Population: Maharashtra data was reported at 127.928 Person mn in 2025. This records an increase from the previous number of 126.954 Person mn for 2024. Population: Maharashtra data is updated yearly, averaging 109.697 Person mn from Mar 1994 (Median) to 2025, with 32 observations. The data reached an all-time high of 127.928 Person mn in 2025 and a record low of 83.531 Person mn in 1994. Population: Maharashtra data remains active status in CEIC and is reported by Ministry of Statistics and Programme Implementation. The data is categorized under Global Database’s India – Table IN.GBG001: Population. [COVID-19-IMPACT]

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

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.

The overall population of pet dogs in India was over 33 million in 2023. The population is likely to reach more than 51 million by 2028. The growth in the number of pet dogs has led to an increase in pet food sales across the country.

Abstract

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.

Geographic coverage

• National (29 states )
• Regional (for HIV Prevalence : Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu)
• Local (population and health indicators for slum and non-slum populations for eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur)

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Universe

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.

Kind of data

Sample survey data

Sampling procedure

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

The number of workers across the Indian state of Maharashtra during financial year 2023 was over 1.7 million workers. This was an increase from the previous year. The south Asian country of India had over 14 million workers in financial year 2023.

Abstract

Millions of farmers in India have made significant contributions in providing food and nutrition to the entire nation, while also providing livelihoods to millions of people in the country. During the past five decades of planned economic development, India has moved from food-shortage and imports to self-sufficiency and exports. Food security and well being of the farmer appears to be major areas of concern of the planners and policy makers of Indian agriculture. In order to have a comprehensive picture of the farming community at the commencement of the third millennium, and to analyze the impact of the transformation induced by public policy, investments and technological change on the farmers' access to resources and income, as well as well-being; the Ministry of Agriculture decided to collect information on Indian farmers through a Situation Assessment Survey (SAS) and entrusted the job of conducting the survey to the National Sample Survey Organisation (NSSO).

The SAS 2003 is the first of its kind to be conducted by NSSO. Though information on a majority of items to be collected through SAS have been collected in some round or other of NSS, an integrated schedule - Schedule 33, covering some basic characteristics of farming households and their access to basic and modern farming resources was canvassed for the first time in SAS. Moreover, information on consumption of various goods and services in an abridged form were also collected to have an idea about the pattern of consumption expenditure of the farming households.

Schedule 33 was designed for collecting information on aspects relating to farming and other socio-economic characteristics of farming households. The information was collected in two visits to the same set of sample households. The first visit was made during January to August 2003 and the second, during September to December 2003. The survey was conducted in rural areas only. It was canvassed in the Central Sample except for the States of Maharashtra and Meghalaya where it was canvassed in both State and Central samples.

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified multi-stage sampling design was adopted for the SAS 2003, 59th round. The First Stage Unit (FSU), also known as the primary sampling unit, was the census village in the rural sector and UFS block in the urban sector. The Ultimate Stage Units (USUs) were households in both sectors. Hamlet-group / sub-block constitute the intermediate stage, if these are formed in the selected area.

The list of villages (panchayat wards for Kerala) based on the Population Census of 1991 constituted the sampling frame for FSUs in rural areas, while the latest UFS frame was the sampling frame used for urban areas. For stratification of towns by size class, provisional population of towns as per Census 2001 was used. A detailed description of the sampling strrategy can be found in the estimation procedure document attached in the documentation/external resource.

Mode of data collection

Face-to-face paper [f2f]

The estimated per capita income across the western state of Maharashtra in India stood at around 278 thousand Indian rupees in the financial year 2024. There was a significant increase in the income per capita in the state since the financial year 2012. Sikkim recorded the highest per capita income in the country.

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.

There were over 37 million registered vehicles across the Indian state of Maharashtra at the end of fiscal year 2020. The south Asian country's transport sector accounted for a 4.59 percent share of the GVA with road transport accounting for over three percent of it. The GVA from railways was about 0.74 percent and air transport accounted for about 0.12 percent during the same time period.

In 2011, approximately 9.74 million out of 26.8 million of people with disability in India were reportedly employed. Indian disabled workers were mostly found in Uttar Pradesh and Maharashtra, with respectively 1.4 million and 1.2 million people. In comparison, there were only more than 300 disabled workers in Lakshadweep from a total of over 1.6 thousand of disabled people in this region.

In the fiscal year of 2024, around *** million people across India were covered under health insurance schemes. Of these, the highest number of people were insured under ******************** health insurance schemes, while********************* plans had the lowest number of people. Key figures of public health insurance The gross direct premium income of the Indian health insurance industry was about *** billion Indian rupees in financial year 2021. Public health insurance recorded the highest premium income of over *** billion Indian rupees that year, with the highest share of premiums written in the western state of Maharashtra. The healthcare system India has a decentralized approach to health care and that allows health insurance to be optional. Technically, all citizens are eligible for free healthcare at government facilities, and individual states are responsible for organizing these services. However, the country’s health system is severely underfunded in terms of staff as well as supply shortages. A vast number of people seek care from private providers. Over ** percent of the total healthcare expenditure in the country was from out-of-pocket expenses in fiscal year 2020.

The statistic displays the population in India that had completed college education in 2011, with a breakdown by state and union territory. In that year, the state of Uttar Pradesh was at the top of the list, with just under 10 million college graduates, followed by the state of Maharashtra with some 8.6 million graduates.

The statistic shows the number of physically disabled people in India in 2011, broken down by state and union territory. In that year. the region with the highest number of physically disabled people was the state of Uttar Pradesh, with some 2.7 million people, followed by the state of Maharashtra with a little over 2 million people.

In 2011, around 20.31 percent of India's total children with disability were in Uttar Pradesh, at approximately 414.8 thousand out of 2.04 million of disabled children. Meanwhile, the disabled children in Bihar and Maharashtra accounted for respectively around 14.24 percent and 10.64 percent of the total disabled children all across India

As of July 2020, the state of Maharashtra housed the largest population of GST taxpayers in India amounting to about 1.56 million in number. The overall size of the GST taxpaying population in India that year tallied approximately 12.38 million. The GST was introduced by the Indian government on July 1, 2017 as a singular indirect tax on the supply of goods and services which replaced most of the existing indirect taxes levied in the country.