In 2020, the total population of Mexico City reached 9.2 million and a population density of 6,163.3 residents by square kilometer. Population density has grown considerably in the country's capital during the past few decades, as it stood at 5,494 inhabitants per square meter in 1990.

Mexico City ranked as the most densely populated city in Mexico as of 2023. The capital recorded 8,657 inhabitants per square kilometer. Xalapa and Acapulco followed with 7,150 and 5,750 inhabitants per square kilometer, respectively.

Mexico population density for 2022 was 66.16, a 0.76% increase from 2021.

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<li>Mexico population density for 2021 was <strong>65.66</strong>, a <strong>0.67% increase</strong> from 2020.</li>
<li>Mexico population density for 2020 was <strong>65.23</strong>, a <strong>0.82% increase</strong> from 2019.</li>
<li>Mexico population density for 2019 was <strong>64.69</strong>, a <strong>0.95% increase</strong> from 2018.</li>
</ul>Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.

Population density (people per sq. km of land area) in Mexico was reported at 66.16 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mexico - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on May of 2025.

In 2022, the population density in Mexico remained nearly unchanged at around 66.16 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density refers to the number of people living in a certain country or area, given as an average per square kilometer. It is calculated by dividing the total midyear population by the total land area.Find more key insights for the population density in countries like United States.

Mexico MX: Population Density: People per Square Km data was reported at 66.444 Person/sq km in 2017. This records an increase from the previous number of 65.609 Person/sq km for 2016. Mexico MX: Population Density: People per Square Km data is updated yearly, averaging 43.056 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 66.444 Person/sq km in 2017 and a record low of 20.265 Person/sq km in 1961. Mexico MX: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted average;

Mexico Population Density data was reported at 61.000 Person/sq km in 2015. This records an increase from the previous number of 57.300 Person/sq km for 2010. Mexico Population Density data is updated yearly, averaging 51.250 Person/sq km from Dec 1990 (Median) to 2015, with 6 observations. The data reached an all-time high of 61.000 Person/sq km in 2015 and a record low of 41.000 Person/sq km in 1990. Mexico Population Density data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.G003: Population Density.

Mexico: Population density, in people per sq. mile: The latest value from is people per sq. mile, unavailable from people per sq. mile in . In comparison, the world average is 0 people per sq. mile, based on data from countries. Historically, the average for Mexico from to is people per sq. mile. The minimum value, people per sq. mile, was reached in while the maximum of people per sq. mile was recorded in .

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

This map shows the population density of Mexico in relation to freshwater sources and water bodies.

Mexico MX: Population Density: Inhabitants per sq km data was reported at 66.940 Person in 2022. This records an increase from the previous number of 66.350 Person for 2021. Mexico MX: Population Density: Inhabitants per sq km data is updated yearly, averaging 55.120 Person from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 66.940 Person in 2022 and a record low of 43.300 Person in 1990. Mexico MX: Population Density: Inhabitants per sq km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Mexico – Table MX.OECD.GGI: Social: Demography: OECD Member: Annual.

In 1800, the present-day region of Mexico had a population of just over six million people. Mexico gained its independence from the Spanish crown in 1821, and population growth remained steady for the next 85 years. Growth then halted with with the Panic of 1907, an American financial crisis whose ripple effects in Mexico would set the stage for the Mexican Revolution in 1910. This revolution would see population flatline at just over fifteen million between 1910 and 1920, as widespread conflict and result in the death of between 1.7 to 2.7 million over the decade, and the coinciding 1918 Spanish Flu epidemic would see the loss of another 300,000 in this time period. Following the end of both the Mexican Revolution and the Spanish Flu epidemic in 1920, the population of Mexico would begin to increase rapidly as modernization would see mortality rates fall and standards of living rise throughout the country. This growth has continued steadily into the 21st century, and in 2020, Mexico is estimated to have a population of just under 129 million.

