This statistic shows the biggest cities in Ecuador in 2022. In 2022, approximately **** million people lived in Guayaquil, making it the biggest city in Ecuador.

Population in largest city in Ecuador was reported at 3193267 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ecuador - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Ecuador EC: Population in Largest City data was reported at 2,844,281.000 Person in 2017. This records an increase from the previous number of 2,790,791.000 Person for 2016. Ecuador EC: Population in Largest City data is updated yearly, averaging 1,502,366.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 2,844,281.000 Person in 2017 and a record low of 456,225.000 Person in 1960. Ecuador EC: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ecuador – Table EC.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

This statistic shows the total population of Ecuador from 2020 to 2022, with projections up until 2030. In 2022, the total population of Ecuador amounted to approximately 17.72 million inhabitants. Ecuador's population The population of Ecuador continues to increase slowly but steadily. In 2014, the total population of Ecuador amounted to around 16 million. Yet, the population growth rate has been decreasing slightly since 2008. This means that more people have died than were born and/or more people have migrated out of as opposed to into the country. The fertility rate has been decreasing as well; ten years ago the fertility rate stood at around 3 children per woman, but today it stands at around 2.5 children per woman. This decrease has likely caused the slump in the population growth rate, even though it still remains above the natural replacement rate of 2, causing the population to still grow overall. Further, Ecuador’s life expectancy is around 76 years nowadays, with the percentage of adults aged over 65 years being less than seven percent (451305). The population of Ecuador is quite young, with about a third of the population under 14 years of age. The population is spread all over the country: Guayaquil and Quito are the largest cities in Ecuador and home to close to 4 million people combined. All other cities are smaller and the majority of them inhabit less than 250,000 people.

Population in the largest city (% of urban population) in Ecuador was reported at 27.08 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ecuador - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Ecuador EC: Population in Largest City: as % of Urban Population data was reported at 26.261 % in 2017. This records a decrease from the previous number of 26.292 % for 2016. Ecuador EC: Population in Largest City: as % of Urban Population data is updated yearly, averaging 28.257 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 30.401 % in 1963 and a record low of 26.261 % in 2017. Ecuador EC: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ecuador – Table EC.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted Average;

Historical dataset of population level and growth rate for the Quito, Ecuador metro area from 1950 to 2025.

Historical dataset of population level and growth rate for the Guayaquil, Ecuador metro area from 1950 to 2025.

This bar chart displays male population (people) by capital city using the aggregation sum in Ecuador. The data is filtered where the date is 2021. The data is about countries per year.

Comprehensive socio-economic dataset for Ecuador including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

A survey carried out in the third quarter of 2021 in Ecuador showed that Quito, the nation's capital, had the highest unemployment rate amongst selected cities, a total of **** percent. It was followed by Machala, with *** percent. In 2021, the unemployment rate in Ecuador reached nearly ***** percent in urban areas.

Historical dataset of population level and growth rate for the Cuenca, Ecuador metro area from 1950 to 2025.

This statistic depicts the largest Ecuadorian-American population groups living in different counties across the United States as of 2010. At this time there were 98,512 people of Ecuadorian origin living in Queens County in New York.

Historical dataset of population level and growth rate for the Santo Domingo, Ecuador metro area from 1950 to 2025.

This dataset contains administrative polygons grouped by country (admin-0) with the following subdivisions according to Who's On First placetypes:
- macroregion (admin-1 including region)
- region (admin-2 including state, province, department, governorate)
- macrocounty (admin-3 including arrondissement)
- county (admin-4 including prefecture, sub-prefecture, regency, canton, commune)
- localadmin (admin-5 including municipality, local government area, unitary authority, commune, suburb)

The dataset also contains human settlement points and polygons for:
- localities (city, town, and village)
- neighbourhoods (borough, macrohood, neighbourhood, microhood)

The dataset covers activities carried out by Who's On First (WOF) since 2015. Global administrative boundaries and human settlements are aggregated and standardized from hundreds of sources and available with an open CC-BY license. Who's On First data is updated on an as-need basis for individual places with annual sprints focused on improving specific countries or placetypes. Please refer to the README.md file for complete data source metadata. Refer to our blog post for explanation of field names.

