Mexico Life Expectancy at Birth: Baja California data was reported at 75.860 Year in 2018. This records an increase from the previous number of 75.750 Year for 2017. Mexico Life Expectancy at Birth: Baja California data is updated yearly, averaging 72.790 Year from Dec 1970 (Median) to 2018, with 49 observations. The data reached an all-time high of 76.200 Year in 2004 and a record low of 62.165 Year in 1970. Mexico Life Expectancy at Birth: Baja California data remains active status in CEIC and is reported by National Population Council. The data is categorized under Global Database’s Mexico – Table MX.G006: Life Expectancy at Birth: by State.

VITAL SIGNS INDICATOR Life Expectancy (EQ6)

FULL MEASURE NAME Life Expectancy

LAST UPDATED April 2017

DESCRIPTION Life expectancy refers to the average number of years a newborn is expected to live if mortality patterns remain the same. The measure reflects the mortality rate across a population for a point in time.

DATA SOURCE State of California, Department of Health: Death Records (1990-2013) No link

California Department of Finance: Population Estimates Annual Intercensal Population Estimates (1990-2010) Table P-2: County Population by Age (2010-2013) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census ZCTA Population (2000-2010) http://factfinder.census.gov

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2013) http://factfinder.census.gov

CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator) Life expectancy is commonly used as a measure of the health of a population. Life expectancy does not reflect how long any given individual is expected to live; rather, it is an artificial measure that captures an aspect of the mortality rates across a population that can be compared across time and populations. More information about the determinants of life expectancy that may lead to differences in life expectancy between neighborhoods can be found in the Bay Area Regional Health Inequities Initiative (BARHII) Health Inequities in the Bay Area report at http://www.barhii.org/wp-content/uploads/2015/09/barhii_hiba.pdf. Vital Signs measures life expectancy at birth (as opposed to cohort life expectancy). A statistical model was used to estimate life expectancy for Bay Area counties and ZIP Codes based on current life tables which require both age and mortality data. A life table is a table which shows, for each age, the survivorship of a people from a certain population.

Current life tables were created using death records and population estimates by age. The California Department of Public Health provided death records based on the California death certificate information. Records include age at death and residential ZIP Code. Single-year age population estimates at the regional- and county-level comes from the California Department of Finance population estimates and projections for ages 0-100+. Population estimates for ages 100 and over are aggregated to a single age interval. Using this data, death rates in a population within age groups for a given year are computed to form unabridged life tables (as opposed to abridged life tables). To calculate life expectancy, the probability of dying between the jth and (j+1)st birthday is assumed uniform after age 1. Special consideration is taken to account for infant mortality.

For the ZIP Code-level life expectancy calculation, it is assumed that postal ZIP Codes share the same boundaries as ZIP Code Census Tabulation Areas (ZCTAs). More information on the relationship between ZIP Codes and ZCTAs can be found at http://www.census.gov/geo/reference/zctas.html. ZIP Code-level data uses three years of mortality data to make robust estimates due to small sample size. Year 2013 ZIP Code life expectancy estimates reflects death records from 2011 through 2013. 2013 is the last year with available mortality data. Death records for ZIP Codes with zero population (like those associated with P.O. Boxes) were assigned to the nearest ZIP Code with population. ZIP Code population for 2000 estimates comes from the Decennial Census. ZIP Code population for 2013 estimates are from the American Community Survey (5-Year Average). ACS estimates are adjusted using Decennial Census data for more accurate population estimates. An adjustment factor was calculated using the ratio between the 2010 Decennial Census population estimates and the 2012 ACS 5-Year (with middle year 2010) population estimates. This adjustment factor is particularly important for ZCTAs with high homeless population (not living in group quarters) where the ACS may underestimate the ZCTA population and therefore underestimate the life expectancy. The ACS provides ZIP Code population by age in five-year age intervals. Single-year age population estimates were calculated by distributing population within an age interval to single-year ages using the county distribution. Counties were assigned to ZIP Codes based on majority land-area.

