Data For India
@dataforin

Insights, charts and data to create shared knowledge and expand our understanding of India.

 India
dataforindia.com
Joined January 2023
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In 1950, a child born in India could expect to live only until the age of 41. By 2024, life expectancy at birth in India had risen to 72 years. Life expectancy is the average number of years a person would live if they were exposed to the sex- and age-specific death rates prevailing at that time. This data for India and other countries comes from the World Population Prospects, 2024 Revision, published by the United Nations Population Division. Across the world, women tend to live longer than men owing to a combination of biological and social factors. Girls are more likely to survive infancy and early childhood, while men are more likely to die from accidents in young adulthood and non-communicable diseases in old age, partly because of differences in health behaviours. However, this global trend did not hold true in India in the first few decades of Independence. In the 1950s, Indian men lived longer than women. That male advantage was reversed only in the early 1980s. By 2024, a newborn girl could expect to live more than three years longer than a boy born in the same year. This female advantage is large and well established only in India’s richer states. In poorer states, it is smaller and more recent. #LifeExpectancy #Ageing #Population #India #DataForIndia
Title: The female advantage in life expectancy in India appeared only in the 1980s Sub-title: Life expectancy at birth in India by gender, 1950–2024 Explanation: Life expectancy rose substantially for both women and men, from about 41 years in 1950 to 74 years for women and 71 years for men in 2024. Men had a slightly higher life expectancy until the early 1980s, when women overtook them. The female advantage then widened, reaching more than three years by 2024. Both groups experienced a sharp temporary decline around the COVID-19 pandemic. Source: World Population Prospects, United Nations Population Division Attribution: Data For India | CC BY

ALT Title: The female advantage in life expectancy in India appeared only in the 1980s Sub-title: Life expectancy at birth in India by gender, 1950–2024 Explanation: Life expectancy rose substantially for both women and men, from about 41 years in 1950 to 74 years for women and 71 years for men in 2024. Men had a slightly higher life expectancy until the early 1980s, when women overtook them. The female advantage then widened, reaching more than three years by 2024. Both groups experienced a sharp temporary decline around the COVID-19 pandemic. Source: World Population Prospects, United Nations Population Division Attribution: Data For India | CC BY

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How does life expectancy look across Indian states? Read @Rukmini's analysis to find out. dataforindia.com/life-expect…

Life expectancy

A child born in India today can expect to live much longer than her parents and grandparents. In this piece we examine what life expectancy is, how it has grown, and where inequalities in outcomes...

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More than half of Indian households own a motorcycle or scooter, while less than one in ten own a car or jeep as of 2024. This data comes from the nationally representative Household Consumption Expenditure Survey (HCES) conducted by the National Statistics Office. The HCES also classifies people by monthly per capita consumption expenditure, or average monthly spending per person, and divides them into five equal groups called quintiles. The bottom quintile represents the poorest 20% of the population, while the top quintile represents the richest 20%. Nearly four decades ago, car ownership was rare across all economic classes. Fewer than 1% of households in even the richest quintile owned a car. By 2024, car ownership has risen meaningfully only among the richest 20% of households, but even among them fewer than one in five own a car. Among all other quintiles, car ownership has remained below 6% of households, and below 3% for the bottom three quintiles. #TwoWheeler #Car #Vehicle #India #DataForIndia
Title: Car ownership has significantly increased only for the richest Indians Sub-title: Share of car ownership by household economic class, over time Explanation: In 1988, fewer than 1% of households in every economic class owned a car. By 2024, ownership had risen to about 19% among the richest 20% of households and nearly 6% among the next-richest group. It remained below 3% for the other three groups, showing that the increase was concentrated among richer households. Source: Household Consumption Expenditure Survey, National Statistics Office Attribution: Data For India | CC BY

ALT Title: Car ownership has significantly increased only for the richest Indians Sub-title: Share of car ownership by household economic class, over time Explanation: In 1988, fewer than 1% of households in every economic class owned a car. By 2024, ownership had risen to about 19% among the richest 20% of households and nearly 6% among the next-richest group. It remained below 3% for the other three groups, showing that the increase was concentrated among richer households. Source: Household Consumption Expenditure Survey, National Statistics Office Attribution: Data For India | CC BY

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How does two-wheeler ownership look across economic classes in India? Read @akwaghmare's piece to learn more. dataforindia.com/vehicle-own…

Vehicle ownership in India

Two-wheeler ownership has become more widespread in India, but car ownership is relatively low and concentrated among some groups.

