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.

Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

According to the 2011 census, the population density in the Indian state of Maharashtra was 365 individuals per square kilometer. Located on the Deccan Plateau, it is the second-most populous state in the country. A steady increase in the population of the state can be attributed to growing urban districts such as Mumbai and Pune, with diverse employment opportunities in several sectors.

India's economic powerhouse

With a contribution of over 22 trillion Indian rupees in the financial year 2017, the state of Maharashtra had the highest gross state domestic product in the country. A per capita income of over 175 thousand Indian rupees was estimated across the state for the preceding year. Based on its economic model, the state was a highly preferred destination for domestic and foreign investments.

The most populous Indian state

Mumbai, the capital city of Maharashtra, was the most populous city after Delhi. As the country's economic core, it serves as the financial and commercial capital while providing numerous job opportunities. Many are attracted to this dream city in search of a lucrative career and to make it big in the world-famous Bollywood film industry.

As of 2019, the south Indian state of Kerala had the highest density of doctors of about ** per ten thousand population in the country. However, Jharkhand had the least density of doctors in the country of about **** doctors per ten thousand people in the state.

Abstract

The National Sample Survey Organisation (NSSO) has been set up by the Government of India in 1950 to collect socio-economic data employing scientific sampling methods. The NSSO conducts regular consumer expenditure surveys as part of its "rounds", each round being normally of a year's duration and covering more than one subject of study. The surveys are conducted through household interviews, using a random sample of households covering practically the entire geographical area of the country. Surveys on consumer expenditure are being conducted quinquennially on a large sample of households from the 27th round (October 1972 - September 1973) onwards. The fourth quinquennial survey on household consumer expenditure was carried out during July 1987 - June 1988. The three previous surveys of this series were carries out in the 27th (October-September 1973) , the 32nd (July 1977 to June 1978) and the 38th (January to December , 1983) rounds of the NSSO. The present survey like the previous one, covered the entire population. Expenditure incurred by the sample household for the purpose of domestic consumption were collected for the 30 days preceding the date of survey. No account has, however, been taken of any expenditure incurred towards the productive enterprises of the household. It may be mentioned here that in order to get more households of the upper income bracket in the Sample , significant changes have been made in the sample design in this round (compared to the design of the 38th round). The survey covered the whole of Indian Union excepting: i) Ladakh and Kargil districts of Jammu & Kashmir ii) Rural areas of Nagaland

The field work for the survey was conducted, as usual, by the Field Operations Division of the Organisation. The collected data were processed by the Data Processing Division of NSSO and tabulated by the Computer Centre of Department of Statistics. The reports have been prepared by Survey Design & Research Division (SDRD) of NSSO under the guidance of the Governing Council, NSSO.

Geographic coverage

The survey covered the whole of Indian Union excepting: i) Ladakh and Kargil districts of Jammu & Kashmir ii) Rural areas of Nagaland

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey will have a two-stage stratified design. The first stage units (f.s.u.s) or villages in the rural sector and urban blocks in the urban sector. The second stage units are households in both the sectors.

Sampling frame for f.s.u.'s: The lists of 1981 census villages constitute the sampling frame for rural sector in most districts. But the 1981 census frame could not be used for a few districts because, either the 1981 census was not held there or the list of 1981 census villages could not be obtained or the lists obtained from the census authorities were found to be grossly incomplete. In such cases 1971 census frame have been used. In the urban sector , the Urban Frame Survey (U.F.S.) blocks constitute the sampling frame.

Stratification: States are first divided into agro-economic regions which are groups of contiguous districts, similar with respect to population density and crop pattern. In Gujarat, however, some districts have been split for the purpose of region formation In consideration of the location of dry areas and the distribution of the tribal population in the state.

RURAL SECTOR: In the rural sector, within each region, each district with 1981 Census rural population less 1.8 million forms a single stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils similar, as for as possible, in respect of rural population Density and crop pattern. (In Gujarat, however, in the case of districts extending over more than one region, even if the rural population was less than 1.8 million, the portion of a district falling in each region constituted a separate stratum. Further, in Assam the old "basic strata" formed on the basis of 1971 census rural population exactly in the above manner, but with cut-off population as 1.5 million have been retained as the strata for rural sampling).

URBAN SECTOR: In the urban sector, strata are formed, again within NSS region, on the basis of the population size class of towns. Each city with population 10 lakhs or more is self-representative, as in the earlier rounds. For the purpose of stratification, in towns with 1981 census population 4 lakhs or more , the blocks have been divided into two categories, viz. - One consisting of blocks in areas inhabited by the relatively affluent section of the population and the other consisting of the remaining blocks.

