Diet, Income, and Healthcare: Global Trends in Health and Longevity
Life expectancy is, for good reason, used by the World Health Organization (WHO) and similar agencies as a key indicator of a population’s health and well-being. While the link between health and life expectancy is obvious, research also shows strong correlations between a country’s average life expectancy and the population’s perception of well-being.
At DeliveryRank, we’re passionate about offering reliable insights into sources of healthy food and diet plans, as well as how access to nutrition affects quality of life. In this article, we look at the most significant factors in longevity and the role nutrition plays.
We reviewed data from three main categories — nutrition, economy, and healthcare — and how they relate to life expectancy. Our goal is to help institutions, policymakers, and individuals work toward a more comprehensive way to address regional and global longevity issues.
By studying regional patterns, we aim to highlight how varying behavioral, social, and economic factors create disparities in life expectancy. We hope that this information will help efforts to devise more sustainable and accessible systems to support people’s health and well-being.
Key Takeaways
- Economic situation is likely one of the biggest drivers in life expectancy.
- Out of 48 territories with life expectancies of at least 80, 45 are high-income economies.
- Healthcare access has a moderate impact on life expectancy.
- Diet types are more of a by-product of other economic and social factors than a primary factor in life expectancy.
Life Expectancy by Region: Major Drivers
In 2022, the global average life expectancy was 72 years — 15 more than it was 50 years ago. To better understand longevity trends, we examined patterns in diet types, income levels, and access to medical care in different countries and territories around the globe. From our data, we analyzed how relevant each factor is to each population’s life expectancy.
Nutrition
Our team looked at the most common diet type per country and region and its potential correlation with life expectancy. We defined diets according to the following categories:
Here are our key observations:
- High-Protein diets are the most common, with 54 nations mainly from Europe and Asia.
- The Mediterranean diet is prevalent in 53 nations, none of which are part of North America.
- Western diets are most prevalent in Europe and uncommon in Asian or African countries.
- The Caribbean diet is observed only in the American regions (17 in the North and 3 in the South).
- The African Traditional, Asian Traditional, and Pacific diets are region-exclusive diets, popular in only one region each.
- Middle Eastern diets are only common in Asia and Africa.
- High-Carbohydrate diets are commonly observed only in Afghanistan.
Notably, a diet consisting mainly of red and processed meats has the population with the highest average life expectancy. This is despite strong evidence that these foods increase the risk of cancer, the second-leading cause of diet-related deaths (next only to cardiovascular diseases).
However, the Western diet is not the most prevalent in any region. It’s only second in Europe (highest average life expectancy) and statistically nonexistent or negligible in Asia (second-highest average life expectancy). Moreover, North and South America and Oceania each only have 5 or fewer nations that subscribe to this diet type.
This observation led us to the preliminary analysis that other factors than diet type may have a bigger influence on life expectancy.
Economy
Many studies have investigated the link between life expectancy and income. However, we wanted to learn if it has a comparable impact as other factors, such as diet and access to medical care.
To examine economic factors’ depth of influence on life expectancy, our team looked at countries’ and territories’ income-level category and their gross national income (GNI) per capita. We also analyzed the interaction between regions’ income levels and diet types most common to their areas.
The most common diet types per income group are:
- High income: Western (33%), Mediterranean (24%), High-Protein (19%)
- Upper-middle income: High-Protein (44%), Mediterranean (22%), Caribbean (13%)
- Lower-middle income: Mediterranean (31%), African Traditional (29%), High-Protein (20%)
- Low income: African Traditional (54%), Mediterranean (23%), High-Protein (15%)
Notably, the Western and Caribbean diets are common only among high- and upper-middle-income economies. The only diets not commonly observed in high-income economies are High-Carbohydrate and African Traditional, which are the bottom two diets in terms of average life expectancy.
The low-income group has the least varied diet types. The three diets with the highest average life expectancies, along with the Pacific diet, are not typically observed in these populations.
The life expectancy gap between income groups is:
- High to upper-middle: 7 years
- Upper-middle to lower-middle: 4 years
- Lower-middle to low: 6 years
The smaller gap between the two middle groups is somewhat unexpected, given the skewed division of income groups. Where the upper-middle-income category covers $9,489 between its upper and lower limits, the lower-middle-income covers only $3,369. This difference can be used to further support studies analyzing the widening longevity gap between the richest and poorest populations.
Looking at every region’s average GNI per capita, the correlation between income or financial ability and life expectancy becomes clearer.
