Geography
Life Expectancy
Life expectancy refers to the average number of years a person is expected to live, based on current mortality rates. It is a key indicator of a population's overall health and well-being. Factors such as access to healthcare, sanitation, nutrition, and socioeconomic status can influence life expectancy.
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11 Key excerpts on "Life Expectancy"
- Kate M. Grady, Andrew M. Severn, Paul R. Eldridge, Susan Riddick-Grisham, Laura Deming, Susan Riddick-Grisham, Laura Deming(Authors)
- 2011(Publication Date)
- Routledge(Publisher)
The authors point out that Life Expectancy does Contents Life Expectancy Defined ........................................................................................................... 855 How Is Life Expectancy Determined? ....................................................................................... 857 Disability Literature ................................................................................................................. 858 Applying the Literature to Practice .......................................................................................... 880 Conclusion .............................................................................................................................. 882 References ............................................................................................................................... 882 856 ◾ Pediatric Life Care Planning and Case Management not refer to the actual time associated with a person living but rather the time it takes for a person to die. Hutton and Pharoah (2006) state that their definition is based on the average time to death of a given population. In other words, Life Expectancy is the average lifespan of multiple individuals who have similar characteristics. The concept of average or mean indi-cates that individual members of a given population may have higher or lower years of Life Expectancy. If one were going to estimate Life Expectancy using this definition, they would be predicting the client’s Life Expectancy based on the average Life Expectancy of multiple indi-viduals with similar demographic characteristics. These demographic characteristics might include age, gender, disability type, severity of impairment, comorbidity, socioeconomic class, access to health care, social support, geographic location, etc. Life Expectancy is thus influ-enced by numerous factors, including demographic characteristics (Forman, Caruthers, & Londner, 2007).
eBook - ePub- James Thorson(Author)
- 2013(Publication Date)
- Routledge(Publisher)
Demography is the study of populations: how many people there are, in what proportions, how these numbers and percentages are changing, and what effect these changes will make. When we usually think about the demography of aging, we think of total numbers and proportions of older people in the population as a whole. We also need to consider their longevity, or how long people live, and mortality-what people die of and how that is changing as well. Demography is influenced by three things: births, deaths, and migration. There are a few additional terms we will use as we look at these different concepts: cohort is a term we have already considered. It is a category within a category. The elderly, for example, are a category within the entire population. One could define an age cohort in terms of the years they were born (for example, those born between 1900 and 1920) or in terms of some common experience, such as baby boomers or depression babies. In other words, a cohort is a group with particular boundaries or characteristics that must be defined. The young old and the old old could be seen to be two different cohorts.Life Expectancy is the average number of years of remaining life from a particular point, such as Life Expectancy from birth or Life Expectancy at age 65. Life Expectancy is usually expressed as an arithmetic mean or average. A 65-year-old white woman, for example, has a Life Expectancy of an additional 19.1 years, on the average.Life span is the maximum possible length of life for the species. Most individuals do not live out their entire potential life span: for humans, for example, the life span is about 115 to 120 years (but hardly anyone makes it this long). For elephants, the life span is about 70 years; for the Galapagos tortoise, it's 150. While we usually think of life span as the maximum potential, it is sometimes used in another way: to speak of the practical potential for most people, not just the few at the extreme end. It has been said, for example, that the practical potential life span for most humans is roughly 85 years (Fries & Crapo, 1981).Mean is the arithmetic average: the mean age of a group is found by adding the ages of each member and dividing by the number in the group. The mean age for a group of two people, say a newborn baby and a ten year-old, would thus be five years.