Allocation for first stage units: The total all-India sample size has been allocated to the states /U.T.'s proportionate to the strength of central field staff. This was allocated to the rural and urban sectors considering the relative size of the rural and urban population. Now the rural samples were allocated to the rural strata in proportion to rural population. The urban samples were allocated to the urban strata in proportion to urban population with double weight age given to those strata of towns with population 4 lakhs or more which lie in area inhabited by the relatively affluent section.

Selection of f.s.u.'s: The sample villages have been selected circular systematically with probability proportional to population in the form of two independent interpenetrating sub-samples (IPNS). The sample blocks have been selected circular systematically with equal probability, also in the form of two IPNS's.

Sample size (central sample): The all India sample in respect of the central sample consists of 8518 villages and 4648 blocks.

Sample size (state sample): All the states and Union Territories except Andaman & Nicobar Islands, Chandigarh, Dadra & Nagar Haveli and Lakshadweep are participating in this round at least on an equal matching basis.

Sampling deviation

There was no deviation from the original sampling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

The NSSO surveys on consumer expenditure aim to measure the household consumer expenditure in quantitative terms disaggregated by various household characteristics.

The data for this survey is collected in the NSS Schedule 1.0 used for household consumer expenditure. For this round, the schedule had 11 blocks.

Blocks 1 and 2 - are similar to the ones used in usual NSS rounds. These are used to record identification of sample households and particulars of field operations.

Block-3: Household characteristics like, household size, principal industry-occupation, social group, land possessed and cultivated, type of dwelling etc. are recorded in this block.

Block-4: In this block the detailed demographic particulars including age, sex, educational level, marital status, number of meals usually taken in a day etc. are recorded.

Block-5: In this block cash purchase and consumption of food, pan, tobacco, intoxicants and fuel & light during the last 30 days are recorded.

Block-6: Consumption of clothing during the last 30 and 365 days is recorded in this block.

Block-7: Consumption of footwear during the last 30 and 365 days is recorded in this block.

Block-8 : Expenditure on miscellaneous goods and services and rents and taxes during the last 30 days has been recorded in this block.

Block-9 : Expenditure for purchase and construction (including repairs) of durable goods for domestic use is recorded here.

Block-10 : Particulars of dwelling units are recorded in this block.

Block-11 : Summary of consumer expenditure during last 30 days is recorded in this block.

• The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
• China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
• The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
• Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
• In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
• This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

Content

• In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
• Rank: Rank by Population.
• CCA3: 3 Digit Country/Territories Code.
• Country/Territories: Name of the Country/Territories.
• Capital: Name of the Capital.
• Continent: Name of the Continent.
• 2022 Population: Population of the Country/Territories in the year 2022.
• 2020 Population: Population of the Country/Territories in the year 2020.
• 2015 Population: Population of the Country/Territories in the year 2015.
• 2010 Population: Population of the Country/Territories in the year 2010.
• 2000 Population: Population of the Country/Territories in the year 2000.
• 1990 Population: Population of the Country/Territories in the year 1990.
• 1980 Population: Population of the Country/Territories in the year 1980.
• 1970 Population: Population of the Country/Territories in the year 1970.
• Area (km²): Area size of the Country/Territories in square kilometers.
• Density (per km²): Population Density per square kilometer.
• Growth Rate: Population Growth Rate by Country/Territories.
• World Population Percentage: The population percentage by each Country/Territories.

Abstract

Through this schedule, it is aimed to collect information relating to availability of some general facilities to the villagers like education, Facilities for cultural activities and health and Facilities for disabled persons. If a facility is available in general to the villagers, it is considered as a facility. The required information has been obtained by contacting the village officials and / or other knowledgeable person(s). In case they were not aware of the existence of a particular facility, the nearest Block Development Officer or other related Agencies were contacted for collection of the relevant information.

Geographic coverage

Geographical coverage: The survey covered the whole of the Indian Union except (i) Leh and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Randomly selected villages based on sampling procedure

Universe

The survey covered randomly selected rural villages of the country

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified two stage sample design was adopted for the NSS 47th round. The first stage units were in most cases 1981 census villages in rural areas. In some areas where either the 1981 census was not undertaken or the available list was incomplete, the list of 1971 census villages were used.

