What is the average age someone dies

The difference in life expectancy at 65 years between males and females increased 0. It's not that a person born in is expected to have a shorter life span than a person who was 65 in , says Jiaquan Xu, a medical doctor and lead author of the report.

But the averages for people born in includes those who will be subject to infant mortality and teen mortality, which are higher than for a group of older people.

As far as the life expectancy difference between the sexes, Xu says it's not clear whether genetics plays a role, but behavior probably does. The report attributes much of the recent improvement in both death rates and life expectancy to reductions in deaths from such major illnesses as heart disease, cancer and stroke.

Those 10 causes accounted for And looking at the change over time, we see that as countries spend more on health, life expectancy of the population increases. This means the proportional highest gains are achieved in poor countries with low baseline levels of spending.

This pattern is similar to that observed between life expectancy and per capita income. The countries are color-coded by world region, as per the inserted legends. Many of the green countries Sub-Saharan Africa achieved remarkable progress over the last 2 decades: health spending often increased substantially and life expectancy in many African countries increased by more than 10 years. The most extreme case is Rwanda, where life expectancy has increased from 32 to 64 years since — which was one year after the Rwandan genocide.

The two most populous countries of the world — India and China — are emphasized by larger arrows. It is interesting to see that in China achieved already relatively good health outcomes at comparatively low levels of health spending.

The association between health spending and increasing life expectancy also holds for rich countries in Europe, Asia, and North America in the upper right corner of the chart. The US is an outlier that achieves only a comparatively short life expectancy considering the fact that the country has by far the highest health expenditure of any country in the world.

In this chart we see the relationship between years lived with disability or disease burden versus average per capita health expenditure. Here we see a positive correlation whereby countries with higher healthcare expenditure tend to live more years with disability or disease burden. This is likely to result from increased healthcare resourcing in general care and treatment allowing for an extension of life with a given illness or disability.

Mortality in England began to decline in the wake of the Enlightenment, directly through the application to health of new ideas about personal health and public administration, and indirectly through increased productivity that permitted albeit with some terrible reversals better levels of living, better nutrition, better housing and better sanitation. Ideas about the germ theory of disease were critical to changing both public health infrastructure and personal behavior.

Similarly, knowledge about the health effects of smoking in the middle of the twentieth century has had profound effects on behavior and on health. Most recently, the major life-saving scientific innovations in medical procedures and new pharmaceuticals have had a major effect, particularly on reduced mortality from cardiovascular disease.

There have also been important health innovations whose effect has been mainly in poor countries: for example, the development of freeze-dried serums that can be transported without refrigeration, and of oral rehydration therapy for preventing the death of children from diarrhea. This graph displays the correlation between life expectancy and gross domestic product GDP per capita.

It shows that In general, countries with higher GDP tend to have a higher life expectancy. It is a logarithmic relationship: the difference in life expectancy per difference in GDP per capita is higher for poorer than for richer countries. The cross-sectional relationship between life expectancy and per capita income is known as the Preston Curve , named after Samuel H.

Preston who first described it in a famous paper from In the chart we are plotting the cross-sectional relationship for the years , , , and Interestingly we then find that the life expectancy associated with a given level of real income is rising over time. If economic development was the only determinant of health countries then we would see a steady relationship between the two metrics and the curve would not shift over time. Since this is not the case we can conclude that economic development cannot be the sole determinant of health.

A possible explanation for this changing relationship is that scientific understanding and technological progress makes some very efficient public health interventions — such as vaccinations , hygiene measures, oral rehydration therapy , and public health measures — cheaper and brings these more and more into the reach of populations with lower and lower incomes. The Preston curves below show the correlation between prosperity and life expectancy across countries.

How did life expectancy change over time when countries got richer? The historical research focuses on England as it is the country that first achieved economic growth and also the country for which we have the best long-run data. The historical data for life expectancy in England shows clearly that life expectancy did not increase for much of the early period of British industrialization. According to the famous research by historian and Nobel laureate Robert Fogel living conditions for most people declined during the early period of industrialization.