eBook - PDF- M. McGillivray, I. Dutta, D. Lawson, M. McGillivray, I. Dutta, D. Lawson(Authors)
- 2010(Publication Date)
- Palgrave Macmillan(Publisher)
45 1 Introduction Increasing disparity in Life Expectancy among countries has been widely documented and discussed. The depressing and disturbing story is well-known but worth reiterating briefly. Global Life Expectancy, as was noted in Chapter 1, has improved continually from 48 years in the early 1950s to 68 years in the early 2000s (WHO 1996; UNDP 2007). The star regional performer has been Asia, which has achieved an increase in Life Expectancy from 41.1 to 67 years over the same period (Dorling et al. 2006). Life Expectancy in many countries now exceeds 80 years. The highest achievers are Japan and Hong Kong, in which Life Expectancy was 82.3 and 81.9 years, respectively (UNDP 2007). The experience for many other countries has been radically different. Life Expectancy in sub-Saharan Africa increased steadily from 38.2 years in the early 1950s to 50.1 years in the early 2000s. It fell to 48.8 years by the early 2000s, some 33 years less than in OECD countries, owing mainly to the HIV/ AIDS pandemic experienced in the region (Dorling et al. 2006). Four sub-Saharan African countries in the early 2000s recorded life expectan- cies that were less than 42.4 years, which was the regional achievement some 40 years earlier (UNDP 2007). Life Expectancy had fallen by the mid-2000s to 39.2 years in Lesotho, more than 43 years less than in Japan during the same period (UNDP 2007). Sub-Saharan Africa is not alone in experiencing declines. Life Expectancy in a number of former Soviet, Eastern European countries fell during the 1990s. Between the early 1970s and early 2000s it fell from 71.5 to 68.4, 69 to 64.8 and 70.1 to 67.6 years in Belarus, Russia and Ukraine, respectively. These divergent trends and the global disparities they imply have not been ignored by the researchers. There is, in fact, a huge literature on 3 Global Inequality in Health: Disparities in Human Longevity among Countries Mark McGillivray
eBook - ePub- OECD(Author)
- 2017(Publication Date)
- OECD(Publisher)
Chapter 2. What has driven Life Expectancy gains in recent decades? A cross-country analysis of OECD member statesCountries with higher national income and health spending tend to have longer life expectancies. But these factors can only account for a part of Life Expectancy differences across countries. This chapter analyses the factors contributing to health status, including a closer assessment of the determinants of health that go beyond the health system. It shows that on average, a 10% increase in health spending per capita is associated with a gain of 3.5 months of Life Expectancy. The same rate of improvement in healthier lifestyles (10%) is associated with a gain of 2.6 months of Life Expectancy. Wider social determinants are also important: a 10% increase in income per capita is associated with a gain of 2.2 months of Life Expectancy, and a 10% increase in primary education coverage with 3.2 months. For income, minimum absolute levels are particularly critical to protecting people’s health.The main policy implication emerging from this analysis is the significant opportunities for health improvement from coordinated action across ministries responsible for education, the environment, income and social protection, alongside health ministries. This includes inter-sectoral action to address health-related behaviours. Collaboration with the private sector will also be important, especially with employers in relation to working conditions.Introduction
Life Expectancy has risen steadily in most OECD countries, increasing over ten years on average since 1970. Mortality rates from the main causes of death, cardiovascular diseases and cancer, have generally fallen. Today, countries with higher national income and health spending tend to have longer life expectancies. But these factors can only account for a part of Life Expectancy differences across countries. Furthermore, Life Expectancy varies across population groups. For example, Life Expectancy is lower amongst individuals with lower levels of education across all OECD countries (Murtin et al., 2017).
