In 1800, the population of the area of modern-day Pakistan was estimated to be just over 13 million. Population growth in the 19th century would be gradual in the region, rising to just 19 million at the turn of the century. In the early 1800s, the British Empire slowly consolidated power in the region, eventually controlling the region of Pakistan from the mid-19th century onwards, as part of the British Raj. From the 1930s on, the population's growth rate would increase as improvements in healthcare (particularly vaccination) and sanitation would lead to lower infant mortality rates and higher life expectancy. Independence In 1947, the Muslim-majority country of Pakistan gained independence from Britain, and split from the Hindu-majority country of India. In the next few years, upwards of ten million people migrated between the two nations, during a period that was blemished by widespread atrocities on both sides. Throughout this time, the region of Bangladesh was also a part Pakistan (as it also had a Muslim majority), known as East Pakistan; internal disputes between the two regions were persistent for over two decades, until 1971, when a short but bloody civil war resulted in Bangladesh's independence. Political disputes between Pakistan and India also created tension in the first few decades of independence, even boiling over into some relatively small-scale conflicts, although there was some economic progress and improvements in quality of life for Pakistan's citizens. The late 20th century was also characterized by several attempts to become democratic, but with intermittent periods of military rule. Between independence and the end of the century, Pakistan's population had grown more than four times in total. Pakistan today Since 2008, Pakistan has been a functioning democracy, with an emerging economy and increasing international prominence. Despite the emergence of a successful middle-class, this is prosperity is not reflected in all areas of the population as almost a quarter still live in poverty, and Pakistan ranks in the bottom 20% of countries according to the Human Development Index. In 2020, Pakistan is thought to have a total population of over 220 million people, making it the fifth-most populous country in the world.

With almost all major religions being practiced throughout the country, India is known for its religious diversity. Islam makes up the highest share among minority faiths in the country. According to the Indian census of 2011, the Muslim population in Uttar Pradesh more than 35 million, making it the state with the most Muslims.

Socio-economic conditions of Muslims
Muslims seem to lag behind every other religious community in India in terms of living standards, financial stability, education and other aspects, thereby showing poor performance in most of the fields. According to a national survey, 17 percent of the Muslims were categorized under the lowest wealth index, which indicates poor socio-economic conditions.

Growth of Muslim population in India
Islam is one of the fastest-growing religions worldwide. According to India’s census, the Muslim population has witnessed a negative decadal growth of more than 16 percent from 1951 to 1960, presumably due to the partitions forming Pakistan and Bangladesh. The population showed a positive and steady growth since 1961, making up 14 percent of the total population of India . Even though people following Islam were estimated to grow significantly, they would still remain a minority in India compared to 1.3 billion Hindus by 2050.

Facebook and Columbia University - CIESIN provide the High Resolution Settlement Layer as the world's most accurate population datasets. More info can be found here: https://dataforgood.fb.com/tools/population-density-maps/

These maps are the distribution of human population spanning Pakistan and India. Each of the 13 TIFF files is a 10 x 10 degree tile (the lower latitude coordinate and longitude coordinates are in the file name). A VRT file is also included.

The US Census Bureau defines Asian as "A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. This includes people who reported detailed Asian responses such as: Indian, Bangladeshi, Bhutanese, Burmese, Cambodian, Chinese, Filipino, Hmong, Indonesian, Japanese, Korean, Laotian, Malaysian, Nepalese, Pakistani, Sri Lankan, Taiwanese, Thai, Vietnamese, Other Asian specified, Other Asian not specified.". 2020 Census block groups for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted from the 2020 State of Kansas Census Block Group shapefile provided by the State of Kansas GIS Data Access and Support Center (https://www.kansasgis.org/index.cfm).Change in Population and Housing for the Sedgwick County area from 2010 - 2020 based upon US Census. Census Blocks from 2010 were spatially joined to Census Block Groups from 2020 to compare the population and housing figures. This is not a product of the US Census Bureau and is only available through City of Wichita GIS. Please refer to Census Block Groups for 2010 and 2020 for verification of all data Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number. For example, blocks 3001, 3002, 3003… 3999 in census tract 1210.02 belong to Block Group 3. Due to boundary and feature changes that occur throughout the decade, current block groups do not always maintain these same block number to block group relationships. For example, block 3001 might move due to a change in the census tract boundary. Even if the block is no longer in block group 3, the block number (3001) will not change. However, the identification string (GEOID20) for that block, identifying block group 3, would remain the same in the attribute information in the TIGER/Line Shapefiles because block identification strings are always built using the decennial geographic codes.Block groups delineated for the 2020 Census generally contain between 600 and 3,000 people. Local participants delineated most block groups as part of the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated block groups only where a local or tribal government declined to participate or where the Census Bureau could not identify a potential local participant.A block group usually covers a contiguous area. Each census tract contains at least one block group and block groups are uniquely numbered within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.Block groups have a valid range of 0 through 9. Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore.