Stratification: States are first divided into agroeconomic regions by grouping contiguous districts which are similar in respect of population density and crop pattern. In Gujarat, however, some districts have been split for the purpose of region formation in consideration of the allocation of dry areas and distribution of tribal population in the state. In the rural sector, within each region each district with the 1981 census rural population less than 1.8 million formed a separate stratum. Districts with largest population are divided in to two or more strata depending on population, by grouping contiguous tehsils similar, as far as possible, in respect of rural population density and crop pattern.In Gujarat, however, in case of districts extending over more than one region, even if the rural population was less than 1.8 million , the portion of a district falling in each region constituted a separate stratum.

Selection of FSUs: The sample villages have been selected circular systematically with probability proportional to population in the form of two independent sub-samples. The sample blocks have been selected circular systematically with equal probability also in the form of two independent subsamples. The number of sample villages surveyed in this round were 4373, and the sample size for the Village Facilities Survey was 4298.

More information on sample design for this survey round is available in Section Two of the Report 391 NSS47 Round.pdf available under external resources.

Mode of data collection

Face-to-face [f2f]

Research instrument

Schedule 3.1 consists of the following blocks:

Block 1: identification of sample village Block 2: particulars of field operation Block 3: distance from nearest facility Block 4: remarks by investigator Block 5: comments by supervisory officer(s)

Blocks 3 is the main block of this schedule and is meant for recording the information relating to distance of specified facilities from the centre of the sample village. Blocks 1is meant for recording the identification particulars of the sample village. Block 2, 5 and 6 are used for official purposes to record the particulars relating to field operations, Remarks of the investigators and those of the supervisory officer(s) respectively.

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.

According to the latest Indian census in 2011, every square kilometer in the southern state of Karnataka was inhabited by 319 people, up from 101 in 1951. The highest population density in the state was in Bangalore.

As of 2019, the capital Indian territory of Delhi had the highest density of nurses and midwives of about ** per ten thousand people in the country. However, Bihar had the least density of nurses and midwives in the country of about *** per ten thousand people in the state.

Abstract

A nationwide survey on "Particulars of Slums" was carried-out by the National Sample Survey Organisation (NSSO) during the period January-June, 1993 in its 49th round to ascertain the extent of civic facilities available in the slums. The 49th round survey among other objectives also collected data on the condition of slum dwellings as well as on some general particulars of slum areas. Apart from formulating the sampling design with an emphasis to obtain an adequate number of slum households for the survey on housing condition and migration, surveyed the slum areas and collected information on slums. The schedule 0.21 was canvassed in both the rural and urban areas. All the slums, both the declared ones as well as the others (undeclared), found in the selected first stage units were surveyed even if hamlet-group/sub-block selection was resorted to in some of then. To ascertain the extent of civic facilities available in the slums as well as the information regarding the improvement of slum condition during a period of last five years was also collected. Information was collected by contacting one or more knowledgeable persons in the FSU on the basis of predominant criterion in both declared and undeclared slums, and not through household approach.

Geographic coverage

The geographical coverage of the survey was the whole of the Indian Union except Ladakh & Kargil districts of Jammu & Kashmir, 768 interior villages of Nagaland and 172 villages in Andaman & Nicobar islands which remain inaccessible throughout the year. However, certain districts of Jammu & Kashmir viz. Doda, Anantanag, Pulwama, Srinagar, Badgam, Barmula & Kupwara, as well as Amritsar district in Punjab, had to be excluded from the survey coverage due to unfavourable field conditions.

Sampling procedure

Sample Design : The first stage units in the rural sector and urban sector were census villages and urban frame survey (UFS) blocks respectively. However for newly declared towns of the 1991 census,for which UFS frames were not available, census EBs were used as first stage units.

Sampling frame for fsu's : In the rural sector, the sampling frame in most of the districts was the 1981 census list of villages. However, in Assam and in 8 districts of Madhya Pradesh, 1971 Census lists of villages were used. For Nagaland, the villages situated within 5 kms of a bus route constituted the sampling frame. For the Andaman & Nicobar islands the list of accessible villages was used as sampling frame. In the urban sector, the lists of NSS urban frame survey (UFS) blocks were the sampling frames used in most cases. However, 1991 Census house - listing enumeration blocks were considered as the sampling units for some of the newly declared towns of the 1991 population census, for which UFS frames were not available.