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New Data Byte: In most Indian states, 90% of births now take place in healthcare facilities, by @nileena_suresh Institutional births refer to deliveries that take place in a health facility, whether public or private. As of 2021, nearly nine in ten births in India were institutional. Among the larger states, Tamil Nadu and Kerala reported the highest levels of institutional births. At the other end, more than one in five deliveries still took place at home in five of India's states - Arunachal Pradesh, Bihar, Jharkhand, Meghalaya and Nagaland - as of 2021. Ensuring that women give birth in a health facility is one of the most effective ways to reduce both maternal and infant deaths. Childbirth can involve complications that require timely medical care, making access to skilled health personnel and emergency obstetric services critical. India has made significant progress in improving the number of institutional deliveries in the last three decades. In 1993, only about 25% of births took place in a public or private health facility. By 2021, this increased to nearly 90% of deliveries, and much of this progress came from rural areas. Some states in particular have seen rapid progress. In Rajasthan and Odisha, for instance, only about one in ten births took place in a health facility in the early 1990s. By 2021, this had increased to more than nine in ten births. Public health facilities account for most institutional deliveries in India, particularly in rural areas. Yet access remains uneven. Among the poorest rural households, more than 25% of births still occur at home. #Birth #Child #Health #India #DataForIndia
Title: Share of institutional births in India across states (2021) Sub-title: Data Byte: In most Indian states, 90% of births now take place in healthcare facilities Explanation: Most states report institutional birth shares of 80–100%. Meghalaya and Nagaland have the lowest shares, at around 50%, meaning nearly half of births in these two states happen at home. Source: National Family Health Survey, IIPS Attribution: Data For India | CC BY

ALT Title: Share of institutional births in India across states (2021) Sub-title: Data Byte: In most Indian states, 90% of births now take place in healthcare facilities Explanation: Most states report institutional birth shares of 80–100%. Meghalaya and Nagaland have the lowest shares, at around 50%, meaning nearly half of births in these two states happen at home. Source: National Family Health Survey, IIPS Attribution: Data For India | CC BY

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Data Bytes brings you one chart about India every week, and the story behind the data. Subscribe to receive the next Data Byte, right in your inbox. dataforindia.com/data-bytes/…

Data Bytes

Our weekly newsletter bringing you one chart about India, and the story behind the data.