The territories of Pakistan and India are mostly covered by the non-political blocks AS42 through AS50, going roughly from West to East. Please see the attached map of these non-political boundary blocks.

The population density in Pakistan increased by 5.5 inhabitants per square kilometer (+1.77 percent) in 2022. With 316.13 inhabitants per square kilometer, the population density thereby reached its highest value in the observed period. Notably, the population density continuously increased over the last years.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 India and Sri Lanka.

In 2022, the population density in India remained nearly unchanged at around 479.43 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density is calculated by dividing the total population by the total land area, to show the average number of people living there per square kilometer of land.Find more key insights for the population density in countries like Sri Lanka and Pakistan.

The data shows for each state/union territory the area, population by gender and population by urban/rural.

Note: The area figures of States and U.T's do not add up to area of India because : (i) The shortfall of 7 square km. area of Madhya Pradesh and 3 square km. area of Chhattisgarh is yet to be resolved by the Survey of India. (ii) Disputed area of 13 square km. between Pondicherry and Andhra Pradesh is neither included in Pondicherry nor in Andhra Pradesh. For All India: 1) The population figures excludes population of the area under unlawful occupation of Pakistan and China where Census could not be taken. 2) Area figures includes the area under unlawful occupation of Pakistan and China. The area includes 78,114 sq.km. under illegal occupation of Pakistan, 5,180 sq. km.illegally handed over by Pakistan to China and 37,555 sq.km. under illegal occupation of China.

In 2022, Indonesia has the largest population of Muslims worldwide with around 241.5 million. This was followed with around 225.6 million Muslims in Pakistan and 211.16 million Muslims in India.

In 2022, 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

2.547 (People per square kilometer) in 2011. Notes: a. Includes estimated population of Paomata, Mao Maram and Purul sub-divisions of Senapati District of Manipur for 2001. b. For working out the density of India and Jammu & Kashmir the entire area and population of those portions of Jammu & Kashmir which are under illegal occupation of Pakistan and China have not been taken into account. c. India figures include estimated figures for those of the three sub-divisions viz. Mao Maram, Paomata and Purul of Senapati district of Manipur as population census 2001 in these three subdivisions were cancelled due to technical and administrative reasons although a population census was carried out in this sub-division as per schedule.

133.312 (number) in 2019. According to U.S. Office of Management and Budget (OMB), “Asian” refers to a person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. The Asian population includes people who indicated their race(s) as “Asian” or reported entries such as “Asian Indian,” “Chinese,” “Filipino,” “Korean,” “Japanes"".

94,253 (number) in 2019. According to U.S. Office of Management and Budget (OMB), “Asian” refers to a person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. The Asian population includes people who indicated their race(s) as “Asian” or reported entries such as “Asian Indian,” “Chinese,” “Filipino,” “Korean,” “Japanes"".

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File. Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:Population by RaceWhite – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American – A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.Some Other Race - this category is chosen by people who do not identify with any of the categories listed above. People can identify with more than one race. These people are included in the Two or More Races Hispanic or Latino PopulationThe Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

47.799 (number) in 2019. According to U.S. Office of Management and Budget (OMB), “Asian” refers to a person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. The Asian population includes people who indicated their race(s) as “Asian” or reported entries such as “Asian Indian,” “Chinese,” “Filipino,” “Korean,” “Japanes"".

