According to latest figures, the Chinese population decreased by 1.39 million to around 1.408 billion people in 2024. After decades of rapid growth, China arrived at the turning point of its demographic development in 2022, which was earlier than expected. The annual population decrease is estimated to remain at moderate levels until around 2030 but to accelerate thereafter. Population development in China China had for a long time been the country with the largest population worldwide, but according to UN estimates, it has been overtaken by India in 2023. As the population in India is still growing, the country is very likely to remain being home of the largest population on earth in the near future. Due to several mechanisms put into place by the Chinese government as well as changing circumstances in the working and social environment of the Chinese people, population growth has subsided over the past decades, displaying an annual population growth rate of -0.1 percent in 2024. Nevertheless, compared to the world population in total, China held a share of about 17 percent of the overall global population in 2024. China's aging population In terms of demographic developments, the birth control efforts of the Chinese government had considerable effects on the demographic pyramid in China. Upon closer examination of the age distribution, a clear trend of an aging population becomes visible. In order to curb the negative effects of an aging population, the Chinese government abolished the one-child policy in 2015, which had been in effect since 1979, and introduced a three-child policy in May 2021. However, many Chinese parents nowadays are reluctant to have a second or third child, as is the case in most of the developed countries in the world. The number of births in China varied in the years following the abolishment of the one-child policy, but did not increase considerably. Among the reasons most prominent for parents not having more children are the rising living costs and costs for child care, growing work pressure, a growing trend towards self-realization and individualism, and changing social behaviors.

The total population in China was estimated at 1409.7 million people in 2023, according to the latest census figures and projections from Trading Economics. This dataset provides - China Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context

Some friends at kaggle said them would like to see more dataset about China. I'm just uncertain what kind of data do you want. So I simply collect a population dataset as a beginning. I'm very glad that our international friends can know more about the real China, my great motherland from these datasets.

Content

注：1981年及以前人口数据为户籍统计数；1982、1990、2000、2010、2020年数据为当年人口普查数据推算数；其余年份数据为年度人口抽样调查推算数据。总人口和按性别分人口中包括现役军人，按城乡分人口中现役军人计入城镇人口。 数据来源：国家统计局

Note: Population data in 1981 and before are household registration statistics; The data of 1982, 1990, 2000, 2010 and 2020 are calculated from the census data of the same year. Data for the remaining years were derived from annual population sampling surveys. Active servicemen are included in the total population and population by sex, and active servicemen are included in the urban population by urban and rural population. Source: National Bureau of Statistics.

Tips: what you should notice is that all the numbers with the counting unit (10 thousand) or we said in Chinese ‘万’, as a very usual counting unit rather than 'thousand' in English.

Inspiration

By this dataset, you can see the progress of China's urbanization.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: Not applicable - Households: Households can be classified into two types: domestic and collective. Individuals who live in the same place mostly due to family relationships are counted as a domestic household. Singles who live alone are counted as a domestic household. Individuals who live in the same domestic household should be registered as one household only, regardless of the type of working places and the type of household registrations (agricultural or non-agricultural), and whether they have the formal household registrations. - Group quarters: Collective dorms of work units (including their branch units) such as organs, groups, schools, factories, mines, construction sites, farms, companies, shops, hospitals, nurseries, old people's homes, monasteries, churches, prisons, places for reform through labor and reeducation.

Universe

All individuals who have Chinese nationality and reside in China

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: National Bureau of Statistics

SAMPLE SIZE (person records): 11835947.

SAMPLE DESIGN: Stratified cluster sample

Mode of data collection

Face-to-face [f2f]

Research instrument

A single questionnaire for regular and collective households.

As of 2023, the bulk of the Chinese population was aged between 25 and 59 years, amounting to around half of the population. A breakdown of the population by broad age groups reveals that around 61.3 percent of the total population was in working age between 16 and 59 years in 2023. Age cohorts below 25 years were considerably smaller, although there was a slight growth trend in recent years. Population development in China Population development in China over the past decades has been strongly influenced by political and economic factors. After a time of high fertility rates during the Maoist regime, China introduced birth-control measures in the 1970s, including the so-called one-child policy. The fertility rate dropped accordingly from around six children per woman in the 1960s to below two at the end of the 20th century. At the same time, life expectancy increased consistently. In the face of a rapidly aging society, the government gradually lifted the one-child policy after 2012, finally arriving at a three-child policy in 2021. However, like in most other developed countries nowadays, people in China are reluctant to have more than one or two children due to high costs of living and education, as well as changed social norms and private values. China’s top-heavy age pyramid The above-mentioned developments are clearly reflected in the Chinese age pyramid. The age cohorts between 30 and 39 years are the last two larger age cohorts. The cohorts between 15 and 24, which now enter childbearing age, are decisively smaller, which will have a negative effect on the number of births in the coming decade. When looking at a gender distribution of the population pyramid, a considerable gender gap among the younger age cohorts becomes visible, leaving even less room for growth in birth figures.

