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Provided by Eat This, Not That! trader joes cashier in face mask

The next time you go to the grocery store, you might want to consider thanking the checkout person for their service. At the same time, you'll want to make sure you're doing so while wearing a mask and standing at a healthy social distance, as a new study published in the scientific journal Occupational&Environmental Medicine suggests the COVID-19 virus hit these frontline workers especially hard.

To address what they characterize as a knowledge gap regarding how COVID-19 has impacted retail workers, the study, led by Justin Yang, M.D., of Harvard T.H. Chan School of Public Health in Boston, chose a single grocery store in the Boston, Massachusetts area and tested its employees for COVID using nasal swabs. The researchers then spent several days assessing the employees' health history, anxiety levels, and perceptions about COVID.

Dr. Yang's team found that out of the 104 grocery store workers, 21 tested positive (20%) for COVID-19. Of those who tested positive, 91 percent had a job that involved direct interaction with customers, and 76 percent showed no symptoms (whereas only 40% of the general population are asymptomatic when infected). (In other health news, check out these 108 Most Popular Sodas Ranked By How Toxic They Are.)

According to the scientists' data, those grocery store workers with direct exposure to customers were five times more likely to test positive than their back-office colleagues.In addition, 24 of the workers were found to have anxiety. Eight were found to have depression. The study authors noted that those whose jobs permitted them to practice social distancing were significantly less affected by anxiety and depression than their colleagues.

Scientists had already known that essential workers, including grocery store employees, are at an increased risk for the SARS-CoV-2 infection. They also knew that those workers are at an increased risk of spreading the virus to their friends, families, and communities. What the scientists did not know until reviewing the numbers was exactlyhowbad the infection rate can be.

While the study is limited by the small number of test subjects, among other things, the authors believe that the findings support "policyrecommendations that employers and government officials should take actions on implementing preventive strategies" to ensure the health and safety of essential workers.

In the meantime, here are 10 things you can do to make it safer for your local grocery store's employees, not to mention yourself. And here is the one thing you absolutely need to stop doing at the grocery store.

Read the original article on Eat This, Not That!

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20 Percent of Grocery Workers Went To Work With COVID, Study Says - msnNOW

Former members of alleged sex cult Nxivm have spoken out about founder and leader Keith Raniere's various manipulation tactics, like providing family secrets and notarized house deeds under the guise of personal accountability.

During Raniere's lifetime prison sentence hearing on October 27, former members talked about Raniere's request for diet restriction among multiple women members, including those in Nxivm's secret sorority DOS.

According to India Oxenberg, who executive produced the docuseries "Seduced" about her seven years in the cult and two years as a DOS sex slave, Raniere framed diet restriction as the ultimate show of self-improvement and convinced some followers to believe that.

In reality, Raniere restricted women's diets to make them look more child-like, Oxenberg said during her victim impact statement at the sentencing.

Oxenberg, who was also branded with Raniere's initials, isn't the only former Nxivm member to say Raniere restricted her diet.

When Ivy Nevares defied Raniere's strict diet, eating pumpkin seeds to stave off her hunger, he became angry, Nevares said during her own victim impact statement.

Camila, who didn't share her last name during her testimony, said Raniere raped her when she was 15 and he was 45. She said Raniere was obsessed with her weight for the entirety of their relationship, which lasted until she left Nxivm at 27.

"From the time we started having sex, he would ask me my weight every single day," Camila said at Raniere's sentencing. "This continued into my adulthood. His goal for me was to be 100 pounds or less."

During an appearance on Dr. Oz that airs October 29, former member Tabby Chapman said Raniere falsely told her diet restriction was a useful tool for self-improvement.

"I was originally food-restricted because Keith had everyone convinced that the fastest way to work your issues was to work your relationship with food," Chapman told Oz.

She said she often wondered how eating fewer calories would lead her to business success, but continued to eat between 500 and 900 calories daily as Raniere requested.

Bonnie Piesse, a former member, left Nxivm when she noticed various women were restricting their food intake and looked dangerously underweight, she said in HBO's docuseries "The Vow." She said one of those women was "Smallville" actress Allison Mack, who recruited Oxenberg and others into DOS. Mack now awaits her own sentencing, and pleaded guilty to racketeering for her involvement in the cult.

Raniere, 60, was sentenced to 120 years in prison after being found guilty of child sex trafficking and conspiracy to commit forced labor.

If you or someone you know is struggling with an eating disorder, you can call NEDA's Helpline (1-800-931-2237) on weekdays for support, resources, and information about treatment options. In crisis situations, NEDA offers 24/7 support just text "NEDA" to 741-741.

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Ex-members of Nxivm say leader Keith Raniere brainwashed women into starving themselves - Insider - INSIDER

Staying at home has never felt as good as before. But it also adds on the kilos. The virus has forced people to turn to technology as a solution to better health, physical and mental, in more entertaining ways than just pushups on the bedroom carpet.

YouTube workout videos of Leslie Sansone and Lucy Wyndham tell you how to walk in one place at home and sweat it out. Tarun Gills tough fitness videos.

And then there are FitTuber and Beer Biceps. Bicycle helmets with wireless backup and 3D modelling.

The Apple Watch has a heart monitor, which alerts you of an impending heart attack.

Garmin Venu sells a smartwatch boasting health tracking for various functions, including menstrual cycles. Drone racing gets the body parts moving.

Drones are integrated into outdoor fitness and exercise programmes or used in the home gym to capture a 360 view of training and performance, constantly reviewing, adjusting and urging you to push the envelope.

Holographic tennis and workout podcasts are new regimens. Amaresh Ojha, CEO & Founder, Gympik, observes, Podcasts offer the right counselling on health and fitness by industry professionals. Food and nutrition or weight loss and muscle gain, podcasts bring the latest news in wellness and fitness trends.

Got a pool at home? Alternate Augmented Reality (AR) Form goggles with a Google Glass head-mounted display strapped to your eyes.

The accelerometer in the goggles tracks strokes and speed in real time to monitor metabolism during aquatic AR. E-sports are the new frontier in muscle construction.

Diksha Chhabra, Fitness Expert, Nutritionist & Founder, Diksha Chhabra Fitness Consultation, notes, A client of mine who had no time confessed the online programme gave her better results. She did not miss her exercises and she was emailed the schedule in advance with the necessary instructions and guidelines.

Nintendos home workout kits combine legendary villains with a silent Adventure mode.

Then there is the ultimate rock star in the digital wellness spaceArtificial Intelligence (AI). AI-based personal trainers integrated with wearable devices follow and correct workout posture and provide real-time feedback like a trainer does.

You can also customise lifestyle and diet with AI apps such as Millie Fit and Aaptiv Coach. There are apps such as Lifesum that integrate your diet with lifestyle habits to help you achieve your health and fitness goals. Most of them can be paired with other health apps such as Apple Health, Fitbit, Google Fit and Withings.

Theres more to wearable tech than watches. Nocturnal tech to save cyclists and bikers from careless drivers is getting more sophisticated by the day.

A unique jacket has a cape sphere4,000 glass globes embedded in each sq cm that reflect and scatter light. During the day, it has a psychedelic look with shifting metallic sheens of colour.

Another has phosphorescent membranes to catch and store light: the stronger the light the brighter the glow. Strobe-lit spheres clipped on to your shoes warn errant motorists when you are on a jog.

Many apps are built with data gathered from professional athletes. BlazePod, a Bluetooth flash reflex training system, uses reaction-training lights, and works by tapping touch-sensitive pods with your hands, knees, or feet during a workout.

The pods light up in different colours during the exercise, signalling reaction time, coordination, balance, and strength. E-games cater to every need.

The Stealth Plankster acts on your core using a balance board plugged into a cellphone and works out up to 29 muscles.

Virtually the best

The most exciting universe in e-exercise is Virtual Reality (VR), which is pushing boundaries of gadgets and games.

This essentially involves pulling on a VR headset attached to a computer or a cellphone to run apps and games, hands-free or connected.

Top-quality headphones and hand-controllers that operate specially designed treadmills enhance simulated experiences of being in another world.

As you play, your body moves fast with the controllers applying real-world gestures in the game or app. Standard gaming joypads are cheaper.

There are special app stores to browse and download games and apps on the VR device itself. Some VR games stores can be browsed on the computer.

Many built-for-VR games such as Beat Saber, Iron Man VR or Star Trek: Bridge Crew do not really work anywhere else except on their download gadgets.

Facebook-owned company Occulus has launched Occulus Quest 2, the most sophisticated VR gadget available at present. Strap it to your head using rubber and Velcro straps, and youre ready to go. Its field of vision and higher refresh frame rate make the screen expansive and crisp with improved resolution.

The headset features 6GB of memory and uses Qualcomms Snapdragon XR2 chipset. Hand recognition is smooth. HTC Vive, its direct rival, has singular features, including a front-facing camera to bring the real world into your virtual world using specific apps.

Two hand-worn gestural controllers and a base station track your movements inside VR space. The greatest advantage of VR workouts is data.

The aquatic AR goggles use data collected from a multitude of champion swimmers to monitor user performance.

VR is a gift to the routine exercise buff, since it breaks the monotony of regular gymming, which has anyway been put off due to the pandemic.

You can upload an immersive boxing VR game on your headset to duck and weave, and burn calories because you are in the game.

The Virtual Reality Institute of Health and Exercise that researches the effect of VR on the body has concluded that these workouts with the right games burn more calories than sweating out in a conventional gym.

Being an internet device, you can play with people across the world. Rookies in the gym are often subjected to self-conscious gymtimidationa term that defines people ashamed of their physical shape and ignorance of weights and routines in a gym.

This is no longer a problem with VR. You can download avatars like in computer games that hide your identity while looking like Salman Khan.

This is a great psychological leg-up since you are essentially competing with yourself. A study by the USs National Center for Biotechnology Information suggests that VR exercise has a positive impact on an individuals physiological, psychological, and rehabilitative outcomes compared to traditional exercise. Sanjay Sehgal, CEO, MSys Technologies Pvt Ltd, says, VR workouts can be done on rowing machines, exercise bikes, resistance cords, and elliptical machines at home or in the gym.

This combination of the complete immersion and dedication helps people to forget that they are working out. The gamification and competition encourage them to push the limits, making the experience more appealing. Like Rishi Baveja, Co-Founder, BoxFit, admits that he gained a lot of weight during the lockdown. He got back into shape using online training.

We conducted a survey which suggested 84 percent of people would continue with online workouts even once everything opens again, he says. Some apps such as Box VR and Dance Central enable high-impact workouts. Sanjeev Singhai, Founder, Wellnessta explains, In a VR workout, the environment is completely replaced by digital surroundings. The thought that you can be shipped to a lovely area like the Swiss Alps for your next bicycle ride, as opposed to gazing at the sweat-soaked back of your fellow gym mate is motivating.

App you like it

There are many apps that monitor weight and suggest lifestyle changes. G Nivedith, travel and tech blogger from Bengaluru, weighed 126 kg in March 2020. My body fat was 46 percent. After some online research, I made my low carb-high protein diet plan and focused on losing fat without losing muscle. I bought an Omron weighing scale with the Omron connect app that gave me indicators like body mass index, visceral fat and other parameters. I now weigh 75 kg, losing 51 kg over the last seven months, he explains. Sohini Ghaie, video creator and a freelance publicist, also tracks her calories using an app, Healthifyme. I was so excited when I saw Nora Fatehi conduct a dance session of 30 minutes on Cure.fit. Gyms do not give you that sense of satisfaction because you get a complex while your gym trainers compare you with the others who are working out, she says.

