In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.
The statistic displays the main states and union territories with the highest number of people living in urban areas in India in 2011. In that year, the state of Maharashtra had the highest population with over 50 million people living in urban areas. The population density in India from 2004 to 2014 can be seen here.
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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.
The statistic shows the Hindu population in India in 2011, by state and union territory. The region with the highest Hindu population was Uttar Pradesh, followed by the state of Maharashtra, with close to 90 million Hindus. The region with the least Hindu population was Lakshadweep in that year. The countries with the largest number of Hindus in 2010 can be found here.
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
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India Census: Population: by Religion: Muslim: Urban data was reported at 68,740,419.000 Person in 2011. This records an increase from the previous number of 49,393,496.000 Person for 2001. India Census: Population: by Religion: Muslim: Urban data is updated yearly, averaging 59,066,957.500 Person from Mar 2001 (Median) to 2011, with 2 observations. The data reached an all-time high of 68,740,419.000 Person in 2011 and a record low of 49,393,496.000 Person in 2001. India Census: Population: by Religion: Muslim: Urban data remains active status in CEIC and is reported by Census of India. The data is categorized under India Premium Database’s Demographic – Table IN.GAE001: Census: Population: by Religion.
The statistic gives the share of aging population in India across selected states and union territories in India in 2011. The regions with the highest share of elderly people were in the state of Kerala, with some 12.6 percent of the population living there were 60 years or older, followed by the state of Goa with 11.2 percent. The share of aging population in the whole country that year was 8.6 percent.
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Chart and table of India population from 1950 to 2025. United Nations projections are also included through the year 2100.
According to the latest census data, Lakshadweep, the island union territory had the highest share of Muslim population in the country, where 97 percent of its population identified as followers of the Islamic faith. Jammu & Kashmir ranked second at 68 percent during the same time period. 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.
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Census: Population: Punjab data was reported at 27,743,338.000 Person in 03-01-2011. This records an increase from the previous number of 24,358,999.000 Person for 03-01-2001. Census: Population: Punjab data is updated decadal, averaging 10,367,652.500 Person from Mar 1901 (Median) to 03-01-2011, with 12 observations. The data reached an all-time high of 27,743,338.000 Person in 03-01-2011 and a record low of 6,731,510.000 Person in 03-01-1911. Census: Population: Punjab data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAB002: Census: Population: by States.
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Census: Population: Sikkim data was reported at 610,577.000 Person in 03-01-2011. This records an increase from the previous number of 540,851.000 Person for 03-01-2001. Census: Population: Sikkim data is updated decadal, averaging 149,957.000 Person from Mar 1901 (Median) to 03-01-2011, with 12 observations. The data reached an all-time high of 610,577.000 Person in 03-01-2011 and a record low of 59,014.000 Person in 03-01-1901. Census: Population: Sikkim data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAB002: Census: Population: by States.
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Census: Population: Karnataka data was reported at 61,095,297.000 Person in 03-01-2011. This records an increase from the previous number of 52,850,562.000 Person for 03-01-2001. Census: Population: Karnataka data is updated decadal, averaging 21,494,364.000 Person from Mar 1901 (Median) to 03-01-2011, with 12 observations. The data reached an all-time high of 61,095,297.000 Person in 03-01-2011 and a record low of 13,054,754.000 Person in 03-01-1901. Census: Population: Karnataka data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAB002: Census: Population: by States.
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Vital Statistics: Natural Growth Rate: per 1000 Population: Andhra Pradesh data was reported at 9.300 NA in 2020. This records a decrease from the previous number of 9.500 NA for 2019. Vital Statistics: Natural Growth Rate: per 1000 Population: Andhra Pradesh data is updated yearly, averaging 10.600 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 13.600 NA in 1998 and a record low of 8.900 NA in 2017. Vital Statistics: Natural Growth Rate: per 1000 Population: Andhra Pradesh data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH004: Vital Statistics: Natural Growth Rate: by States.
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Vital Statistics: Natural Growth Rate: per 1000 Population: Tripura data was reported at 6.900 NA in 2020. This records a decrease from the previous number of 7.400 NA for 2019. Vital Statistics: Natural Growth Rate: per 1000 Population: Tripura data is updated yearly, averaging 9.500 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 11.600 NA in 1998 and a record low of 6.900 NA in 2020. Vital Statistics: Natural Growth Rate: per 1000 Population: Tripura data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH004: Vital Statistics: Natural Growth Rate: by States.
In 2021, Kerala reflected the highest share of its population belonging to the elderly age group with 16.5 percent as opposed to only 10.5 percent in 2001. This was an increase in six percent in two decades.