Higher-income regions consistently have higher average life expectancies. The only exception is Asia, which is tied with North America in life expectancy despite having a higher average GNI per capita. However, Asia has low-income nations, while North America has a majority of high-income and upper-middle-income groups, with a few lower-middle-income populations.
Healthcare
In 2019, a study found that healthcare access in the United States has a “modest effect” on life expectancy compared to other determinants. Yet, separate investigations in multiple countries have demonstrated a link between longevity and access to healthcare services.
For instance, research published in the Journal of Global Health in 2022 concluded that publicly funded healthcare can lengthen life expectancy. However, the study used a binary measurement (present vs. not present). It didn’t account for potential variations in other determinants, such as costs, geographic accessibility, support and training for healthcare providers, and more.
To build on previous research and establish a more definitive correlation between healthcare access and life expectancy, we looked at the World Health Organization’s Universal Health Coverage (UHC) service coverage index.
The index scores countries from 0 to 100 based on their performance in 14 UHC indicators. Higher scores are given to countries and territories where people can receive all essential health services “when and where they need them, without financial hardship.”
First, we compared the performance of different income groups in the index. The biggest disparity falls between the upper-middle- and lower-middle-income groups. The high-income and low-income groups both have a difference of 12 points from their respective adjacent categories. Meanwhile, the middle groups have 15 points in between.
Looking at the average life expectancy of nations within certain ranges of UHC service coverage index scores, the biggest gap in life expectancy is between the 74-82 and 83-91 groups.
Our other main observations include the following:
- Out of 190 nations with available index scores, 111 received at least 65 points (58%).
- The most populated group is the 74-82 range, with 51 countries (27%).
- Only 8 nations scored 36 and lower — the least populated range group (4%).
Europe, Oceania, and Africa displayed a proportional link between their average life expectancies and UHC service coverage index scores relative to other regions. On the other hand, South America’s average index score was higher than Asia’s and North America’s despite trailing behind the two regions in life expectancy.
Overall Insights and Trends
The results of our research show that a population’s economic situation is potentially one of the biggest drivers in life expectancy. Or, at the very least, it has the largest impact on micro-drivers, such as access to safe drinking water, available health expenditure, and reproductive education.
Below are the key observations that led to our analysis:
- Of the data points investigated per factor, only the GNI per capita displayed the most consistent relationship with life expectancy.
- Asia ranked 4th out of 6 in healthcare access but had the second-highest average GNI per capita. It ranks 2nd in average life expectancy.
- The upper-middle- and lower-middle-income economies have the biggest difference in average UHC service coverage index score but the smallest life expectancy gap of adjacent income groups.
- Out of 48 territories with life expectancies of at least 80, 45 are high-income economies, and 3 have upper-middle incomes.
Given our findings, we must note that the average longevity in countries with a wide income gap may be misleading. National life expectancy values cannot accurately account for individuals at the top or bottom percentiles of the public in terms of income. Moreover, countries with a large population or land area may have vastly different socioeconomic situations per locale.
Our study also suggests that diet types are more of a by-product of other economic and social aspects than a primary factor in life expectancy. The Western diet, which was observed to be associated with the highest average life expectancy, is well-documented to have multiple health risks. However, it is very common in high-income countries.
Moreover, considering dietary habits the primary agent in life expectancy potentially overlooks other biological and socioeconomic factors, such as the continuing problem of world hunger and exposure to serious, geographically bound diseases — both of which would be valuable to include in further studies.
Methodology
DeliveryRank researchers gathered data from multiple sources to find potential correlations between life expectancy and nutrition, access to healthcare, and economic stability. We covered 212 countries and territories, omitting those without verifiable life expectancy data. Our team took life expectancy data from the World Bank.
We categorized each country and territory into 6 major regions: Europe, Asia, North America, South America, Oceania, and Africa. For nations that sit on the boundary between two or more regions, we assigned the region where the nation occupies a larger territorial area.
The predominant diet types per country were gathered from the Food and Agriculture Organization (FAO) of the United Nations (UN), the World Bank, the WHO, and the Organisation for Economic Co-operation and Development (OECD).
Our researchers used the official income-based economic classification from the World Bank. Meanwhile, our GNI per capita figures were based on the UNDP Human Development Report, with minor processing by OurWorldinData.org.
Out of the 212 territories included in our research, we didn’t find a UHC service coverage index for 8 countries in North America, 7 in Europe, 3 in Oceania, and 2 each in South America and Asia.
Most of the data used in our research are from 2022 and later, although a few older figures may be included for countries with less publicly available information.