The statistic depicts the unemployment rate in Mexico from 1999 to 2023. In 2023, Mexico's unemployment rate was around 2.77 percent. Mexico's population Mexico is the third largest country in North America. Mexico’s economy has developed and improved over the years, partially due to a better relationship with the United States. Mexico’s total population was estimated to amount to around 120 million people in 2014, with the majority, i.e. more than 60 percent, having a Mestizo background. Despite a remarkably high migration flow between Mexico and the United States, with more than 11.5 million Mexican migrants living in the United States, Mexico’s population is still growing at a constant rate. In addition, life expectancy in Mexico is increasing, pointing towards an improvement of living conditions. However, the high total population numbers affect the population density. In 2012, there were more than 62 inhabitants per square kilometer registered, ten more than a decade ago. This trend is most likely to increase but not worriyngly so, since Mexico is still far from being one of the countries with the highest population density . Among the Mexican metropolises, Mexico City has the highest number of residents by far.

From the year 2015 to 2020, there has been an increase in the population density in the Mexican city of Monterrey starting with 3,414.5 inhabitants per square kilometer and ending with 2020 with 3523.3 inhabitants, an 108.8 increase.

From the year 2015 to 2020 there has been an increase in the population density in Guadalajara, Mexico. During the last year, the city had around 9,658 inhabitants per square meter, while five years prior the density was lower than 9,180 inhabitants.

Through the time period displayed in the Mexican state of Guadalajara there has been a decrease in the population since the year 2000 which registered about 1.63 million people until the last population count conducted in 2020 resulted in 1.38 million people, almost 300 thousand people less.

PurposeIn Mexico, 39.5% of adolescents do not meet the World Health Organisation’s physical activity guidelines. Urbanicity is a potential correlate of physical activity. The aim of this study was to examine the associations between different aspects of urbanicity and adolescents’ physical activity.MethodsParticipants were 4,079 Mexican adolescents aged 15–18 from Mexico City and Oaxaca, Mexico. Data was collected between February and June 2016. Multiple imputation of missing data was implemented after confirming values were missing at random. Multivariable regression models examined associations between five domains of self-reported physical activity: 1) moderate-to-vigorous physical activity, 2) sports activities, 3) leisure time activities, 4) Physical Education class at school, 5) active commuting to school; and a composite measure of urbanicity and its seven sub-scores: 1) demographic, 2) economic activity, 3) built environment, 4) communication, 5) education, 6) diversity and 7) health services. Multivariable regression models were adjusted for parents’ education and participants’ age.ResultsUrbanicity was positively associated with activity spent in Physical Education class. The association between urbanicity and sport activities depended on state context. Communication-based urbanicity was negatively associated with leisure physical activity and active commuting. Population density was positively associated with active commuting.ConclusionUrbanicity is associated with adolescents’ physical activity in Mexico. Findings were largely consistent between Mexico City and Oaxaca and highlight the value of examining urbanicity as a multidimensional construct.

In the year 2020, Mazahua stood out as the predominant indigenous language among the prominent ones spoken in Mexico State, with a count over 111,000 people proficient in the language. Not far behind was Otomi, with a significant number of 102.600 speakers.

Climate change, urbanization, and global trade have contributed to the recent spread of dengue viruses. In this study, we investigate the relationship between dengue occurrence in humans, climate factors (temperature and minimum quarterly rainfall), socio-economic factors (such as household income, regional rates of education, regional unemployment, housing overcrowding, life expectancy, and medical resources), and demographic factors (such as migration flows, age structure of the population, and population density). From a geographical perspective, this study focuses on Mexico and parts of the United States to exploit similarity in climate conditions and differences in socio-economic and demographic factors, so as to try to isolate the role of the latter. Areas at risk of dengue are first selected based on the predicted presence of at least one of the two mosquito vectors responsible for dengue's transmission: Aedes aegypti and Aedes albopictus. The presence of the mosquito in a region...

