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Visualizing India’s Population Growth from 2022-2100

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Charting out India's population growth over the years

Visualizing India’s Population Growth from 2022-2100

For years, India has been on track to overtake China as the world’s most populated country.

In fact, we’ve covered this phenomenon in past articles, back when India was expected to overtake China’s population by the end of the decade.

However, according to the UN’s latest population prospects, this takeover is projected to happen sooner than previously expected—as early as next year.

This graphic by Pablo Alvarez provides an up-to-date chart of India’s population growth projections compared to other countries. Projection data from Our World in Data ranges from 1800 all the way to until 2100.

Some Historical Context

For over three centuries, China has had the largest population of any country in the world.

In the 1800s, China’s population was about 322 million, which was nearly double India’s at the time. And until the mid-20th century, both countries’ populations stayed relatively stable.

However, in 1949, China’s population started to experience dramatic growth. This occurred after the Chinese Civil War when the People’s Republic of China was first established.

Around the same time, India’s population had also started to increase. Since both countries were experiencing population booms, the status quo remained the same, and China kept its position as the world’s most populated country.

YearChina's PopulationIndia's Population
1950543,979,233357,021,106
1951553,613,990364,922,356
1952564,954,522372,997,192
1953577,378,687381,227,710
1954589,936,006389,731,408
1955603,320,152398,577,988
1956616,283,025407,656,598
1957630,003,022416,935,404
1958643,791,575426,295,767
1959652,179,197435,900,351
1960654,170,699445,954,573
1961655,260,384456,351,883
1962664,614,653467,024,195
1963683,903,564477,933,620
1964704,593,776489,059,307
1965723,846,349500,114,347
1966742,948,545510,992,615
1967761,006,267521,987,066
1968780,371,962533,431,917
1969801,430,969545,314,679
1970822,534,453557,501,303
1971843,285,425569,999,181
1972862,840,402582,837,969
1973881,652,084596,107,487
1974899,367,646609,721,954
1975915,124,664623,524,225
1976929,375,929637,451,444
1977942,581,333651,685,632
1978955,138,940666,267,761
1979968,298,969681,248,379
1980982,372,463696,828,379
1981997,259,502712,869,300
19821,013,483,168729,169,469
19831,029,226,907745,826,550
19841,044,172,200762,895,161
19851,060,239,983780,242,087
19861,077,770,524797,878,992
19871,096,851,842815,716,128
19881,115,889,802833,729,683
19891,134,414,721852,012,670
19901,153,704,251870,452,162
19911,170,626,176888,941,763
19921,183,813,393907,574,051
19931,195,855,556926,351,289
19941,207,286,682945,261,956
19951,218,144,429964,279,137
19961,228,298,833983,281,216
19971,237,801,4491,002,335,231
19981,246,836,1111,021,434,572
19991,255,433,2371,040,500,049
20001,264,099,0691,059,633,672
20011,272,739,5871,078,970,908
20021,280,926,1211,098,313,030
20031,288,873,3651,117,415,122
20041,296,816,7061,136,264,583
20051,304,887,5571,154,638,717
20061,313,086,5681,172,373,788
20071,321,513,2271,189,691,814
20081,330,167,1441,206,734,803
20091,339,125,5921,223,640,160
20101,348,191,3711,240,613,616
20111,357,095,4851,257,621,190
20121,366,560,8181,274,487,221
20131,376,100,3011,291,132,067
20141,385,189,6711,307,246,508
20151,393,715,4481,322,866,506
20161,401,889,6851,338,636,336
20171,410,275,9561,354,195,684
20181,417,069,4621,369,003,309
20191,421,864,0321,383,112,049
20201,424,929,7851,396,387,128
20211,425,893,4631,407,563,841
20221,425,887,3351,417,173,176
20231,425,671,3531,428,627,666
20241,425,178,7811,441,719,857
20251,424,381,9231,454,606,728
20261,423,255,2001,467,231,220
20271,421,809,0611,479,578,524
20281,420,045,5771,491,671,044
20291,417,974,6401,503,470,599
20301,415,605,9031,514,994,087
20311,412,946,0061,526,208,895
20321,410,012,8701,537,108,031
20331,406,810,3821,547,689,840
20341,403,314,8201,557,919,804
20351,399,547,5021,567,802,259
20361,395,546,7251,577,302,810
20371,391,338,4191,586,438,626
20381,386,952,0011,595,245,784
20391,382,367,1261,603,664,860
20401,377,556,9401,611,676,335
20411,372,522,3921,619,318,358
20421,367,267,0981,626,585,371
20431,361,737,2531,633,430,527
20441,355,912,8141,639,837,776
20451,349,756,9051,645,863,188
20461,343,210,2391,651,513,758
20471,336,262,9051,656,777,044
20481,328,873,6081,661,705,661
20491,321,004,2041,666,284,988
20501,312,636,3241,670,490,601
20511,303,756,6021,674,343,637
20521,294,381,0841,677,872,878
20531,284,539,8721,681,073,177
20541,274,244,7571,683,955,037
20551,263,512,5561,686,563,352
20561,252,371,9861,688,894,376
20571,240,879,9941,690,942,710
20581,229,126,1551,692,704,326
20591,217,157,9371,694,150,262
20601,205,020,6481,695,285,494
20611,192,805,2281,696,121,515
20621,180,553,3711,696,684,918
20631,168,316,2551,696,976,688
20641,156,145,6371,696,961,377
20651,144,050,9181,696,634,190
20661,132,053,3981,695,973,643
20671,120,182,1211,694,997,001
20681,108,424,5871,693,712,645
20691,096,787,1331,692,129,035
20701,085,287,6181,690,230,784
20711,073,902,3901,687,990,288
20721,062,612,8891,685,415,098
20731,051,380,9061,682,564,511
20741,040,194,8511,679,449,249
20751,029,035,6031,676,034,859
20761,017,860,4641,672,328,378
20771,006,663,1521,668,352,088
2078995,438,0141,664,100,419
2079984,185,3951,659,592,784
2080972,906,8891,654,856,929
2081961,612,9871,649,862,775
2082950,338,4101,644,678,011
2083939,100,1171,639,364,769
2084927,912,3831,633,888,924
2085916,808,8041,628,242,630
2086905,821,0241,622,427,549
2087894,960,2591,616,451,908
2088884,243,8891,610,366,043
2089873,694,7041,604,195,815
2090863,319,5371,597,908,860
2091853,111,7681,591,484,817
2092843,067,0311,584,943,122
2093833,162,1871,578,296,210
2094823,380,9811,571,569,445
2095813,718,7281,564,797,337
2096804,153,5921,557,945,215
2097794,673,4851,551,000,312
2098785,270,3151,543,990,233
2099775,944,4291,536,933,456
2100766,673,2681,529,850,116