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UPDATE: Our booth is now on the Ground floor! Come find us at IndiaFOSS 2026 this weekend at NIMHANS Convention Centre, Bengaluru.
Data For India
@dataforin
Sep 24
We are heading to IndiaFOSS 2026 this weekend! September 26–27 at NIMHANS Convention Centre, Bengaluru. @nileena_suresh Suresh and @TheDataAreClean from Data For India will host a hands-on booth to showcase our work on “the last mile of public data”. Together, we will explore what stands between data being publicly available and being genuinely usable. Come meet us on the 1st floor! Also at IndiaFOSS, @Rukmini will speak about "Telling India’s Story Through Data" on Sunday, September 27, at 11:45 am in Hall 1. Register here: fossunited.org/indiafoss/202… #OpenData #PublicData #OpenSource #FOSS #DataForIndia
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We are heading to IndiaFOSS 2026 this weekend! September 26–27 at NIMHANS Convention Centre, Bengaluru. @nileena_suresh Suresh and @TheDataAreClean from Data For India will host a hands-on booth to showcase our work on “the last mile of public data”. Together, we will explore what stands between data being publicly available and being genuinely usable. Come meet us on the 1st floor! Also at IndiaFOSS, @Rukmini will speak about "Telling India’s Story Through Data" on Sunday, September 27, at 11:45 am in Hall 1. Register here: fossunited.org/indiafoss/202… #OpenData #PublicData #OpenSource #FOSS #DataForIndia
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Obesity is rising in India. In 2021, almost a quarter of adults aged 15–49 were overweight or obese. By 2024, this figure had reached nearly 30%. Excess body weight increases the risk of cardiovascular disease, diabetes and hypertension, making obesity a growing public health concern. This data comes from the National Family Health Survey (NFHS), which surveyed over 600,000 households in 2021 and recorded anthropometric measurements such as height, weight, waist circumference and hip circumference. Body Mass Index (BMI) is calculated by dividing a person's weight in kilograms by the square of their height in metres. The NFHS classifies a BMI of 25 kg/m² or higher as overweight and 30 kg/m² or higher as obese, following the World Health Organization (WHO) definition. We monitor both overweight and obesity levels, because the Indian population faces health risks at lower BMI levels than many western populations, particularly the risk of cardiovascular disease and diabetes. Overweight and obesity are more prevalent in urban areas and among women. More than one in three urban women are overweight or obese, and nearly three in ten urban men fall into these categories. Greater access to ultra-processed foods, changing meal patterns and lower levels of physical activity may contribute to higher rates in urban areas. Among women, biological and hormonal changes, particularly with age, may increase the risk. Early-life factors, including maternal undernutrition, may also increase susceptibility to obesity later in life. #Obesity #Overweight #Health #DataForIndia #India
Title: A quarter of all Indian adults are overweight or obese Sub-title: Share of overweight and obese men and women across sector (2021) Explanation: Overweight and obesity were more common in urban India than in rural India. Among urban adults, 30% of men and 34% of women were overweight or obese. In rural areas, the corresponding shares were 19% for both men and women. Obesity alone was most prevalent among urban women, at 11%. Source: National Family Health Survey, International Institute for Population Sciences Attribution: Data For India | CC BY

ALT Title: A quarter of all Indian adults are overweight or obese Sub-title: Share of overweight and obese men and women across sector (2021) Explanation: Overweight and obesity were more common in urban India than in rural India. Among urban adults, 30% of men and 34% of women were overweight or obese. In rural areas, the corresponding shares were 19% for both men and women. Obesity alone was most prevalent among urban women, at 11%. Source: National Family Health Survey, International Institute for Population Sciences Attribution: Data For India | CC BY

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How does obesity vary across different states in India? Read @nileena_suresh's analysis to find out. dataforindia.com/obesity/?ut…

Obesity in India

Rates of obesity have grown sharply in India, especially among women and among the poorest households. At the same time, the way we measure obesity needs a re-examination.

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Six in ten workers in India are self-employed, making up the largest category of workers. India's labour statistics define the self-employed as persons who operate their own farm or non-farm enterprise, or are engaged independently in a profession or trade on their own, or with one or a few partners in household enterprises. Unlike salaried and casual workers, the self-employed are not paid wages, but their earnings come from the profits of the enterprise. Workers with lower levels of education are much more likely to be self-employed, while those with a higher education are more likely to be in salaried work. Among workers who have a higher education, 40% are in self-employment, while nearly 60% are in salaried work. Among illiterate workers, on the other hand, 66% are self-employed while just 7% are in salaried work. Self-employed people may be own-account workers who run their own enterprise without employees, employers who run the enterprise by hiring paid employees, or unpaid helpers who work in a household enterprise for no wages. #Employment #SelfEmployment #Work #India #DataForIndia
Title: The less educated are more likely to be self-employed in India Sub-title: Type of employment, by education level (2024) Explanation: Self-employment becomes less common as education levels rise, falling from 66% among illiterate workers to 40% among workers with higher education. Salaried work shows the opposite pattern, rising from about 7% among illiterate workers to 58% among those with higher education. Casual work also declines sharply, from 28% to about 2%. Source: Periodic Labour Force Survey, National Statistics Office Attribution: Data For India | CC BY