The ability to track and quantify health parameters is also serving as a motivation to get fit. Nikhil Arora, Vice President & Managing Director, GoDaddy India, who has been following an exercise and running regimen for over a decade, now uses fitness tech to calibrate his workouts based on input parameters such as running cadence, speed, distance, heart rate, calorie burn rate, and output or performance metrics like VO2 max (a kind of oxygen efficiency parameter), weight loss and calorie density.

Ive always believed that you cant manage what you cant measure. Technology gives people a lot more control over their fitness by giving them access to a whole lot of data about their regimen and health. This, in turn, makes them more independent and self-driven. I use technology to track basic health metrics such as hydration levels, sleep cycles and stress. Being able to measure this data has given me a lot more confidence to keep trying out new stuff and see what works best, says Arora.

Mallika Parekh, MS, MPH, owner of Physique 57 India, notes, We are in the middle of launching a Video on Demand platform, which will allow clients to do shorter workout bursts using specially applicable scientific methods, pause and rewind when required, and not stick to a schedule if they choose. These videos will be accessible through social media channels as well as app stores.

FITTING ANSWERSZoom is not just meant to hold meetings; it also helps you get fit on your phone or computer. Celebrity fitness coach Shivoham observes, Ive been using Zoom and Instagram for my classes and clients. We will be coming up with something more user-friendly and personal soon. If you have an eye for detail and are good at communication, then virtual classes are great for you. Decathlon launched self-powered bikes and ellipticals to help users practice in any environment.

With Kinomap (a fitness reality application), users can connect their fitness equipment with this reality software to experience running a marathon in Delhi or rowing on a beautiful lake, or even participate in Tour de France, says Jade Dutta, Omni Merchandiser, Domyos, Decathlon Sports India. Incidentally, Decathlons All For Sports platform provides various fitness live sessions for users to stay fit at home. Sumaya Dalmia, celebrity trainer, fitness and wellness expert, adds: The pandemic has really forced people to look at virtual fitness differently and online fitness. When we didnt have a choice, people had to learn how to connect with the trainers online like kids have learnt how to study on Zoom. Likewise, we have learnt how to do a Zoom workout or an online workout. Numerous gyms are presently streaming expertly trained classes through apps that permit clients to reproduce the experience of individual instruction with a mentor through their earphones.

There are workouts that cater to all ages, metabolic capacities, illnesses and even time constraints. From five minutes of intense HIIT to 90 minutes of relaxing yoga, all are now available with the click of a button. Yoga expert Samiksha Shetty explains, While online fitness was already happening on a smaller scale, it has become the go-to for the past eight months. It allowed people to change a common belief system that working out is only worth its while when you are in a specific kind of environment. Timing matters.

Dr Nila Paul, who works at Vellore Government Hospital and has been with F45 Neelankarai (a gym in Chennai) for the past six months, agrees, Being a doctor, the timings of the sessions have been very convenient as I spend most of my day at the Covid-19 wards at Vellore. The 45-minute morning cardio sessions with F45 Neelankarai gives me the mindset to go out and conquer the world. Workouts are modified as per my fitness level every day and the trainers make it a point to challenge me constantly. With growing awareness on mental health, people are more mindful about the vitality of yoga and breathwork. Its also easy on the wallet.

Grin and wear it

Wearable technology such as smartwatches and fitness bands has been around for a while, being constantly upgraded to become more accurate than before. Since the appetite for data is increasing each day, we are seeing innovation and better application of technologies that push the limits to improve overall health and fitness with personalised regimens. Privacy and security protocols must be prioritised to make tech safe, says Darshan Lama, Chief Commercial Officer, Question Whats Real (QWR). According to Forbes, the wearable technology industry is estimated to be over $27 billion by 2022. Vishal Gondal, Founder & CEO, GOQii, points out, Wearables that include fitness trackers, smartwatches, heart rate monitors and GPS tracking devices help in the monitoring and tracking of Covid-19 symptoms.

The future of personal tech is invisible wearables. Super thin and almost transparent gadgets with powerful sensors combined with AI that download genetic and other data are being tested in labs. Harvard-MIT researchers have come up with a smart tattoo with sensors powered by subcutaneous fluids. As celebrity motivational speaker Jim Rohn advised, Take care of your body. It's the only place you have to live. Log in for better health.

Virtual Reality

Involves pulling on a VR headset attached to a computer or a cell phone to run apps and games, hands free or connected. Top-quality headphones and hand controllers that operate specially designed treadmills enhance simulated experiences of being in another world.

Built-for-VR gamesBeat Saber, Iron Man VR or Star Trek: Bridge Crew

Facebooks Occulus Quest 2 is the most sophisticated VR gadget available at present. Strap it to your head using rubber and Velcro straps, and youre ready to go.

HTC Vive has singularfeatures, including a front-facing camera to bring the real world into your virtual world using specific apps.

Virtual trainers

Stealth Plankster works on your core using a balance board plugged into a cellphone and works out up to 29 muscles

BlazePod, a Bluetooth flash reflex training system, uses reaction-training lights, and works by tapping touch-sensitive pods with your hands, knees, or feet during a workout

Decathlons self-powered bikes and ellipticals make practice possible in any environment. With Kinomap app, users can connect their equipment with this reality software.

Podcasts

Holographic tennis and workout podcasts are new regimens. Podcasts offer the right counselling on health and fitness by industry professionals. Food and nutrition or weight loss and muscle gain, podcasts bring the latest news in wellness and fitness trends.

Online Workout Sessions

Numerous gyms are presently streaming expertly trained classes through apps such as Zoom and Instagram that permit clients to reproduce the experience of individual instruction with a mentor through their earphones.

There are workouts that cater to all ages, metabolic capacities, illnesses and even time constraints. From five minutes of intense HIIT to 90 minutes of relaxing yoga, all are now available with the click of a button.Decathlons All For Sports platform provides various fitness live sessions for users to stay fit at home.

Wearables

Bicycle helmets with wireless backup and 3D modelling

The Apple Watch has a heart monitor, which alerts you of an impending heart attack. Garmin Venus smartwatch boasts health tracking for various functions, including menstrual cycles.

Google Glass: The accelerometer in the goggles tracks strokes and speed in real time to monitor metabolism during aquatic AR.

AI-based personal trainers, integrated with wearable devices, follow and correct workout postures real-time

Nocturnal tech to save cyclists and bikers from careless drivers is getting more sophisticated by the day. A unique jacket has a cape sphere4,000 glass globes embedded in each sq cm that reflect and scatter light. During the day, it has a psychedelic look with shifting metallic sheens of colour. Another has phosphorescent membranes to catch and store light. Strobe-lit spheres clipped on to your shoes warn errant motorists when you are on a jog.

App-ropriate for Fitness

Aaptiv Coach Comes with a virtual personal trainer known as Coach for every individual with different fitness goals

Lifesum Integrates your diet with lifestyle habits to help you achieve your health and fitness goals

Ring Fit Adventure The latest fitness game for Nintendo Switch blends exercise routines with adventure

Fitness Boxing Its more like kickboxing and helps you tone your arms and upper body

Burn It Up The Zumba session allows you to have a private session at home, with 30 different kinds of classes and lessons

Wii Fit Plus Helps you work on the aerobics and exercise part. There are multiplayer activities that allow one to play and do workouts with friends.

Healthifyme Provides services such as calorie tracking, one-on-one nutrition and fitness coaching, and diet and workout plans

Millie Fit The AI-powered, on-demand virtual fitness trainer offers live feedback and correction during workouts

Omron Connect Works together with Omron health devices to help you manage your health data. It gives indicators such as body mass index, visceral fat and other parameters.

Box VR Brings music-enhanced, boxing-inspired workouts to VR gaming

Dance Central Tracks your estimated calories burned as you play

Drones

These flying machines are integrated into outdoor fitness and exercise programmes or used in the home gym to capture a 360 view of training and performance, constantly reviewing, adjusting and urging you to push the envelope.

E-sports

Nintendos home workout kits combine legendary villains with a silent Adventure mode

See the rest here:
The WiFi fit list: Virtual training apps, sessions to help you combat weight gain amid COVID house arrest - The New Indian Express

Extra emission controls, but with a difference.

In efforts to keep diesel-fuelled engines on the right side of emissions laws, manufacturers are turning to more and more aggressive means of reducing the kind of bad stuff coming out of the tailpipe.

And when things like exhaust gas recirculation and diesel particulate filters arent cutting the mustard, something called selective catalytic reduction (SCR) is employed.

Such technology is particularly prevalent in European vehicles, where ever-tightening emissions laws are forcing the hand of manufacturers.

So, what is it? And how does it work?

AdBlue is a trading name that has gone into common vernacular, like Hoover and Kleenex. A more common name is diesel exhaust fluid (DEF), which enables that process called selective catalytic reduction. In particular, it targets your exhaust's nitrogen oxide (NOx) content and looks to reduce it.

Essentially, a bunch of sensors in your exhaust system monitor the contents of your exhaust gasses. When required, a spray of DEF is injected into the exhaust system.

This fluid, which is a solution of urea and distilled water, causes a reaction. Urea contains ammonia, which reacts with the nitrogen oxide inside a catalyst and breaks it down. So, instead of nitrogen oxide leaving the tailpipe, its nitrogen and water.

DEF consumption is typically very low, around 25 per cent of your fuel consumption. For example, a Ford Everests 18-litre tank will cover 2400km of driving. Other vehicles will have enough range to only require top-ups at service time.

However, its worth knowing that under law, a vehicle with an empty DEF fluid tank will not start. And under hard working conditions (like four-wheel driving and towing), consumption will increase along with your fuel consumption. Dont get caught out; its just as bad as having no fuel.

This technology has allowed diesel-powered vehicles to remain on sale in some markets, but has also allowed manufacturers to turn up the wick, so to speak, with efficient and high-performance diesel-powered vehicles. Heres looking at you, Audi SQ5.

While most vehicles have a filler point next to the fuel tank, they are sometimes tucked away in the boot. Its worth knowing where your filler point is, and knowing how to check on the level. Often, its hidden somewhere within your multifunction display.

Not all diesel-powered vehicles require this system, and it depends mostly upon emissions laws for particular vehicles in different markets.

For example, Volkswagens early and higher-specification Amaroks with 580Nm made in Hannover Germany have selective catalytic reduction. As production has been taken over by the Argentine factory at Pacheco, the additional emission controls were removed.

As time rolls on, the availability of diesel exhaust fluid (or AdBlue) is becoming greater and greater. While some of your country and outback servos might be a bit hit-and-miss, the fact that many trucks have SCR means you should be able to find it in most places these days.

Some service stations will have AdBlue available through a bowser, which often works out to be the cheapest way to top up. Other service stations (and auto stores) will have bottles in various sizes. This is handy if you want some spare in the boot for that long road trip you are planning.

For example, Caltex has 130 locations around Australia with AdBlue available at the pump, along with 330 additional locations with bottles.

Diesel exhaust fluid has a shelf life of 12 months. We arent sure how bad out-of-date stuff is, but if youve got an ageing bottle sitting around, you might as well dump it in your tank and buy a fresh one.

Diesel exhaust fluid is another complication that serious 4WDers will need to accommodate. Along with calculating your fuel range on big trips, know how long you can comfortably go between DEF refills, and carry some extra with you.

