Physical quality of life index: Some international and Indian applications

In this paper, an attempt has been made to construct the physical quality of life index (PQLI) for some countries and for the Indian States as well. Three important indicators, viz. literacy rate, infant mortality rate and life expectancy at birth, reflecting the quality of life have been chosen and combined with equal weights to obtain PQLI. The rationale of equal weights, apart from any subjective judgement, may also be found in a mathematical model presented here. It is observed that PQLI rises sharply with per capita GNP but after a certain stage, an increase of per capita GNP is not accompanied by an increase of PQLI.     

Measurement of social development: an international comparison

PQLI and HDI are the two most popular measures of development, besides per capita income. Over the years, PQLI appears to be not much in use for regional comparisons, especially after the introduction of HDI. While PQLI considers only the physical variables—adult literacy, life expectancy at birth and infant survival rate, HDI has life expectancy at birth, educational attainment and real GDP per capita (PPP$). PQLI and HDI are similar, the main difference between the two being the inclusion of income in HDI and exclusion of the same from PQLI. In a sense, HDI represents both physical and financial attributes of development and PQLI has only the physical aspects of life. The present author took the lines of PQLI to express development in terms of physical variables and considering development as a multidimensional phenomenon, Ray (1989) [Ray, A. K. (1989). On the measurement of certain aspects of social development, Social Indicators Research (Vol. 21, pp. 35–92). The Netherlands: Kluwer Academic Publishers.] included as many as 13 physical variables to represent social development across 40 countries; no financial variable was included in the construction of composite index, termed as the Social Development Index, SDI. Incidentally, like PQLI, SDI was introduced before HDI. Unlike PQLI and HDI, SDI considers (i) a large number of indicators representing various concern areas and (ii) a set of objective methods for combining the development indicators as a composite index. Ray (1989) has been restated and updated in this article with newer cross-country information. In the present study, SDI has been constructed for over 102 countries, including 21 OECD countries, using 10 development indicators, instead of 13 indicators in the past. Apart from presenting objective methods for combining indicators into SDI, the present study asserts that SDI works better than HDI as a measure of development for an international comparison. The views expressed in the article are those of the author and not of the institution he serves.     

How female literacy affects fertility: the case of India

Recent studies indicate that there is a direct correlation between increased literacy and decreased fertility. This link was demonstrated in study that covered 90% of India's population. Studies in other developing countries have confirmed this finding. In addition, high literacy rates have been found to correspond to high infant survival rates. Researchers also found that there was little change in the relationship between literacy and fertility when they were both controlled for different levels of urbanization. The problem is that only 1 in 4 Indian women are literate. However, India's government has a program in place the goal of which is to have universal literacy. In Kerala, female literacy is the highest (65%). And at 3.4 children/women, it has 1 of the lowest fertility rates. For the 14 states studied, the total fertility rate was 5.0 children/woman, the child mortality rate was 126/1000, and the female literacy rate was 22%. In contrast in Rajasthan where female literacy is 11% (the lowest of the 14 states studied) fertility is the highest at 6.0 children/woman. No state with higher than average fertility had higher than average female literacy rates. Literate women are likely to have more surviving children because they are more aware of good health practices, and they tend to live in better circumstances. As a result, couples need fewer births to reach their desired family size.     

[An analysis of regional differential mortality].]

Regional differences in mortality and life expectancy in China are explored, and the socioeconomic, cultural, and educational factors affecting such differences are considered using data from the 1982 census. The author notes that mortality, particularly infant mortality, is highest in economically underdeveloped areas, and female infant mortality is high in both rural and urban areas. It is also observed that female life expectancy is 3.26 years longer than for males in urban areas, and 1.38 years longer in rural areas.     

A study on mortality rates and expectation of life at birth in demography]

An "age-time-area diagram" (referred to as a-t diagram) which is used as the basis for discussing different used and applications of variously defined mortality rates, as well two kinds of measurements for life expectancy is proprosed. The proposal is built upon the Lexis diagram. The a-t diagram is used to define a new way of measuring child mortality, projecting population, and proposing a formula for measuring successive and nonsuccessive life expectancy.     

Diet,mortality and life expectancy: a cross national analysis

"There are numerous reasons why mortality and life expectancy vary between countries. Epidemiological studies seem to indicate that dietary variations may be among them. A sample of 51 countries studied with data from the International Comparisons Project and other sources, shows that after controlling for nutrient intake, consumption of medical goods and services, income distribution, weather, and literacy, countries with more meat and poultry in their diet have lower life expectancies after age five. The results for infant mortality and child death between one and five indicate that a more animal-intensive diet may be actually beneficial, especially if fish consumption is increased and meat and poultry consumption reduced."     