This is a hybrid gridded dataset of demographic data for China from 1979 to 2100, given as 21 five-year age groups of population divided by gender every year at a 0.5-degree grid resolution.

The historical period (1979-2020) part of this dataset combines the NASA SEDAC Gridded Population of the World version 4 (GPWv4, UN WPP-Adjusted Population Count) with gridded population from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, Histsoc gridded population data).

The projection (2010-2100) part of this dataset is resampled directly from Chen et al.’s data published in Scientific Data.

This dataset includes 31 provincial administrative districts of China, including 22 provinces, 5 autonomous regions, and 4 municipalities directly under the control of the central government (Taiwan, Hong Kong, and Macao were excluded due to missing data).

Method - demographic fractions by age and gender in 1979-2020

Age- and gender-specific demographic data by grid cell for each province in China are derived by combining historical demographic data in 1979-2020 with the national population census data provided by the National Statistics Bureau of China.

To combine the national population census data with the historical demographics, we constructed the provincial fractions of demographic in each age groups and each gender according to the fourth, fifth and sixth national population census, which cover the year of 1979-1990, 1991-2000 and 2001-2020, respectively. The provincial fractions can be computed as:

\(\begin{align*} \begin{split} f_{year,province,age,gender}= \left \{ \begin{array}{lr} POP_{1990,province,age,gender}^{4^{th}census}/POP_{1990,province}^{4^{th}census} & 1979\le\mathrm{year}\le1990\\ POP_{2000,province,age,gender}^{5^{th}census}/POP_{2000,province}^{5^{th}census} & 1991\le\mathrm{year}\le2000\\ POP_{2010,province,age,gender}^{6^{th}census}/POP_{2010,province}^{6^{th}census}, & 2001\le\mathrm{year}\le2020 \end{array} \right. \end{split} \end{align*}\)

Where:

- \( f_{\mathrm{year,province,age,gender}}\)is the fraction of population for a given age, a given gender in each province from the national census from 1979-2020.

- \(\mathrm{PO}\mathrm{P}_{\mathrm{year,province,age,gender}}^{X^{\mathrm{th}}\mathrm{census} }\) is the total population for a given age, a given gender in each province from the X^th national census.

- \(\mathrm{PO}\mathrm{P}_{\mathrm{year,province}}^{X^{\mathrm{th}}\mathrm{census} }\) is the total population for all ages and both genders in each province from the X^th national census.

Method - demographic totals by age and gender in 1979-2020

The yearly grid population for 1979-1999 are from ISIMIP Histsoc gridded population data, and for 2000-2020 are from the GPWv4 demographic data adjusted by the UN WPP (UN WPP-Adjusted Population Count, v4.11, https://beta.sedac.ciesin.columbia.edu/data/set/gpw-v4-population-count-adjusted-to-2015-unwpp-country-totals-rev11), which combines the spatial distribution of demographics from GPWv4 with the temporal trends from the UN WPP to improve accuracy. These two gridded time series are simply joined at the cut-over date to give a single dataset - historical demographic data covering 1979-2020.

Next, historical demographic data are mapped onto the grid scale to obtain provincial data by using gridded provincial code lookup data and name lookup table. The age- and gender-specific fraction were multiplied by the historical demographic data at the provincial level to obtain the total population by age and gender for per grid cell for china in 1979-2020.

Method - demographic totals and fractions by age and gender in 2010-2100

The grid population count data in 2010-2100 under different shared socioeconomic pathway (SSP) scenarios are drawn from Chen et al. published in Scientific Data with a resolution of 1km (~ 0.008333 degree). We resampled the data to 0.5 degree by aggregating the population count together to obtain the future population data per cell.

This previously published dataset also provided age- and gender-specific population of each provinces, so we calculated the fraction of each age and gender group at provincial level. Then, we multiply the fractions with grid population count to get the total population per age group per cell for each gender.