eBook - PDFCrisis Call For New Preventive Medicine, A: Emerging Effects Of Lifestyle On Morbidity And Mortality
Emerging Effects of Lifestyle on Morbidity and Mortality
- Joseph A Knight(Author)
- 2004(Publication Date)
- World Scientific(Publisher)
6 Chapter 1 Together, these two lifestyle-related conditions accounted for 9.4% of the total US health care expenditures. Schneider 18 recently suggested that the issue most likely to affect the quality of life is their future health needs. Their health will not only affect future health care costs but will also have major consequences on their economic, housing and transportation needs. He proposed the following two possible scenarios that define “the most likely range of future health changes.” (1) Appropriate funding for aging research, disease prevention and improved treatment will result in the triumph of the current major causes of disease and disability of older individuals. As a result, the health of an 85-year-old person in the year 2040 would resemble that of a 70-year-old today. (2) Continue at the current relatively low levels for research sup-port, prevention and treatment such that current health trends continue to show small, if any, improvements in the average health of the elderly. As a result, the future 85+ age group in the year 2040 will not be significantly different from that of a current person in the same age group with its considerable needs for both acute and long-term care. Life Expectancy The estimated life expectation at birth represents the average num-ber of years that a group of newborns would be expected to live if, throughout their lifetime, they were to experience the age-specific prevailing death rates during the year of their birth. In this regard, the average Life Expectancy of a Roman citizen 2000 years ago was about 22 years. 19 In 1900, the average Life Expectancy (birth to death) was 47 years; in 2000 it had increased to a record high of 76.9 years: white females, 80.0 years; black females, 75.0 years; white males 74.8 years; and black males, 68.3 years 20 (Fig. 1.2). Olshansky et al. 21,22 suggested that the average Life Expectancy would not exceed 85 years “in the absence of scientific breakthroughs that modify the
No longer available |Learn moreThe World's Women 2015
Trends and Statistics
- Department of Economic and Social Affairs(Author)
- 2015(Publication Date)
- United Nations Publications(Publisher)
It is derived from age-spe-cific mortality rates and denotes the average number of years a newborn child can expect to live given the current levels of mortality. 7 United Nations, 2013a. The increase in Life Expectancy for women and men is observed in all regions and most coun-tries, but the improvement has not followed the same pattern everywhere (figure 2.1). Advances in Life Expectancy stagnated in sub-Saharan Af-rica during the 1990s as a consequence of the HIV epidemic. Since HIV/AIDS hit women harder than men in that region, 8 the gender gap in Life Expectancy decreased from 2.9 years in 1990–1995 to 1.7 years in 2000–2005. Dur-ing that period, the effect was most striking in Southern Africa, where Life Expectancy at birth dropped from 66 to 54 years for women and from 59 to 51 years for men. More recently, the trend in Life Expectancy has reversed, mainly due to a slowdown in the spread of new HIV in-fections and greater access to and more efficient HIV treatment, together with other health im-provements. 9 Although women’s Life Expectancy recovered more than men’s, the gender gap of 2.4 years in 2010–2015 in sub-Saharan Africa has not yet reached the pre-AIDS-crisis level (figure 2.1). The gender gap generally widens as life expec-tancy increases (figure 2.1). Sub-Saharan Africa has the narrowest gender gap (2.4 years in 2010– 2015), a consequence of high mortality levels overall, the ongoing HIV epidemic and gener-ally high maternal mortality. 10 The region is also home to all 30 countries in the world with a Life Expectancy under 60 years. Sierra Leone has the lowest Life Expectancy at birth in the world, at 46 years for women and 45 years for men, followed by Botswana (47 years for women, 48 for men) and Swaziland (49 years for women, 50 for men). Botswana and Swaziland are also the countries where women in 2010–2015 were expected to die before men (women’s Life Expectancy is 1.5 years less than men’s in Botswana and 1.2 years less in Swaziland).