Additionally, depending on how your four-wheel drive is designed, the DEF tank might be in an unprotected location underneath. Consider some additional protection if you're planning on dragging yourself over plenty of rocks, especially if its a plastic tank.

While human urine also contains urea, its only a few per cent (depending on your diet). The concentration isnt strong enough to act as a substitute, and it contains all manner of other things (once again, depending on your diet) that could damage your AdBlue system. Repairs and replacement will cost well in the thousands, not the hundreds.

MORE: Which fuel type do I need? MORE: Fuel economy testing: What is WLTP and how does it work?MORE: The cars with the best (and worst) driving range in AustraliaMORE: All advice stories

What is diesel exhaust fluid (AdBlue), and how does it work?

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What is diesel exhaust fluid (AdBlue), and how does it work? - CarAdvice

Bryan Washington amongst the curry bread and migas. Illustration: Eliana Rodgers

Probably everything, says Bryan Washington, the Houston writer, when asked what he likes about Japanese food. Growing in Houston, he says, you feel like its just normal to have eight cuisines in arms reach, and Washington is a writer whose writing often explores food whether achiote or Japanese curry bread as well as queer life and his hometown. Called a lit world wunderkind by Los Angeles magazine, next week he will publish his debut novel, Memorial, which is about a maybe-ending romantic relationship and set in Houston and Osaka. Already optioned by A24, its his follow-up to the critically acclaimed Lot, for which he was named a National Book Foundation honoree. This past week, Washington spent a lot of his time signing books while watching K-dramas, recipe testing his croquettes (my lifes mission), spoiling his mom with a breakfast of migas with lump crab, and getting dim sum after drive-through voting.

Wednesday, October 14So breakfast was egg curry rice from last nights leftover curry (using the One Meal a Day recipe) that I ate with my boyfriend. I usually end up making boxed curry once a week I buy Golden Curry and get the extra hot because I think its a perfect recipe. Its super-quick, maybe ten minutes of actual work altogether. I usually make a little bit extra because I know Ill either make egg curry rice the next day, or if Im not fucking lazy that week, Ill make kare pan at some point. So, I like making a little more than Ill immediately need. Yeah, no, one curry a week isnt enough, to put it lightly, especially if its a busy week, because its just so quick and so good.

I really like One Meal a Day, and I havent tried a single recipe of theirs that didnt work. I fall into YouTube holes a few times a week, just watching people cook. I think the first OMAD one I saw was for tuna egg rice, but I dont know for sure. I mean, its just really simple, really good. I learned how to make some pretty decent rolled omelettes from them, and theyve got a really good galbi-jjim recipe. And then theres their steamed egg recipe, the drunken egg recipe

Honestly, this was kind of a strange fucking week because Ive been doing a lot of publicity for my novel Memorial, in the middle of our pandemic, so things have been pretty planned out to the hour or whatever. I did some promo after breakfast and had plans to see a friend in the park by the Rothko Chapel: Our social revolutions had been our respective significant others and parents since like March, so this was the first time we were seeing someone that wasnt them in a minute. And there arent a lot of third places in Houston that you dont need to spend cash at, so the park is in a lovely juncture: Youve got the Menil and the Rothko Chapel and a bunch of other museums in walking distance. Ive picnicked out therea lot more this year than I ever have. Its just a really nice vibe. So we ate lunch in the park: bnh m from My Baguettes, nem nng from Nem Nng & Rolls, and c ph sa from Long Coffee.

I really like My Baguettes. Its super-chill. And the nem nng place is right next door, just beside Long. Youve got hella options for boba and iced coffee in Houston, but Long Coffee is one of my favorites, and Im usually there like once a week. And theyre all within walking distance from each other, so it wasnt a a big fucking expedition. So I hit that triangle real quick and then drove back to Montrose, and then my friend and I cried for a bit and smoked for a bit and caught up and snacked on everything.

Ill order the shredded chicken bnh m most days, but, honestly, I think that the croissant sandwich from My Baguettes, with egg and pat and the rest of the fillings, is easily a top-five sandwich in the city. Easily. But I always end up passing through at 3 p.m. or 4 p.m. and by then theyre out of croissants and its always the same routine. Ill show up and ask for a croissant and theyll say, No, we dont fucking have anymore because youre too late. Im just happy to be there though, so it all works out.

That night, my boyfriend and I debated about what to cook or pick up because it was pretty late by the time we started thinking about dinner, so we ended up frying eggs and making rice with some drizzled sesame oil. And, on the side, we had some kimchee from Korean Noodle House. Its this restaurant on Longpoint Drive, super-delicious, and once a week Ill go and pick up a big tub of kimchee, and thatll just be my happiness for the week. I think, even when we were in lockdown lockdown and I was staying home, and we were all really going through it, one thing that Id do every week is pick up that tub of kimchee. It was this one solid thing I could count on, you know? Its just really fucking good.

Thursday, October 15Went to vote with my BF we did the drive-up at NRG Stadium, and it took maybe two minutes, super-organized and fluid and then afterward picked up dim sum from Fungs Kitchen: stir-fried lobster with honey-black pepper, fried squid calamari in spicy salt, Chinese broccoli with oyster sauce, and beef flat rice noodles with gravy.

Were always kind of flirting with the question of whether we actually need to pick up dim sum, because it really is a lot of food, but of course we usually end up passing through. Dim sum always wins. And well end up heading to Ocean Palace or Fungs or this one other place by the 99 Ranch out in Sugarland. So we took that home, because Im not quite sold on actually eating in restaurants just yet. Id rather just pick it up and leave a massive tip.

For lunch, I ate egg noodles and stir-fried shrimp with my BF. They were essentially leftovers from earlier in the week.And then we had leftovers from the dim sum earlier, so this served as fridge clearing in a lot ways. I cook this way pretty often. But, like, what a fucking privilege that your problem is you have to create more room for the food you have, you know? (Which would be a good time to plug the Houston Food Bank and also Mutual Aid Hou.) I hate wasting food. I hate it.

Dinner was breakfast cheeseburgers and fries from M&M Grill, takeout. M&M Grill, theyre really rad. Theyre Arabian-influenced American and Mexican food, but they also do Tex-Mex well, too, and their meat is halal. The breakfast burger is really just a cheeseburger with an egg on it. But its a solid burger and, frankly, I am just an egg person. Theres a cookbook by Rachel Khong called All About Eggs, and when it was published, I was like, This is the best fucking day, because what is better than a cookbook thats literally just egg recipes?

Friday, October 16 Breakfast was French toast made with challah from Three Bros. Bakery; eggs basted with soy sauce; sausage cooked in onions; ate with BF.

Three Bros. is maybe ten minutes from my place; theyre a local chain, and they have really good challah. So the French toast was pretty simple I just cracked an egg with some milk and sugar, mixed all of it, and let the bread chill there for a minute before I fried it up. Then the eggs basted with soy sauce is pretty simple; its fried egg with some soy sauce on it. Saying basted makes it sound like a whole fucking thing, but it isnt. I usually get Aloha soy sauce because I just really like it, but every now and then Ill opt for the usukuchi from Yamasa. Those are usually my two defaults. Ive been using sweet soy sauce lately, too, but Ive been using it sparingly because its a lot, it can overpower a dish. Or maybe Ive just got a sweet tooth.

I cook a lot of French toast though, or at least lately. Ive never cooked as much French toast as I have these past nine months. But its delicious so Im like, Okay, if the rest of this day still fucking sucks, Ill have made French toast. This can be a good thing I can count on. Theres a Chinese restaurant near me called Hong Kong Food Street, where they drizzle the French toast with condensed milk. But I dont do that at my place because I know if I started, no good would come of it. None. Id just never stop.

Im recipe-testing potato korokke for work, so I munched on those solo. Its partly for a piece Im working on, partly because I feel like my lifes mission is just to get this recipe correct. I had it once at a stall beside the Shinjuku Gyoen a few years back, and Ive been chasing the dragon ever since. But croquettes are a good way to practice deep-frying, honestly, because everything is already cooked. So youre just working on adjusting the color and crispiness to your desire. But, yeah, just trying to figure out how to make it do what I want it to do has been a challenge.

Theres a super, super-solid potato korokke recipe over at Just One Cookbook, but Ive been pulling from croquette recipe on Martha Stewarts site, too. So Ive ended up with one thats like a variation of Namis recipe from Just One Cookbook, and a variation of the Martha Stewart recipe, and I use a variation from Jo Cooks, just mixing and matching details. Im trying to figure out how to take different components from all of them and make something that works for me. Its fine if I never get there.

Ive started using lump crab meat instead of beef, which is what I originally used, and Im liking how thats turning out. So I spent much of Friday trying to do that and procrastinating around the promo I have to do. This whole week, Ive been signing a lot of books: There were 70 boxes of Memorial sitting at my place. In the weeks prior, Id just sign the bookplates, and I think there are something like 11,000 signed copies out in the world right now. I dont dwell on the number. So a lot of this cooking was also me just trying not to think about the boxes. I had to do this recipe testing, and thats a certain amount of work, but it was also not opening 70 boxes (which, all jokes aside, is actually a lovely thing to get to do).

My mom stayed with me this evening; she was in the area. I had an Asahi, and she had some wine,and I made her doria, which is pretty similar to gratin rice is the primary base of it. Just like a cream chicken dish over rice. What Ill do is make a creamy chicken stew with somerice on the side, layer the stew on the cooked rice,top it with a little bit of cheese, broil it for a bit, and add parsley. Its deeply comforting.

I also took some marinated onions out of the fridge (Our Korean Kitchen, by Rejina Pyo and Jordan Bourke, has this really great recipe that takes less than five minutes to prep, and it goes really good with grilled meats and Ill find myself making it and holding it and parceling it out), and also made miso soup and a really simple cucumber salad that an old roommate of mine taught me. Usually I make my own dashi, but I wasnt trying to do all of that this evening, so I made the powdered dashi. I started using a bunch of it since everyones been inside, and its less work and still pretty satisfying. We played with my puppy (I have a puppy surprise) and caught up for a few hours.

Saturday, October 17I cooked migas (a variation of Ford Frys recipe) with lump crab meat and salsa de aguacate for breakfast with my mom. When shes over, I usually try to cook a bunch of things, which is to say that it isnt like fucking three-day-old curry.

I usually have tortilla chips in my pantry, and theyre just chilling, waiting for something to happen. And then I had lump crab leftover from the croquettes, so I used that as a protein base and made salsa de aguacate. I moved apartments fairly recently, I guess a month and half ago now, and that experience was actually the seventh level of hell, but my one housewarming gift to myself was a Magic Bullet. I resisted getting it for a while because Im an idiot, but then I got it and it makes life easier. So. I made the salsa with that. And then I also made coffee from Third Coast beans; they have a Laos blend, and its super-good. I had it in Austin for the first time a few months back, so I just buy it whenever I see it now.

After my mom left, I signed about 20 boxes of books, and theres a show called Youns Kitchen, that I had on in the background. Its really lovely. These K-drama actors like, dumb famous in Korea are essentially running a restaurant in Spain. This season I think it was Spain. So I watched that and answered emails and signed for a bit until my wrist started to freak out and then I went to get lunch solo.

Got a croissant sandwich from Nguyen Ngo(another top-five Houston sandwich) and coffee from Tapioca House, this boba shop across the way. I think they just might make my favorite coffee in Houston. Their iced coffees super-dark, but also super-sweet, and they do it in such a way thats just absolutely delicious. So I got two coffees from them, and brought those and the food back to eat while watching Youns Kitchen and then a little bit of Romance Is a Bonus Book, which Ive already seen and love.