The Middle East population puzzle

An overview is provided of Middle Eastern countries on the following topics; population change, epidemiological transition theory and 4 patterns of transition in the middle East, transition in causes of death, infant mortality declines, war mortality, fertility, family planning, age and sex composition, ethnicity, educational status, urbanization, labor force, international labor migration, refugees, Jewish immigration, families, marriage patterns, and future growth. The Middle East is geographically defined as Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, United Arab Emirates, Yemen, Gaza and the West Bank, Iran, Turkey, and Israel. The Middle East's population grew very little until 1990 when the population was 43 million. Population was about doubled in the mid-1950s at 80 million. Rapid growth occurred after 1950 with declines in mortality due to widespread disease control and sanitation efforts. Countries are grouped in the following ways: persistent high fertility and declining mortality with low to medium socioeconomic conditions (Jordan, Oman, Syria, Yemen, and the West Bank and Gaza), declining fertility and mortality in intermediate socioeconomic development (Egypt, Lebanon, Turkey, and Iran), high fertility and declining mortality in high socioeconomic conditions (Bahrain, Iraq, Kuwait, Qatar, Saudi Arabia, and the United Arab Emirates), and low fertility and mortality in average socioeconomic conditions (Israel). As birth and death rates decline, there is an accompanying shift from communicable diseases to degenerative diseases and increases in life expectancy; this pattern is reflected in the available data from Egypt, Kuwait, and Israel. High infant and child mortality tends to remain a problem throughout the Middle East, with the exception of Israel and the Gulf States. War casualties are undetermined, yet have not impeded the fastest growing population growth rate in the world. The average fertility is 5 births/woman by the age of 45. Muslim countries tend to have larger families. Contraceptive use is low in the region, with the exception of Turkey and Egypt and among urban and educated populations. More than 40% of the population is under 15 years of age. The region is about 50% Arabic (140 million). Educational status has increased, particularly for men; the lowest literacy rates for women are in Yemen and Egypt. The largest countries are Iran, Turkey, and Egypt.     

A survey of population in the ESCAP region

In 1983, the ESCAP region added 44 million people, bringing its total population to 2600 million, which is 56% of the world population. The annual rate of population growth was 1.7% in 1983 compared to 2.4% in 1970-75. The urban population rose from 23.4% in 1970 to 26.4% in 1983, indicative of the drift from rural areas to large cities. In 1980, 12 of the world's 25 largest cities were in the ESCAP region, and there is concern about the deterioration of living conditions in these metropoles. In general, however, increasing urbanization in the developing countries of the ESCAP region has not been directly linked to increasing industrialization, possibly because of the success of rural development programs. With the exception of a few low fertility countries, a large proportion of the region's population is concentrated in the younger age groups; 50% of the population was under 22 years of age in 1983 and over 1/3 was under 15 years. In 1983, there were 69 dependents for every 100 persons of working age, although declines in the dependency ratio are projected. The region's labor force grew from 1100 million in 1970 to 1600 million in 1983; this growth has exceeded the capacity of country economies to generate adequate employment. The region is characterized by large variations in life expectancy at birth, largely reflecting differences in infant mortality rates. Whereas there are less than 10 infant deaths/1000 live births in Japan, the corresponding rates in Afghanistan and India are 203 and 121, respectively. Maternal-child health care programs are expected to reduce infant mortality in the years ahead. Finally, fertility declines have been noted in almost every country in the ESCAP region and have been most dramatic in East Asia, where 1983's total fertility rate was 40% lower than that in 1970-75. Key factors behind this decline include more aggressive government policies aimed at limiting population growth, developments in the fields of education and primary health care, and greater availability of contraception through family planning programs.     

HIV/AIDS and Cross-National Convergence in Life Expectancy

This article analyzes the effect of HIV/AIDS on the cross-national convergence in life expectancy as well as infant and child survival rates by comparing three scenarios. One is based on historical and future best-guess estimated values given the existence of the epidemic. The second scenario assumes that the effect of the epidemic is much worse than expected. The final scenario is based on hypothetical values derived from estimations where the mortality caused by the epidemic is removed. For life expectancy, convergence becomes stalled in the late 1980s (without weighting by country population size) or 1990s (with weighting). Convergence in infant and child survival rates does not become stalled, but slows down. These results are mainly attributable to the epidemic since all signs of stalled convergence or even divergence disappear in the “No AIDS scenario.” Given the existence of the epidemic, however, the reduced degree of inequality in life expectancy attained by 1985 is only expected to be achieved again by 2015 at the earliest. If the epidemic turns out much worse than expected, divergence could continue to 2050. No divergence is to be expected in infant and child survival rates in any of the scenarios.     