eBook - PDF- Chloe E. Bird, Peter Conrad, Allen M. Fremont, Stefan Timmermans, Chloe E. Bird, Peter Conrad, Allen M. Fremont, Stefan Timmermans(Authors)
- 2010(Publication Date)
- Vanderbilt University Press(Publisher)
54 Handbook of Medical Sociology becomes even greater. The comparative life ex-pectancy rates listed in Table 4.1 help capture these differences, showing that both the size of the gender gap and the pattern of longevity vary considerably by country and by national wealth (United Nations 2005). As one would expect, the gap in Life Expectancy at birth between the thirty countries with the highest Life Expectancy and the thirty with the lowest Life Expectancy is dramatic, ranging from 82.3 years in Japan to 40.5 years in Zambia and 40.9 years in Zimbabwe. The countries with the lowest Life Expectancy, with few exceptions, are mainly poor countries in Southeast Asia and sub-Saharan Africa. However, a country’s wealth does not necessarily guaran-tee higher average longevity. For example, Japan ranks first in overall Life Expectancy (82.3) but sixteenth in its gross domestic product (GDP) per capita ($31,267). Luxembourg ranks first in GDP per capita ($60,228) but twenty-fourth in Life Expectancy (78.4 years). In fact, none of the four wealthiest countries (Ireland, United States, Luxembourg, and Norway) rank among the top five countries in terms of overall Life Expectancy. Another interesting aspect of the information in Table 4.1 is that the variation in the gender gap in Life Expectancy itself is greater in the thirty wealthier countries (with higher overall life ex-pectancy) than in the thirty poor countries (with lower Life Expectancy). The gap ranges from 3.2 to 7.5 years in the wealthier countries and –1.8 to 4 years in the poorer countries, with some exceptions. Pinnelli (1997), a demographer, has discussed “male supermortality” and suggests that a five-year life-expectancy gender gap favoring women might be normal.
eBook - PDF- Japhet Killewo, Kristian Heggenhougen, Stella R. Quah(Authors)
- 2010(Publication Date)
- Academic Press(Publisher)
A gain in Life Expectancy associated with adopting one health strategy over another (or of being in one exposure group versus another) is the area between the respective survival curves. In order to put a given gain into proper perspective, it is necessary to understand the baseline risk in the control group and the proportion of people who are likely to benefit from the intervention. It is certainly a misconception to view gains in life expec-tancy as increments of time tacked onto the end of a fixed life span. Life Expectancy can be estimated from empirical data by a variety of methods that each have strengths and weaknesses. See also: Clinical Epidemiology; Longevity in Specific Populations; Methods of Measuring and Valuing Health. Citations Beck JR, Kassirer JP, and Pauker SG (1982a) A convenient approximation of Life Expectancy (the DEALE): 1. Validation of the method. American Journal of Medicine 73: 883–888. Beck JR, Pauker SG, Gottlieb JE, Klein K, and Kassirer JP (1982b) A convenient approximation of Life Expectancy (the DEALE): 2. Use in medical decision making. American Journal of Medicine 73: 889–897. Benbassat J, Zajicek G, Van Oortmarssen GJ, Ben-Dov I, and Eckman MH (1993) Inaccuracies in estimates of life expectancies of patients with bronchial cancer in clinical decision making. Medical Decision Making 13: 237–244. Keeler E and Bell R (1992) New DEALES: Other approximations of Life Expectancy. Medical Decision Making 12: 307–311. Kuntz KM and Weinstein MC (1995) Life Expectancy biases in clinical decision making. Medical Decision Making 15: 158–169. Tsevat J, Weinstein MC, Williams LW, et al. (1991) Expected gains in Life Expectancy from various coronary heart disease risk factor modifications. Circulation 83: 1194–1201. Van Den Hout WB (2004) The GAME estimate of reduced Life Expectancy. Medical Decision Making 24: 80–88. Van Den Hout WB (2004) The GAME Estimate of Reduced Life Expectancy: Worked-out Example .
eBook - PDF- Duncan Needham, Julius Weitzdörfer(Authors)
- 2019(Publication Date)
- Cambridge University Press(Publisher)
8 ONS regional life expectancies, 2014–2016 (Data from Office for National Statistics. Retrieved 25 February 2018 from www.statistics.gov.uk/ StatBase/Product.asp?vlnk=8841&Pos=1&ColRank=1&Rank=272) Sarah Harper 134 there are considerable inequalities in Life Expectancy between those indi- viduals living in affluent and non-affluent areas (Figure 7.8), and also between urban and rural regions (Figure 7.9), as English ONS data for England and Wales illustrate. 17 In addition, a study by Harper et al. revealed that even among a more affluent subset – those individuals fortunate to be in receipt of an occupa- tional pension – there were considerable differentials for both men and women. Analysis of 500,000 individuals who had died when in receipt of occupational pensions revealed considerable variation in Life Expectancy based on variation in income, occupation, and health (Table 7.1). 18 Retiring in ‘normal health’ can add up to 3.5 years of extra life than retiring in ‘ill-health’. Of most importance is health across the life course – all else being equal, there is a difference of up to 4 to 5 years in Life Expectancy between the least healthy and healthiest lifestyles. Income has an impact on Life Expectancy to lifestyle, although the effect is different for men and women. Men with a history of high salaries have a life expect- ancy of 3 years longer than those with the lowest salaries, but the effect of personal income is smaller for women than for men. Occupation – whether an individual has carried out a ‘manual’ or ‘non-manual’ role – can account for up to a 0.75 year difference in Life Expectancy for men and up to 1.5 years for women. Manual workers tend to have shorter life expectancies.