Dinner was shrimp tacos that my BF and I cooked. I usually have like two pounds of frozen shrimp in the freezer at all times, because were on the Gulf and shrimp is not prohibitively expensive here. Every few weeks Ill buy a few pounds and cook some them the week of and then freeze the rest in Baggied portions, thawing them whenever I need them.

We made those with a red salsa, some Sriracha, and some cheese, and then we watched the Blackpink documentary, which was cool as hell, and then a few episodes of Greenleaf, which is basicallya K-drama set in Memphis.

Sunday, October 18Woke up pretty late, past breakfast time. I had the rest of the books to sign, because they had to be shipped by Monday, and I would simply have to walk into the ocean if they werent finished, so I made banana-nut scones, and while they were in the oven, I started signing again and queued upsome Ghibli movies in the background. Once the scones were done, I chewed on them with some coffee and alternated between signing and emails.I usually have the coffee concentrate from Lees; its a half-gallon or gallon, basically liquid gold.

I wasnt hungry until later that evening, so dinner was stir-fried eggs and tomatoes with crab (the last of the lump meat), stir-fried ground pork with basil and peppers, and rice that I cooked with my BF. I love crab, but its a bit more expensive than shrimp. But I had a lot of crab; I bought too much for these croquettes and it goes bad quickly.

For the eggs, theres this recipe from somebodys mom on YouTube that is simply a stunner, and I spent like two years trying to replicate it, but now I cant find that video anymore. But lately Ive been using the Chinese Cooking Demystified version, and then I stir-fried crab with it, and we also had the stir-fried pork.

Im really fortunate in that, while the neighborhood where I grew up was hella white, the street we lived on and the street immediately adjacent to it were deeply diverse, and my parents friends were deeply diverse. We ate a lot of Cuban food, a lot of Filipino food, a good amount of Japanese food; we ate quite a lot of Jamaican food, a lot of Nigerian food. A lot of that was just being in close proximity to friends and loved ones eating a lot of different stuff. The diversity of cuisines and the allowance for the diversity of cuisines in Houston is objectively astounding, but, among Houstonians, its not terribly remarkable. It never struck me as something that was noteworthy. Then you get older, and then you get more context to see not everyone has fuckingeight different cuisines lined up next to one another in every strip mall.

My mom is Jamaican, and my dad is from Florida. They met in Florida. Houston feels very much like home. But Ive been really fortunate to be able to travel a little bit, and Ive come around to thinking many places can seem like home. Being open to different places is definitely something I think about often. Just being around a bunch of different folks who are from a litany of places, the idea of being rooted to one place is definitely lovely and viable, but not essential for me or from my standpoint. Although I will say a lot of people who leave Houston and then they end up coming back because its so much itself I do wonder if that would be me, if I ever choose to leave full time. Maybe home is actually just a feeling, wherever you end up finding it.

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Originally posted here:
Bryan Washington Requires More Than One Curry Per Week - Grub Street

There are few better feelings in life than being totally well rested. Unfortunately, though, our sleeping patterns dont always play ball, and there are a number of different factors in our day-to-day lives that can make it difficult to doze off, including everything from stress to our central heating.

One key thing that is often overlooked when it comes to getting a good nights sleep is our diets. Studies have found that our dietary patterns and consumption of specific foods can have a significant impact on our sleep quality, with some foods having the potential to really disrupt our time in the land of Nod.

As Brielle explains, eating healthy, well balanced meals supports your bodys pathways when regulating your hormones, some of which impact how much sleep you get and how well you sleep. This means that eating foods containing nutrients that support sleep and in the right amounts is crucial to ensuring you are able to drift off when your head hits the pillow.

In the same way that your diet can influence your sleep, poor sleep is in turn associated with unhealthy eating habits, says Aishah. Therefore, if one becomes compromised, this will have a knock-on effect on the other. But your sleep and diet are supposed to support one another, because both influence your energy levels throughout the day. SoBrielle recommends trying to keep a consistent sleeping and eating pattern, so that they are able to work together to supply your body with energy.

Aishah explains that there is growing evidence to suggest that the time you eat can impact your circadian rhythm, also known as your sleep-wake cycle. As a result, eating too close to when you go to bed can potentially impact your sleep routine, and so its best to eat earlier in the evening, allowing yourself a couple of hours to digest your meal before going to sleep.

However, there is no hard and fast rule for when you should be eating. As Brielle explains, its important to listen to your body and how you feel, and aim to feel satisfied when you eat in the evening, but not stuffed or hungry. Really, it all depends on what works well for you.

While some foods are fine to eat throughout the day, whether because they are good fuel or a tasty pick-me-up, they may not always be a good idea to eat close to bedtime. Both Brielle and Aishah particularly warn against the consumption of caffeine too late in the day, because it stimulates the brain and gives you energy, thus keeping you awake, says Brielle.

Foods high in sugar can be stimulating as well. As Aishah explains, they heighten arousal and give you a dopamine hit, which keeps you feeling alert, and so she recommends you stay away from sugary foods like sweets, chocolate and cakes at least two to three hours before going to bed.

According to Brielle, some foods cause disrupted sleep simply because they take longer for the body to digest. If youre struggling with your sleep, try to stay away from heavy proteins in your evening meals, and minimise the carb-rich foods like rice and pasta. Instead, she recommends trying plant-based alternatives, which are lighter and less likely to keep you awake.

Brielle explains that kiwis are excellent sleep aids. In fact, in a study, participants who started consuming kiwis regularly before bed were able to fall asleep 42% faster than they did before. Foods high in melatonin are great as well, because melatonin is the hormone that helps to regulate your circadian rhythm. Aishah recommends cherries and nuts such as walnuts and almonds as good sources of this crucial hormone.

Fatty fish such as salmon and tuna are a good option for your evening meal. They are a great source of vitamin D and omega 3 fatty acids, which help to regulate serotonin, the hormone that is responsible for maintaining sleep, explains Brielle. Milk contains vitamin D, too, as well as tryptophan, both of which have been linked to supporting sleep.

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Images: Getty

Continued here:
How our diets disrupt our sleep, and what to eat before bed - Stylist Magazine

The sweepstakes are easy to enter. Just fill in your boss's first and last name, their email address, and 500 characters or less about why you think your boss deserves the grand prize. Then you just need to fill in your own name, email address, and date of birth, and you're good to go. Entrants have until 11:59 pm ET on November 16th, a month after National Boss Day, to submit their forms, according to theDiet Coke National Boss's Day Sweepstakes Official Rules.

You can nominate up to four times before the deadline, but each nomination has to be unique. So basically, if you work under multiple people and want to nominate a few of them, go ahead you don't have to choose. But for obvious reasons, you can't nominate any of them more than once.

Don't sweat about composing theperfect description of your boss's Diet-Coke-worthiness. The judging organization "will select the names of the potential winning Nominees in a random drawing of all eligible entries received during the Promotion Period."So go ahead, enter your boss. If they're areally good boss, maybe they'll share a couple of their 365 cans of Diet Coke with you.

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How to win a year's worth of free Diet Coke - Mashed

As Prime Minister Yoshihide Suga prepares for the start of an extraordinary Diet session, set to open Monday, he also has to contend with the growing question of when he will call an election.

Sugas tenure as Liberal Democratic Party (LDP) president will end next September and the terms of Lower House lawmakers will expire the following month, leaving Suga with limited wiggle room to form a strategy on dissolving the Lower House.

Calling an election at the right moment has been always an arduous task for prime ministers. For Suga, who was appointed to the role just a month ago, it is an important test of his acumen as a politician and, depending on the outcome, could embolden or weaken his standing within the ruling party.

Buoyed by optimism and high expectations for the new administration that were reflected in early polls, political spectators in Nagatacho, the nations political center, had anticipated Suga would pull the trigger in the early days of his administration. A Kyodo News survey conducted shortly after he took office in mid-September showed the approval rating for his Cabinet at 66.4%, with disapproval at just 16.2%.

But Suga himself seemed to extinguish the prospect of an early Lower House election.

I want to get some work done, since I just assumed the role of LDP president, Suga said in a news conference immediately after his victory in the partys leadership contest, adding that he needed to take the pandemic situation into consideration as well.

If the prime minister decides to hold an election next year, he will have very little flexibility on when to do so as several important events are already scheduled. The postponed Olympic Games are expected to take place in July, and the Tokyo assembly election is set to take place around that time as well.

The Tokyo vote is vital for Komeito, the LDPs junior coalition partner, and it has been widely noted that Komeito is averse to holding a general election immediately before or after a local campaign as it would wish to concentrate its efforts on the latter.

If the summer of 2021 is out of the picture, only three viable scenarios remain: at the start of next years Diet session, in January; immediately after the fiscal 2021 budget is passed, in the spring, or close to the expiration of Lower House lawmakers terms, in the fall.

Besides cooperation with Komeito, Suga may also contemplate working with Nippon Ishin no Kai, a right-leaning opposition party with whose leaders the prime minister has strong working relationships, said Jun Iio, a professor of Japanese politics at the National Graduate Institute for Policy Studies.

Suga, the professor predicted, will probably not dissolve the Lower House this year, as keeping the decision available to him as long as possible, like a trump card, would help maintain his power.

Even though Suga may be tempted to call for a snap vote if his Cabinets approval rating slips, the LDP holds a commanding lead in all major polls on approval compared to other parties.

In a Kyodo News poll this month, the LDPs approval rating was 45.8% far ahead of the rating for the Constitutional Democratic Party of Japan (CDP), the largest opposition party, which saw the approval of just 6.4%.

Nippon Ishin, which had a 4.2% approval rating in the Kyodo poll, is currently preoccupied with Novembers referendum on the Osaka metropolis plan. Ichiro Matsui, head of the party, said in September he would prefer the general election to be held the same day as the referendum to boost voter turnout.

But the prime minister might have been dissuaded from such move, since Nippon Ishin and the LDPs Osaka chapter are divided on the issue. The administration has been ambivalent on whether it supports the metropolis proposal, and holding the general election on the same day could be taken as an implicit nod for the plan.

Like most prime ministers, Suga has been tight-lipped on when he may call a vote. In maintaining this uncertainty, it is convenient for the prime minister to hint at the possibility of a snap election whenever he thinks it necessary to shake things up within the party, Iio said.

Suga is a self-assured individual who doesnt believe his administrations popularity will decline, as he believes he is getting work done (on lowering cell phone bills and promoting digitalization) and would dare to challenge anyone who seeks to replace him, Iio said. Itd be advantageous to hold on to the right to call a general election, to avoid the possibility of being forced out by (the LDPs) factional dynamics.

Traditionally, prime ministers from the LDP are members of one of its factions, to maintain their status and amass support. But Suga doesnt belong to any of them, leaving him without a solid support base and more vulnerable to friction between caucuses.

Political parties have begun preparations to field candidates for each electoral district. The CDP, which acquired new lawmakers from the Democratic Party for the People through a merger this summer, is looking to work with other opposition parties to back the same candidates. Some within the party, though, are unwilling to cooperate further with the Japanese Communist Party.

The opposition parties undertaking for a unified counterforce against Suga could break down, Iio said, if Nippon Ishin puts forward candidates across the country to divide up votes.

Suga doesnt believe hed win an election without machinating on various fronts, he added.

PHOTO GALLERY (CLICK TO ENLARGE)

Original post:
Speculation over Japan election timing grows ahead of Diet session - The Japan Times

One can simply extract the aloe vera gel from the plant.

