Our World in Data @OurWorldInData

Read more in Hannah's recent article on this topic, with breakdowns by region: ourworldindata.org/what-has-drive… Other sources & data: nature.com/articles/s4301… ourworldindata.org/grapher/driver…

Beef production has been the largest driver of deforestation this century. Over the last two decades, around 128 million hectares of forest have been cleared to make way for agriculture and forest plantations. That’s an area five times the size of the United Kingdom. What has driven this deforestation? A recent paper estimated the contribution of different agricultural products over the last few decades. In the chart, you can see the breakdown. Beef production has been the largest driver by far, contributing over 40% of the total. This has mostly been the clearing of forest for grazing pasture, especially across Brazil and other countries in Latin America. Oilseeds — mostly soy and oil palm — were the second-largest driver, again concentrated in Latin America for soy and in Indonesia and Malaysia for palm oil. While deforestation for palm oil was high in the early 2000s and 2010s, it has fallen a lot in recent years. Forest plantations have been a large driver of deforestation in North America and East Asia. Deforestation for most other products — including cereals, roots and tubers, and cash crops like cocoa and coffee — has been concentrated in Africa, where yields have not grown quickly enough to offset rising demand. (written by @_HannahRitchie)

Read the article by @_HannahRitchie: ourworldindata.org/wild-mammal-de…

Since the rise of humans, wild land mammal biomass has declined by 85%. Around 100,000 years ago, all of the wild land mammals on Earth summed up to around 20 million tonnes of carbon. By around 10,000 years ago, there had been a huge decline, likely in the range of 25% to 50%. It was almost exclusively the world’s largest mammals that vanished, in what is referred to as the Quaternary Megafauna Extinction. Most evidence now points towards humans being a key driver, mostly through hunting, even though there were likely fewer than five million people in the world at the time. By 1900, wild mammals had seen another large decline, but the pressures had shifted. The rise of agriculture alleviated some of the direct pressure from hunting, but the need for agricultural land meant the loss of wild habitats. Wild mammals saw another large decline in the last century, while the human population increased, and livestock even more so. With only around three million tonnes of wild land mammal biomass left, a return to wild hunting is not an option at any larger scale: if the world relied on wild mammals for the livestock meat it consumes, they would all be eaten within a month. But the alternative of continued growth in livestock consumption is also not sustainable. If we can reduce agricultural land — and primarily land use for livestock — we can free up land for wild mammals to return. Agricultural land per person has more than halved since 1960, and global agricultural land has declined slightly since 2000. Plant-based diets and alternative meat products could help, but the biggest barriers will be scale and affordability.

Read more about the history of malaria, and how the world can continue to make progress against it: ourworldindata.org/malaria Other sources & data: who.int/teams/global-m… who.int/publications/i…

Haiti and the Dominican Republic share the last Caribbean island with endemic malaria. Malaria was once endemic across much of the Caribbean. This map shows how much progress has been made: the islands in green are all malaria-free. Some of these islands were certified by the WHO to have eliminated the disease decades ago. This requires, among other things, zero indigenous cases for three consecutive years. The list includes Grenada and Saint Lucia in 1962, Trinidad and Tobago in 1965, Dominica and Jamaica in 1966, and Cuba in 1973. Others are on the WHO’s list of countries where malaria never existed, and those where it disappeared without a deliberate anti-malaria campaign. At the center, you can see Haiti and the Dominican Republic, which share the island of Hispaniola. They are the Caribbean’s last island countries with endemic malaria. The Dominican Republic is much closer to elimination — it reported around 1,200 locally acquired cases in 2024, compared with almost 38,600 in Haiti. But its success depends on Haiti’s too, because malaria doesn’t stop at the border. This is why malaria eradication needs coordinated efforts across countries. (written by @EOrtizOspina)

Explore all of the updated data in our interactive charts: ourworldindata.org/search?dataset…

How fast is the world building up solar power? The International Renewable Energy Agency (IRENA) is an intergovernmental organization with 172 countries and the European Union. Its Renewable Energy Statistics is a reference dataset on how much renewable power capacity has been installed around the world. IRENA gathers the figures each year from national statistical offices, energy ministries, and industry associations, and fills gaps from official reports. The data covers almost every country from 2000 to 2025, broken down by technology: solar, wind, hydropower, bioenergy, geothermal, and others. The chart shows the total solar capacity installed in each country, in gigawatts. Note that the figures are cumulative: they count every panel still in operation, not only those added in a given year. The world added more than 500 gigawatts of solar in 2025 alone — more than twice all the solar capacity that existed anywhere in 2015. China alone accounts for half of the world’s cumulative total, with 1,200 gigawatts. Our principal data scientist Pablo Rosado recently updated our charts with IRENA’s July 2026 release, which adds data for 2025. In the same pass, he updated two other IRENA datasets we rely on: the cost of electricity from renewable plants, and patents in renewable energy technologies.