eBook - ePubGeographies of Health, Disease and Well-being
Recent Advances in Theory and Method
- Mei-Po Kwan(Author)
- 2016(Publication Date)
- Routledge(Publisher)
Dartmouth Medical School, Center for the Evaluative Clinical Sciences 1998 ) that traced the patterns of medical procedures, expenses, and outcomes among hospital service areas across the nation. How long you live, your quality of life, and how you die evidently depend to a remarkable degree on where you live. The rather urgent need for public education amidst transformative changes and the bewilderment of a daily onslaught of specialized research reports seems obvious. Yet one thing notably lacking in the cacophony about global conditions and locally lived life today has been a cogent public voice of geography.Forty years ago I was on a plane from New York to Hong Kong when the man sitting next to me asked what a young woman alone was doing going to Asia. Fully expecting incomprehension and some comment about knowing capitals, I simply stated that I was a medical geographer on my way to Malaysia to do my doctoral research. He immediately replied, “I read the Geography of Life and Death by that guy, Stamp, I think. Are you going to study conditions for infectious diseases like malaria in the countryside or the increase of heart disease and cancer as all those million-person cities develop everywhere?” Two years later on a plane returning home, I responded to a similar question by telling the man next to me that I had just defended my geography dissertation on changing disease ecology and land development for agricultural settlement in the rainforest of Malaysia. He casually responded, “I read the Geography of Life and Death. You wanted to know where the diseases are more or less, and why they are there and changing the way they are, what the people there are doing.” Really. I remember those two random conversations clearly (confirmed by my field journal), startled as I was to realize how people cared about the subject and the potential of geographic research to improve health and save lives. Apparently L. Dudley Stamp’s (1964)
- (Author)
- 2011(Publication Date)
- The National Academies Press(Publisher)
All rights reserved. Life Expectancy IN THE U.S. AND OTHER HIGH-INCOME COUNTRIES 11 International comparisons of various measures of self-reported health and biological markers of disease reveal similar patterns of U.S. disadvan- tage. In 2006, Banks and colleagues reported that the U.S. population of late middle age was considerably less healthy than the equivalent English population. For every disease the authors studied, Americans across the socioeconomic distribution reported a higher disease burden: approximately 30 percent higher prevalence for lung disease and myocardial infarction, 60 percent higher for all heart disease and stroke, and 100 percent higher for diabetes (Banks et al., 2006). Furthermore, the design of the study strongly suggested that the American health disadvantage could not be explained sim- ply by reference to problems associated with an inefficient health care system, the lack of universal health care coverage, or large racial and socioeconomic disparities in the United States. Moreover, subsequent analyses have found no significant reason to doubt the basic underlying finding that the burden of disease in America is much higher than that in many other countries (Avendano et al., 2009; Crimmins et al., 2008, 2010). The relatively poor performance of the United States with respect to achieved Life Expectancy in the recent past is perhaps all the more surprising in light of the fact that the United States spends far more on health care than any other nation in the world, both absolutely and as a percentage of gross national product. Motivated by these concerns, the National Institute on Aging requested that the National Research Council convene a panel of leading experts to clarify patterns in the levels and trends in Life Expectancy across nations, to examine the evidence on competing explanations for the divergence among nations, and to identify strategic opportunities for health-related interventions to reduce this divergence.
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