Highlights

There are many prized ingredients in our nature that comes with wonderful health benefits. One such example is of aloe vera (ghritkumari). Ever since the bright green, succulent plant found value and mention in Ayurveda, health and beauty remedies by experts, it has taken over gardens and window shelves of many homes around the world. No wonder there are tonnes of gels, creams and juices being made with the wonderful plant.

But did you know, as much as there are amazing benefits of using aloe vera for skin, there are some health benefits of consuming aloe vera as well?! The nutritionally dense plant has countless benefits that are enough for us to start finding ways to include it in our diet. One of the most important benefits of aloe vera is that it may also help you in weight loss! Besides being loaded with vitamins and minerals, aloe vera is believed to have certain active compounds, which may help you shed a few pounds. It is also known to boost metabolism, which helps burn more of body fat aiding weight loss. Its laxative properties aid digestion when consumed in small quantities that can lead to weight loss too.

There are many ways to consume aloe vera; however, it must be consumed in small quantities and avoided by pregnant women and those with frequent tummy troubles and problems like diarrhoea or loose motions. Aloe vera juice is one of the most popular ways to reap in the many benefits of the plant. Not only is it easy, but is known to boost the body's immunity. The wide range of antioxidants, present in aloe vera also helps fight cell damage caused by free-radical activity and strengthens your immunity.

(Also Read:Aloe Vera Juice Benefits: 7 Amazing Reasons To Drink Aloe Vera Juice Everyday)

Aloe vera must be consumed in small quantities.

One can simply buy a pack of aloe vera juice from the market or extract the aloe vera gel from the plant. It might be bitter in taste but you can always add a teaspoon of honey for taste. Here we have a quick and simple aloe vera juice recipe packed with the goodness of lemon and honey that may help you shed a few kilos along with boosting your immunity!

Ingredients-

. Aloe vera gel- 2 tsp

. Lemon- 1 (juiced)

. Honey- 1 tsp

. Mint leaves (chopped)- 5-6

Method-

. All you need to do is blend all the ingredients well till smooth and serve.

Promoted

As per many health experts, one can even combine aloe vera with other healthy herbs such as giloy, amla or tulsi for more health benefits. Be cautious about not consuming too much of aloe vera since it can have side effects.

Try this aloe vera, lemon and honey juice for weight loss empty stomach every morning. Share your experience with us in the comments section below.

About Aanchal MathurAanchal doesn't share food. A cake in her vicinity is sure to disappear in a record time of 10 seconds. Besides loading up on sugar, she loves bingeing on FRIENDS with a plate of momos. Most likely to find her soulmate on a food app.

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This Aloe Vera Juice With Lemon And Honey May Work Wonders For Weight Loss - NDTV Food

Abstract

The mismatch between evolved human physiology and Western lifestyles is thought to explain the current epidemic of cardiovascular disease (CVD) in industrialized societies. However, this hypothesis has been difficult to test because few populations concurrently span ancestral and modern lifestyles. To address this gap, we collected interview and biomarker data from individuals of Turkana ancestry who practice subsistence-level, nomadic pastoralism (the ancestral way of life for this group), as well as individuals who no longer practice pastoralism and live in urban areas. We found that Turkana who move to cities exhibit poor cardiometabolic health, partially because of a shift toward Western diets high in refined carbohydrates. We also show that being born in an urban area independently predicts adult health, such that life-long city dwellers will experience the greatest CVD risk. By focusing on a substantial lifestyle gradient, our work thus informs the timing, magnitude, and evolutionary causes of CVD.

It has become increasingly clear that the spread of Western, industrialized lifestyles is contributing to a rapid rise in metabolic and cardiovascular diseases (CVDs) worldwide (15). Since the Industrial Revolution, modern advancements in agriculture, transportation, and manufacture have had a profound impact on human diets and activity patterns, such that calorie-dense food is often easily accessible and adequate nutrition can be achieved with a sedentary lifestyle. This state of affairs, which is typical in Western, industrialized societies but rapidly spreading across developing countries, stands in stark contrast to the ecological conditions experienced over the vast majority of our evolutionary history. Consequently, the mismatch between human physiologywhich evolved to cope with a mixed plant- and meat-based diet, activity-intensive foraging, and periods of resource scarcityand Western, industrialized lifestyles has been hypothesized to explain the current epidemic of cardiometabolic disease (14).

Attempts to test the evolutionary mismatch hypothesis thus far have largely focused on comparing cardiometabolic health outcomes between industrialized nations and small-scale, subsistence-level groups (e.g., hunter-gatherers, horticulturalists, and pastoralists). Arguably, the diets and activity patterns of these subsistence-level groups are relatively in line with their recent evolutionary history, and these populations can thus be thought of as matched to their evolutionary past (1, 5). In support of the evolutionary mismatch hypothesis, essentially, all subsistence-level populations studied to date show minimal type 2 diabetes, hypertension, obesity, and heart disease relative to the United States and Europe (513). Two other classes of studies provide further support: (i) Indigenous populations that have recently transitioned to market-based economies show higher rates of obesity and metabolic syndrome compared to subsistence-level groups [e.g., (14, 15)] and (ii) comparisons between rural and urban areas in developing countries have found higher rates of hypertension, type 2 diabetes, and obesity in the urban, industrialized setting (1620).

Despite the groundwork that has been laid so far in understanding how Western lifestyles influence health, most prior studies leave two major gaps. First, the participants genetic backgrounds are either heterogeneous (in the case of urban versus rural comparisons within a country) or confounded with lifestyle (in the case of subsistence-level versus U.S. or Europe comparisons). This makes it difficult to disentangle genetic versus environmental contributions to health. A more robust study design would be to compare health between individuals living their ancestral, traditional way of life versus individuals from the same genetic background living a modern, industrialized lifestyle. This type of natural experiment is difficult to come by [but see (13)], and large-scale work that has assessed acculturation effects on cardiometabolic health within a single group has therefore been limited to more modest lifestyle gradients [e.g., work with the Tsimane (15, 17), Shuar (10), or Yakut (18, 21)]. A second major gap is that research to date has focused on industrialization and acculturation effects at particular life stages, mainly in adulthood, despite strong evidence that early-life conditions influence adult health and that life-course perspectives are likely important (19, 20). Of particular relevance is the hypothesis that individuals use cues during development to predict what the adult environment will be like and develop phenotypes well suited for those conditions. Under such a predictive adaptive response (PAR) framework, industrial transitions are thought to be especially detrimental because individuals may be born in resource-poor environments but exposed to resource-rich environments as adults; individuals are thus phenotypically prepared for scarcity but encounter plenty instead, leading to a within-lifetime environmental mismatch and subsequent cardiometabolic disease (2224). Despite the popularity and potential significance of this idea, little work has robustly and empirically tested it against other evolutionary explanations for why early-life resource scarcity is commonly associated with poor adult cardiometabolic health (20, 2528). In particular, the developmental constraints (DC) hypothesis alternatively predicts that early-life nutritional challenges will be unavoidably costly and associated with poor health outcomes no matter the adult environment (20, 25, 28).

To address these gaps, we collected interviews and cardiometabolic health biomarker data from the Turkana, a subsistence-level, pastoralist population from a remote desert in northwest Kenya (Fig. 1) (29, 30). The Turkana and their ancestors have practiced nomadic pastoralism in arid regions of East Africa for thousands of years (30), and present-day, traditional Turkana still rely on livestock for subsistence: 62% of calories are derived from fresh or fermented milk, and another 12% of calories come from animal meat, fat, or blood (29) [specifically, the Turkana herd dromedary camels, zebu cattle, fat-tailed sheep, goats, and donkeys (29)]. The remaining calories are derived from wild foods or products obtained through occasional trade (e.g., cereals, tea, and oil) (29). However, as infrastructure in Kenya has improved in the past few decades, small-scale markets have expanded into northwest Kenya, leading some Turkana to no longer practice nomadic pastoralism and to rely more heavily on the market economy; specifically, these individuals make and sell charcoal or woven baskets or keep animals in a fixed location for trade rather than subsistence. In addition to the emergence of this nonpastoralist (but still relatively subsistence-level) subgroup, some individuals have left the Turkana homelands entirely and now live in highly urbanized parts of central Kenya (Fig. 1). The Turkana situation thus presents a unique opportunity, in that individuals of the same genetic background can be found across a substantial lifestyle gradient ranging from relatively matched to extremely mismatched with their recent evolutionary history. Further, because many Turkana are currently migrating between rural and urban areas within their lifetime, we were able to empirically test the PAR hypothesis by asking whether individuals who experienced rural conditions in early life but urban conditions in adulthood exhibited worse cardiometabolic health than individuals whose early and adult environments were similar. We tested this idea against the DC hypothesis, which predicts that early-life challenges incur simple long-term costs that are not contingent on the adult environment (20, 25, 28).

(A) Sampling locations throughout northern and central Kenya are marked with red dots; the county borders are marked with dashed lines. In both Laikipia and Turkana counties, the largest city (which is generally central within each county) is marked with a black dot. (B) Schematic describing the three lifestyle groups that were sampled as part of this study. (C) The proportion of people from each lifestyle group who reported that they consumed a particular item regularly, defined as one to two times per week, more than two times per week, or every day. People who reported that they consumed a particular item rarely or never were categorized as not consuming the item regularly. Animal products are a staple of the traditional pastoralist diet (85), while carbohydrates and added nutrients, which can only be obtained through trade, are indicative of market integration.

Capitalizing on this natural experiment, we sampled 1226 adult Turkana in 44 locations from the following groups: (i) individuals practicing subsistence-level pastoralism in the Turkana homelands, (ii) individuals that do not practice pastoralism but live in the same remote, rural area, and (iii) individuals living in urban centers (Fig. 1). We found that cardiometabolic profiles across 10 biomarkers were favorable in pastoralist Turkana, and rates of obesity and metabolic syndrome were low, similar to other subsistence-level populations (612). Comparisons within the Turkana revealed a nonlinear relationship between the extent of industrialization or evolutionary mismatch and cardiometabolic health: No significant biomarker differences were found between pastoralists and nonpastoralists from rural areas. However, we found strong, sometimes sex-specific, differences in health between these two groups and nonpastoralists living in urban areas, although metabolic dysfunction among urban Turkana did not reach the levels observed in the United States. Using formal mediation analyses (31, 32), we show that consumption of processed, calorically dense foods (primarily carbohydrates and cooking fats) and indices of market integration may explain health shifts in urban Turkana. Last, we show that a proxy of urbanization (population density) experienced around the time of birth is associated with worse adult cardiometabolic health, independent of adult lifestyle. In other words, the health costs of living an industrialized lifestyle in early life and adulthood are additive, such that within-lifetime environmental mismatches do not appear to exacerbate health issues as has been previously suggested (22, 24).

To characterize the health of the Turkana people, we collected extensive interview and biomarker data from adult Turkana sampled throughout Kenya (Table 1 and Fig. 1). We measured body mass index (BMI), waist circumference, total cholesterol, triglycerides, high- and low-density lipoproteins (HDLs and LDLs), body fat percentage, systolic and diastolic blood pressure, and blood glucose levels (Table 2). We also created a composite measure of health, defined as the proportion of measured biomarkers that exceed cutoffs set by the U.S. Centers for Disease Control and Prevention (CDC) or the American Heart Association as being indicative of disease (see Supplementary Materials and Methods).

NHANES, National Health and Nutrition Examination Survey; MI, market integration. M, Male; F, Female.

