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Over 1 Billion People Now Have Obesity, Study Finds: What To Know About Global Weight Trends

Obesity rates severely increased between 1990 and 2022 while rates of underweight people decreased in most countries, according to a new study, and the researchers believe access to more nutritious foods is the key to simultaneously decreasing obesity while tackling the remaining rates of underweight. KEY FACTS Global obesity rates among adult women more than doubled between 1990 and 2022, while rates among adult men tripled, according to a study published Thursday in the Lancet; childhood obesity rates were four times higher in 2022 compared to 1990. The nations of Tonga and American Samoa had the highest adult female obesity rates, while Nauru and American Samoa had the rates among adult males, making up 60% of each population; Niue and the Cook Islands had the highest childhood obesity rates, where over 30% of kids have obesity. Obesity rates among U.S. women more than doubled from 21.2% in 1990 to 43.8% in 2022, while obesity rates among men soared from 16.9% in 1990 to 41.6% in 2022, putting the U.S. at No. 36 for highest female obesity rates and the 10th highest for male obesity rates. The U.K. ranked 87th for highest female obesity rates and 55th for highest male obesity rates, and China ranked the 11th lowest for women (190th highest) and the 52nd lowest for men (142th highest). Childhood obesity rates in the U.S. increased from 11.6% to 19.4% in girls—the 22nd highest—and from 11.5% to 21.7% in boys, making it the 26th-highest country. The U.K. ranked 72nd for highest childhood obesity rates among girls and 91st among boys, while China ranked 99th lowest (102nd highest) for girls and 70th highest for boys. KEY BACKGROUND Obesity and underweight are both forms of malnutrition, according to the World Health Organization. Climate change, the Covid pandemic and the war in Ukraine could potentially be causing a rise in malnutrition “by increasing poverty and the cost of nutrient-rich foods,” Guha Pradeepa, study co-author from the Madras Diabetes Research Foundation, said in a statement. The study researchers believe increasing access to nutrient-rich foods is needed to address the remaining underweight numbers while tackling the rise in obesity. The combined prevalence of both forms of malnutrition has increased in most countries—with the exception of some sub-Saharan African and south and southeast Asian countries—mainly driven by the global rise in obesity, according to the Lancet study’s authors. Both forms of malnutrition have detrimental effects on health. Being overweight or obese increases risk of death, high blood pressure, type 2 diabetes, stroke, high cholesterol, several types of cancers, coronary heart disease, sleep apnea, gallbladder disease and mental health issues like depression and anxiety. Being underweight increases the risk of bone less, delayed wound healing, nutrient deficiencies, anemia, heart irregularities, bone vessel disease and the loss of periods, troubles getting pregnant, depression and osteoporosis in women. BIG NUMBER 1 billion. That’s how many people globally were living with obesity in 2022, according to the Lancet paper. That’s 879 million adults, and 159 million children. SURPRISING FACT The number of adults who were underweight dropped by more than 50% in the same timeframe. The number of underweight girls fell by about 20% and underweight boys fell by around 33%, according to the study. Eritrea and Timor-Leste had the highest rates of underweight women, and Ethiopia and Eritrea had the highest rates of underweight men, totaling 20% of the adult populations in each country. Countries with the highest prevalence of underweight girls were India and Sri Lanka and India, and Niger for boys, where over 15% of children lived with obesity. CRUCIAL QUOTE “Getting back on track to meet the global targets for curbing obesity will take the work of governments and communities, supported by evidence-based policies from WHO and national public health agencies,” ​​Tedros Adhanom Ghebreyesus, WHO director-general, said in a statement. “Importantly, it requires the cooperation of the private sector, which must be accountable for the health impacts of their products.” TANGENT Though research is limited, there have been theories that the Covid pandemic worsened obesity. A study done on high-income countries found the pandemic resulted in a slight rise in obesity, while research done on low- and middle-income countries found diet quality and food scarcity worsened after the pandemic. However, the Lancet study authors are unsure “whether these effects are transitory or permanent.”