71.504 (number) in 2019. According to U.S. Office of Management and Budget (OMB), “Asian” refers to a person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. The Asian population includes people who indicated their race(s) as “Asian” or reported entries such as “Asian Indian,” “Chinese,” “Filipino,” “Korean,” “Japanes"".

Chart and table of the Pakistan fertility rate from 1950 to 2025. United Nations projections are also included through the year 2100.

In 2022, roughly 43 percent of Bhutan's population resided in urban areas. Comparatively, approximately 19 percent of Sri Lanka's population lived in urban areas in 2022.

Urbanization in the APAC region

The Asia-Pacific region is currently experiencing a significant trend towards urbanization, with a growing number of individuals relocating from rural areas to urban centers in pursuit of improved economic prospects. From 2015 to 2020, there was an increase in the urban population throughout Asia. The projection for the region indicates a continuation of urbanization, although at a decelerated rate. As of 2021, a third of the entire population of India resided in urban areas. The data shows a notable upsurge in urbanization in India over the past ten years, indicating a shift of the populace from rural to urban centers in search of employment opportunities and livelihood.

 Population of megacities in APAC 

The APAC region is home to some of the world's most populous megacities. According to recent data, in 2023, the annual metropolitan population growth rate of China surpassed that of other megacities in the APAC region. In contrast to other cities, the three megacities in Japan, namely Tokyo, Osaka, and Nagoya, exhibited the lowest annual population growth rates. That same year, the APAC region was home to 28 megacities, more than ten of which were in China. India, Japan, and Pakistan also had more than once megacity each as of January 2023.

Abstract

The third wave of the Asian Barometer survey (ABS) conducted in 2010 and the database contains nine countries and regions in East Asia - the Philippines, Taiwan, Thailand, Mongolia, Singapore, Vietnam, Indonesia, Malaysia and South Korea. The ABS is an applied research program on public opinion on political values, democracy, and governance around the region. The regional network encompasses research teams from 13 East Asian political systems and 5 South Asian countries. Together, this regional survey network covers virtually all major political systems in the region, systems that have experienced different trajectories of regime evolution and are currently at different stages of political transition.

The mission and task of each national research team are to administer survey instruments to compile the required micro-level data under a common research framework and research methodology to ensure that the data is reliable and comparable on the issues of citizens' attitudes and values toward politics, power, reform, and democracy in Asia.

The Asian Barometer Survey is headquartered in Taipei and co-hosted by the Institute of Political Science, Academia Sinica and The Institute for the Advanced Studies of Humanities and Social Sciences, National Taiwan University.

Geographic coverage

13 East Asian political systems: Japan, Mongolia, South Koreas, Taiwan, Hong Kong, China, the Philippines, Thailand, Vietnam, Cambodia, Singapore, Indonesia, and Malaysia; 5 South Asian countries: India, Pakistan, Bangladesh, Sri Lanka, and Nepal

Analysis unit

-Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Compared with surveys carried out within a single nation, cross-nation survey involves an extra layer of difficulty and complexity in terms of survey management, research design, and database modeling for the purpose of data preservation and easy analysis. To facilitate the progress of the Asian Barometer Surveys, the survey methodology and database subproject is formed as an important protocol specifically aiming at overseeing and coordinating survey research designs, database modeling, and data release.

As a network of Global Barometer Surveys, Asian Barometer Survey requires all country teams to comply with the research protocols which Global Barometer network has developed, tested, and proved practical methods for conducting comparative survey research on public attitudes.

Research Protocols:

• National probability samples that give every citizen in each country an equal chance of being selected for interview. Whether using census household lists or a multistage area approach, the method for selecting sampling units is always randomized. The samples may be stratified, or weights applied, to ensure coverage of rural areas and minority populations in their correct proportions. As such, Asian Barometer samples represent the adult, voting-age population in each country surveyed.

A model Asian Barometer Survey has a sample size of 1,200 respondents, which allows a minimum confidence interval of plus or minus 3 percent at 95 percent probability.

Mode of data collection

Face-to-face [f2f]

Research instrument

A standard questionnaire instrument containing a core module of identical or functionally equivalent questions. Wherever possible, theoretical concepts are measured with multiple items in order to enable testing for construct validity. The wording of items is determined by balancing various criteria, including: the research themes emphasized in the survey, the comprehensibility of the item to lay respondents, and the proven effectiveness of the item when tested in previous surveys.