BP, blood pressure.

As has been observed in other subsistence-level populations (5), we found extremely low levels of cardiometabolic disease among traditional, pastoralist Turkana: No individuals met the criteria for obesity (BMI > 30) or metabolic syndrome (33), and only 6.4% of individuals had hypertension [blood pressure > 135/85 (33)]. Further, across eight cardiometabolic biomarkers that have been measured consistently in other subsistence-level populations (612), the means observed in the Turkana were generally within the range of what others have reported (table S1, A and B). Mean body fat percentage (mean SD for females = 20.45 4.57%) and BMI (19.99 2.14 kg/m2) were on the lower extremes but were similar to other pastoralists (mean BMI in the Fulani and the Maasai = 20.2 and 20.7 kg/m2, respectively) and to a small study of the Turkana conducted in the 1980s [mean BMI = 17.7 kg/m2 (34)]. Notably, the only biomarkers that were strongly differentiated in traditional, pastoralist Turkana were HDL (72.69 14.72 mg/dl) and LDL cholesterol levels (60.89 20.22 mg/dl), both of which were even more favorable than what has been observed in other subsistence-level groups, including the Fulani and the Maasai (range of reported means for HDL = 34.45 to 49.11 mg/dl and LDL = 72.70 to 92.81 mg/dl). It remains to be seen why the Turkana HDL/LDL profiles appear as strong and consistent outliers relative to other subsistence-level groups, but one possibility is that there has been selection on Turkana lipid traits as a result of their unique diet, ecology, and lifestyle. This possibility could be explored in future evolutionary genetic and metabolic studies.

Next, we sought to understand the shape of the relationship between industrialization and cardiometabolic health within the Turkana, by comparing biomarker values across the three lifestyle categories. Using linear models controlling for age and sex, we found that Turkana practicing traditional pastoralism did not differ in any of the 10 measured biomarkers relative to nonpastoralist Turkana living in similarly rural areas (all P values > 0.05; Fig. 2 and table S2A), despite there being major dietary difference between these groups (Fig. 1). Pastoralist and rural nonpastoralist Turkana did significantly differ in our composite measure, with nonpastoralist Turkana exhibiting more biomarker values above clinical cutoffs [average proportion of biomarkers above cutoffs = 4.02 and 6.82% for pastoralists and nonpastoralists, respectively; P value = 1.39 103; false discovery rate (FDR) < 5%; Fig. 2].

(A) Effect sizes for contrasts between pastoralist, rural nonpastoralist, and urban nonpastoralist Turkana (from linear models controlling for age and sex; table S2A). Effect sizes are standardized, such that the x axis represents the difference in terms of SDs between groups. BP, blood pressure. (B) Standardized effect sizes for contrasts between rural Turkana (pastoralist and rural nonpastoralist grouped together), urban nonpastoralist Turkana, and the U.S. (from linear models controlling for age and sex; table S2B). In (A) and (B), lighter colored bars represent effect sizes that were not significant [false discovery rate (FDR) > 5%], and analyses of body fat and blood glucose focus on females only (see Supplementary Materials and Methods). Symbols correspond to FDR significance thresholds as follows: *FDR < 0.1%, FDR < 1%, and +FDR < 5%. (C) Predicted values for a typical rural Turkana (pastoralist and rural nonpastoralist grouped together), urban Turkana, and U.S. individual are shown for a subset of significant biomarkers. Estimates and error bars were obtained using coefficients and their SEs from fitted models, for a female of average age (see Supplementary Materials and Methods).

Notably, biomarker values for both pastoralist and nonpastoralist, rural Turkana were consistently more favorable than among Turkana living in urban areas in central Kenya. People living in urban areas exhibited composite measures indicative of worse cumulative cardiometabolic health (average proportion of biomarkers above cutoffs = 13.42%), higher BMIs and body fat percentages, larger waist circumferences, higher blood pressure, and higher levels of total cholesterol, triglycerides, and blood glucose (all FDR < 5%; Fig. 2 and table S2A). The only tested variables that did not exhibit differences between urban and rural Turkana (both pastoralists and nonpastoralists) were the HDL and LDL cholesterol levels, which were favorable in all Turkana regardless of lifestyle (tables S1A and S2A). Using standardized effect sizes, we found that the biomarkers that differed most between the two rural groups and urban residents were blood glucose, triglycerides, and BMI (Fig. 2). For example, the average urban Turkana resident has a 9.69 and 8.43% higher BMI relative to pastoralist and nonpastoralist rural Turkana, respectively.

For all 11 measures, we explored the possibility of age by lifestyle category and sex by lifestyle category interactions. We found no evidence that age modifies the response to lifestyle change (FDR > 5% for all biomarkers; likelihood ratio test comparing models with versus without the interaction term). However, we did find that inclusion of a sex by lifestyle category term improved the model fit for blood glucose levels (P value from a likelihood ratio test = 1.838 104) and body fat percentage (P value = 4.234 103; table S2A). In both cases, women experienced worse health with increasing market integration and industrialization, while men did not (fig. S1). The nature of this interaction is consistent with several previous studies (10, 21, 35, 36); however, the specific reasons behind the heightened sensitivity of women to acculturation (in our study and elsewhere) remain unknown. Previous work has speculated that these sex-specific effects are driven by social and behavioral factors that affect diet and activity patterns (e.g., rate of acquisition of wage labor jobs) and that change more markedly for women versus men during industrial transitions (10). It is likely that this general explanation applies to the Turkana as well, although follow-up work is needed to understand the specifics.

We next asked whether the biomarker levels observed among urban Turkana approached those observed in a fully Western, industrialized society (specifically, the United States). We note that a caveat of these analyses is that they must include different genetic backgrounds since Turkana individuals are rarely found in fully industrialized countries.

To compare metabolic health between the U.S., rural Turkana (grouping pastoralists and nonpastoralists since these groups were minimally differentiated in previous analyses), and urban Turkana, we downloaded data from the CDCs National Health and Nutrition Examination Survey (NHANES) conducted in 2006 (37), focusing on adults (ages 18-65) to recapitulate the age distribution of our Turkana dataset (see Table 1 for sample sizes). Comparisons between NHANES and our Turkana dataset revealed that, while urban Turkana exhibit biomarker values indicative of poorer health than rural Turkana, urban Turkana have more favorable metabolic profiles than the U.S. (Fig. 2, figs. S2 and S3, and table S2B). This pattern held for all measures except (i) blood glucose levels, where no differences were observed (P value for U.S. versus rural Turkana = 0.166, U.S. versus urban Turkana = 0.074); (ii) triglycerides, where urban Turkana could not be distinguished from the U.S. (P = 0.627); (iii) systolic blood pressure, where urban Turkana exhibited higher values than the U.S. (4.55% higher; P = 3.02 106; FDR < 5%); and (iv) diastolic blood pressure, where mean values for both urban and rural Turkana were unexpectedly higher than the U.S. (rural Turkana, 8.77% higher than U.S., P = 4.43 1065; urban Turkana, 11.69% higher than U.S., P = 3.58 1031, FDR < 5% for both comparisons; fig. S4). These differences in diastolic blood pressure remained after removing all U.S. individuals taking cardiometabolic medications (rural Turkana, 6.91% higher than U.S., P = 3.27 1067; urban Turkana, 10.37% higher than U.S., P = 2.21 1035). However, two pieces of evidence suggest that the higher diastolic blood pressure values observed in the Turkana are not pathological: (i) Values for rural Turkana (77.43 15.22 mmHg) are similar to estimates from other subsistence-level populations without cardiometabolic disease (range of published means = 70.9 to 79.9 mmHg; table S1A) and (ii) few rural Turkana meet the criteria for hypertension relative to the U.S. (fig. S3). Future work is needed to understand the environmental and/or genetic sources of the observed differences in blood pressure between Turkana and U.S. individuals.

For measures that exhibited differences between urban Turkana and the U.S. in the expected directions, these effect sizes were consistently much larger in magnitude than the differences that we observed between rural and urban Turkana (Fig. 2). For example, while the average urban Turkana experiences a 9% higher BMI than their rural counterparts, the average U.S. individual has a BMI that is 44 and 32% higher than rural and urban Turkana, respectively. Similarly, while the average proportion of biomarkers above clinical cutoffs is 6.22% in rural Turkana and 13.42% in urban Turkana, this number rises to 38.84% in the U.S.

We next sought to identify the specific dietary, lifestyle, or environmental inputs that drive differential health outcomes between urban and rural Turkana. To do so, we turned to interview data collected for each individual (see Supplementary Materials and Methods), which revealed substantial variation in diet, market access, and urbanicity [a term that we use to mean living in an urbanized area and engaging in an urban lifestyle, following (38); Figs. 1 and 3]. We paired these interview data with mediation analyses (31, 32) to formally test whether the effect of a predictor (X) on an outcome (Y) was direct or, instead, indirectly explained by a third variable (M) such that XMY (Fig. 3). Using this statistical framework, we tested whether the following factors could explain the decline in metabolic health observed in urban Turkana: increased consumption of market-derived, calorically dense foods (e.g., carbohydrates such as soda, bread, rice, as well as fats such as cooking oil), reduced consumption of traditional animal products, poorer health habits, ownership of more market-derived goods and modern amenities (e.g., cell phone, finished floor, and electricity), occupation that is more market integrated (e.g., formal employment), and residence in a more populated or developed area (measured via population density, distance to a major city, and female education levels) (see Supplementary Materials and Methods). In particular, we predicted that lifestyle effects on health would be mediated by a shift toward a diet that incorporates more carbohydrates and fewer animal products in urban Turkana. These analyses focused on biomarkers for which our sample sizes were the largest since dietary data were not available for all individuals (see table S3 for sample sizes).

(A) Key measures of urbanicity and market integration used in mediation analyses, with means and distributions shown for urban and rural Turkana. (B) Schematic of mediation analyses. Specifically, mediation analyses test the hypothesis that lifestyle effects on health are explained by an intermediate variable, such as consumption of particular food items (red arrows); alternatively, lifestyle effects on health may be direct (black arrow) or mediated by a variable that we did not measure. (C) Summary of mediation analysis results, where colored squares indicate a variable that was found to significantly explain urban-rural health differences in a given biomarker. Significant mediators are colored on the basis of how much the lifestyle effect (urban/rural) decreased when a given mediator was included in the model. MI, market integration. Full results and sample sizes for mediation analyses are presented in table S3.

In support of our predictions, urban-rural differences in waist circumference, BMI, and our composite measure of health were mediated by greater consumption of processed, calorically dense foods (including carbohydrates and fats) and lower consumption of traditional animal products (milk and blood) in urban Turkana (Fig. 3 and table S3). Notably, the total number of different carbohydrate items that an individual consumed was a strong and consistent predictor across these three biomarkers, suggesting that individual dietary components may matter less than overall exposure to refined carbohydrates. However, it is important to note that refined carbohydrates are commonly processed with oil or other additives, and it is therefore likely a combined effect of exposure to both carbohydrates and fats that drives the negative health effects that we observe.

Contrary to our predictions, we did not find that dietary differences mediated urban-rural differences in systolic blood pressure, diastolic blood pressure, or body fat percentage. Instead, these measures were explained by variables that captured how industrialized and market-integrated a given individuals lifestyle was, which was also important for waist circumference, BMI, and our composite measure of health in addition to dietary effects. For example, fine-scale measures of population density and degree of market reliance of occupation both significantly mediated five of six tested biomarkers (Fig. 3 and table S3). Further, these indices of urbanicity and market integration tended to be stronger mediators than dietary variables (Fig. 3).