ZIP Codes in the Bay Area vary in population from over 10,000 residents to less than 20 residents. Traditional life expectancy estimation (like the one used for the regional- and county-level Vital Signs estimates) cannot be used because they are highly inaccurate for small populations and may result in over/underestimation of life expectancy. To avoid inaccurate estimates, ZIP Codes with populations of less than 5,000 were aggregated with neighboring ZIP Codes until the merged areas had a population of more than 5,000. ZIP Code 94103, representing Treasure Island, was dropped from the dataset due to its small population and having no bordering ZIP Codes. In this way, the original 305 Bay Area ZIP Codes were reduced to 217 ZIP Code areas for 2013 estimates. Next, a form of Bayesian random-effects analysis was used which established a prior distribution of the probability of death at each age using the regional distribution. This prior is used to shore up the life expectancy calculations where data were sparse.

From the mid-19th century until today, life expectancy at birth in the United States has roughly doubled, from 39.4 years in 1850 to 79.6 years in 2025. It is estimated that life expectancy in the U.S. began its upward trajectory in the 1880s, largely driven by the decline in infant and child mortality through factors such as vaccination programs, antibiotics, and other healthcare advancements. Improved food security and access to clean water, as well as general increases in living standards (such as better housing, education, and increased safety) also contributed to a rise in life expectancy across all age brackets. There were notable dips in life expectancy; with an eight year drop during the American Civil War in the 1860s, a seven year drop during the Spanish Flu empidemic in 1918, and a 2.5 year drop during the Covid-19 pandemic. There were also notable plateaus (and minor decreases) not due to major historical events, such as that of the 2010s, which has been attributed to a combination of factors such as unhealthy lifestyles, poor access to healthcare, poverty, and increased suicide rates, among others. However, despite the rate of progress slowing since the 1950s, most decades do see a general increase in the long term, and current UN projections predict that life expectancy at birth in the U.S. will increase by another nine years before the end of the century.

Mexico Life Expectancy at Birth: Female: Baja California data was reported at 78.960 Year in 2018. This records an increase from the previous number of 78.850 Year for 2017. Mexico Life Expectancy at Birth: Female: Baja California data is updated yearly, averaging 75.920 Year from Dec 1970 (Median) to 2018, with 49 observations. The data reached an all-time high of 79.170 Year in 2012 and a record low of 64.390 Year in 1970. Mexico Life Expectancy at Birth: Female: Baja California data remains active status in CEIC and is reported by National Population Council. The data is categorized under Global Database’s Mexico – Table MX.G006: Life Expectancy at Birth: by State.

Mexico Life Expectancy at Birth: Male: Baja California Sur data was reported at 72.700 Year in 2018. This records an increase from the previous number of 72.570 Year for 2017. Mexico Life Expectancy at Birth: Male: Baja California Sur data is updated yearly, averaging 69.530 Year from Dec 1970 (Median) to 2018, with 49 observations. The data reached an all-time high of 73.510 Year in 2006 and a record low of 57.560 Year in 1970. Mexico Life Expectancy at Birth: Male: Baja California Sur data remains active status in CEIC and is reported by National Population Council. The data is categorized under Global Database’s Mexico – Table MX.G006: Life Expectancy at Birth: by State.

This statistic shows the average life expectancy in North America for those born in 2022, by gender and region. In Canada, the average life expectancy was 80 years for males and 84 years for females.

Life expectancy in North America

Of those considered in this statistic, the life expectancy of female Canadian infants born in 2021 was the longest, at 84 years. Female infants born in America that year had a similarly high life expectancy of 81 years. Male infants, meanwhile, had lower life expectancies of 80 years (Canada) and 76 years (USA).

Compare this to the worldwide life expectancy for babies born in 2021: 75 years for women and 71 years for men. Of continents worldwide, North America ranks equal first in terms of life expectancy of (77 years for men and 81 years for women). Life expectancy is lowest in Africa at just 63 years and 66 years for males and females respectively. Japan is the country with the highest life expectancy worldwide for babies born in 2020.