Note that the projected population data from Chen’s dataset covers 2010-2020, while the historical population in our dataset also covers 2010-2020. The two datasets of that same period may vary because the original population data come from different sources and are calculated based on different methods.

Disclaimer

This dataset is a hybrid of different datasets with independent methodologies. Spatial or temporal consistency across dataset boundaries cannot be guaranteed.

Introduction: Gridded population datasets are instrumental for modeling the interactions between human and the environment at fine spatial scales. Here, we introduce an Age-Stratified Population Estimation from the 2020 China Census by Township (ASPECT), estimating total population and population by age groups (0-14, 15-59, 60-64, ≥65 years old) at 100m spatial resolution as of year 2020. We used a dasymetric mapping approach to downscale township-level population data (n=40,718 townships) from the 2020 China Census to 100 by 100 m grid cells. The study area is mainland China.Data records: ASPECT includes GEOTIFF files on population density (persons per hectare) at 100 m spatial resolution. No data areas indicate townships missing the 2020 Census data (n=590) and areas fall outside our study area, mainland China. The files are:population_total_pop: gridded estimates on total populationpopulation_age0_14: gridded estimates on population between 0 and 14 years oldpopulation_age15_59: gridded estimates on population between 15 and 59 years oldpopulation_age60_64: gridded estimates on population between 60 and 64 years oldpopulation_age65above: gridded estimates on population ≥65 years oldpopulation_total_pop_sum: gridded estimates on total population, summed with age-group specific estimates (file 2-5). This file is used to calculate the proportion of each age group.ASPECT also includes GEOTIFF files on the proportion (%) of population by age groups at 100 m spatial resolution. No data areas indicate townships missing the 2020 Census data, places fell outside our study area, and places with zero population. Proportion of a population age group is calculated by dividing its population counts by the sum of population from all age groups (i.e., grid cell values from the “population_total_pop_sum.zip” file). The files are:proportion_age0_14: the proportion of population between 0 and 14 years oldproportion_age15_59: the proportion of population between 15 and 59 years oldproportion_age60_64: the proportion of population between 60 and 64 years oldproportion_age65above: the proportion of population ≥65 years oldAll GEOTIFF files are projected with WGS 1984 geographic coordinate system (EPSG: 4326). The files are compressed in zip format. Once uncompressed, the GEOTIFF files can processed by GIS software such as ArcGIS, and by programing language packages such as Rasterio in Python.Reference: 100-m resolution Age-Stratified Population Estimation from the 2020 China Census by Township (ASPECT), published by Scientific Data [link]Citation: Ju, Y., Liang, Y., Kong, J., Wang, X., Wen, S., Shang, H., & Wang, X. (2025). 100-m resolution Age-Stratified Population Estimation from the 2020 China Census by Township (ASPECT). Scientific Data, 12(1), 1058. https://doi.org/10.1038/s41597-025-05401-1

The graph shows the population growth in China from 2000 to 2024. In 2024, the Chinese population decreased by about 0.1 percent or 1.39 million to around 1.408 billion people. Declining population growth in China Due to strict birth control measures by the Chinese government as well as changing family and work situations of the Chinese people, population growth has subsided over the past decades. Although the gradual abolition of the one-child policy from 2014 on led to temporarily higher birth figures, growth rates further decreased in recent years. As of 2024, leading countries in population growth could almost exclusively be found on the African continent and the Arabian Peninsula. Nevertheless, as of mid 2024, Asia ranked first by a wide margin among the continents in terms of absolute population. Future development of Chinese population The Chinese population reached a maximum of 1,412.6 million people in 2021 but decreased by 850,000 in 2022 and another 2.08 million in 2023. Until 2022, China had still ranked the world’s most populous country, but it was overtaken by India in 2023. Apart from the population decrease, a clear growth trend in Chinese cities is visible. By 2024, around 67 percent of Chinese people lived in urban areas, compared to merely 36 percent in 2000.