To understand the degree to which the mediators that we identified explain the relationship between lifestyle and a given biomarker, we compared the magnitude of the lifestyle effect in our original models (controlling for age and sex, without any mediators) to the effect estimated in the presence of all significant mediators. If the mediators fully explain the relationship between lifestyle and a given biomarker, then we would expect the estimate of the lifestyle effect to be zero in the second model. These analyses revealed that the mediators that we identified explain most of the relationship between lifestyle and waist circumference (effect size decrease = 90.7%), BMI (79.9%), systolic blood pressure (74.9%), and composite health (64.1%) but explain only a small portion of lifestyle effects on diastolic blood pressure (10.0%) and body fat (23.5%; table S3).

Last, we were interested in understanding whether early-life conditions had long-term effects on health, above and beyond the effects of adult lifestyle that we had already identified. We were motivated to ask this question because work in humans and nonhuman animals has demonstrated strong associations between diet and ecology during the first years of life and fitness-related traits measured many years later (20, 25, 39, 40). Two major hypotheses have been proposed to explain why this embedding of early-life conditions into long-term health occurs. First, the PAR hypothesis posits that organisms adjust their phenotype during development in anticipation of predicted adult conditions. Individuals that encounter adult environments that match their early conditions are predicted to gain a selective advantage, whereas animals that encounter mismatched adult environments should suffer a fitness cost (19, 22, 25, 41, 42). In contrast, the DC or silver spoon hypothesis predicts a simple relationship between early environmental quality and adult fitness: Individuals born in high-quality environments experience a fitness advantage regardless of the adult environment (25, 28, 43). Under DC, poor-quality early-life conditions cannot be ameliorated by matching adult and early-life environments; instead, the effects of environmental adversity accumulate across the life course.

We found no evidence that individuals who experienced matched early-life and adult environments had better metabolic health in adulthood than individuals who experienced mismatched early-life and adult conditions (P > 0.05 for all biomarkers). In particular, we tested for interaction effects between the population density of each individuals birth location (estimated for their year of birth) and a binary factor indicating whether the adult environment was urban or rural (table S4A; see table S4B for parallel analyses using population density to define the adult environment as a continuous measure). This analysis was possible given the within-lifetime migrations of many Turkana between urban and rural areas: Only 19.52 and 33.01% of urban and rural Turkana, respectively, were sampled within 10 km of their birthplace, and the correlation between birth and sampling location population densities was low (R2 = 0.115; P < 1016; fig. S5).

While we observed no evidence for interaction effects supporting PAR, we did find strong main effects of early-life population density on adult waist circumference (b = 0.272, P = 7.33 108), BMI (b = 0.266, P = 1.35 107), body fat (b = 0.306, P = 1.57 105), diastolic blood pressure (b = 0.124, P = 2.01 102), and our composite measure of health (b = 0.296, P = 3.40 104; all FDR < 5%), in support of DC. For all biomarkers, being born in a densely populated location was associated with poorer adult metabolic health (Fig. 4 and table S4A). Furthermore, the early-life environment effect was on the same order of magnitude as the effect of living in an urban versus rural location in adulthood (see table S4A and Supplementary Materials and Methods). For example, BMIs are 5.69% higher in urban versus rural areas, while individuals born in areas from the 25th versus 75th percentile of the early-life population density distribution exhibit BMIs that differ by 3.34%. Similarly, the effect of the adult environment (urban compared to rural) on female body fat percentages is 11.14%, while the effect of early-life population density (25th compared to 75th percentile) is 20.7% (table S4A).

The relationship between the population density of each individuals birth location and (A) BMI, (B) our composite measure of health, (C) waist circumference, and (D) diastolic blood pressure are shown for individuals sampled in rural and urban locations, respectively. Notably, while the intercept for a linear fit between early-life population density and each biomarker differs between rural and urban sampling locations (indicating mean differences in biomarker values as a function of adult lifestyle), the slope of the line does not. In other words, we find no evidence that the relationship between early-life conditions and adult health is contingent on the adult environmnt (as predicted by PAR). Instead, being born in an urban location predicts poorer metabolic health regardless of the adult environment.

By sampling a relatively endogamous population across a substantial lifestyle gradient, we show that (i) traditional, pastoralist Turkana exhibit low levels of cardiometabolic disease and (ii) increasing industrialization, in both early life and adulthood, has detrimental, additive effects on metabolic health (in opposition of popular PAR models that have rarely been tested empirically in humans) (20, 22, 24). Our findings offer strong support for the evolutionary mismatch hypothesis, more so than existing studies that cannot disentangle lifestyle and genetic background effects (612, 44, 45, 46) or that assess lifestyle effects across much more modest gradients (10, 17, 21, 47, 48). Our work also provides some of the first multidimensional, large-scale data on acculturation and industrialization effects on cardiometabolic health in pastoralists [see also (34, 49, 50)], which have received less attention than other subsistence modes [e.g., horticulturalists such as the Shuar and Tsimane (10, 15, 51, 52)].

Our observation that pastoralist Turkana do not suffer from cardiometabolic diseases echoes long-standing findings from other subsistence-level groups (612). However, it also provides empirical support for a more recent and controversial hypothesis: that many types of mixed plant- and meat-based diets are compatible with cardiometabolic health (1, 53, 54) and that mismatches between the distant human hunter-gatherer past and the subsistence-level practices of horticulturalists or pastoralists do not lead to disease (55). In other words, contemporary hunter-gatherers are most aligned with human subsistence practices that evolved ~300 thousand years ago (56), but they do not exhibit better cardiometabolic health relative to horticulturalists or pastoralists, whose subsistence practices evolved ~12 thousand years ago (tables S1A to S3) (57). Instead, we find evidence consistent with the idea that extreme mismatches between the recent evolutionary history of a population and lifestyle are needed to produce the chronic diseases now prevalent worldwide; in the Turkana, this situation appears to manifest in urban, industrialized areas but not in rural areas with changing livelihoods but limited access to the market economy.

Because our study assessed health in individuals who experience no, limited, or substantial access to the market economy, we were able to determine that industrialization has nonlinear effects on health in the Turkana. In particular, we find no differences between pastoralists and nonpastoralists in rural areas for 10 of 11 variables (Fig. 2), despite nonpastoralists consuming processed carbohydrates that are atypical of traditional practices (Fig. 1 and table S1A). Nevertheless, rural nonpastoralists still live in remote areas, engage in activity-intensive subsistence activities, and rely far less heavily on markets than urban Turkana. Given the mosaic of lifestyle factors that can change with modernization, often in concert, our results suggest that this type of lifestyle has not crossed the threshold necessary to produce cardiometabolic health issues. This threshold model may help explain heterogeneity in previous studies, where small degrees of evolutionary mismatch and market integration have produced inconsistent changes in cardiometabolic health biomarkers (10, 58, 59).

While our dataset does not capture every variable that mediates urban-rural health differences in the Turkana, we were able to account for a substantial portion (>60%) of lifestyle effects on waist circumference, BMI, systolic blood pressure, and composite health. In line with our expectations, increases in these biomarkers in urban areas were mediated by greater reliance on processed, calorically dense foods (i.e., refined carbohydrates and cooking fats) and reduced consumption of animal products (Figs. 1 and 3). However, our mediation analyses also show that broader measures of lifestyle modernization (e.g., population density, distance to a major city, and female education levels) have stronger explanatory power than diet alone. It is likely that these indices serve as proxies for unmeasured, more proximate mediators, such as psychosocial stress, nutrient balance, total caloric intake, or total energy expenditure, all of which vary by industrialization and can affect health (1, 12, 6063). The fact that the number of meals eaten per day (which is typically one in rural areas and two to three in urban areas) was a strong mediator for three of six variables points to total caloric intake, while the importance of occupation suggests activity levels are also probably key. More generally and as expected, our mediation analyses suggest that the link between lifestyle change and health is complex, multifactorial (e.g., driven by a suite of dietary and other factors), and potentially quite different for different biomarkers. Work with the Turkana is under way to address some of the unmeasured sources of variance that we hypothesize to be especially critical, namely, total caloric intake and total energy expenditure.

In addition to the pervasive influence of adult lifestyle on metabolic physiology that we observe in the Turkana, our analyses also revealed appreciable effects of early-life environments. In particular, controlling for the adult environment (urban or rural), birth location population density was a significant predictor of BMI, waist circumference, diastolic blood pressure, our composite measure of health, and body fat. Further, the impact of early-life and adult conditions appears to be on the same order of magnitude, although they do, in some cases, vary up to twofold. In particular, we observed 2 to 6% differences in BMI, waist circumference, and diastolic blood pressure, as a function of each life stage, while body fat and our composite measure show changes in the 11 to 20% range (note, however, that the measures that we used to quantify early-life and adult conditions are not the same, making direct effect size comparisons difficult; table S4A).

We did not find evidence that individuals who grew up in rural versus urban conditions were more prepared for these environments later in life, as predicted by PAR. These findings agree with work in preindustrial human populations and long-lived mammals, which have found weak or no support for PARs (26, 27, 6466). Together, these findings suggest that because early-life ecological conditions are often a poor predictor of adult environments for long-lived organisms, a strategy matching individual physiology to an unpredictable adult environment is unlikely to evolve (6769). Instead, our work joins others in concluding that challenging early-life environments simply incur long-term health costs (26, 27, 6466). While previous work in subsistence-level groups has clearly shown an effect of early-life environments (including acculturation) on health outcomes (52, 59), it has not explicitly tested whether PAR versus DC models explain these associations. Our attempt to do so here in the context of urbanicity exposure suggests that rapid industrial transitions are unlikely to create health problems because of within-lifetime environmental mismatches (26, 27, 70). Instead, our findings suggest that greater cumulative exposure to urban, industrialized environments across the life course will create the largest burdens of cardiometabolic disease.

Our study has several limitations. First, with the exception of our biomarker measurements, most of our data are self-reported. It is possible that recall may be imperfect, answers may be exaggerated to appear impressive (e.g., in interviews about the ownership of market goods), or participants may not wish to reveal private details (e.g., in interviews about health habits or covariates). On the basis of our conversations with study participants, we expect intentionally provided misinformation to be rare, but there are two areas where self-reporting contributes to specific limitations worthy of discussion. First, because our age data are self-reported, this key covariate is likely noisy and more so for rural than for urban participants (who are more likely to know their exact birth date). We do not have a reason to believe that this issue affects our estimate of the lifestyle-cardiometabolic health relationship, but it does likely complicate our ability to identify age by lifestyle interactions, which is a critical area for future study. Second, because our diet data are self-reported, we are currently unable to tease apart the precise nutritional components that drive health variation in the Turkana. Our mediation analyses reveal that several market-derived foods are key contributors, suggesting that broad exposure to processed, high-energy foods (including both carbohydrates and fats) is important for cardiometabolic health. Future work that estimates the total caloric intake and the intake of fat, protein, carbohydrates, and micronutrients [as in (71)] in the Turkana are planned.