Life expectancy is calculated according to current mortality rates of the population in question. Global variations in life expectancy are caused by differences in medical care, public health and diet, and reflect global inequalities in economic circumstances. Africa’s low life expectancy, for example, can be attributed in part to the AIDS epidemic. In 2019, around 72,000 people died of AIDS in South Africa, the largest amount worldwide. Nigeria, Tanzania and India were also high on the list of countries ranked by AIDS deaths that year. Likewise, Africa has by far the highest rate of mortality by communicable disease (i.e. AIDS, neglected tropics diseases, malaria and tuberculosis).

Life tables for California, draft 1999-2017. CDPH published estimates of life expectancy at birth for 1990-2009 compared. Draft, subject to revision.

Mexico Life Expectancy at Birth: Female: Baja California Sur data was reported at 78.910 Year in 2018. This records an increase from the previous number of 78.810 Year for 2017. Mexico Life Expectancy at Birth: Female: Baja California Sur data is updated yearly, averaging 75.750 Year from Dec 1970 (Median) to 2018, with 49 observations. The data reached an all-time high of 79.110 Year in 2012 and a record low of 58.120 Year in 1970. Mexico Life Expectancy at Birth: Female: Baja California Sur data remains active status in CEIC and is reported by National Population Council. The data is categorized under Global Database’s Mexico – Table MX.G006: Life Expectancy at Birth: by State.

Everyone should have the opportunity to be healthy. One's health is shaped dramatically by community characteristics - like housing, education, economic, and other social factors – which often are themselves shaped through policy. The results shown below can be used to explore, identify and strategize pathways to improve healthy community conditions. The California Healthy Places Index (HPI) combines 25 community characteristics into a single indexed HPI Score correlated to life expectancy at birth. Individual HPI indicators are available for a deeper look at community conditions impacting health. The scores are displayed in quartiles, allowing for straightforward comparisons within a specific geography and across the state.

The California Healthy Places Index (HPI) is a powerful new tool, developed by the Public Health Alliance of Southern California, to assist you in exploring local factors that predict life expectancy and comparing community conditions across the state. The HPI provides overall scores and more detailed data on specific policy action areas that shape health, like housing, transportation, education and more. This website offers other resources everyone will find useful, including an interactive map, graphs, data tables, and policy guide with practical solutions for improving community conditions and health.The purpose of the HPI is to prioritize public and private investments, resources and programs. It contains user-friendly mapping and data resources at the census tract level across California. The HPI also provides scores based on community conditions to allow for comparisons between areas, as well as deeper dives on conditions in any given area. The tool includes detailed policy guides to support specific policy interventions that improve community conditions and health.Source: https://healthyplacesindex.org/More information: https://healthyplacesindex.org/faq/

The California Healthy Places Index 3.0 data file was acquired on 04/25/22 from the Public Health Institute on behalf of the Public Health Alliance of Southern California.According to the Public Health Institute, "The HPI tool evaluates the relationship between 23 identified key drivers of health and life expectancy at birth -- which can vary dramatically by neighborhood. Based on that analysis, it produces a score ranking from 1 to 99 that shows the relative impact of conditions in a selected area compared to all other such places in the state." The HPI score is divided across four quartiles. (The Enhanced HPI 3.0: Advancing Health Equity Through High-Quality Data)Potential indicators assigned to eight policy action areas (domains):EconomicsEducationHealthcare accessHousingNeighborhood ConditionsClean EnvironmentSocial EnvironmentTransportationAn HPI score, domains, and individual indicator values and their percentile rankings are presented in the table.For more information, visit the California Healthy Places Index website at https://www.healthyplacesindex.org/ProcessConverted the XLSX file received from the Public Health Institute to a file geodatabase table. Filtered the statewide data to Los Angeles County only. The filtered dataset retains the original default HPI score rank, which is based on conditions across statewide census tracts. Edited field alias names for readability. Joined table to CENSUS_TRACTS_2010 from the Los Angeles County eGIS Data Repository. Exported to new file geodatabase feature class.

