Chart and table of population level and growth rate for the Munich, Germany metro area from 1950 to 2025.

This statistic shows data on the residential population of the independent city of Munich in 2021, broken down by age group. Munich is the capital of the state of Bavaria and is Germany's third largest city after Berlin and Hamburg. In the period of consideration, the largest age group represented among the Munich population was 30 to 39 years at 279,401 people.

This statistic shows data on the residential population of the city of Munich from 2011 to 2020, broken down by gender. In 2020, roughly 772 thousand men and 790 thousand women lived in Munich. Munich is Germany's third largest city after Berlin and Hamburg.

About this dataset

Context

The dataset tabulates the population of Munich by race. It includes the population of Munich across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Munich across relevant racial categories.

Key observations

The percent distribution of Munich population by race (across all racial categories recognized by the U.S. Census Bureau): 83.33% are white, 1.16% are Asian and 15.50% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Munich
• Population: The population of the racial category (excluding ethnicity) in the Munich is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Munich total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Munich Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the New Munich population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of New Munich across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of New Munich was 363, a 0.82% decrease year-by-year from 2022. Previously, in 2022, New Munich population was 366, an increase of 0.83% compared to a population of 363 in 2021. Over the last 20 plus years, between 2000 and 2023, population of New Munich increased by 34. In this period, the peak population was 366 in the year 2022. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the New Munich is shown in this column.
• Year on Year Change: This column displays the change in New Munich population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Munich Population by Year. You can refer the same here

This statistic shows the development of the residential population of the independent city of Munich from 1995 to 2023. Munich is Germany's third largest city after Berlin and Hamburg. In 2023, Munich was home to roughly **** million people.

(also referred to as external migration balance per 1000 German inhabitants)

Difference between German non-urban residents (main residence) of the corresponding category and those who moved away (main residence) of the corresponding category per 1 000 German main residents (middle German main residence population in the calendar year) of the corresponding category.

Only extra-urban (beyond the city limits of Munich) immigrants and emigrants are taken into account.

Please refer to Data descriptions (PDF file).

Information on the indicator atlas

About this dataset

Context

The dataset tabulates the New Munich population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of New Munich.

Content

The dataset constitues the following two datasets across these two themes

• New Munich, MN Population Breakdown by Gender
• New Munich, MN Population Breakdown by Gender and Age

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

About this dataset

Context

The dataset tabulates the data for the Munich, ND population pyramid, which represents the Munich population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Munich, ND, is 34.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Munich, ND, is 21.8.
• Total dependency ratio for Munich, ND is 56.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Munich, ND is 4.6.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Munich population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Munich for the selected age group is shown in the following column.
• Population (Female): The female population in the Munich for the selected age group is shown in the following column.
• Total Population: The total population of the Munich for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Munich Population by Age. You can refer the same here

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The largest age groups among Berlin’s residential population were aged 25-39 and 40-59 years. The latter was actually the most represented age group in the German capital. The age group with the least number of residents were babies aged younger than one year. Slowly growing population Berlin’s residential population has been growing in recent years, though at a slow pace. Generally, the urban population in Germany has been increasing, with over 77 percent living in cities. Berlin does not have the most expensive rent space in Germany, compared to Munich in the south or Frankfurt in central Germany, which could be a draw for younger age groups moving to the capital. On the other hand, just as in the rest of the country, the city’s age group structure is affected by a struggling birth rate. Uncertain future Based on recent figures, Berlin’s total population was almost at four million. Germany’s population count currently stands at almost 84.5 million and is forecast to decrease rather than increase in the 2020s.

About this dataset

Context

The dataset tabulates the Munich population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Munich across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Munich was 188, a 2.59% decrease year-by-year from 2021. Previously, in 2021, Munich population was 193, a decline of 1.03% compared to a population of 195 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Munich decreased by 78. In this period, the peak population was 266 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Munich is shown in this column.
• Year on Year Change: This column displays the change in Munich population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Munich Population by Year. You can refer the same here

Content

A dataset of counties that are representative for Germany with regard to

• the average disposable income,
• the quota of divorces,
• the respective quotas of employees working in the services (excluding logistics, security, and cleaning) and the MINT sectors,
• the proportions of age groups in the total proportion of the respective population, with age groups in five-year strata for the population aged between 30 and 65 and the population in the age range between 65 and 75 each considered separately for the calculation of representativeness.
• population density, if the benchmark is defined as the national average density weighted by county population. This value is calculated by averaging the population-per-square-kilometer figures of all German counties, weighted by the population size of each county. In contrast to a simple arithmetic mean of county-level densities, which would disproportionately reflect sparsely populated areas, this method reflects the actual density of the environments where people live. The resulting value for the selected counties falls within the 95% confidence interval of the national weighted average.

In addition, data from the four big cities Berlin, München (Munich), Hamburg, and Köln (Cologne) were collected and reflected in the dataset.

The dataset is based on the most recent data available at the time of the creation of the dataset, mainly deriving from 2022, as set out in detail in the readme.md file.

Method applied

The selection of the representative counties, as reflected in the dataset, was performed on the basis of official statistics with the aim of obtaining a confidence rate of 95%. The selection was based on a principal component analysis of the statistical data available for Germany and the addition of the regions with the lowest population density and the highest and lowest per capita disposable income. A check of the representativity of the selected counties was performed.

In the case of Leipzig, the city and the district had to be treated together, in deviation from the official territorial division, with respect to a specific use case of the data.

This study is a contribution to hitorical anthropometric research.

Anthropometric historiy deals with the interaction of biological and economical processes. Body height and body weight are important indicators of the living standard, having strong effects on economic factors like work productivity and capital formation. Because of the close connection between nutritional status and body height, fertility rate and mortality rate, changes of body height serves a very valuable support for explaining demographic processes. Changes in body height are also indicators for changes in economic situation and for changing living standards of the population.