Explore all of our data and research on smoking across the world: ourworldindata.org/smoking Other sources & data: ourworldindata.org/grapher/share-…

Around one-fifth of adults in the world use tobacco. But large gaps often exist in smoking rates between genders. Globally, more than one-third of men use tobacco, while less than one in ten women do. Men are more likely to use tobacco in almost every country in the world. You can see this on the chart, which plots the share of men (on the vertical axis) versus the share of women (on the horizontal axis). Nearly all countries lie above the diagonal line, which means more men do so. This data is collated and published by the World Health Organization. It’s based on adults aged 15 years and older and includes all tobacco products. In most countries, smoking is the main form of tobacco use, but in some, smokeless or chewing tobacco is more common. (written by @_HannahRitchie and @parriagadap)

Read the article by @_HannahRitchie: ourworldindata.org/is-organic-far…

📝 New article on Our World in Data: Is organic farming better for the environment than conventional farming? One of the most common questions we’re asked about food systems is whether organic farming is better for the environment than conventional methods. We wrote about this many years ago, but wanted to revisit this question and answer it based on the most recent available studies. The very clear takeaway is that there is no clear-cut winner. Organic farming tends to perform better on ecotoxicity metrics and can support more biodiversity on a given farm. Conventional farming consistently wins in land use; it achieves higher yields, so it requires less land to grow a given amount of food. On impacts such as greenhouse gas emissions and water pollution, organic farming tends to win per hectare. But because it achieves lower yields, this benefit disappears when we compare it per kilogram of food. When it comes to carbon emissions, there is no obvious winner. The largest differences we see are between different types of foods. The environmental impacts of beef or pork, for example, are far higher than those of plant-based foods, regardless of whether they’re organic or conventionally farmed. The key limiting factor for organic farming is land use. A future with more organic farming and less agricultural land than today would only be possible with larger shifts toward more plant-based, less land-hungry diets.

Read Hannah's article on how much energy data centers and artificial intelligence use: ourworldindata.org/how-much-energ… Other sources & data: qz.com/us-states-data… powering-intelligence.epri.com/executive-summ… cso.ie/en/statistics/…

Around 5% of electricity in the United States is used for data centers — far more than the global average. Around 1.5% of the world’s electricity was used for data centers in 2025. People are often surprised by how low this number is. While data centers are a relatively small share of global electricity demand, this is not true everywhere. You can see the differences across several world regions in the chart. The United States is home to the largest share of the world’s data centers. In 2025, they consumed around 5% of the country’s electricity. But demand is even more localized than this. There are numerous states where data centers represent more than 10% of power demand. In Virginia, it’s over a quarter. Even in Europe, this demand is very concentrated; beneath its 2% figure is Ireland, where data centers consume over 20% of electricity. This local concentration of demand — combined with the speed at which AI is progressing — puts pressure on grids, even if electricity demand is not overwhelming at the global level. (written by @_HannahRitchie)

Read the article by @_HannahRitchie: ourworldindata.org/stunting-defin…

Stunting is one of the leading measures used to assess childhood malnutrition. It indicates that a child has failed to reach their growth potential as a result of disease, poor health, and malnutrition. A child is defined as “stunted” if they are too short for their age. Stunting is not just an issue during childhood. It affects both physical and cognitive development – impacts that can persist throughout someone’s life. Stunting is measured based on a child’s height relative to their age. The World Health Organization sets out global growth curves — these show the expected trajectory of a child’s growth from birth through to adulthood. Of course, we would not expect everyone to be exactly the same height — there are a range of factors, such as genetics, which influence our height and are not a reflection of poor health or malnutrition. These growth curves, therefore, span a range of heights, with an ‘acceptable’ range of two standard deviations above and below the median. A child whose height falls below the bottom of that range — that is, two standard deviations below their expected height for their age — is defined as “stunted”. In a population, the prevalence of stunting is defined as the share of children under five years old who fall two standard deviations below the expected height for their age. Stunting can occur throughout childhood, but is largely determined by a child’s “first 1,000 days”. This stretches from the period just before conception through to the child’s second birthday. This is when a child experiences their most rapid phase of growth and development.

Compare China against other countries across dozens of indicators in our country profile: ourworldindata.org/search?countri… Other sources & data: ourworldindata.org/grapher/resear… ourworldindata.org/data-insights/… ourworldindata.org/grapher/labor-…

China only just missed the income cutoff to become a high-income country this year. In July every year, the World Bank sorts countries into income groups based on their per capita gross national income (GNI) in the previous year. In this year’s update, China was very close to entering the high-income group: its GNI per person was $14,230; just short of the World Bank’s high-income threshold of $14,375. The chart puts this in perspective. The bars show GNI per person for countries with at least 25 million people, ordered from poorest to richest. Beyond income, China is already comparable to high-income countries in many dimensions. Its spending on research and development as a share of GDP, for example, is higher than in many European countries. It’s also a global leader in several technology fields, including clean energy and artificial intelligence. But in other ways, China is closer to middle-income countries. Its productivity, measured by GDP per hour worked, for example, remains much lower than in high-income countries. (written by @EOrtizOspina)

Explore the interactive version of this map: ourworldindata.org/grapher/public…

The World Bank’s Worldwide Bureaucracy Indicators (WWBI) is a key dataset that helps us understand employment and wages in the public sector: how many people work there; their age, gender, and education; how their pay compares with the private sector; and more. The World Bank bases these figures on household and labor force surveys and administrative records. The WWBI covers around 200 countries and economies and has data going back to 2000, though coverage varies by indicator. The map here shows one of the WWBI’s key indicators: public sector employment as a share of total employment. Because that total includes the self-employed, the share is smaller in countries where many people work for themselves, as is the case in much of South Asia and Sub-Saharan Africa. Our data scientist @parriagadap recently updated this chart with the latest WWBI release, which adds data for 2021 and 2022 for a handful of countries and earlier years for many more. Because these surveys aren’t run every year, most countries’ latest data is from 2020 or earlier, and the map shows each country’s most recent year since 2012.