Stratification : Each state/u.t. was divided into one or more agro-economic regions by grouping contiguous districts which are similar with respect to population density and crop pattern. In Gujarat, however, some districts were subdivided for the purpose of region formation on the basis of location of dry areas and the distribution of tribal population in the state. The total number of regions formed in the whole of India was 78.

In the rural sector, within each region, each district with a rural population of less than 1.8 million according to the 1981 Census formed a single basic stratum. Districts with larger population were divided into two or more strata, depending on population, by grouping contiguous tehsils, similar as far as possible in respect of rural population density & crop pattern. In Gujarat, however, in the case of districts extending over more than one region, the portion of a district falling in each region constituted a separate stratum even if the rural population of the district as a whole was less than 1.8 million. Further, in Assam, the strata formed for the earlier NSS round on the basis of 1971 Census rural population exactly in the above manner, but with a cutoff point of 1.5 million population, were retained as the strata for rural sampling.

In the urban sector, strata were formed, within NSS regions, on the basis of 1981 (1991 in some of the new towns) Census population. Each city with a population of 10 lakhs or more formed a separate stratum itself. The remaining towns of each region were grouped to form three different strata on the basis of 1981 (1991 in a few cases) census population.

Sub stratification of urban strata : In order to be able to allocate a large proportion of the first stage sample to slum-dominated areas than would otherwise be possible, each stratum in the urban sector was divided into two "sub-strata" a s follows. Sub-stratum 1 was constituted of the UFS blocks in the stratum with a "slum area" indicated in the frame. Substratum 2 was constituted of the remaining blocks of the stratum.

Allocation of sample : A total all-India sample of 8000 first stage units (5072 villages and 2928 urban blocks) determined on the basis of investigator strength in different state/u.t's and the expected workload per investigator was first allocated to the states/u.t's in proportion to Central Staff available. The sample thus obtained for each state/u.t. was then allocated to its rural & urban sectors considering the relative sizes of the rural & urban population with double weightage for the urban sector. Within each sector of a state/u.t., the allotted sample size was reallocated to the different strata in proportion to stratum population. Stratum-level allocations were adjusted so that the sample size for a stratum (rural or urban) was at least a multiple of 4. This was done in order to have equal sized samples in each sub-sample and sub-round.

In the urban sector, stratum-level allocations were further allocated to the two sub-strata in proportion to the number of UFS blocks in the sub-strata, with double weightage to sub-stratum 1, with a minimum sample size of 4 blocks to sub-stratum 1 (2 if stratum allocation was only 4). Sub-stratum level allocations were made even in number.

Selection of fsu's : Sample villages except in Arunachal Pradesh were selected by pps systematic sampling with population as the size variable and sample blocks by simple random sampling without replacement. In both sectors the sample of fsu's was drawn in the form of two independent sub-samples. (In Arunachal Pradesh the sample of villages was drawn by a cluster sampling procedure. The field staff were supplied with a list of sample "nucleus" villages and were advised to select cluster of villages building up each cluster around a nucleus village according to prescribed guidelines. The nucleus villages were selected circular-systematically with equal probability in the form of two ) independent sub-samples.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire consisted of 6 blocks (including 0) as given below : Block - 0 : descriptive identification of sample village/block having slum Block - 1 : identification of sample village/block having slum. Block - 3 : Remarks by investigator. Block - 4 : Comments by Supervisory Officer(s). Block - 5 : Particulars about slum.

Response rate

1572 slums spread over 5072 villages and 2928 urban blocks in the sample have been surveyed.

Abstract

The 52nd round of the National Sample Survey was carried out by the National Sample Survey Office from July 1995 to June 2006 and included the following topics: consumer expenditure and labor participation, utilisation of maternity and child health care services, morbidity and utilisation of medical services, problems of aged persons, and participation in education.

Schedule 25.2 - Participation in Education - is documented here.

Details on educational services received by the household were collected from each sampled household. General demographic information such as age, sex, educational level attained, current enrolment status, etc., were collected from all the household members. But the target group of the schedule was household members age 5-24 years. The questions directed to those who were currently studying included details of the course, level and year of study, type of management of educational institution they were attending, whether the institution was recognised or not, the facilities utilised by them in terms of scholarship, free studentship, etc., and details of private expenditure on education incurred by them. Those currently not attending any educational institution were asked whether they were ever enrolled or not, whether they had completed their education or discontinued midcourse and what were the reasons for dropping out or for non-enrolment.

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir (for central sample), (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

• household members 5-24 years old, irrespective of whether they are currently attending any educational institution or not.