The debate about how living conditions changed then is still very much alive today, 14 but what is clear however from this research is that rising prosperity itself is not sufficient to improvements in health.

Life expectancy vs food supply. Share of the population living in poverty vs life expectancy. Life satisfaction vs Life expectancy. Extreme poverty vs Life expectancy at birth. Life expectancy has doubled in all world regions. What does this mean exactly? In this section, we try to fill this gap. By definition, life expectancy is based on an estimate of the average age that members of a particular population group will be when they die. One important distinction and clarification is the difference between cohort and period life expectancy.

The cohort life expectancy is the average life length of a particular cohort — a group of individuals born in a given year. You can think of life expectancy in particular year as the age a person born in that year would expect to live if the average age of death did not change over their lifetime. It is of course not possible to know this metric before all members of the cohort have died.

Because of that statisticians commonly track members of a particular cohort and predict the average age-at-death for them using a combination of observed mortality rates for past years and projections about mortality rates for future years. An alternative approach consists in estimating the average length of life for a hypothetical cohort assumed to be exposed, from birth through death, to the mortality rates observed at one particular period — commonly a year.

Period life expectancy estimates do not take into account how mortality rates are changing over time and instead only reflects the mortality pattern at one point in time.

Because of this, period life expectancy figures are usually different to cohort life expectancy figures. Since period life expectancy estimates are ubiquitous in research and public debate, it is helpful to use an example to flesh out the concept.

You can hover the mouse over a country to display the corresponding estimate. For Japan, we can see that life expectancy in was This means that a hypothetical cohort of infants living through the age-specific mortality of Japan in could expect to live But if life expectancies are increasing the reality for a cohort born then is that the cohort life expectancy is higher than that period life expectancy. In general, the commonly-used period life expectancies tend to be lower than the cohort life expectancies, because mortality rates were falling over the course of modern development.

Whenever mortality rates are falling then the period life expectancy is lower than the life expectancy of the cohort born then. An important point to bear in mind when interpreting life expectancy estimates is that very few people will die at precisely the age indicated by life expectancy, even if mortality patterns stay constant.

For example, very few of the infants born in South Africa in will die at Most will die much earlier or much later, since the risk of death is not uniform across the lifetime. Life expectancy is the average. In societies with high infant mortality rates many people die in the first few years of life; but once they survive childhood, people often live much longer. Indeed, this is a common source of confusion in the interpretation of life expectancy figures: It is perfectly possible that a given population has a low life expectancy at birth, and yet has a large proportion of old people.

Given that life expectancy at birth is highly sensitive to the rate of death in the first few years of life, it is common to report life expectancy figures at different ages, both under the period and cohort approaches. For example, the UN estimates that the period global life expectancy at age 10 in was This means that the group of year-old children alive around the world in could expect to live another Finally, another point to bear in mind is that period and cohort life expectancy estimates are statistical measures, and they do not take into account any person-specific factors such as lifestyle choices.

Clearly, the length of life for an average person is not very informative about the predicted length of life for a person living a particularly unhealthy lifestyle. In practical terms, estimating life expectancy entails predicting the probability of surviving successive years of life, based on observed age-specific mortality rates. How is this actually done? Age-specific mortality rates are usually estimated by counting or projecting the number of age-specific deaths in a time interval e.

To ensure that the resulting estimates of the probabilities of death within each age interval are smooth across the lifetime, it is common to use mathematical formulas, to model how the force of mortality changes within and across age intervals.

For some countries and for some time intervals, it is only possible to reconstruct life tables from either period or cohort mortality data. As a consequence, in some instances—for example in obtaining historical estimates of life expectancy across world regions —it is necessary to combine period and cohort data.

Life tables are not just instrumental to the production of life expectancy figures as noted above , they also provide many other perspectives on the mortality of a population. This chart provides an example, plotting survival curves for individuals born at different points in time, using cohort life tables from England and Wales. For the same period for women, the median age at death was By and large, women live longer than men.