Created for the 2023-2025 State of Black Los Angeles County (SBLA) interactive report. To learn more about this effort, please visit the report home page at https://ceo.lacounty.gov/ardi/sbla/. For more information about the purpose of this data, please contact CEO-ARDI. For more information about the configuration of this data, please contact ISD-Enterprise GIS. table_name indicator_name Universe source timeframe source_url

life_expectancy_countyhealthrankings_2020 Life Expectancy Total Population County Health Rankings 2018-2020 https://www.countyhealthrankings.org/app/california/2022/measure/outcomes/147/data

obese_est_adult_lachs_2018 Obese Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

obese_perc_adult_lachs_2018 Obese Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

overweight_est_adult_lachs_2018 Overweight Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

overweight_perc_adult_lachs_2018 Overweight Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

diabetes_est_adult_lachs_2018 Ever Diagnosed with Diabetes Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

diabetes_perc_adult_lachs_2018 Ever Diagnosed with Diabetes Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

regular_source_of_care_est_adult_lachs_2018 Reported Having a Regular Source of Health Care Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

regular_source_of_care_perc_adult_lachs_2018 Reported Having a Regular Source of Health Care Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

depression_est_adult_lachs_2018 Ever Diagnosed with Depression Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

depression_perc_adult_lachs_2018 Ever Diagnosed with Depression Percent (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

perceived_safe_est_adult_lachs_2018 Perceived Their Neighborhood to Be Safe from Crime Estimate (#) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

perceived_safe_perc_adult_lachs_2018 Perceived Their Neighborhood to Be Safe from Crime Estimate (%) Adults (Ages 18 Years and Older) LAC Health Survey 2018 www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

dental_care_est_child_lachs_2018 Had Dental Care within the past Year Estimate (#) Children (Ages 17 Years and Younger) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

dental_care_perc_child_lachs_2018 Had Dental Care within the past Year Percent (%) Children (Ages 17 Years and Younger) LAC Health Survey 2018www.publichealth.lacounty.gov/ha/LACHSDataTopics2018.htm

no_usual_source_est_chis_2020 No usual source of care Estimate (#) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

no_usual_source_perc_chis_2020 No usual source of care Percent (%) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

delayed_care_est_chis_2020 Delayed or didn't get medical care last year Estimate (#) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

delayed_care_est_chis_2020 Delayed or didn't get medical care last year Percent (%) Total Population California Health Interview Survey 2020 https://ask.chis.ucla.edu/AskCHIS/tools/_layouts/AskChisTool/home.aspx

covid_vax_one_or_more_est_2022 COVID-19 Vaccination 1+ Dose Estimate (#) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_perc_2022 COVID-19 Vaccination 1+ Dose Percent (%) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_full_est_2022 COVID-19 Fully Vaccinated Estimate (#) Population 6 months and older LAC DPH Sep-22publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_full_perc_2022 COVID-19 Fully Vaccinated Percent (%) Population 6 months and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_children_est_2022 COVID-19 Vaccination 1+ Dose - Children under 5 Estimate (#) Population older than 6 months and under 5 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_children_perc_2022 COVID-19 Vaccination 1+ Dose Children under 5 Percent (%) Population older than 6 months and under 5 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_youth_est_2022 COVID-19 Vaccination 1+ Dose - Youth 5-17 Estimate (#) Population 5-17 years LAC DPH Sep-22publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_youth_perc_2022 COVID-19 Vaccination 1+ Dose Youth 5-17 Percent (%) Population 5-17 years LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_adults_est_2022 COVID-19 Vaccination 1+ Dose - Adults Estimate (#) Population 18 and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

covid_vax_one_or_more_adults_perc_2022 COVID-19 Vaccination 1+ Dose Adults Percent (%) Population 18 and older LAC DPH Sep-22 publichealth.lacounty.gov/media/coronavirus/vaccine/vaccine-dashboard.htm

insured_pop_est_acs_2020 Insured population # Civilian noninstitutionalized population 2016-2020 ACS - S2701 https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S2701

insured_pop_perc_acs_2020 Insured population % Civilian noninstitutionalized population 2016-2020 ACS - S2701 https://data.census.gov/cedsci/table?g=0500000US06037&tid=ACSST5Y2020.S2701

mch_indicators_2019 Babies Born with Positive MCH Indicators Babies born in time frame Strong Start Index 2016-2019 https://infogram.com/1pj576jwy166z1s6ywvk32l5lkammrym3wy?live