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified two-stage design was adopted in this round. The first-stage units were the census villages for the rural areas (panchayat wards in case of Kerala) and the NSSO Urban Frame Survey(UFS) blocks for the urban areas. The second stage units were the households in both the cases.

Sampling Frame for First-Stage Units (FSUs):

The list of census villages of the 1991 census (1981 census list for Jammu & Kashmir) constituted the sampling frame for the rural areas. For Kerala, however, the list of panchayat wards was used as the sampling frame for the selection of first stage units in the rural areas. For Nagaland, the villages located within 5 km of a bus route constituted the sampling frame, whereas for Andaman & Nicobar Islands, the list of 'accessible' villages formed the sampling frame. For the urban areas, the list of NSSO Urban Frame Survey(UFS) blocks has been used as the sampling frame.

Stratification:

For the socio-economic surveys of the NSSO, each state or union territory (u.t.) is divided into one or more agro-climatic regions by grouping contiguous districts which are similar with respect to population density and crop pattern. In Gujarat, however, some districts are subdivided for the purpose of region formation on the basis of location of dry areas and the distribution of tribal population in the state. In all, there are 78 regions covering the entire geographical area of the country.

Allocation of First Stage Units (FSUs):

A sample of 13,000 FSUs (rural & urban combined) was selected as the 'central sample' at the all-India level. The sample size of FSUs (rural & urban combined) for the central sample for a state/u.t. was allocated to its rural and urban areas considering the relative sizes of the rural and urban population with double weightage to the urban areas. The state level rural sample size was allocated to the rural strata in proportion to their rural population figures as per the census. Similarly, urban sample size of the state/u.t. was allocated to the urban strata in proportion to urban population figures as per the census. All the stratum-level allocations were adjusted to multiples of 8 as far as possible (otherwise to multiples of 4) in order to allocate them equally in each sub-sample x sub-round combination (2 sub-samples x 4 sub-rounds).

Selection of First-Stage Units:

The sample FSUs in the rural areas were selected circular systematically with equal probability. In the Union Territory of Daman & Diu, the district Diu consists of only two villages. These two were selected for the survey in both the central and the state sample. Sample blocks in the urban areas were also selected circular systematically with equal probability. Sample FSUs of both the rural and urban areas were selected in the form of two independent sub-samples. The only departure from the general procedure of selection of FSUs was made for the rural areas of Arunachal Pradesh for which the procedure of cluster sampling was followed. The nucleus villages were selected circular systematically with equal probability, in the form of two independent sub-samples. A cluster, generally of 4 to 6 villages, was formed around each nucleus village.

Selection of Hamlet-Groups/ Sub-Blocks (for 'large' FSUs only):

A large FSU was divided into a suitable number of hamlet-groups/ sub-blocks having equal population content. Two hamlet-groups were selected from each large FSU in the rural areas and only one sub-block was selected from each large FSU of the urban areas.

Selection of Households (Second-Stage Units):

In each of the selected FSUs, three different enquiries, "Survey on Health Care", "Survey on Participation in Education" and "Survey on Consumer Expenditure", were conducted on three independent samples of the households. For the present enquiry, i.e. survey on education, a sample of 6 households was selected for the detailed enquiry. However, before selection, the listed households were first grouped into two second-stage strata.

Mode of data collection

Face-to-face [f2f]

BackgroundThe global prevalence of crimes against women has made it an enduring public health challenge that has persisted over time. The achievement of the 2030 Sustainable Development Goal (SDG) is intricately tied to the actions taken to prevent these crimes as their repercussions directly affect progress across various SDGs. This study aimed to provide a comprehensive examination of the prevalence of crimes against women across districts and states in India, analyzing changes from 2020 to 2022, and subsequently identifying associated factors.MethodsThe study is an ecological analysis conducted across all districts of India using the data on crimes against women for the period 2020 and 2022 obtained from the National Crime Records Bureau (NCRB) of India. A small area estimation method was used to obtain district-level relative risks of crime against women for both periods. Hotspot analysis was carried out to identify the current hotspots and coldspots. Further spatial regression was used to identify the factors associated with crimes against women in the year 2022.ResultsThe results indicated a rise in the reported crime against women cases between 2020 and 2022. The rate of crimes against women at the national level was found to be 57 in the year 2020, whereas, in 2022, it increased to 67. The highest crime rate in the year 2022 was found to be 145 in Delhi, while Nagaland had the lowest crime rate of 5. The relative risk of crime against women varied from 0.046 to 4.68 in 2020, while in 2022, it spanned from 0.02 to 6.10. Significant hotspots were found in parts of Rajasthan, Madhya Pradesh, Haryana, Telangana, and Odisha. The results of the spatial error regression model showed that the sex ratio and the population density of the district have significant associations with the occurrence of crimes against women.ConclusionThe rise in the incidence of crime against women emphasizes the importance of tackling the spatial inequality in relative risk across Indian districts. By thoughtfully addressing this variation and conducting targeted studies in high-risk areas, we can enhance our understanding of the obstacles to implementing effective measures against violence targeting women.