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India Population: Andaman & Nicobar Islands data was reported at 0.431 Person mn in 2017. This records an increase from the previous number of 0.422 Person mn for 2016. India Population: Andaman & Nicobar Islands data is updated yearly, averaging 0.407 Person mn from Mar 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 0.489 Person mn in 2011 and a record low of 0.349 Person mn in 2000. India Population: Andaman & Nicobar Islands data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.GEI006: Memo Items: State Economy: Population.
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Vital Statistics: Natural Growth Rate: per 1000 Population: Bihar: Urban data was reported at 15.700 NA in 2020. This records a decrease from the previous number of 16.000 NA for 2019. Vital Statistics: Natural Growth Rate: per 1000 Population: Bihar: Urban data is updated yearly, averaging 16.500 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 18.500 NA in 2000 and a record low of 14.700 NA in 2014. Vital Statistics: Natural Growth Rate: per 1000 Population: Bihar: Urban data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH004: Vital Statistics: Natural Growth Rate: by States.
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Census: Number of Migrants: Punjab data was reported at 13,735,616.000 Person in 03-01-2011. This records an increase from the previous number of 9,189,438.000 Person for 03-01-2001. Census: Number of Migrants: Punjab data is updated decadal, averaging 9,189,438.000 Person from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 13,735,616.000 Person in 03-01-2011 and a record low of 6,960,431.000 Person in 03-01-1991. Census: Number of Migrants: Punjab data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAG001: Census of India: Migration: Number of Migrants: by States.
The National Family Health Surveys (NFHS) programme, initiated in the early 1990s, has emerged as a nationally important source of data on population, health, and nutrition for India and its states. The 2005-06 National Family Health Survey (NFHS-3), the third in the series of these national surveys, was preceded by NFHS-1 in 1992-93 and NFHS-2 in 1998-99. Like NFHS-1 and NFHS-2, NFHS-3 was designed to provide estimates of important indicators on family welfare, maternal and child health, and nutrition. In addition, NFHS-3 provides information on several new and emerging issues, including family life education, safe injections, perinatal mortality, adolescent reproductive health, high-risk sexual behaviour, tuberculosis, and malaria. Further, unlike the earlier surveys in which only ever-married women age 15-49 were eligible for individual interviews, NFHS-3 interviewed all women age 15-49 and all men age 15-54. Information on nutritional status, including the prevalence of anaemia, is provided in NFHS3 for women age 15-49, men age 15-54, and young children.
A special feature of NFHS-3 is the inclusion of testing of the adult population for HIV. NFHS-3 is the first nationwide community-based survey in India to provide an estimate of HIV prevalence in the general population. Specifically, NFHS-3 provides estimates of HIV prevalence among women age 15-49 and men age 15-54 for all of India, and separately for Uttar Pradesh and for Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu, five out of the six states classified by the National AIDS Control Organization (NACO) as high HIV prevalence states. No estimate of HIV prevalence is being provided for Nagaland, the sixth high HIV prevalence state, due to strong local opposition to the collection of blood samples.
NFHS-3 covered all 29 states in India, which comprise more than 99 percent of India's population. NFHS-3 is designed to provide estimates of key indicators for India as a whole and, with the exception of HIV prevalence, for all 29 states by urban-rural residence. Additionally, NFHS-3 provides estimates for the slum and non-slum populations of eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur. NFHS-3 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOHFW), Government of India, and is the result of the collaborative efforts of a large number of organizations. The International Institute for Population Sciences (IIPS), Mumbai, was designated by MOHFW as the nodal agency for the project. Funding for NFHS-3 was provided by the United States Agency for International Development (USAID), DFID, the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and MOHFW. Macro International, USA, provided technical assistance at all stages of the NFHS-3 project. NACO and the National AIDS Research Institute (NARI) provided technical assistance for the HIV component of NFHS-3. Eighteen Research Organizations, including six Population Research Centres, shouldered the responsibility of conducting the survey in the different states of India and producing electronic data files.
The survey used a uniform sample design, questionnaires (translated into 18 Indian languages), field procedures, and procedures for biomarker measurements throughout the country to facilitate comparability across the states and to ensure the highest possible data quality. The contents of the questionnaires were decided through an extensive collaborative process in early 2005. Based on provisional data, two national-level fact sheets and 29 state fact sheets that provide estimates of more than 50 key indicators of population, health, family welfare, and nutrition have already been released. The basic objective of releasing fact sheets within a very short period after the completion of data collection was to provide immediate feedback to planners and programme managers on key process indicators.
The population covered by the 2005 DHS is defined as the universe of all ever-married women age 15-49, NFHS-3 included never married women age 15-49 and both ever-married and never married men age 15-54 as eligible respondents.