In 2024, around **** million babies were born in China. The number of births has increased slightly from **** million in the previous year, but is much lower than the ***** million births recorded in 2016. Demographic development in China In 2022, the Chinese population decreased for the first time in decades, and population decline is expected to accelerate in the upcoming years. To curb the negative effects of an aging population, the Chinese government decided in 2013 to gradually relax the so called one-child-policy, which had been in effect since 1979. From 2016 onwards, parents in China were allowed to have two children in general. However, as the recent figures of births per year reveal, this policy change had only short-term effects on the general birth rate: the number of births slightly increased from 2014 onwards, but then started to fell again in 2018. In 2024, China was the second most populous country in the world, overtaken by India that year. China’s aging population The Chinese society is aging rapidly and facing a serious demographic shift towards older age groups. The median age of China’s population has increased massively from about ** years in 1970 to **** years in 2020 and is projected to rise continuously until 2080. In 2020, approximately **** percent of the Chinese were 60 years and older, a figure that is forecast to rise as high as ** percent by 2060. This shift in demographic development will increase social and elderly support expenditure of the society as a whole. One measure for this social imbalance is the old-age dependency ratio, measuring the relationship between economic dependent older age groups and the working-age population. The old-age dependency ratio in China is expected to soar to ** percent in 2060, implying that by then three working-age persons will have to support two elderly persons.

Explore population projections for China on this dataset webpage. Get valuable insights into the future demographic trends of one of the world's most populous countries.

Population, China, projections ChinaFollow data.kapsarc.org for timely data to advance energy economics research..Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimatesSource: (1) United Nations Population Division. World Population Prospects: 2019 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.

Hong Kong HK: Population: Growth data was reported at 0.748 % in 2017. This records an increase from the previous number of 0.619 % for 2016. Hong Kong HK: Population: Growth data is updated yearly, averaging 1.089 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 5.465 % in 1979 and a record low of -0.197 % in 2003. Hong Kong HK: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hong Kong – Table HK.World Bank: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

In 2024, there were around 719 million male inhabitants and 689 million female inhabitants living in China, amounting to around 1.41 billion people in total. China's total population decreased for the first time in decades in 2022, and population decline is expected to accelerate in the upcoming years. Birth control in China From the beginning of the 1970s on, having many children was no longer encouraged in mainland China. The one-child policy was then introduced in 1979 to control the total size of the Chinese population. According to the one-child policy, a married couple was only allowed to have one child. With the time, modifications were added to the policy, for example parents living in rural areas were allowed to have a second child if the first was a daughter, and most ethnic minorities were excepted from the policy. Population ageing The birth control led to a decreasing birth rate in China and a more skewed gender ratio of new births due to boy preference. Since the negative economic and social effects of an aging population were more and more felt in China, the one-child policy was considered an obstacle for the country’s further economic development. Since 2014, the one-child policy has been gradually relaxed and fully eliminated at the end of 2015. However, many young Chinese people are not willing to have more children due to high costs of raising a child, especially in urban areas.

Population: Census: Jiangsu: Nanjing data was reported at 9,314.685 Person th in 12-01-2020. This records an increase from the previous number of 8,004.680 Person th for 12-01-2010. Population: Census: Jiangsu: Nanjing data is updated decadal, averaging 8,004.680 Person th from Dec 2000 (Median) to 12-01-2020, with 3 observations. The data reached an all-time high of 9,314.685 Person th in 12-01-2020 and a record low of 6,126.165 Person th in 12-01-2000. Population: Census: Jiangsu: Nanjing data remains active status in CEIC and is reported by Nanjing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: By Census.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of China by race. It includes the distribution of the Non-Hispanic population of China across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of China across relevant racial categories.

Key observations

Of the Non-Hispanic population in China, the largest racial group is White alone with a population of 487 (70.78% of the total Non-Hispanic population).

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 (for Non-Hispanic) for the China
• Population: The population of the racial category (for Non-Hispanic) in the China is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China total Non-Hispanic 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 China Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of China town by race. It includes the distribution of the Non-Hispanic population of China town across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of China town across relevant racial categories.

Key observations

Of the Non-Hispanic population in China town, the largest racial group is White alone with a population of 4,231 (96.75% of the total Non-Hispanic population).