Adult female blue-winged teal (n = 112,639) were captured in traps and nets prior to the hunting season (July-September) in the prairie potholes and aspen parklands of the North American midcontinent from 1973 to 2016 (Figure 1). Teal were ringed with uniquely engraved metal markers, and some marked individuals were killed by hunters. A portion of these markers were retrieved and reported to the USGS Bird Banding Lab (n = 2,518; USGS Patuxent Wildlife Research Center). From 1974-2016, waterfowl breeding population and habitat surveys were flown at the beginning of the breeding season over the same area by the U.S. Fish and Wildlife Service and the Canadian Wildlife Service to estimate the total number of breeding pairs of teal (y_n,t) and other ducks, and the number of ponds (y_p,t), a landscape scale measure of habitat suitability for breeding waterfowl (Walker et al. 2013, U.S. Fish & Wildlife Service 2018). We downloaded the ringing and recovery data from the GameBirds Database CD (Bird Banding Lab, USGS Patuxent Wildlife Research Center), and the Waterfowl Breeding Population and Habitat Survey data from the USFWS Migratory Birds Data Center. We retained females marked in Canada and the United States in Waterfowl Breeding Population and Habitat Survey strata 20-49 (U.S. Fish & Wildlife Service 2018), and we restricted re-encounters to harvested individuals recovered and reported by hunters in the United States and Canada from September through early February, with half of all reported hunting mortality occurring in September. We excluded recoveries in Mexico, Central and South America, and the Carribean (n = 316) due to the inclusion of band reporting probabilities (r = r_1973, ... , r_2016) in our analyses, which were not available for Latin America. Mark-recovery data were downloaded from the USGS Bird Banding Lab Celis-Murillo et al. 2020. We accessed estimates of teal abundance and pond abundance from the Waterfowl Breeding Population and Habitat Survey (U.S. Fish & Wildlife Service 2018), as well as data on federal duck stamp sales, which are required to hunt for waterfowl in the United States. Third party data were used for this study, collection of which followed appropriate ethical guidelines. No additional ethical approval was required from our respective insitutions. We formatted the capture-recovery data into a multinomial array to reduce computational requirements. Please contact the authors for additional information about data processing. 1. Harvest of wild organisms is an important component of human culture, economy, and recreation, but can also put species at risk of extinction. Decisions that guide successful management actions therefore rely on the ability of researchers to link changes in demographic processes to the anthropogenic actions or environmental changes that underlie variation in demographic parameters. 2. Ecologists often use population models or maximum sustained yield curves to estimate the impacts of harvest on wildlife and fish populations. Applications of these models usually focus exclusively on the impact of harvest and often fail to consider adequately other potential, often collinear, mechanistic drivers of the observed relationships between harvest and demographic rates. In this study, we used an integrated population model and long-term data (1973-2016) to examine the relationships among hunting and natural mortality, the number of hunters, habitat conditions, and population size of blue-winged teal (Spatula discors), an abundant North American dabbling duck with a relatively fast-paced life history strategy. 3. Over the last two and a half decades of the study, teal abundance tripled, hunting mortality probability increased slightly (< 0.02), and natural mortality probability increased substantially (> 0.1) at greater population densities. We demonstrate strong density-dependent effects on natural mortality and fecundity as population density increased, indicative of compensatory harvest mortality and compensatory natality. Critically, an analysis that only assessed the relationship between survival and hunting mortality would spuriously indicate depensatory hunting mortality due to multicollinearity between abundance, natural mortality, and hunting mortality. 4. Our findings demonstrate that models that only consider the direct effect of hunting on survival or natural mortality can fail to accurately assess the mechanistic impact of hunting on population dynamics due to multicollinearity among demographic drivers. This multicollinearity limits inference and may have strong impacts on applied management actions globally. The open-source programs R and JAGS are required to run the integrated population model described in this manuscript.