The population of the southern city of Chennai in India amounted to about *********** inhabitants. This was an increase of approximately *********** inhabitants compared to the year 2000. Chennai, formerly known as Madras is the capital city of the state of Tamil Nadu.

Census: Population: City: Chennai data was reported at 4,646.732 Person th in 03-01-2011. This records a decrease from the previous number of 6,425.000 Person th for 03-01-2001. Census: Population: City: Chennai data is updated decadal, averaging 5,422.000 Person th from Mar 1991 (Median) to 03-01-2011, with 3 observations. The data reached an all-time high of 6,425.000 Person th in 03-01-2001 and a record low of 4,646.732 Person th in 03-01-2011. Census: Population: City: Chennai 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.GAB004: Census: Population: by Selected Cities.

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 statistic represents the results of a survey regarding the share of affluent population living in urban areas across India in FY 2016, by region. During the measured time period, the share of affluent population across the country in the Chennai region was approximately **** percent.

Census: Population: City: Chennai在03-01-2011达4,646.732Person th，相较于03-01-2001的6,425.000Person th有所下降。Census: Population: City: Chennai数据按decadal更新，03-01-1991至03-01-2011期间平均值为5,422.000Person th，共3份观测结果。该数据的历史最高值出现于03-01-2001，达6,425.000Person th，而历史最低值则出现于03-01-2011，为4,646.732Person th。CEIC提供的Census: Population: City: Chennai数据处于定期更新的状态，数据来源于Office of the Registrar General & Census Commissioner, India，数据归类于India Premium Database的Demographic – Table IN.GAB004: Census: Population: by Selected Cities。

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

Registered Motor Vehicles: City: Chennai data was reported at 6,351.729 Unit th in 2020. This records an increase from the previous number of 5,996.624 Unit th for 2019. Registered Motor Vehicles: City: Chennai data is updated yearly, averaging 3,455.789 Unit th from Mar 2002 (Median) to 2020, with 19 observations. The data reached an all-time high of 6,351.729 Unit th in 2020 and a record low of 1,355.550 Unit th in 2002. Registered Motor Vehicles: City: Chennai data remains active status in CEIC and is reported by Ministry of Road Transport and Highways. The data is categorized under India Premium Database’s Automobile Sector – Table IN.RAE001: Number of Registered Motor Vehicles: by Cities.

Comprehensive population and demographic data for Tiruvottiyur Tehsil

Comprehensive population and demographic data for Alandur Tehsil

*Includes population screened by X-ray and /or TB symptoms# Smr = Smear; Cult = Culture; Bact = BacteriologicallyPrevalence of Smear and Culture Positive Pulmonary Tuberculosis by Age and Sex (per 100,000 population).

Comprehensive population and demographic data for Ayanavaram Tehsil

The India Sports Team and Clubs Market is experiencing robust growth, fueled by a burgeoning young population with a rising disposable income and increasing engagement with sports. The market's substantial size, currently estimated at several billion dollars (a precise figure requires further data, but given a CAGR of over 7% and a value unit of millions, a multi-billion dollar valuation is reasonable), is projected to expand significantly over the forecast period (2025-2033). Key growth drivers include the rising popularity of both spectator and participatory sports, increasing media coverage and sponsorship deals, and the growing professionalization of various sporting leagues and clubs. The market is segmented by sport type (spectator vs. participatory) and revenue streams (media rights, merchandising, ticketing, and sponsorships). While spectator sports like cricket and football dominate revenue generation through media rights and sponsorships, participatory sports like golf and tennis contribute significantly through membership fees and club activities. Challenges include infrastructure limitations in certain regions and the need for better governance and transparency within some sports organizations. The market's segmentation offers multiple opportunities for growth. For example, leveraging digital platforms to enhance fan engagement and monetize media rights can significantly boost revenue. Further, targeted marketing campaigns catering to different demographic groups can drive participation in participatory sports. The strong presence of established clubs like Royal Challengers Bangalore and Chennai Super Kings, alongside emerging clubs and federations, indicates a dynamic and competitive landscape. Strategic investments in infrastructure development, talent scouting and training, and robust marketing strategies are crucial for sustained growth in this thriving market. The long-term outlook remains positive, driven by continued government support for sports development and a rising passion for sports among Indian citizens. Recent developments include: In August 2023, BigHit partnered with FC Bayern as their official regional partner in India. This collaboration marks a significant milestone for Indian football, opening doors for aspiring players and bridging the gap between Indian and international teams. BigHit is a sports app designed for the entirety of the sporting community, and FC Bayern is one of Europe's biggest and most successful sports clubs., On March 2023, Indian Premier League cricket club Mumbai Indians, owned by Reliance Industries, acquired Major League Cricket side, MI New York. The MI New York will be the fifth franchise after Mumbai Indians (IPL), MI Cape Town (SA20), MI Emirates (ILT20), and Mumbai Indians (WPL), in three different continents, four different countries, and five different leagues.. Key drivers for this market are: Rise In Sports Advertisement and Marketing Revenue, Rising spectators for different sports in India. Potential restraints include: Rise In Sports Advertisement and Marketing Revenue, Rising spectators for different sports in India. Notable trends are: Cricket Leading Sports Team and Club Market In India.

