Chart and table of population level and growth rate for the Indore, India metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

Census: Population: Madhya Pradesh: Indore: Male data was reported at 1,129,348.000 Person in 03-01-2011. This records an increase from the previous number of 796,673.000 Person for 03-01-2001. Census: Population: Madhya Pradesh: Indore: Male data is updated decadal, averaging 190,494.000 Person from Mar 1901 (Median) to 03-01-2011, with 12 observations. The data reached an all-time high of 1,129,348.000 Person in 03-01-2011 and a record low of 30,154.000 Person in 03-01-1911. Census: Population: Madhya Pradesh: Indore: Male 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.GAC020: Census: Population: By Towns and Urban Agglomerations: Madhya Pradesh.

This data collection is comprised of interviews with Smart City stakeholders and actors across four Smart Cities in India as well as a set of interviews with national-level actors in Delhi. These interviews took place between September 2018 and October 2019 and are a reflection of the nationally-led Smart City Mission from 2015-2020. The cities represented include Jaipur, Bengaluru, Kochi, Indore, and Delhi.

This research has two primary aims. The first is to develop cutting edge, theoretically informed, insights into the nature of mobility governance reform and the potential to generate more sustainable urban mobility in India. The combined pressures of a growing urban population, increasing urban sprawl, and rapidly rising income, coupled with inadequate public transport, lack of coordinated infrastructure, and increased motorisation have placed huge and unequal burdens on India's urban areas. This has resulted in highly congested roads, poor air quality, high pedestrian casualty rates and poor accessibility and quality of life particularly for the urban poor. In this context, redesigning urban mobility governance has been identified as a critical element of progress in delivering more inclusive and economically, environmentally and socially sustainable cities in India (MoUD, 2006, MoUD, 2015 and NITI Aayog, 2017). Efforts to reform urban transport governance, primarily through the bolstering of local-level capacity, have been underway in India since 2006 but with limited affect due to lack of meaningful delegation of authority and financial power. However, in 2015 the Indian national government launched the Smart Cities Mission, aimed at going beyond what has been achieved before at the local level. The focus of the initiative is to promote 'cities that provide core infrastructure and give a decent quality of life to its citizens' through the application of 'Smart' Solutions (MoUD, 2015, p5). Within this context then, this research uses the Smart Cities Mission as a major opportunity to understand the aims and processes of transport governance reform and the extent to which these reforms are capable of achieving a significant improvement in the mobility system. To this end, the research will undertake a qualitative comparative analysis of previous and planned reforms in four of India's designated smart cities; Jaipur, Kochi, Indore and Bangalore. The research will characterise governance arrangements and governance reforms across each of the four cities, and in using the multi-level governance framework to guide empirical analysis, will be innovative in developing this framework within a non-Western context. The research will also trace the impacts of governance reforms through to impacts on the economic prosperity and quality of life of citizens through analysing changing processes and outcomes. This is essential if we are to move beyond identifying problems to understanding how to overcome them. The second aim of the research is to bring together, develop and inspire a community of researchers and practitioners to advance the study and understanding of mobility governance across India and between the UK and India. The research will be bottom-up in its approach; working with WRI India, the project will engage practitioners in the four cities from the outset to ensure the findings are as meaningful as possible. The interview protocol will be co-created with stakeholders and the data collection informed by the key challenges of urban mobility governance identified by stakeholders through exploratory workshops at the start of the project. A study visit to three UK cities that have experienced different levels of transport governance reform will be held for stakeholders from each of the four 'smart cities' to learn lessons from the UK experience and draw on practitioner expertise. A special session of the World Conference on Transport Research in Mumbai will also be convened to bring practitioners into dialogue with scholars at the forefront of research on transport governance in India and beyond. The project will also convene a 'summer school' in India for researchers to develop their research methods, theoretical perspectives and networks in relation to transport governance and reform. These activities will build both professional and research capacity to address future transport governance challenges.

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

As per the results of a large scale survey in 2021, 50.3 percent of Indians were found to be unhealthy. About 56 percent of people in the city of Indore were found to be unhealthy, while the city of Pune had about 55 percent of unhealthy residents. The health risk assessment took into account multiple health aspects like nutrition, lifestyle, physical activity levels, immunity, disease affliction and others to draw this conclusion. Overall, the south Asian country had a high share of people with diabetes and heart problems.