Literacy Rate: West Bengal data was reported at 76.300 % in 12-01-2011. This records an increase from the previous number of 68.640 % for 12-01-2001. Literacy Rate: West Bengal data is updated decadal, averaging 48.650 % from Dec 1951 (Median) to 12-01-2011, with 7 observations. The data reached an all-time high of 76.300 % in 12-01-2011 and a record low of 24.610 % in 12-01-1951. Literacy Rate: West Bengal 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 Education Sector – Table IN.EDA001: Literacy Rate.

The statistic displays the literacy rate in the state of West Bengal in India between 1991 and 2011, broken down by gender. In 2001, ** percent of the male population in West Bengal knew how to read or write. India's literacy rate from 1981 through 2011 can be found here.

The dataset contains Year and State wise Literacy Rate

Note: 1. Literacy rates for 1951, 1961 and 1971 Censuses relate to population aged five years and above. The rates for the 1981, 1991, 2001 and 2011 Censuses relate to the population aged seven years and above. The literacy rate for 1951 in case of West Bengal relates to total population including 0-4 age group. Literacy rate for 1951 in respect of Chhattisgarh, Madhya Pradesh and Manipur are based on sample population. 2. India and Manipur figures exclude those of the three sub-divisions viz., Mao Maram, Paomata and Purul of Senapati district of Manipur as census result of 2001 in these three sub-divisions were cancelled due to technical and administrative reasons.

Literacy in India has been increasing as more and more people receive a better education, but it is still far from all-encompassing. In 2023, the degree of literacy in India was about 77 percent, with the majority of literate Indians being men. It is estimated that the global literacy rate for people aged 15 and above is about 86 percent. How to read a literacy rateIn order to identify potential for intellectual and educational progress, the literacy rate of a country covers the level of education and skills acquired by a country’s inhabitants. Literacy is an important indicator of a country’s economic progress and the standard of living – it shows how many people have access to education. However, the standards to measure literacy cannot be universally applied. Measures to identify and define illiterate and literate inhabitants vary from country to country: In some, illiteracy is equated with no schooling at all, for example. Writings on the wallGlobally speaking, more men are able to read and write than women, and this disparity is also reflected in the literacy rate in India – with scarcity of schools and education in rural areas being one factor, and poverty another. Especially in rural areas, women and girls are often not given proper access to formal education, and even if they are, many drop out. Today, India is already being surpassed in this area by other emerging economies, like Brazil, China, and even by most other countries in the Asia-Pacific region. To catch up, India now has to offer more educational programs to its rural population, not only on how to read and write, but also on traditional gender roles and rights.

This layer shows State-Wise Literacy Rates (1951-2011).Source of data: https://www.indiabudget.gov.in/economicsurvey/doc/stat/tab85.pdfNote:India and Manipur figures exclude those of the three sub-divisions viz. Mao Maram, Paomata and Purul of Senapati district of Manipur as census results of 2001 in these three sub-divisions were cancelled due to technical and administrative reasons.Literacy rates for 1951, 1961 and 1971 Censuses relate to population aged five years and above and from 1981 onwards Literacy rates relate to the population aged seven years and above. The literacy rate for 1951 in case of West Bengal relates to total population including 0-4 age group. Literacy rate for 1951 in respect of Chhattisgarh, Madhya Pradesh and Manipur are based on sample population.This web layer is offered by Esri India, for ArcGIS Online subscribers. If you have any questions or comments, please let us know via content@esri.in.

The statistic displays the numbers of literate people below primary school level in India in 2011, by state and union territory. The region with the highest numbers of literate people below primary school was the state of Uttar Pradesh, with over ********** literate people, followed by the state of West Bengal, with close to ********** people.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for village level demographic analysis within basic applications to support graphical overlays and analysis with other spatial data.

this graph was created in PowerBi,Tableau and Loocker Studio :

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ntroduction

The National Sample Survey (NSS) Multi Indicator Survey (MIS) 78th Round (2020-21) is a comprehensive dataset that provides key socio-economic insights about Kolkata and other regions of India. Conducted by the National Statistical Office (NSO), Ministry of Statistics and Programme Implementation (MoSPI), Government of India, this survey aimed to gather extensive data on multiple indicators, including education, health, employment, migration, consumption patterns, and digital access.

This document provides a detailed explanation of the Kolkata-specific findings of the NSS 78th Round, offering insights into various socio-economic dimensions of the city's population.

Objectives of the NSS 78th Round

The primary objectives of the 78th Round Multi Indicator Survey were:

To assess the education levels and literacy rates in Kolkata.

To understand household health conditions and access to healthcare facilities.

To analyze employment and labor force participation in urban settings.

To examine migration trends within and outside Kolkata.

To evaluate consumption patterns and expenditure levels.

To study digital access and usage among households.

Key Findings for Kolkata

1. Education and Literacy

The survey revealed that Kolkata maintains a high literacy rate, with a considerable percentage of its population having completed secondary and higher education.

A growing number of children are enrolled in private schools, though government schools still play a significant role.

Female literacy has shown an increasing trend, but disparities still exist in lower-income communities.

1. Health and Healthcare Access

Kolkata has a high hospital density, with most households reporting access to primary healthcare centers and hospitals.

The survey recorded a moderate prevalence of chronic diseases, including diabetes and hypertension, particularly among the elderly.

Public healthcare facilities are widely used, but there is significant reliance on private hospitals, especially for specialized treatments.

1. Employment and Labor Market

The workforce participation rate in Kolkata remains steady, with a majority engaged in the service sector, trade, and informal employment.

There has been a decline in manufacturing jobs, partly due to automation and industry shifts.

The gig economy and self-employment have seen a rise, reflecting national trends.

1. Migration Trends

Kolkata experiences both in-migration and out-migration, with many individuals moving to the city for employment and education.

The survey indicated that a large percentage of migrants come from rural West Bengal, Bihar, and Jharkhand.

Out-migration has been observed primarily among skilled professionals seeking opportunities in other metropolitan cities or abroad.

1. Consumption Patterns and Expenditure

The average household consumption expenditure in Kolkata is higher than the national average, reflecting its status as a major urban center.

Food consumption patterns indicate a preference for cereals, fish, and dairy products, with an increase in processed food consumption.

Housing and transportation form a significant portion of monthly expenses for urban residents.

1. Digital Access and Usage

The survey highlighted a strong penetration of digital connectivity, with most households having access to smartphones and the internet.

Digital literacy is improving, with increased use of online banking, e-commerce, and educational platforms.

However, a digital divide persists among lower-income groups and elderly populations.

Policy Implications

Based on the survey findings, the following policy recommendations are suggested:

Enhancing educational infrastructure to bridge the literacy gap in underprivileged areas.

Strengthening public healthcare systems to reduce dependence on private hospitals.

Promoting employment generation programs and support for informal workers.

Affordable housing initiatives to address rising living costs in Kolkata.

Expanding digital literacy programs to bridge the digital divide.

Conclusion

The Kolkata-specific insights from the NSS 78th Round (2020-21) offer valuable data for policymakers, researchers, and urban planners. These findings provide a comprehensive picture of the city's socio-economic...

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