China’s baby boom lasted two decades. But by the late 1970s, the Chinese government implemented a one-child policy in an attempt to slow things down and control population growth, out of fear that China was becoming overpopulated.

The plan worked—according to China’s National Health and Family Planning Commission spokesman Mao Qunan, the government’s efforts ended up reducing the number of births over the years by roughly 400 million.

China’s Population is Aging Faster Than India’s

These days, China has one of the most rapidly aging populations in the world. By 2040, it’s expected that 28% of the country’s population will be over the age of 60.

In contrast, India’s population is relatively young—half of its population is under 30, and only an eighth is over 60.

Does this mean that India’s GDP will eventually outpace China’s? Not necessarily.

As quoted in an article published in Business Standard, Madan Sabnavis, Chief Economist of the Bank of Baroda says that India needs to increase its labor participation, as well as general access to education, in order to reap the benefits of its increasing working-age population.

As of 2022, India’s workforce participation rate sits at 46%, compared to China’s 68%. How will this change in the future?

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This article was published as a part of Visual Capitalist's Creator Program, which features data-driven visuals from some of our favorite Creators around the world.

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How America’s Poverty Rates Differ by Race

This chart shows how poverty rates in America swing between 10–20% when accounting for race.

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This cropped chart lists the rate and number of Americans below the poverty level, categorized by self-selected race.

Charted: How America’s Poverty Rates Differ by Race

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

The U.S. poverty rate stands at 12%, affecting about 41 million people across the country. At the state level, this rate ranges from 7% to 18%, depending on local economic conditions. But how does poverty differ when examined through the lens of racial demographics?

This chart visualizes the percentage and number of Americans living below the poverty threshold, categorized by race, based on data from the American Community Survey 2022 conducted by the Census Bureau. It focuses on respondents who selected a single race.

ℹ️ The Census Bureau sets poverty thresholds based on family size and composition. For families with incomes below these thresholds, every individual in the family is considered in poverty.

Racial Disparities in Poverty

The data reveals distinct differences in poverty rates among racial groups, reflecting the complex social and economic dynamics that have evolved over generations.

Race% Below Poverty Level# Below Poverty Level
American Indian/Alaska Native21.7%675,913
African American21.3%8,317,088
Other*17.9%4,303,587
Native Hawaiian/Other Pacific Islander17.6%113,693
Asian10.1%1,937,553
White9.9%19,544,155

*Hispanic/Latino populations usually select “other race” in census surveys. Figures rounded.

While poverty exists across all racial groups, there are some significant variations in both the rates and total numbers. These disparities reflect a combination of historical factors, structural inequalities, and ongoing challenges unique to different communities.

Native and Black Americans Face Higher Poverty Rates

Both Native Americans and Black Americans have the highest poverty rates, with about one in five individuals from these groups living below the poverty line. These groups are considered “overrepresented” in poverty statistics, meaning their share in poverty exceeds their proportion of the total U.S. population.

Long-standing issues have created cycles of poverty that, despite some progress, remain challenging to overcome in the face of ongoing systemic inequalities.

Other racial groups also grapple with poverty as well. There are 19.5 million white Americans below the poverty line. Although the rate is lower, about one-in-ten, the absolute number of people below the poverty threshold is the largest of all groups.

Learn More on the Voronoi App

The U.S. also falls behind its peers when it comes to government support to help socio-economic mobility. Check out Hours of Work Needed to Escape Poverty to see how it measures up against other high income economies.

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