ALT Title: The less educated are more likely to be self-employed in India Sub-title: Type of employment, by education level (2024) Explanation: Self-employment becomes less common as education levels rise, falling from 66% among illiterate workers to 40% among workers with higher education. Salaried work shows the opposite pattern, rising from about 7% among illiterate workers to 58% among those with higher education. Casual work also declines sharply, from 28% to about 2%. Source: Periodic Labour Force Survey, National Statistics Office Attribution: Data For India | CC BY

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How does self-employment in India break down by type and gender? Read @akwaghmare's piece to find out. dataforindia.com/self-employ…

Self-employment

The self-employed make up the majority of the Indian workforce. But self-employment plays out in different ways among men and women, and between rural and urban India.

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New Data Byte: One in every 250 young men in Punjab and Delhi is in prison, by Ameya Bokil The incarceration rate - the number of people in prisons for every 100,000 persons - is an important measure of a country's socio-economic environment, and criminal and justice systems. India's incarceration rate of around 40 persons in jail for every 100,000 residents is one of the lowest in the world. However national averages hide high incarceration rates among some groups in particular. The incarceration rate for men, and for young men in particular, is much higher. The incarceration rate for men aged 18-30 years is over three times the national average. It is also significantly higher in some states in particular. Punjab has India's highest incarceration rate, led to a large extent by charges under anti-narcotics laws. Young men in the 18-30 age group in Punjab and Delhi are ten times more likely to be in prison than an average person in the country. With an incarceration rate of over 400, over one in every 250 young men in these two states is in prison. For context, the United States of America, which has among the highest incarceration rates in the world, had 520 people in prison for every 100,000 residents in 2023. A large number of those in prison are undertrials. 85% of the incarcerated young men in Punjab's jails and 96% in Delhi's jails were undertrials, meaning that they were awaiting completion of their trial and had yet to be convicted of an offence. #Prison #Jail #Inmates #Law #India #DataForIndia
Title: Incarceration rate among men aged 18–30 years, 2023 Sub-title: One in every 250 young men in Punjab and Delhi is in prison Explanation: In 2023, 144 of every 100,000 men aged 18–30 in India were in prison. The rate was nearly three times as high in Punjab and Delhi, at 418 and 423 per 100,000 respectively. This means roughly one in every 250 young men in these two states was incarcerated. Source: Prison Statistics India, National Crime Records Bureau Attribution: Data For India | CC BY

ALT Title: Incarceration rate among men aged 18–30 years, 2023 Sub-title: One in every 250 young men in Punjab and Delhi is in prison Explanation: In 2023, 144 of every 100,000 men aged 18–30 in India were in prison. The rate was nearly three times as high in Punjab and Delhi, at 418 and 423 per 100,000 respectively. This means roughly one in every 250 young men in these two states was incarcerated. Source: Prison Statistics India, National Crime Records Bureau Attribution: Data For India | CC BY

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Data Bytes brings you one chart about India every week, and the story behind the data. Subscribe to receive the next Data Byte, right in your inbox. dataforindia.com/data-bytes/…

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Our weekly newsletter bringing you one chart about India, and the story behind the data.

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One in three young Indians were enrolled in higher education as of 2024. However, this is still below the enrolment rate in higher education of the world on average, as well as that of many developed countries. In the early 2000s, India's higher education enrolment rates were similar to those of China, for instance. But in the two decades since, China has made big strides, and more than eight in ten young Chinese adults are now in higher education. To understand how many students are in education, we look at a measure called the enrolment ratio. The Gross Enrolment Ratio (GER) is the number of students enrolled in an education level relative to their population. Higher education includes undergraduate (or equivalent) and postgraduate (or equivalent) levels of study. 33 million students enrolled at the undergraduate level in 2022. In addition to this, 5.1 million students enrolled in postgraduate programmes such as master's degrees.  More male students than female students are enrolled in undergraduate courses. At the postgraduate level, however, there are substantially more female students enrolled than male students.  #Enrolment #Education #HigherEducation #India #DataForIndia
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How does India’s higher education enrolment split across public and private institutions? Read @akwaghmare's piece to find out. dataforindia.com/enrolment-i…

Enrolment in education

Independent India has brought almost every Indian child into school. But there's still a long way to go with higher education.