Data corrections can be proposed using Write Field, an web app for making quick data edits. You’ll need a Github.com account to login and propose edits, which are then reviewed by the Who's On First community using the Github pull request process. Approved changes are available for download within 24-hours. Please contact WOF admin about bulk edits.

The data collected through the APGAR test aimed to measure family functions and changes in a postmodern context. Over three years, this study has been conducted to 77 individuals, 71 of whom were adults while the remaining 6 were underage people. These participants belong to 37 families from different social strata in the city of Quito-Ecuador, which were selected through convenience and non-probabilistic sampling. The APGAR design used a modification of the work [1], extrapolated to the Ecuadorian context. The data has been collected, cleaned, and unified in a single file in a CSV structured format and without missing values. The participants’ personal information has been concealed to guarantee their identity remains anonymous. Additionally, those who participated in the project have given their consent for the use of their information for academic purposes, which include: scientific journals, presentations, and digital academic repositories. The structured data, within the file, has a distribution in the form of rows and columns. Each row (instance) represents an APGAR test executed on an individual, while the columns represent the different variables (attributes) of the dataset. Each APGAR test has metadata collected during the process. The metadata corresponding to the informative data of the individuals are located in attributes 1 to 7 of the dataset and their description is as follows. • Person_ID: Identifier of each individual who participated in the APGAR test. Discrete quantitative variable. • Year: Data collection year. Discrete quantitative variable. • Family_ID: Unique identifier of each family. Discrete quantitative variable. • Age: Participant age in years. Discrete quantitative variable. • Familiar_Rol: Self-identification of the role played by the individual in the family. Nominal qualitative variable with open categories. Seven different classes were identified: father, mother, son, daughter, nephew, grandmother, and stepfather. • Gender: Self-identification of the individual's gender. Nominal qualitative variable with open categories. Two classes were identified: male and female. • Location: Geographical location of the family home. Nominal qualitative variable with closed categories determined by the official zones that make up the metropolitan district of Quito. Nineteen classes were identified in total. In the Ecuadorian context, a person is of legal age if he has reached an age equal to or greater than 18 years. Therefore, in order to discern these two segments of subpopulations within the family, the design of two different question types for the APGAR tests was required. The Questions (Qi) for adults were: • Q1: I am satisfied with the help I receive from my family when I have a problem or need. • Q2: I am satisfied with the participation that my family gives me and allows me. • Q3: I am satisfied with how my family accepts and supports my desire to undertake new activities. • Q4: I am satisfied with how my family expresses affection and responds to my emotions, such as anger, sadness, love, etc. • Q5: I am satisfied with how we share in my family: a) time to be together, b) spaces in the house, c) money. The Questions (Qi) for underage people were: • Q1: When I am worried about anything, I can ask my family for help. • Q2: I like how my family talks and shares their problems with me. • Q3: I like how my family allows me to do the new things I want to do. • Q4: I like what my family does when I am happy, sad, angry, etc. • Q5: I like how my family and I spend time together. On the other hand, for each question, 5 possible answers were designed with different weights based on a linear symmetric likert scale, and with the same ratings for adults and underage people. The Likert scale weighted Answers (Ai), offered for the participants were: • A1: Never (0 Points) • A2: Almost Never (1 Point) • A3: Sometimes (2 Points) • A4: Almost Always (3 Points) • A5: Always (4 Points) Variables 8 to 32 correspond to the execution of the APGAR test, per se, and were coded in the form of a tuple, Question-Answer (Qi-Aj). The ‘i’ value identifies the 5 types of questions, while the ‘j’ index determines the 5 types of answers. All the tuples Qi-Aj were encoded through a boolean variable (0/1). Where ‘0’ indicates the absence of a value in the tuple and ‘1’ the presence of a value in the tuple. All the APGAR tests were taken in Spanish since it is the official language of Ecuador, and then transcribed into English. Although the data has been collected by using the APGAR test to measure family functions and their changes in the postmodern context, it is important to note that the collected data could be used for other different purposes.