Sample survey data
SAMPLE SIZE
Since a large number of the key indicators to be estimated from NFHS-3 refer to ever-married women in the reproductive ages of 15-49, the target sample size for each state in NFHS-3 was estimated in terms of the number of ever-married women in the reproductive ages to be interviewed.
The initial target sample size was 4,000 completed interviews with ever-married women in states with a 2001 population of more than 30 million, 3,000 completed interviews with ever-married women in states with a 2001 population between 5 and 30 million, and 1,500 completed interviews with ever-married women in states with a population of less than 5 million. In addition, because of sample-size adjustments required to meet the need for HIV prevalence estimates for the high HIV prevalence states and Uttar Pradesh and for slum and non-slum estimates in eight selected cities, the sample size in some states was higher than that fixed by the above criteria. The target sample was increased for Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland, Tamil Nadu, and Uttar Pradesh to permit the calculation of reliable HIV prevalence estimates for each of these states. The sample size in Andhra Pradesh, Delhi, Maharashtra, Tamil Nadu, Madhya Pradesh, and West Bengal was increased to allow separate estimates for slum and non-slum populations in the cities of Chennai, Delhi, Hyderabad, Indore, Kolkata, Mumbai, Meerut, and Nagpur.
The target sample size for HIV tests was estimated on the basis of the assumed HIV prevalence rate, the design effect of the sample, and the acceptable level of precision. With an assumed level of HIV prevalence of 1.25 percent and a 15 percent relative standard error, the estimated sample size was 6,400 HIV tests each for men and women in each of the high HIV prevalence states. At the national level, the assumed level of HIV prevalence of less than 1 percent (0.92 percent) and less than a 5 percent relative standard error yielded a target of 125,000 HIV tests at the national level.
Blood was collected for HIV testing from all consenting ever-married and never married women age 15-49 and men age 15-54 in all sample households in Andhra Pradesh, Karnataka, Maharashtra, Manipur, Tamil Nadu, and Uttar Pradesh. All women age 15-49 and men age 15-54 in the sample households were eligible for interviewing in all of these states plus Nagaland. In the remaining 22 states, all ever-married and never married women age 15-49 in sample households were eligible to be interviewed. In those 22 states, men age 15-54 were eligible to be interviewed in only a subsample of households. HIV tests for women and men were carried out in only a subsample of the households that were selected for men's interviews in those 22 states. The reason for this sample design is that the required number of HIV tests is determined by the need to calculate HIV prevalence at the national level and for some states, whereas the number of individual interviews is determined by the need to provide state level estimates for attitudinal and behavioural indicators in every state. For statistical reasons, it is not possible to estimate HIV prevalence in every state from NFHS-3 as the number of tests required for estimating HIV prevalence reliably in low HIV prevalence states would have been very large.
SAMPLE DESIGN
The urban and rural samples within each state were drawn separately and, to the extent possible, unless oversampling was required to permit separate estimates for urban slum and non-slum areas, the sample within each state was allocated proportionally to the size of the state's urban and rural populations. A uniform sample design was adopted in all states. In each state, the rural sample was selected in two stages, with the selection of Primary Sampling Units (PSUs), which are villages, with probability proportional to population size (PPS) at the first stage, followed by the random selection of households within each PSU in the second stage. In urban areas, a three-stage procedure was followed. In the first stage, wards were selected with PPS sampling. In the next stage, one census enumeration block (CEB) was randomly selected from each sample ward. In the final stage, households were randomly selected within each selected CEB.
SAMPLE SELECTION IN RURAL AREAS
In rural areas, the 2001 Census list of villages served as the sampling frame. The list was stratified by a number of variables. The first level of stratification was geographic, with districts being subdivided into contiguous regions. Within each of these regions, villages were further stratified using selected variables from the following list: village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. In addition to these variables, an external estimate of HIV prevalence, i.e., 'High', 'Medium' or 'Low', as estimated for all the districts in high HIV prevalence states, was used for stratification in high HIV prevalence states. Female literacy was used for implicit stratification (i.e., villages were
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Vital Statistics: Death Rate: per 1000 Population: Puducherry: Urban data was reported at 6.100 NA in 2020. This records a decrease from the previous number of 6.500 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: Puducherry: Urban data is updated yearly, averaging 6.700 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 8.200 NA in 2004 and a record low of 5.400 NA in 2003. Vital Statistics: Death Rate: per 1000 Population: Puducherry: Urban data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.
In 2022, the union territory of Delhi had the highest urban population density of over 18 thousand persons per square kilometer. While the rural population density was highest in union territory of Puducherry, followed by the state of Bihar.