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When a country’s Total Fertility Rate (TFR) drops to 2.1 children per woman, demographers say it has reached “replacement fertility”. This is a key milestone for a country, indicating that the population will eventually stop growing and replace itself. If fertility falls further, the population will decline in absolute numbers over time. India's fertility rate has dropped to 1.9 children per woman as of 2023. In the global conversation around falling birth rates, choices made by women around education and work are usually seen as the leading cause. However India shows that this theory does not hold universally.    In North America, Europe and East Asia, falling fertility could in part be explained by the opportunity costs faced by women who leave the workforce to have children. But most adult women in India do not work for pay outside the home. Yet India’s birth rate is now comparable to Viet Nam’s, where the labour force participation rate for women is two times that of India. The age at which women have their children is also lower in India than in East Asia, North America or Europe, meaning that women delaying childbirth for their careers is also not an explanation for falling fertility here.  In their 2025 book, After the Spike: Population, Progress, and the Case for People, economists Dean Spears and Michael Geruso argue against a grand theory for this trend. Instead, they suggest that many types of improvements in people’s lives have raised the opportunity cost of having children. These may include economic opportunities, but they may also include more leisure, and more ways to spend one’s time.  #Fertility #Births #Population #India #DataForIndia
Title: The share of women in the labour force is more than twice as high in Viet Nam as in India, yet fertility rates are similar Sub-title: Fertility rate and female labour force participation, by country (2022) Explanation: In 2022, 76% of women in Viet Nam were in the labour force, compared with 32% in India. Despite this large difference, both countries had a total fertility rate of about 1.9 children per woman. Source: World Development Indicators, World Bank Attribution: Data For India | CC BY

ALT Title: The share of women in the labour force is more than twice as high in Viet Nam as in India, yet fertility rates are similar Sub-title: Fertility rate and female labour force participation, by country (2022) Explanation: In 2022, 76% of women in Viet Nam were in the labour force, compared with 32% in India. Despite this large difference, both countries had a total fertility rate of about 1.9 children per woman. Source: World Development Indicators, World Bank Attribution: Data For India | CC BY

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What is the future of fertility in India? Read @Rukmini's analysis to find out. dataforindia.com/fertility/?…

Fertility in India

India has reached a key demographic milestone - fertility in India is now below replacement levels. In India's southern and western states, fertility levels are now particularly low. Birth rates are...

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New Data Byte: Minimum temperatures in India are rising faster than maximum temperatures, by Juhi Chatterjee Warming in India is not occurring uniformly. While both daytime and night-time temperatures have risen over the past seven decades, minimum temperatures have increased faster than maximum temperatures, indicating that nights are warming more rapidly than days. An anomaly is the departure of a given year's temperature from the long-term average over a reference period. The current baseline in use in India is the average of the 1990-2020 period. During the 1950s up to the 1980s, both maximum and minimum temperatures fluctuated around the baseline, with some years warmer and some cooler. In recent years, however, the data shows not just sustained warming, but a sharp acceleration, particularly in minimum temperatures. Since 2020, the pace has increased markedly. The minimum anomaly rose from +0.43°C in 2023 to approximately +0.90°C in 2024 - the highest recorded value in the entire series. The maximum anomaly reached +0.40°C over the same period, showing the faster pace of increase in the minimum temperature anomaly. Together, the persistence of positive anomalies and the faster increase in minimum temperatures point to a warming climate in which heat is becoming both more intense during the day and more sustained through the night. This asymmetry limits overnight recovery, raising health risks, affecting agriculture, increasing energy demand and intensifying heat stress on vulnerable populations. #Climate #Temperature #Heat #India #DataForIndia
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Data Bytes brings you one chart about India every week, and the story behind the data. Subscribe to receive the next Data Byte, right in your inbox. dataforindia.com/data-bytes/…

Data Bytes

Our weekly newsletter bringing you one chart about India, and the story behind the data.

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