the differentiation of isolated populations and isolation-by-distance among continuous populations. Previous work on Ptilonorhynchus violaceus has shown that advertisement call structure is strongly influenced by the acoustic environment of different habitats. Divergence in vocalizations among genetically related populations in different habitats indicates that satin bowerbirds match their vocalizations to the environment in which they live, despite the homogenizing influence of gene flow. In combination with convergence of vocalizations among genetically divergent populations occurring in the same habitat, this shows the overriding importance that habitat-related selection can have on the establishment and maintenance of variation in vocalizations.

Population dynamics and gene flow of Helicoverpa armigera (Lepidoptera : Noctuidae) on cotton and grain crops in the Murrumbidgee Valley, Australia

The population dynamics of Helicoverpa armigera (Hubner) (Lepidoptera: Noctuidae) in the Murrumbidgee Valley, Australia, has been characterized using five highly variable microsatellite loci. In the 2001-2002 growing season, there were very high levels of migration into the Murrumbidgee Valley with no detectable genetic structuring, consistent with previous analyses on a national scale. By contrast, there was significant genetic structuring over the 2002-2003 growing season, with three distinct genetic types detected. The first type corresponded to the first two generations and was derived from local individuals emerging from diapause and their progeny. The second genetic type corresponded to generation 3 and resulted from substantial immigration into the region. There was another genetic shift in generation 4, which accounts for the third genetic type of the season. This genetic shift occurred despite low levels of immigration. During the third generation of the 2002-2003 growing season, different population dynamics was characterized for H. armigera on maize, Zea mays L., and cotton Gossipium hirsutum L. Populations on cotton tended to cycle independently with very little immigration from outside the region or from maize within the region. Maize acted as a major sink for immigrants from cotton and from outside the region. If resistance were to develop on cotton under these circumstances, susceptible individuals from maize or from other regions would not dilute this resistance. In addition, resistance is likely to be transferred to maize and be perpetuated until diapause, from where it may reemerge next season. If low levels of immigration were to occur on transgenic cotton, this may undermine the effectiveness of refugia, especially noncotton refugia.