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.

Major demographic changes in Bangladesh and their socio-economic correlates: Analysis of trends

Catalogues the demographic changes in Bangladesh during the period 1975-2000 and examines how they relate to key socio-economic attributes. Trends are examined in population growth, growth of the working age population, women’s workforce participation, age-dependency ratio, female-male ratio, longevity, fertility, mortality and mean age at first marriage. Bangladesh has made significant breakthroughs in all these areas, a feat not matched by most other South Asian countries, but comparable with the South-East Asia region as whole. The study isolates factors contributing to the changes in each attribute. It assesses the correlation between Bangladesh’s demographic changes and selected socio-economic indicators namely, its per capita GDP, female labour force participation, per capita public health expenditure and educational achievements by both men and women. All five socio-economic variables display statistically significant correlation, in varying degrees, with measures of the demographic changes. Per capita GDP is probably the most significant determinant of demographic changes in Bangladesh. The study observes that men’s education reinforces women’s education and with increased workforce participation contributed to reduced fertility. The study suggests that the role of family planning programs in curbing population growth in Bangladesh maybe overestimated.

Trends in cigarette smoking in 36 populations from the early 1980s to the mid-1990s: Findings from the WHO MONICA Project

Objectives. This report analyzes cigarette smoking over 10 years in populations in the World Health Organization (WHO) MONICA Project (to monitor trends and determinants of cardiovascular disease). Methods. Over 300 000 randomly selected subjects aged 25 to 64 years participated in surveys conducted in geographically defined populations. Results. For men, smoking prevalence decreased by more than 5% in 16 of the 36 study populations, remained static in most others, but increased in Beijing. Where prevalence decreased, this was largely due to higher proportions of never smokers in the younger age groups rather than to smokers quitting. Among women, smoking prevalence increased by more than 5% in 6 populations and decreased by more than 5% in 9 populations. For women, smoking tended to increase in populations with low prevalence and decrease in populations with higher prevalence; for men, the reverse pattern was observed. Conclusions. These data illustrate the evolution of the smoking epidemic in populations and provide the basis for targeted public health interventions to support the WHO priority for tobacco control.