. In developing countries are female literacy levels and fertility levels connected?

Question

. In developing countries are female literacy levels and fertility levels connected?

Answer 1

Here are 5 developing countries with both the female literacy level and fertility level.

Country.....literacy — fertility

Argentina...97.2 — 2.09

Russia.... 99.2 — 1.4

India.....54.16 — 4.55

S. Africa..80.9 — 2.11

Brazil...88.6 — 1.86

Russia has the highest literacy with the lowest fertility and India has the lowest literacy with the highest fertility - good for your theory! But look at the other 3 countries. There literacy and fertility are not quite as conclusive. But I do personally agree that literacy and fertility go hand in hand. Religion also enters into the picture.

While trying to find India's fertility level I did come across this paragraph that talks about female literacy and fertility. It states that there is a direct relationship between the two. Keep in mind it is for India only.

"Survey data from India consistently show that female education above the primary school-level is the most powerful determinant of lowered fertility. The Government of India's strategies of increasing accessibility to family planning methods and improving the population's quality of life have been impeded by low levels of female education. The finding that rural women experience 0.8 more live births than their urban counterparts is a reflection of the higher education of the latter group. Within Calcutta, females in slum areas had an average of 5.6 live births compared to 3.5 births among those from nonslum parts of the city, again reflecting the influence of education on fertility. In the high-fertility states of Uttar Pradesh, Rajasthan, Bihar, Madhyapradesh, Haryana, and Jammu and Kashmir, the percentage of females with an education above the primary level is under 5%. "

http://www.popline.org/docs/0038/063969....

Answer 2

hi,,,

The influence of economic conditions on mortality has been

recognized at least since biblical times. Empiricism of the most casual sort was sufficient to establish the link between food supply and mortality. Other components of living standards, such as shelter and living space, awaited a revolution in scientific method before their influence was finally acknowledged. But recent years have witnessed a movement away from economic determinism in mortality analysis. It is widely believed that mortality has become increasingly dissociated from economic level because of a diffusion of medical and health technologies, facilities and personnel that occurred, in large part, independently of economic level, yet this position has its critics who have gained a sympathetic audience.1–4 This

article utilizes readily available evidence in a new but obvious

way to estimate the relative contribution of economic factors

to increases in life expectancy during the 20th century. The

evidence consists of cross-sectional relationships between

national life expectancies and national income per head

evaluated during three different decades of the 20th century.

These relationships are further used to assess the realism

of certain economic-demographic models and to re-examine

what have become classical distinctions regarding sources

of mortality declines in Western and non-Western areas.

There are several reasons for focusing on national income

rather than on another socio-economic variable. First, national income is probably the best single indicator of living standards in a country, since it comprises the value of all final products (goods and services) produced in a certain period. A wide range of these products can be expected to influence mortality, and expenditures on all of them are represented, with varying weights, in national income. It is the indicator most comprehensive of these multiple factors. Secondly, as the leading index of level of economic development, income per head is the focus of growth models from which policy measures are derived.

Types of relationships

National income per head in constant dollars is an index of the total value of final products produced per inhabitant during a defined period, exclusive of goods which merely replace losses from depreciation of capital equipment. There is no reason to expect a direct influence of national income per head on mortality; it measures simply the rate of entry of new goods and services into the household and business sectors. Its influence is indirect; a higher income implies and facilitates, though it does not necessarily entail, larger real consumption of items affecting health, such as food, housing, medical and public health services,education, leisure, health-related research and, on the negative side, automobiles, cigarettes, animal fats and physical inertia. Levels of mortality and economic development can be related

to one another conceptually and substantively in a variety of

ways. It is useful at the outset to distinguish among at least

three different types of relationships that have been proposed

by various analysts, although the exact formulation is often

only implicit in their work. In order to simplify the task, we

confine the review to international studies. Level of income influences level of mortality at a moment in time

Attempts at empirical estimation have focused on the crosssectional relationship between mortality and economic level.  Most commonly, the relationship between national infant mortality rates and levels of income has been examined.5–7 Coefficients of correlation between the variables have been found to be consistently high, of the order of
0.8. The relationship is sufficiently strong for infant mortality rates on occasion to have been used as indicators of income levels when the requisite data for computing the latter are missing.8 Gordon et al.9 have suggested that the death rate of children in their second year of life may be a better indicator of general health levels than infant morality, which responds to a number of influences not present at other ages. Frederiksen2 provides partial support by showing that death rates at ages 1–4 are more closely correlated with gross national product per head in15 countries than are death rates at ages 0–1, 20–24, or 65–69. One study, confined to less developed countries, has demonstrated a close cross-national relationship between an index of mortality at all ages and from all causes, life expectancy at birth and the level of national income. Vallin suggests that no country can attain a life expectancy of more than 60 years without having made very substantial progress out of the category, ‘less developed’.10 At the same time, he stresses that the relationship is not deterministic and that a nation can, within limits, modify its life expectancy independently of its level of income. We shall re-examine the type of relationship studied by Vallin in a subsequent section.

On several occasions the United Nations Population Division

has expressed the opinion that the cross-sectional relationship between mortality and level of economic development has become progressively weaker over time.11,12 Others have echoed this claim and referred to a ‘dissociation’ of the two types of variables.  However, data to support the claim have not been presented, and the present analysis fails to support the contention.

Rate of change of income influences rate of change of mortality. A cross-sectional relationship between income and mortality, firmly established in the references cited earlier, also implies a dynamic relationship between the two. If the relationship is indeed causal, then a certain change in income should be associated with a particular change in mortality, with relative magnitudes of change determined by coefficients of the relationship. Additional elements may figure in the dynamic relationship, however. In particular, the cross-sectional relationship between mortality and income may itself be changing in response to new influences.

Malthus, of course, postulated a negative dynamic relationship between mortality and income level as a central tenet of his dismal theory. Those who have recently examined the relationship fail to uncover support for the postulated relationship. Stolnitz14 states that recent mortality trends in Asia, Latin America and Africa have been ’remarkably neutral’ with respect to economic events. Demeny states that ‘the large amount of statistical material on underdeveloped countries which is available for the past two or three decades reveals the almost complete absence of such a relationship . . . . There is a high degree of uniformity between mortality trends through time and in different countries—a uniformity not existent as far as

trends in per capita income are concerned’. Although perhaps obvious, it may be worth emphasizing that such a pattern is not inconsistent with a tight cross-sectional relationship between mortality and economic level throughout the period under consideration, provided that the structure of the cross-sectional relationship is changing.

WOW...

Your questions dear is very deep & I think I will end-up with a news paper, which going to make you really bored.

I wish this will help

:-:NTS