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 (for Non-Hispanic) for the China town
• Population: The population of the racial category (for Non-Hispanic) in the China town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China town total Non-Hispanic 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 China town Population by Race & Ethnicity. You can refer the same here

Introduction: Blood eosinophil count has been shown markedly variable across different populations. However, its distribution in Chinese general population remains unclear. We aimed to investigate blood eosinophil count and its determinants in a Chinese general population. Methods: In this population-based study, general citizens of Sichuan province in China were extracted from the China Pulmonary Health study. Data on demographics, personal and family history, living condition, lifestyle, spirometry and complete blood count test were obtained and analyzed. A stepwise multivariate binary logistic regression analysis was performed to identify determinants of high blood eosinophils (>75th percentile). Results: A total of 3310 participants were included, with a mean age (SD) of 47.0 (15.6) years. In total population, the median blood eosinophil count was 110.0 (IQR 67.2-192.9) cells/μL, lower than that in smokers (133.4 cells/μL, IQR 79.3-228.4) and patients with asthma (140.7 cells/μL, IQR 79.6-218.2) or post-bronchodilator airflow limitation (141.5 cells/μL, IQR 82.6-230.1), with a right-skewed distribution. Multivariate analyses revealed that oldness (aged ≥60 years) (OR 1.66, 95% CI 1.11-2.48), smoking ≥ 20 pack-years (OR 1.90, 95% CI 1.20-3.00), raising dog/cat (OR 1.72, 95% CI 1.17-2.52) and occupational exposure to dust, allergen and harmful gas (OR 1.58, 95% CI 1.15-2.15) were significantly associated with high blood eosinophils. Conclusion: This study identifies a median blood eosinophil count of 110.0 cells/μL and determinants of high blood eosinophils in a Chinese general population, including oldness (aged ≥60 years), smoking ≥ 20 pack-years, raising dog/cat and occupational exposure to dust, allergen and harmful gas.

Title: Population Data of Indian Cities (2011 and 2001)

Description: This dataset contains population information for various cities in India, categorized by rank, city name, and population figures for the years 2011 and 2001. Additionally, it includes the corresponding state or union territory to which each city belongs. The dataset provides insights into population changes over a decade in different cities across India.

Columns:

Rank: This column represents the rank of each city based on its population in the year 2011. Cities are typically ranked in descending order of population, with the most populous city having the rank 1.

City: This column contains the names of the cities for which population data is recorded.

Population (2011): This column displays the population count of each city as of the year 2011. The population figures are likely to be recorded in thousands or millions

Population (2001): This column provides the population count of each city as of the year 2001. Comparing this data with the 2011 population figures allows for an analysis of population growth or decline over the decade.

State or Union Territory: This column indicates the administrative division to which each city belongs. In India, cities are typically grouped into states or union territories, and this column helps identify the geographical context of each city.

In 2025, India overtook China as the world's most populous country and now has almost 1.46 billion people. China now has the second-largest population in the world, still with just over 1.4 billion inhabitants, however, its population went into decline in 2023. Global population As of 2025, the world's population stands at almost 8.2 billion people and is expected to reach around 10.3 billion people in the 2080s, when it will then go into decline. Due to improved healthcare, sanitation, and general living conditions, the global population continues to increase; mortality rates (particularly among infants and children) are decreasing and the median age of the world population has steadily increased for decades. As for the average life expectancy in industrial and developing countries, the gap has narrowed significantly since the mid-20th century. Asia is the most populous continent on Earth; 11 of the 20 largest countries are located there. It leads the ranking of the global population by continent by far, reporting four times as many inhabitants as Africa. The Demographic Transition The population explosion over the past two centuries is part of a phenomenon known as the demographic transition. Simply put, this transition results from a drastic reduction in mortality, which then leads to a reduction in fertility, and increase in life expectancy; this interim period where death rates are low and birth rates are high is where this population explosion occurs, and population growth can remain high as the population ages. In today's most-developed countries, the transition generally began with industrialization in the 1800s, and growth has now stabilized as birth and mortality rates have re-balanced. Across less-developed countries, the stage of this transition varies; for example, China is at a later stage than India, which accounts for the change in which country is more populous - understanding the demographic transition can help understand the reason why China's population is now going into decline. The least-developed region is Sub-Saharan Africa, where fertility rates remain close to pre-industrial levels in some countries. As these countries transition, they will undergo significant rates of population growth.

About this dataset

Context

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

Key observations

The percent distribution of China population by race (across all racial categories recognized by the U.S. Census Bureau): 72.09% are white, 16.37% are Black or African American, 3.03% are Asian, 1.46% are some other race and 7.06% 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 China
• Population: The population of the racial category (excluding ethnicity) in the China is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China 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 China Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of China town population by race (across all racial categories recognized by the U.S. Census Bureau): 95.37% are white, 0.67% are Asian, 0.27% are some other race and 3.69% 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 China town
• Population: The population of the racial category (excluding ethnicity) in the China town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China town 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 China town Population by Race & Ethnicity. You can refer the same here