Replication Data for: "Geographic and socio-economic barriers to rural electrification: New evidence from Indian villages". Citation for the article is the following: Dugoua, Eugenie and Liu, Ruinan and Urpelainen, Johannes, Geographic and Socio-Economic Barriers to Rural Electrification: New Evidence from Indian Villages (March 22, 2017). Energy Policy, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2939880 Abstract: The International Energy Agency estimates that more than a billion people remain without household electricity access. However, countries such as India have recently made major progress in rural electrification. Who has benefited from these achievements? We focus on 714 villages in six energy-poor states of northern and eastern India to investigate trends in electricity access. We use data both from the 2011 Census of India and an original energy access survey conducted in 2014 and 2015. During the three years that separated the surveys, distance to the nearest town and land area lose their power as predictors of the percentage of households in the village that has access to electricity. In this regard, the Indian government's flagship rural electrification program seems to have managed to overcome a major obstacle to grid extension. On the other hand, socio-economic inequalities between villages related to caste status and household expenditure remain strong predictors. These findings highlight the importance of socio-economic barriers to rural electricity access and alleviate concerns about remoteness and population density as obstacles to grid extension. To access the full ACCESS dataset: http://dx.doi.org/10.7910/DVN/0NV9LF. If you want to use the full ACCESS dataset, please, cite both of the following: Aklin, Michaël; Cheng, Chao-yo; Ganesan, Karthik; Jain, Abhishek; Urpelainen, Johannes; Council on Energy, Environment and Water. Access to Clean Cooking Energy and Electricity: Survey of States in India (ACCESS). 2016. Harvard Dataverse, V1. http://dx.doi.org/10.7910/DVN/0NV9LF. Aklin, Michaël, Chao-yo Cheng, Johannes Urpelainen, Karthik Ganesan, and Abhishek Jain. 2016. "Factors Affecting Household Satisfaction with Electricity Supply in Rural India." Nature Energy 1(16170). DOI: 10.1038/nenergy.2016.170. (http://www.nature.com/articles/nenergy2016170)

The southern state of Tamil Nadu in India recorded a population density of 555 people for every square kilometer according to the country's latest census in 2011. This was a significant increase compared to a decade earlier where the figure stood at 480.

Delhi was the largest city in terms of number of inhabitants in India in 2023.The capital city was estimated to house nearly 33 million people, with Mumbai ranking second that year. India's population estimate was 1.4 billion, ahead of China that same year.

This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Niger, the Democratic Republic of Congo, and Chad, the population increase peaks at over three percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. However, African cities are currently growing at larger rates. Indeed, most of the fastest-growing cities in the world are located in Sub-Saharan Africa. Gwagwalada, in Nigeria, and Kabinda, in the Democratic Republic of the Congo, ranked first worldwide. By 2035, instead, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria.

The growth in India's overall population is driven by its young population. Nearly ** percent of the country's population was between the ages of 15 and 64 years old in 2020. With over *** million people between 18 and 35 years old, India had the largest number of millennials and Gen Zs globally.

In 1800, the population of the region of present-day India was approximately 169 million. The population would grow gradually throughout the 19th century, rising to over 240 million by 1900. Population growth would begin to increase in the 1920s, as a result of falling mortality rates, due to improvements in health, sanitation and infrastructure. However, the population of India would see it’s largest rate of growth in the years following the country’s independence from the British Empire in 1948, where the population would rise from 358 million to over one billion by the turn of the century, making India the second country to pass the billion person milestone. While the rate of growth has slowed somewhat as India begins a demographics shift, the country’s population has continued to grow dramatically throughout the 21st century, and in 2020, India is estimated to have a population of just under 1.4 billion, well over a billion more people than one century previously. Today, approximately 18% of the Earth’s population lives in India, and it is estimated that India will overtake China to become the most populous country in the world within the next five years.