Study population characteristics among private practitioners comparing point-of-care (POC) testing practices in Chennai, India (n = 228).

Comprehensive population and demographic data for Guindy Tehsil

BackgroundHeart failure (HF) is a growing health problem and around two percent are affected in the general population. Accurate diagnostic markers that have the potential for early diagnosis of HF are lacking. This study aimed to compare the expression levels of microRNA-210-3p with biomarkers NT-proBNP, sST2, and galectin-3, in heart failure patients with preserved and reduced ejection fractions.Materials and methodsThe cross-sectional study was conducted on 270 hypertensive heart failure patients in the age group of 30 to 75 years of both genders. The participants with evidence of HF were recruited from the Department of Cardiology in a tertiary care hospital in Chennai, India. MicroRNA-210-3p was analyzed by qRT-PCR in a stratified sample of 80 HF patients and 20 apparently healthy individuals. Biomarkers were analyzed by ELISA. Institutional ethics committee approval and written informed consent were obtained. Statistical analysis was performed using R software (4.2.1). Based on the type of distribution of data, appropriate statistical tools were used. p-value ≤  0.05 was considered to be statistically significant.ResultsAll the biomarkers including microRNA-210-3p were significantly higher in HFrEF than in HFpEF. MAGGIC score showed a positive correlation with all the biomarkers. The cut-off of microRNA-210-3p was 5.03.ConclusionAll the biomarkers were significantly elevated in HFrEF compared to HFpEF. However, microRNA-210-3p could be an early marker in the diagnosis of heart failure. The strategy of employing a multi-marker approach could help in the early diagnosis as well as in stratifying the HF patients.

The estimated per capita income across the southern state of Tamil Nadu in India stood at around *** thousand Indian rupees in the financial year 2024. There was a consistent increase in the income per capita in the state since the financial year 2012. Sikkim recorded the highest per capita income in the country.

Comprehensive population and demographic data for Mambalam Tehsil

Comprehensive population and demographic data for Purasawalkam Tehsil

Persons experiencing homelessness (PEHs) have a higher risk of morbidity and mortality compared to the general population and are highly vulnerable during the coronavirus disease (COVID-19) pandemic. Understanding their experience of the pandemic is important for mitigating the effects of the pandemic. Accordingly, we conducted a qualitative study on their lived experiences during the COVID-19 pandemic. Semi-structured interviews were conducted in nine PEHs from Chennai, India, recruited at food stalls between September 14–25, 2020. Data were analyzed using interpretive phenomenological analysis. The participants shared their experiences of the COVID-19 pandemic, its impact on them, and their coping strategies. All the participants were migrant workers living alone, and were the sole breadwinners of their families. Five group experiential themes emerged relating to the experiences of the participants during the COVID-19 pandemic. Most participants reported significant psychosocial stress, but low suicide risk and robust coping mechanisms. They delayed seeking healthcare for non-COVID-19-related problems. Public hospitals were preferred over private hospitals due to cost constraints and prior experience of discrimination. Upward classism was observed as participants blamed the rich for the spread of COVID-19. Initial assumption that COVID-19 would only affect the rich was also reported. Free government testing and quarantine facilities assuaged their medico-psychosocial needs. Engaging in collective activities was a key stress mitigator. We highlight several important policy implications. Firstly, we underscore the importance of involving social workers to facilitate communication between healthcare providers and patients from vulnerable communities. This engagement can help minimize discrimination and promote equitable access to healthcare. Secondly, we emphasize the need for effective public health communication. Specifically, there is a need to address and alleviate concerns about the transmission of COVID-19 within hospital premises. Lastly, the research suggests that government initiatives aimed at fostering community participation should persist both during and after the pandemic.

Comprehensive population and demographic data for Egmore Tehsil