New estimates of the vital rates of the United States black population during the nineteenth century

The difficulties of obtaining credible estimates of vital rates for the black population throughout the entire nineteenth century are overcome in this study. The methodology employed the notion of deviating networks of mortality rates for each general mortality level, which was taken from the United Nations studyThe Concept of a Stable Population. Period life tables and vital rates for intercensal periods were generated from the new estimates of the black population at each census date. The results of this study are highly compatible both with the life tables for the death-registration states in the twentieth century and the recent Coale and Rives reconstruction for the period from 1880 to 1970 and with several estimates of vital rates previously made for the mid-nineteenth century. This study places the mean life expectancy at birth for the black population during the nineteenth century at about 33.7 years for both sexes. The infant death rate (1000m (0)) is shown to have varied between 222 and 237 for females and between 266 and 278 for males. The intrinsic crude death rate centered on 30.4 per thousand during the century, while the birth rate declined from 53.2 early in the century to about 43.8 at the end.     

The Segmented Trend Line of Highest Life Expectancies

The well‐known Oeppen–Vaupel straight line of maximum female life expectancies showed that the highest life expectancy observed in a given year increased linearly from 1840 to 2000. Their analysis fueled major controversy, especially when used to extrapolate future improvements in life expectancy at the same pace. We improve on the empirical analysis by enriching the dataset, expanding the period to 1750–2005, and considering both maximum life expectancy at birth and lowest age‐specific survival rates. It clearly appears that the original Oeppen–Vaupel straight line must be divided into several segments characterized by different slopes and that each segment corresponds to a major advance in the health transition. There is room to push life expectancy higher, but unless some new breakthrough increases the human life span, progress will very likely decelerate as mortality reduction affects individuals at older and older ages. The main key to the future lies not in knowing whether the observed straight line can be extrapolated but in anticipating the next major health improvement that will lead to an additional increase in life expectancy.     

Asia's population and development in retrospect and prospect

By 1989 Asia's population will reach 3 billion. That Asia's countries can change the course of population development has been shown by China, whose population growth rate has decreased to 1.2%. 58% of the world's population in 1985 was Asian, and 53% of it was concentrated in 11 Asian countries, of which 37.6% was accounted for by India and China. Asia's population density is 3 times the world average, and the number of persons sustained by a square kilometer of land in Asia is 2.5 times the world average. Asia's population is young (median age 20.3), which means a high dependency burden, a large number of women of childbearing age, and low quality of life, as measured by infant mortality, life expectancy, and literacy. Rapid population growth ensures a low rate of development. Asia's goals are to achieve a 1% growth rate by year 2000, zero population growth and replacement level by 2015 for East Asia and 2020 for South Asia. The World Bank estimates that Asia's population will not stabilize until the end of the 21st century, by which time it will have reached 6 billion. Asia must find a way of achieving both population control and economic development. 5 recommendations are made to the Asian Forum of Parliamentarians on Population and Development (AFPPD): 1) that the AFPPD sponsor the activities of "the Day of 3 billion"; 2) that seminars and conferences on population be held among Asian nations; 3) that high-fertility countries adopt late marriages, few births, and programs for maternal and child health; 4) that organizations for family planning be strengthened and given the resources to upgrade the status of women; and 5) that international cooperation in the area of population be intensified.     

Falling Short of Highest Life Expectancy: How Many Americans Might Have Been Alive in the Twentieth Century?

Life expectancy at birth in the United States during the twentieth century was lower than in many other highly developed countries. We investigate how this mortality disadvantage in the last 100 years translates into the number of hypothetical lives lost and their sex and age structure. We estimate the hypothetical US population if it had experienced in each decade since 1900 the mortality level of the country with the then highest life expectancy and compare the results to the actual figures in 2000. By 2000, the number of additional people who could have been alive had the mortality levels in the United States been as low as those in countries with the highest life expectancy was 66 million. This number is distributed equally between males and females. Suboptimal mortality at reproductive ages is crucial for the cumulative effect of potential lives lost, resulting from premature deaths of women who could still become first‐time mothers or bear additional children. Out of the 66 million additional persons who could have been alive in 2000, 45 million are attributable to those indirect deaths. Although the differences in the composition of the population by sex and age under the two mortality regimes are minor, the majority of people who might have been alive—54 million—were of working age or younger.     