The study is an anthropometric contribution to the nutrition, economics and agrarian history of a region, using body size data of Bavarian people liable for military service. Two topics are treated: 1) The economic circumstances of various goups of society should be described in a very differentiated way. 2) Medical care and living conditions of the population (infant mortality, emergence of deseases, causes of death, etc.) in different county districts should be described. For this purpose the birth cohorts 1813 to 1842 of the county districts Munich city, Munich on the left hand of the Isar, Munich on the right hand of the Isar, Miesbach, Reichenhall, Toelz and Wasserburg were analyzed.

Variables (n = 19562): - District of the provincial court (Landgerichtsbezirk) - Birth year - Body height of inductees, in different measures - Legitimacy of Birth (born in wedlock, born out of wedlock) - Occupation of inductees - Occupation of the Father - Death of mother and the father respectively (or of both parents) - Results of the medical examination (reasons for the exemption from military service) - Results of physical categorization (fitness)

Key aspects of the study: (1) structural investigation of the districts of the provincial court (2) demographic description of the research areas (districts) (3) determinants of biological standard of living of the districts: - the importance of occupation and social class affiliation - the importance of deseases - the importance of livin conditions (4) Trend of body height - fundmental trend - comparison of inductees’ biological living standards, whose parents are employed at the saline with inductees’ biological living standards, whose parents are farmers and craftspeople. - anthropometric investigation of the population in Munich. (5) Infant mortality, fertility and illegitimacy - infant mortality in Southern Germany and in Bavaria - infant mortality in Munich - infant feeding and infant care in the districts of the provincial court - sex-related infant mortality - mortality of infants, born in wedlock and of infants, born out of wedlock - interrelationship of infant mortality and fertility - causes of death - interrelationship of level of prices and infant mortality (6) Mortality, life expectancy and body height.

As of October 2024, the number of Japanese residents in Munich amounted to approximately ***** individuals. The southern German city was home to the second largest Japanese community within Germany after Düsseldorf.

About this dataset

Context

The dataset tabulates the population of Munich by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Munich. The dataset can be utilized to understand the population distribution of Munich by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Munich. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Munich.

Key observations

Largest age group (population): Male # 25-29 years (30) | Female # 55-59 years (41). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Munich population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Munich is shown in the following column.
• Population (Female): The female population in the Munich is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Munich for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Munich Population by Gender. You can refer the same here

Since 2010, the population of pet dogs in Germany has doubled, reaching about **** million dogs in 2023. The population of pet dogs as increased almost every year during this time period, except for in 2021.

About this dataset

Context

The dataset tabulates the population of New Munich by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of New Munich across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 54.91% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the New Munich is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of New Munich total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Munich Population by Race & Ethnicity. You can refer the same here

Summary

This metadata record provides details of the data supporting the claims of the related article: “Genomic context of NTRK1/2/3 fusion-positive tumours from a large real-world population”.

The related study aimed to interrogate a large real-world database of comprehensive genomic profiling data to describe the genomic landscape and prevalence of neurotrophic tropomyosin receptor kinase (NTRK) gene fusions.

Subject of data: Homo sapiens

Sample size: Data from 295,676 de-identified, consented-for-research cases between January 2013 and December 2019 from 75 different solid tumour types were profiled. Sample size for the clinical trials population was the efficacy-evaluable population, i.e., all patients who had received at least one dose of entrectinib and had at least 6 months of follow up.

Recruitment: This is a secondary analysis of data from the clinical trials listed below. Full methods have been published previously in: https://doi.org/10.1016/s1470-2045(19)30691-6

Trial registration number: ALKA-372-001 [EudraCT 2012-000148-88], STARTRK-1 [NCT02097810], STARTRK-2 [NCT02568267]

Data access

The data were generated and analysed under the auspices of Roche, which is a member of the Vivli Center for global clinical research data. Data access conditions are described at https://vivli.org/ourmember/roche/. To request access to individual patient-level data from the clinical trials, first locate the clinical trial in Vivli (https://search.vivli.org/ requires sign up and log in) using the trial registration number (given above), then click the ‘Request Study’ button and follow the instructions. In the event that you cannot see a specific study in the Roche list, an Enquiry Form can be submitted to confirm the availability of the specific study. To request access to related clinical study documents (eg: protocols, CSR, safety reports), please use Roche’s Clinical study documents request form: https://www.roche.com/research_and_development/who_we_are_how_we_work/research_and_clinical_trials/our_commitment_to_data_sharing/clinical_study_documents_request_form.htm.Patient-level data which were derived from the Foundation Research dataset and used in the related study cannot be shared as they contain patient genomic information that, depending on the prevalence of the identified alterations, could be used to identify individuals.

To maximise transparency and provide the most thorough information without compromising patients’ personal information, the authors have created a large number of supplementary files and made them openly available as part of this figshare data record. Data underlying Supplementary Figure 2 are in the file ‘data_underlying_supplementary_figure_2.xlsx’. Data underlying Supplementary Tables 1–4, 6–12, and 14 are in the file ‘FMI NTRK manuscript_Supplementary Tables_17May2021.xlsx’.

Corresponding author(s) for this study

Dr C. Benedikt Westphalen, Comprehensive Cancer Center Munich & Department of Medicine III, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. Tel: +49 (089) 4400-75250; E-mail: cwestpha@med.lmu.de

Study approval

Approval was obtained from the Western Institutional Review Board (Protocol No. 20152817). Written consent was obtained to use the de-identified patient samples for research.

A total of around *** million guests arrives in Munich, Bavaria's capital, in 2023. Of these, around **** million came from abroad.