  • 6 March, 14:33
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These Earrings Can Monitor Your Temperature

University of Washington (UW) researchers have developed the thermal earring, a new wearable they say outperforms smartwatches in measuring a wearer’s skin temperature during periods of rest. The earring has also shown promise for monitoring signs of stress, eating, exercise, and ovulation, according to a statement. UW’s prototype smart earring—which is not currently commercially available—is about the size and weight of a small paper clip and boasts a 28-day battery life. A magnetic clip attaches one temperature sensor to a wearer’s ear, while a second sensor dangles below it and estimates room temperature. The second sensor can include fashion designs made of resin or gemstones, without negatively affecting its accuracy. The earring contains a Bluetooth chip, a battery, two temperature sensors, and an antenna. After reading and sending a person’s temperature, it goes into deep sleep to save power. “I wear a smartwatch to track my personal health, but I’ve found that a lot of people think smartwatches are unfashionable or bulky and uncomfortable,” said Qiuyue (Shirley) Xue, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering, in a statement. “I also like to wear earrings, so we started thinking about what unique things we can get from the earlobe,” added Xue, who coauthored a study on the thermal earring published earlier this year in a technology journal. “We found that sensing the skin temperature on the lobe, instead of a hand or wrist, was much more accurate. It also gave us the option to have part of part of the sensor dangle to separate ambient room temperature from skin temperature.” Xue’s statement said that “current wearables like Apple Watch and Fitbit have temperature sensors, but they provide only an average temperature for the day, and their temperature readings from wrists and hands are too noisy to track ovulation.” Eventually, Xue said, she hoped to develop a full jewelry set for health monitoring. “The earrings would sense activity and health metrics such as temperature and heart rate,” she explained, “while a necklace might serve as an electrocardiogram monitor for more effective heart health data.”

  • 27 February, 08:25
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Using AI, MIT researchers identify a new class of antibiotic candidates

Using a type of artificial intelligence known as deep learning, MIT researchers have discovered a class of compounds that can kill a drug-resistant bacterium that causes more than 10,000 deaths in the United States every year. In a study appearing today in Nature, the researchers showed that these compounds could kill methicillin-resistant Staphylococcus aureus (MRSA) grown in a lab dish and in two mouse models of MRSA infection. The compounds also show very low toxicity against human cells, making them particularly good drug candidates. A key innovation of the new study is that the researchers were also able to figure out what kinds of information the deep-learning model was using to make its antibiotic potency predictions. This knowledge could help researchers to design additional drugs that might work even better than the ones identified by the model. “The insight here was that we could see what was being learned by the models to make their predictions that certain molecules would make for good antibiotics. Our work provides a framework that is time-efficient, resource-efficient, and mechanistically insightful, from a chemical-structure standpoint, in ways that we haven’t had to date,” says James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering. Felix Wong, a postdoc at IMES and the Broad Institute of MIT and Harvard, and Erica Zheng, a former Harvard Medical School graduate student who was advised by Collins, are the lead authors of the study, which is part of the Antibiotics-AI Project at MIT. The mission of this project, led by Collins, is to discover new classes of antibiotics against seven types of deadly bacteria, over seven years. MRSA, which infects more than 80,000 people in the United States every year, often causes skin infections or pneumonia. Severe cases can lead to sepsis, a potentially fatal bloodstream infection. Over the past several years, Collins and his colleagues in MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) have begun using deep learning to try to find new antibiotics. Their work has yielded potential drugs against Acinetobacter baumannii, a bacterium that is often found in hospitals, and many other drug-resistant bacteria. These compounds were identified using deep learning models that can learn to identify chemical structures that are associated with antimicrobial activity. These models then sift through millions of other compounds, generating predictions of which ones may have strong antimicrobial activity. Experiments revealed that the compounds appear to kill bacteria by disrupting their ability to maintain an electrochemical gradient across their cell membranes. This gradient is needed for many critical cell functions, including the ability to produce ATP (molecules that cells use to store energy). An antibiotic candidate that Collins’ lab discovered in 2020, halicin, appears to work by a similar mechanism but is specific to Gram-negative bacteria (bacteria with thin cell walls). MRSA is a Gram-positive bacterium, with thicker cell walls. “We have pretty strong evidence that this new structural class is active against Gram-positive pathogens by selectively dissipating the proton motive force in bacteria,” Wong says. “The molecules are attacking bacterial cell membranes selectively, in a way that does not incur substantial damage in human cell membranes. Our substantially augmented deep learning approach allowed us to predict this new structural class of antibiotics and enabled the finding that it is not toxic against human cells.” The researchers have shared their findings with Phare Bio, a nonprofit started by Collins and others as part of the Antibiotics-AI Project. The nonprofit now plans to do more detailed analysis of the chemical properties and potential clinical use of these compounds. Meanwhile, Collins’ lab is working on designing additional drug candidates based on the findings of the new study, as well as using the models to seek compounds that can kill other types of bacteria.

  • 13 February, 11:50
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