current_asthma Percent of Adults (Ages 18 Years and Older) with Current Asthma Adults Los Angeles County Health Survey 2018 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

no_med_insurance Percent of Insured Adults (Ages 18 Years and Older) Who Reported a Time Without Medical Insurance in the past 12 Months. Adults Los Angeles County Health Survey 2011 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

transportation_problems Percent of Adults (Ages 18 Years and Older) Who Reported That Transportation Problems Kept Them from Obtaining Needed Medical Care in the past Year. Adults Los Angeles County Health Survey 2007 https://www.publichealth.lacounty.gov/ha/HA_DATA_TRENDS.htm

The Hispanic EPESE provides data on risk factors for mortality and morbidity in Mexican Americans in order to contrast how these factors operate differently in non-Hispanic White Americans, African Americans, and other major ethnic groups. The Wave 8 dataset comprises the seventh follow-up of the baseline Hispanic EPESE (HISPANIC ESTABLISHED POPULATIONS FOR THE EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1993-1994: [ARIZONA, CALIFORNIA, COLORADO, NEW MEXICO, AND TEXAS] [ICPSR 2851]). The baseline Hispanic EPESE collected data on a representative sample of community-dwelling Mexican Americans, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. The public-use data cover demographic characteristics (age, sex, marital status), height, weight, BMI, social and physical functioning, chronic conditions, related health problems, health habits, self-reported use of hospital and nursing home services, and depression. Subsequent follow-ups provide a cross-sectional examination of the predictors of mortality, changes in health outcomes, and institutionalization, and other changes in living arrangements, as well as changes in life situations and quality of life issues. During this 8th Wave, 2012-2013, re-interviews were conducted either in person or by proxy, with 452 of the original respondents. This Wave also includes 292 re-interviews from the additional sample of Mexican Americans aged 75 years and over with higher average-levels of education than those of the surviving cohort who were added in Wave 5, increasing the total number of respondents to 744.

A dataset of a longitudinal study of over 3,000 Mexican-Americans aged 65 or over living in five southwestern states. The objective is to describe the physical and mental health of the study group and link them to key social variables (e.g., social support, health behavior, acculturation, migration). To the extent possible, the study was modeled after the existing EPESE studies, especially the Duke EPESE, which included a large sample if African-Americans. Unlike the other EPESE studies that were restricted to small geographic areas, the Hispanic EPESE aimed at obtaining a representative sample of community-dwelling Mexican-American elderly residing in Texas, New Mexico, Arizona, Colorado, and California. Approximately 85% of Mexican-American elderly reside in these states and data were obtained that are generalizable to roughly 500,000 older people. The final sample of 3,050 subjects at baseline is comparable to those of the other EPESE studies. Data Availability: Waves I to IV are available through the National Archive of Computerized Data on Aging (NACDA), ICPSR. Also available through NACDA is the ����??Resource Book of the Hispanic Established Populations for the Epidemiologic Studies of the Elderly����?? which offers a thorough review of the data and its applications. All subjects aged 75 or older were interviewed for Wave V and 902 new subjects were added. Hemoglobin A1c test kits were provided to subjects who self-reported diabetes. Approximately 270 of the kits were returned for analyses. Wave V data are being validated and reviewed. A tentative timeline for the archiving of Wave V data is November 2006. Wave VI interviewing and data collection is scheduled to begin in Fall 2006. * Dates of Study: 1993-2006 * Study Features: Longitudinal, Minority oversamples, Anthropometric Measures * Sample Size: ** 1993-4: 3,050 (Wave I) ** 1995-6: 2,438 (Wave II) ** 1998-9: 1,980 (Wave III) ** 2000-1: 1,682 (Wave IV) ** 2004-5: 2,073 (Wave V) ** 2006-7: (Wave VI) Links: * ICPSR Wave 1: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/2851 * ICPSR Wave 2: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/3385 * ICPSR Wave 3: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/4102 * ICPSR Wave 4: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/4314 * ICPSR Wave 5: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/25041 * ICPSR Wave 6: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/29654