Therefore, their most common age at death is comparatively higher than for men. In to , the routine occupations modal age at death for women was 2.

When these gender gaps were compared with the earlier period to , gaps stood at 7. This means the gender gap in the modal age at death has reduced over time; however, the size of the gender gap was highest for the routine occupations in to , but lowest for these occupations in to Figure 3: Median and modal age at death for men for selected socio-economic positions between to and to , England and Wales Source: Office for National Statistics Longitudinal Study Notes: Figures may not sum due to rounding.

Download this image Figure 3: Median and modal age at death for men for selected socio-economic positions between to and to , England and Wales. Figure 4: Median and modal age at death for women for selected socio-economic positions between to and to , England and Wales Source: Office for National Statistics Longitudinal Study Notes: Figures may not sum due to rounding. Download this image Figure 4: Median and modal age at death for women for selected socio-economic positions between to and to , England and Wales.

NS-SEC is central to show the structure of socio-economic positions in modern societies and to help explain variations in social behaviour and other social phenomenon. In our longitudinal study, the relationship between mortality and socio-economic positions has been under investigation since Figure 5 Download this image Figure 5. Average life spans are usually measured using the life table.

These mortality experiences can be presented using 3 measures of average lifespan. The most commonly used measure of average life span is life expectancy at birth or the mean age at death.

It is the average number of years a person is expected to live before his or her death. We regularly produce period life expectancy which is widely understood and used as a robust measure of population health.

A second measure of life span is the late modal age at death. This measure, which has emerged as an alternative measure of life span in low infant mortality countries such as England and Wales, identifies the age at which the highest number of deaths occur over the life course. This focuses on deaths occurring at older ages in the life table in its calculation.

The third measure is the median age at death. This estimates the age at which half of a cohort would have died and half would still be alive. All 3 measures of life span are summary measures of aging in a population, helping to understand mortality improvements from mid to older ages over time. It feeds into the policies surrounding pension, housing and health and social care. Heart Disease. Cancer Lung, prostate, and colorectal cancers are the most deadly forms of the disease in men.

What you can do to prevent it: Avoid air pollution where possible and exposure to chemicals at work and at home Be physically active Don't smoke , and avoid secondhand smoke from others who do. Eat a healthy die t, including fruits, vegetables, fiber, and fish, while reducing fats and meat Keep up with screening tests for early detection of colorectal and prostate cancers if you are over 50 Limit alcohol use to one to two drinks per day; high consumption has been linked to a higher incidence of colon and lung cancer, for example Wear sunscreen and have any skin changes, like moles, checked by your healthcare provider.

Chronic Lower Respiratory Diseases These include chronic bronchitis and emphysema, which together make up chronic obstructive pulmonary disease , or COPD. Stroke A stroke occurs when the brain doesn't get the blood it needs, either because of a blockage in a blood vessel supplying the brain, or the rupture of a blood vessel in the brain.

What you can do to prevent it: Have your blood pressure checked ; treating high blood pressure lowers the risk for stroke and heart disease Drink only in moderation ; that is, no more than one to two drinks per day If you smoke , take steps to quit since smoking increases your risk of stroke Keep diabetes under control Lower your sodium intake to help reduce high blood pressure Regular exercise and a healthy diet that's low in saturated fats can lower your risk.

Diabetes If you have diabetes , your body has trouble using glucose from your food as fuel. What you can do to prevent it: Eat a healthy plant-based diet that includes lots of fresh fruits and vegetables, whole grains, and fish, while avoiding added sugars, fats and salt If you have a family history of diabetes, talk to your healthcare provider about screening Maintain a healthy weight.

Frequently Asked Questions How much will life expectancy increase in future years? Which demographic has the longest life expectancy? Was this page helpful? Thanks for your feedback! Sign Up. What are your concerns? Verywell Health uses only high-quality sources, including peer-reviewed studies, to support the facts within our articles. Read our editorial process to learn more about how we fact-check and keep our content accurate, reliable, and trustworthy.

Cancer Among Men. Centers for Disease Control and Prevention.