Survey Topics: 1.Economic Evaluations: What is the economic condition of the nation and your family: now, over the last five years, and in the next five years? 2.Trust in institutions: How trustworthy are public institutions, including government branches, the media, the military, and NGOs. 3.Social Capital: Membership in private and public groups, the frequency and degree of group participation, trust in others, and influence of guanxi. 4.Political Participatio: Voting in elections, national and local, country-specific voting patterns, and active participation in the political process as well as demonstrations and strikes. Contact with government and elected officials, political organizations, NGOs and media. 5.Electoral Mobilization: Personal connections with officials, candidates, and political parties; influence on voter choice. 6.Psychological Involvement and Partisanship: Interest in political news coverage, impact of government policies on daily life, and party allegiance. 7.Traditionalism: Importance of consensus and family, role of the elderly, face, and woman in theworkplace. 8.Democratic Legitimacy and Preference for Democracy: Democratic ranking of present and previous regime, and expected ranking in the next five years; satisfaction with how democracy works, suitability of democracy; comparisons between current and previous regimes, especially corruption; democracy and economic development, political competition, national unity, social problems, military government, and technocracy. 9.Efficacy, Citizen Empowerment, System Responsiveness: Accessibility of political system: does a political elite prevent access and reduce the ability of people to influence the government. 10.Democratic vs. Authoritarian Values: Level of education and political equality, government leadership and superiority, separation of executive and judiciary. 11.Cleavage: Ownership of state-owned enterprises, national authority over local decisions, cultural insulation, community and the individual. 12.Belief in Procedural Norms of Democracy: Respect of procedures by political leaders: compromise, tolerance of opposing and minority views. 13.Social-Economic Background Variables: Gender, age, marital status, education level, years of formal education, religion and religiosity, household, income, language and ethnicity. 14.Interview Record: Gender, age, class, and language of the interviewer, people present at the interview; did the respondent: refuse, display impatience, and cooperate; the language or dialect spoken in interview, and was an interpreter present.

Cleaning operations

Quality checks are enforced at every stage of data conversion to ensure that information from paper returns is edited, coded, and entered correctly for purposes of computer analysis. Machine readable data are generated by trained data entry operators and a minimum of 20 percent of the data is entered twice by independent teams for purposes of cross-checking. Data cleaning involves checks for illegal and logically inconsistent values.

Abstract

Aim: In the marine environment, where there are few physical boundaries to gene flow, there is often nevertheless intraspecific diversity with consequences for effective conservation and management. Here we compare two closely related dolphin species with a shared distribution in the Indian Ocean (IO) to better understand the biogeographic drivers of their population structure.

Location: Global oceans and seas with a focus on the Indian Ocean

Taxon: Tursiops sp. and Delphinus sp.

Methods: Bayesian, ordination, assignment, statistical and phylogenetic analyses to assess phylogeography, connectivity and population structure using microsatellite and mitochondrial DNA genetic markers.

Results: Both Tursiops sp. and Delphinus sp. showed population structure across the western IO and, in each case, populations in the Arabian Sea (off India, Pakistan and Oman) were most differentiated. Comparisons with other populations worldwide revealed independent lineages in this geographic region for both genera. For T. aduncus, (for which multiple sites within the IO could be compared), Bayesian modelling best supported a scenario of expansion southwards following a bottleneck event resulting in differentiation between the northern and western IO. For Delphinusthe same pattern is even more pronounced. Populations in the Arabian Sea region of the northwestern IO show genetic isolation for each of the two genera, consistent with other studies of cetacean species in this region.

Main Conclusions: We propose that changes in the intensity of the southwest monsoon during the climate cycles of the Pleistocene could have affected regional patterns of productivity and represent an important biogeographic driver promoting the observed patterns of differentiation and population dynamics seen in our focal species. Patterns of population genetic structure are consistent with phenotypic differences, suggesting an influence from distinct habitats and resources, and emphasising the need for effective conservation measures in this geographic region.