Introduction

Blue Zones refer to five specific geographic areas around the world where people live significantly longer, often reaching 100 years of age or more, and enjoy higher rates of well-being and lower incidences of chronic diseases. The term was popularised by Dan Buettner, a National Geographic journalist and author, who, along with a team of researchers and scientists, studied these regions to understand why their populations experience longer and healthier lives. link

The five recognised Blue Zones are:

1. Okinawa, Japan
2. Sardinia, Italy
3. Nicoya Peninsula, Costa Rica
4. Ikaria, Greece
5. Loma Linda, California, USA

Key Factors of Longevity in Blue Zones

Across these regions, Buettner and his team identified common lifestyle, dietary, and social factors that contribute to the long and healthy lives of the inhabitants. These include:

Plant-Based Diets: The diets of Blue Zone populations are largely plant-based, rich in whole grains, legumes, vegetables, fruits, and nuts, with limited amounts of meat and processed foods. While there is some variation, a diet high in plant-based nutrition seems to be a central factor.

Physical Activity: Regular, low-intensity physical activity is part of everyday life in these communities. People often walk long distances, farm, garden, or do manual labour as part of their daily routines, ensuring that they remain active throughout their lives.

Social Connections: Strong social ties, including family connections, close friendships, and a sense of belonging within a community, contribute significantly to mental and emotional well-being. Loneliness and social isolation, which are risk factors for mortality, are less common in Blue Zones.

Purpose (Ikigai): Many people in Blue Zones have a strong sense of purpose, often referred to as "ikigai" in Japan or "plan de vida" in Costa Rica. This purpose gives individuals a reason to get up every day, which is linked to longevity and life satisfaction.

Moderation and Fasting: Intermittent fasting and moderation in eating are practices commonly seen across Blue Zones. In Okinawa, for example, people follow the "hara hachi bu" principle, which means eating until one is 80% full. Limiting caloric intake without malnutrition is thought to promote longevity.

Stress Management: Stress is inevitable, but Blue Zone populations have developed effective ways to manage it. This includes practices like meditation, prayer, spending time in nature, and taking time to relax or nap in the middle of the day.

Now, let’s explore the characteristics of each Blue Zone in more detail.

1. Okinawa, Japan

Okinawa is home to one of the highest concentrations of centenarians (people aged 100 and older) in the world. Okinawans have traditionally followed a plant-heavy diet rich in vegetables like sweet potatoes, bitter melon, and tofu, along with small amounts of fish and occasionally pork. Their practice of "hara hachi bu," eating only until they are 80% full, helps them avoid overeating and maintain a healthy weight.

Okinawans also benefit from close-knit social networks known as "moai," which provide emotional support and reduce loneliness. They maintain a deep sense of purpose, or "ikigai," which has been shown to improve mental and physical health.

2. Sardinia, Italy

The Blue Zone of Sardinia is found in the mountainous region of the island, where men, in particular, have extremely long lifespans. Sardinians follow a Mediterranean-style diet rich in whole grains, vegetables, fruits, and beans, with a moderate amount of goat’s milk, cheese, and wine. Meat is consumed sparingly, mostly on special occasions.

Their longevity is also attributed to a lifestyle that involves a lot of physical activity, especially in farming and herding. Sardinians have strong family bonds and social connections, which contribute to their happiness and mental well-being.

3. Nicoya Peninsula, Costa Rica

The Nicoya Peninsula in Costa Rica is known for having a lower rate of middle-age mortality and a higher life expectancy than the rest of the country. Nicoyans follow a traditional Mesoamerican diet based on beans, corn, and squash, often referred to as the "three sisters" of agriculture. This diet is low in calories but rich in nutrients and antioxidants.

Nicoyans maintain a strong sense of purpose or "plan de vida," and their family-centred lifestyle fosters intergenerational support, which contributes to emotional well-being. Regular physical activity is part of daily life, with many Nicoyans walking, working outdoors, and engaging in manual labour even into old age.

4. Ikaria, Greece

Ikaria, a small island in the Aegean Sea, has one of the world's lowest rates of dementia and heart disease, along with an unus...