Population statistics] as of July 1, 1998

This article presents estimates of relevant population numbers and vital rates in Thailand as of July 1, 1998. Utilizing the standard demographic techniques of analysis, the estimates provided are assured to be the most accurate demographic estimates possible. Total population was estimated at 61,143,000. Estimates by sex, locales, region, and by age group are included. In addition, the crude birth rate per 1000 population was estimated at 18.7; the crude death rate per 1000 population was 6.5. For the natural growth rate the estimate was at 1.2%, and the infant mortality rate was 25.0 per 1000 live births. In terms of life expectancy at birth, the estimate for males was 69.9 years, while for females it was 74.9 years. Additional years in life expectancy at age 60 were 20.3 years for males and 23.9 years for females. The total fertility rate per woman is 1.98, and contraceptive prevalence is 72.2%. The demographic data will be disseminated to Thai and international population researchers and planners.     

[Age-specific mortality and life expectancy].]

The author attempts to assess the degree of influence of infant mortality on average life expectancy and to develop a method to directly revise average life expectancy given a change in mortality.     

The momentum of mortality change

Mortality change is not usually assigned much importance as a source of population growth when future population trends are discussed. Yet it can make a significant contribution to population momentum. In populations that have experienced mortality change, cohort survivorship will continue varying for some time even if period mortality rates become constant. This continuing change in cohort survivorship can create a significant degree of mortality-induced population change, a process we call the ‘momentum of mortality change’. The momentum of mortality change can be estimated by taking the ratio of e ₀ (the period life expectancy at birth) to CAL (the cross-sectional average length of life) for a given year. In industrialized nations, the momentum of mortality change can attenuate the negative effect on population growth of declining fertility or sustained below-replacement fertility. In India, where population momentum has a value of 1.436, the momentum of mortality change is the greatest contributor to its value.     

Horizontal and Vertical Equity Objectives of Child Benefit Systems: An Empirical Assessment for European Countries

The present study investigates the determinants of life expectancy in the presence of economic misery using Pakistan’s time series data over the period of 1972–2012. The stationary properties of the variables are examined by applying unit root test accommodating structural breaks. The ARDL bounds testing approach to cointegration is applied to examine the long run relationship between the variables. Our findings show that cointegration between the variables is confirmed. Moreover, health spending improves life expectancy. Food supply contributes to life expectancy. A rise in economic misery deteriorates life expectancy. Urbanization enhances life expectancy while illiteracy declines it. The causality analysis reveals that life expectancy is Granger cause of health spending, food supply, economic misery, urbanization and illiteracy. This paper opens up new insights for policy making authorities to consider the role of economic misery while formulating comprehensive economic policy to improve life expectancy in Pakistan.     

The momentum of mortality change

Mortality change is not usually assigned much importance as a source of population growth when future population trends are discussed. Yet it can make a significant contribution to population momentum. In populations that have experienced mortality change, cohort survivorship will continue varying for some time even if period mortality rates become constant. This continuing change in cohort survivorship can create a significant degree of mortality-induced population change, a process we call the 'momentum of mortality change'. The momentum of mortality change can be estimated by taking the ratio of e0 (the period life expectancy at birth) to CAL (the cross-sectional average length of life) for a given year. In industrialized nations, the momentum of mortality change can attenuate the negative effect on population growth of declining fertility or sustained below-replacement fertility. In India, where population momentum has a value of 1.436, the momentum of mortality change is the greatest contributor to its value.     

Vital rates in India 1961-71 estimated from 1971 census data

Abstract In the last decade the increase in the population of India, while, of course, very large, was smaller than predicted by official forecasts. With the use of recent census and sample registration data - in the absence of age-specific rates and adequate vital statistics - this paper provides estimates of fertility and mortality through the reverse-survival and forward-projection methods. Birth rates are estimated as 40·5-42, death rates as 18-20, and life expectancy at birth as 45-46 years. Mortality decline had been smaller than forecast but more than during any comparable period in the past, even though current mortality levels, particularly infant mortality, are still high. Males continue to have a longer life expectation than females, with a difference that has widened in the past decade. The decline of between seven and ten per cent in the crude birth rate is largely due to changes in marital fertility and to some extent to changes in age and marital composition. Because of greater decline in death rates than birth rates, the 1961-71 decade shows a higher rate of population growth than previous periods.     

The threshold hypothesis: evidence from less developed Latin American countries, 1950 to 1980

Historical research among European countries finds large differences in the level of social, economic or demographic development among countries, or regions within countries at the time marital fertility rates began their decline from traditional high levels. This research tests a threshold hypothesis which holds that fertility will decline from traditional high levels if threshold levels of life expectancy and literacy are surpassed. Using a pooled regression analysis of 1950, 1960, 1970 and 1980 crude births rates (CBRs) in 20 less developed Latin American countries, in conjunction with 10-year lagged measures of social, economic and family planning program development, analyses reveal statistically significant effects of passing Beaver's (1975) threshold levels of 1950 literacy, or 1950 life expectancy, that are independent of levels of lagged literacy (or lagged life expectancy), economic and family planning program development, as well as measures that control period effects.