Background: In an elderly population with hypertension, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with a higher incidence of mortality and a protracted course of clinical symptoms.Objective: To assess the perceived risk of infection and complications due to COVID-19 in people with hypertension living in a semi-urban city of Ecuador.Methods: A cross-sectional telephone survey of adult outpatients with a previous diagnosis of hypertension in the semi-urban community of Conocoto in Quito, Ecuador was conducted from August to December 2020.Results: A total of 260 adult outpatients, aged 34–97 years, completed telephone surveys. Of total, 71.5% (n = 186) of respondents were women and 28.5% (n = 74) of respondents were men. Overall, 18.1% believe that their risk of infection is “very high,” 55.4% believe that their risk of infection is “high,” 21.5% believe that their risk of infection is “low,” and 5% believe that their risk of infection is “very low.” The perceived risk of complications, if infected by COVID-19, revealed that 21.9% believe that their risk of complication is “very high,” 65.0% believe that their risk of complication is “high,” 10.4% believe that their risk of complication is “low,” and 2.7% believe that their risk of complication is “very low.”Conclusion: Patients with hypertension are aware of the risks posed by COVID-19 infection and its impact on their health. However, the health system must educate the population on health practices and behaviors to avoid COVID-19 infection until the majority of the population of Ecuador can be vaccinated.

EC：最大城市人口在12-01-2017达2,844,281.000人，相较于12-01-2016的2,790,791.000人有所增长。EC：最大城市人口数据按年更新，12-01-1960至12-01-2017期间平均值为1,502,366.000人，共58份观测结果。该数据的历史最高值出现于12-01-2017，达2,844,281.000人，而历史最低值则出现于12-01-1960，为456,225.000人。CEIC提供的EC：最大城市人口数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的厄瓜多尔 – 表 EC.世行.WDI：人口和城市化进程统计。

Insecticide resistance (IR) can undermine efforts to control vectors of public health importance. Aedes aegypti is the main vector of resurging diseases in the Americas such as yellow fever and dengue, and recently emerging chikungunya and Zika fever, which have caused unprecedented epidemics in the region. Vector control remains the primary intervention to prevent outbreaks of Aedes-transmitted diseases. In many high-risk regions, like southern Ecuador, we have limited information on IR. In this study, Ae. aegypti IR was measured across four cities in southern Ecuador using phenotypic assays and genetic screening for alleles associated with pyrethroid IR. Bottle bioassays showed significant inter-seasonal variation in resistance to deltamethrin, a pyrethroid commonly used by the Ministry of Health, and alpha-cypermethrin, as well as between-city differences in deltamethrin resistance. There was also a significant difference in phenotypic response to the organophosphate, Malathion, between two cities during the second sampling season. Frequencies of the resistant V1016I genotype ranged from 0.13 to 0.68. Frequencies of the resistant F1534C genotype ranged from 0.63 to 1.0, with sampled populations in Machala and Huaquillas at fixation for the resistant genotype in all sampled seasons. In Machala and Portovelo, there were statistically significant inter-seasonal variation in genotype frequencies for V1016I. Resistance levels were highest in Machala, a city with hyperendemic dengue transmission and historically intense insecticide use. Despite evidence that resistance alleles conferred phenotypic resistance to pyrethroids, there was not a precise correspondence between these indicators. For the F1534C gene, 17.6% of homozygous mutant mosquitoes and 70.8% of heterozygotes were susceptible, while for the V1016I gene, 45.6% homozygous mutants and 55.6% of heterozygotes were susceptible. This study shows spatiotemporal variability in IR in Ae. aegypti populations in southern coastal Ecuador, and provides an initial examination of IR in this region, helping to guide vector control efforts for Ae. aegypti.

Abstract Individuals not only have a set of personal resources to carry out their activities, they also have a perception with respect to the availability of these resources. As people age, personal food-related perceived resources (FPR) become increasingly important, and these influence their quality of life (QOL). Since men and women differ in aspects like education, consumption and pensions, this study seeks to identify the gender role in the relationship between FPR and QOL among Ecuadorian elderly. The sample included elderly people of both sexes in the city of Guayaquil, Ecuador, with the application of stratified random sampling. The instrument included: FPR scale, satisfaction with food-related life scale (SWFLS) and the satisfaction with life scale (SWLS). The results indicated that those men and women who have a better perceived satisfaction with their economic situation are in physically and mentally good health, assign greater importance to family, are more satisfied with their food-related life, and have a higher number of FPR and therefore a better QOL. A relevant conclusion is that SWFLS and FPR are predictors of QOL among Ecuadorian elderly and that gender helps to explain the sign and magnitude of the relationship between these variables.