This dataset comprises the third follow-up of the baseline Hispanic EPESE, HISPANIC ESTABLISHED POPULATIONS FOR THE EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1993-1994: ARIZONA, CALIFORNIA, COLORADO, NEW MEXICO, AND TEXAS, and provides information on 1,682 of the original respondents. The Hispanic EPESE collected data on a representative sample of community-dwelling Mexican-American elderly, aged 65 years and older, residing in the five southwestern states of Arizona, California, Colorado, New Mexico, and Texas. The primary purpose of the series was to provide estimates of the prevalence of key physical health conditions, mental health conditions, and functional impairments in older Mexican Americans and to compare these estimates with those for other populations. The Hispanic EPESE attempted to determine whether certain risk factors for mortality and morbidity operate differently in Mexican Americans than in non-Hispanic White Americans, African Americans, and other major ethnic groups. The public-use data cover background characteristics (age, sex, type of Hispanic race, income, education, marital status, number of children, employment, and religion), height, weight, social and physical functioning, chronic conditions, related health problems, health habits, self-reported use of dental, hospital, and nursing home services, and depression. The follow-ups provide a cross-sectional examination of the predictors of mortality, changes in health outcomes, and institutionalization and other changes in living arrangements, as well as changes in life situations and quality of life issues. The vital status of respondents from baseline to this round of the survey may be determined using the Vital Status file (Part 2). This file contains interview dates from the baseline as well as vital status at Wave IV (respondent survived, date of death if deceased, proxy-assisted, proxy-reported cause of death, proxy-true). The first follow-up of the baseline data (Hispanic EPESE Wave II, 1995-1996 [ICPSR 3385]) followed 2,438 of the original 3,050 respondents, and the second follow-up (Hispanic EPESE Wave III, 1998-1999 [ICPSR 4102]) followed 1,980 of these respondents. Hispanic EPESE, 1993-1994 (ICPSR 2851), was modeled after the design of ESTABLISHED POPULATIONS FOR EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1981-1993: EAST BOSTON, MASSACHUSETTS, IOWA AND WASHINGTON COUNTIES, IOWA, NEW HAVEN, CONNECTICUT, AND NORTH CENTRAL NORTH CAROLINA and ESTABLISHED POPULATIONS FOR EPIDEMIOLOGIC STUDIES OF THE ELDERLY, 1996-1997: PIEDMONT HEALTH SURVEY OF THE ELDERLY, FOURTH IN-PERSON SURVEY DURHAM, WARREN, VANCE, GRANVILLE, AND FRANKLIN COUNTIES, NORTH CAROLINA.

Life expectancy for ages 64-69.9

Life expectancy for ages 91 and Over

出生时预期寿命：下加利福尼亚州（墨西哥）在12-01-2018达75.860年，相较于12-01-2017的75.750年有所增长。出生时预期寿命：下加利福尼亚州（墨西哥）数据按年更新，12-01-1970至12-01-2018期间平均值为72.790年，共49份观测结果。该数据的历史最高值出现于12-01-2004，达76.200年，而历史最低值则出现于12-01-1970，为62.165年。CEIC提供的出生时预期寿命：下加利福尼亚州（墨西哥）数据处于定期更新的状态，数据来源于Consejo Nacional de Poblacion，数据归类于全球数据库的墨西哥 – 表 MX.G006：出生时预期寿命：按州划分。

出生时预期寿命：女性：下加利福尼亚州（墨西哥）在12-01-2018达78.960年，相较于12-01-2017的78.850年有所增长。出生时预期寿命：女性：下加利福尼亚州（墨西哥）数据按年更新，12-01-1970至12-01-2018期间平均值为75.920年，共49份观测结果。该数据的历史最高值出现于12-01-2012，达79.170年，而历史最低值则出现于12-01-1970，为64.390年。CEIC提供的出生时预期寿命：女性：下加利福尼亚州（墨西哥）数据处于定期更新的状态，数据来源于Consejo Nacional de Poblacion，数据归类于全球数据库的墨西哥 – 表 MX.G006：出生时预期寿命：按州划分。