A second limitation is that we do not know how our biomarker values are related to outcomes such as heart disease or mortality in the Turkana. We are relying on work in Western cohorts that has related lipid profiles, blood glucose, blood pressure, and measures of adiposity to these outcomes (72), but it is possible that those relationships are different in the Turkana [e.g., work in the United States has already demonstrated how the shape of the BMI-mortality curve may differ by race/ethnicity (73)]. Further, certain biomarkers may not linearly track disease and mortality risk: Notably, in Western cohorts, the effect of BMI on all-cause mortality risk is J shaped, such that underweight individuals experience some increase in risk, normal BMI individuals experience the lowest risk, and overweight and obese individuals experience the greatest risk (74). It is therefore difficult to draw conclusions about the relationship between any one biomarker, lifestyle change, and long-term outcomes in the present study. However, two pieces of evidence suggest that the changing biomarker profiles that we observe in urban Turkana are meaningful. First, work in Western countries has consistently shown that when individuals simultaneously cross clinical thresholds for several biomarkers, as we observe in urban Turkana, risk of cardiovascular events and all-cause mortality increases (72). Second, Kenya has seen a marked rise in CVD in recent decades, with 13% of hospital deaths in 2014 attributed to CVD. CVD risk is much higher in urban relative to rural areas across the country, with hypertension and type 2 diabetes estimated to be at least fourfold more prevalent in urban settings (75).

Last, a third limitation of our study is that we lack data on several key factors known to modify or mediate the relationship between lifestyle change and cardiometabolic health, such as total energy expenditure (1), total caloric intake and nutritional composition of the diet (71), and parasite load (76). Our ongoing research with the Turkana is in the process of gathering data on these sources of variance.

The hypothesis that mismatches between evolved human physiology and Western lifestyles cause disease has become a central tenet of evolutionary medicine, with potentially profound implications for how we study, manage, and treat a long list of conditions thought to arise from evolutionary mismatch (77). However, this hypothesis has been difficult to robustly test in practice because of inadequate population comparisons and the multiple types of mismatch to be considered. Leveraging the lifestyle change currently occurring in the Turkana population, we show that cardiometabolic health is worse in urban relative to rural areas but that small deviations from traditional, ancestral practices in rural areas do not produce health effects. To build upon our results, we advocate for more within-population comparisons spanning large lifestyle gradients, combined with longitudinal sampling designs [e.g., (72)]. Longitudinal study of other populations undergoing industrial transitions would also be invaluable for assessing the generality of the early-life effects on adult cardiometabolic health that we observe here and for identifying the specific early-life ecological, social, or behavioral factors that drive long-term variation in health.

Data were collected between April 2018 and March 2019 in Turkana and Laikipia counties in Kenya. During this time, researchers visited locations where individuals of Turkana ancestry were known to reside (Fig. 1). At each sampling location, healthy adults (>18 years old) of self-reported Turkana ancestry were invited to participate in the study, which involved a structured interview and measurement of 10 cardiometabolic biomarkers. Participation rates of eligible adults were high (>75%). GPS coordinates were recorded on a handheld Garmin GPSMAP 64 device at each sampling location. Additional details on the sampling procedures can be found in Supplementary Materials and Methods.

This study was approved by Princeton Universitys Institutional Review Board for Human Subjects Research (Institutional Review Board no. 10237) and Maseno Universitys Ethics Review Committee (MSU/DRPI/MUERC/00519/18). We also received county-level approval from both Laikipia and Turkana counties for research activities and research permits from Kenyas National Commission for Science, Technology, and Innovation (NACOSTI/P/18/46195/24671). Written, informed consent was obtained from all participants after the study goals, sampling procedures, and potential risks were discussed with community elders and explained to participants in their native language (by both a local official, usually the village chief, and by researchers or field assistants).

Individuals were excluded from analyses if they met any of the following criteria: (i) pregnancy, (ii) extreme outlier values for a given biomarker, (iii) missing data on primary subsistence activity, (iv) missing interview data, and (v) missing gender or age. For the early-life effects analyses, we also excluded individuals that did not report a birth location or for whom GPS coordinates for the reported birth location could not be identified on a map. Those missing birth locations had similar health profiles as individuals for whom a birth location could be assigned (all FDR > 5% for linear models testing for an effect of birth location missingness on each biomarker, controlling for age, sex, and lifestyle; table S4C). Thus, although the sample sizes for our early-life effects analyses are smaller than for analyses focused on current environmental/lifestyle effects (table S4A), this sample size reduction is not systematically biased in a way that is likely to affect the results.

Before statistical analyses, all biomarkers (except the composite measure of health) were mean centered and scaled by their SD, using the scale function in R (78). Consequently, all reported effect sizes are standardized and represent the effect of a given variable on the outcome in terms of increases in SDs.

Testing for lifestyle effects on measured biomarkers. For each of the 10 measured biomarkers, we used the following linear model to test for effects of lifestyle controlling for covariatesyi=0+lil+aia+sis+ei(1)where yi is the normalized (mean centered and scaled by the SD) biomarker value for individual i, li is lifestyle (pastoralist; nonpastoralist, rural; or nonpastoralist, urban), ai is age (in years), si is sex (male or female), and ei represents residual error. To determine whether a given biomarker exhibited a lifestyle by sex interaction, we used a likelihood ratio test to compare the fit of model 1 with the following modelyi=0+lil+aia+sis+(lisi)ls+ei(2)

In model 2, l s represents a lifestyle by sex interaction effect. If the P value for the likelihood ratio test comparing models 1 and 2 was less than 0.05, then we concluded that a lifestyle by sex interaction existed, and we tested for the effects of lifestyle within each gender separately (controlling for age). These analyses revealed lifestyle associations with body fat and blood glucose in females but not males (fig. S1). All additional analyses for these biomarkers therefore analyzed data from females alone.

Analyses of blood glucose levels included a covariate noting whether the individual had fasted overnight before the time of blood collection (which was always in the morning). For analyses of the composite measure of health, we used the same approach and the same main and interaction effects described for models 1 and 2 paired with generalized linear models with a binomial link function to accommodate count data. Specifically, the composite measure of health was modeled as the number of biomarkers that exceeded clinical cutoffs/the number of biomarkers measured for a given individual. Only individuals with three or more measured biomarkers were included in this analysis.

For all 11 measures (10 biomarkers and 1 composite measure), we extracted the P values associated with the lifestyle effect (l) from our models and corrected for multiple hypothesis testing using a Benjamini-Hochberg FDR (79). We considered a given lifestyle contrast to be significant if the FDR-corrected P value was less than 0.05 (equivalent to a 5% FDR threshold). The results of all final models are presented in table S2A.

Identifying factors that mediate lifestyle effects on measured biomarkers. For each biomarker that was significantly associated with lifestyle (table S2A), we were interested in identifying specific variables that mediated urban-rural differences in health. However, we did not perform mediation analyses for lipid traits and for blood glucose, as sample sizes for these biomarkers were smaller to begin with, and, after overlapping with our dietary data, we could only include 50 to 60 urban individuals. Therefore, we focused mediation analyses on waist circumference, BMI, diastolic and systolic blood pressure, body fat, and our composite measure of health (sample sizes for mediation analyses are presented in table S3).

To implement mediation analyses, we used an approach similar to (80, 81) to estimate the indirect effect of lifestyle on a given biomarker through the following potential mediating variables: alcohol and tobacco use (yes/no); consumption of meat, milk, blood, cooking oil, sugar, salt, bread, rice, ugali, potatoes, soda, fried foods, and sweets (frequency of use measured on a 0 to 4 scale); total number of unique carbohydrate items consumed; number of meals eaten per day; distance to the nearest city (in kilometers); log10 population density; main subsistence activity; proportion of mothers in the sampling location with no formal education; and a tally of the number of market-derived amenities an individual had (see Supplementary Materials and Methods). Occupation was coded to reflect integration in the market economy as follows: 0 = animal keeping, farming, fishing, hunting, and gathering; 1 = charcoal burning and mat making; 2 = casual worker, petty trade, and self-employment; and 3 = formal employment. To estimate female education levels in a given area, we calculated the fraction of women sampled in a given area with >0 children who reported having received no education. Population density, distance to a city, the proportion of mothers with no formal education, and the number of owned market goods are all measures that have been used in the literature to describe how urban a given individual/location is (82, 83). Population density estimates were derived from NASAs Socioeconomic Data and Applications Center (https://doi.org/10.7927/H49C6VHW). Specifically, we used the Gridded Population of the World database (version 4.11) to estimate the number of persons per square kilometer for each sampling location based on our GPS coordinates (see the Supplementary Materials).

For all mediation analyses, we used two categories to describe lifestyle, urban and rural, given minimal health differences between pastoralist and nonpastoralist Turkana living in rural areas. For biomarkers with no sex by lifestyle interaction, we estimated the strength of the indirect effect of each mediator as the difference between the effect of lifestyle (urban versus rural) in two linear models: the unadjusted model that did not account for the mediator (equivalent to model 1 in the Testing for lifestyle effects on measured biomarkers section) and the effect of lifestyle in an adjusted model that also incorporated the mediator. If a given variable is a strong mediator, then the effect of lifestyle will decrease when this variable is included in the model and absorbs variance otherwise attributed to lifestyle. For each biomarker, the adjusted model was implemented as followsyi=0+lil+aia+sis+mim+ei(3)

Where m represents the effect of the potential mediator on the outcome variable (all other variables are as defined in model 1). For body fat percentage, which displayed lifestyle effects in females but not males (fig. S1), we modeled females only and removed the sex term (s) from models 1 and 3. For the composite measure of health, we used generalized linear models with a binomial link function instead of linear models.

To assess the significance of each mediating variable, we estimated the decrease in l in model 1 relative to model 3 across 1000 iterations of bootstrap resampling. We deemed a variable to be a significant mediator if the lower bound of the 95% confidence interval (for the decrease in l) did not overlap with 0. As a measure of effect size, we report the proportion of 1000 bootstrap resampling iterations for which the effect of lifestyle (l) was reduced when the potential mediating variable was included in the model (table S3); a proportion of >0.975 is equivalent to a 95% confidence interval that does not overlap with 0. As another measure of effect size, we report the percent change in the lifestyle effect estimated from model 1 relative to model 3 for each biomarker-mediator pair (without bootstrapping and using the full dataset to estimate each effect size; Fig. 3). Further, to understand the degree to which the total set of mediators that we identified explain the relationship between lifestyle and a given biomarker, we report the percent change in effect size for the lifestyle effect estimated from model 1 versus a model that included all the same covariates and all significant mediators for a given biomarker.

Testing for early-life effects on biomarkers of adult health. Several research groups (26, 27, 64, 65, 84) have operationalized the PAR and DC hypotheses by asking whether there is evidence for interaction effects between early-life and adult environments (in support of PAR) or whether early-life adversity is instead consistently associated with compromised adult health (in support of DC). We took a similar approach to disentangle these hypotheses. For biomarkers with no sex and lifestyle interaction, we first asked whether there was any evidence for interaction effects between adult lifestyle and lifestyle/urbanicity during early life using the following linear modelyi=0+lil+aia+sis+did+(lidi)ld+ei(4)where di represents the log10 population density for the birth location of individual i during their birth year, li represents adult lifestyle (urban versus rural), and ld captures the interaction effect between these two variables. For the two variables with lifestyle effects on health in females but not males (body fat percentage and blood glucose levels), we modeled females only and removed the sex term (s). For the composite measure of health, we used generalized linear models with a binomial link function instead of linear models. For each of the 11 models, we extracted the P value associated with ld and corrected for multiple hypothesis testing (79). In all cases, the nominal and FDR-corrected P value was >0.05, suggesting that PARs do not explain early-life effects on health in the Turkana.

Next, we reran the appropriate version of model 4 for each measure after removing the interaction effect (ld). For biomarkers with no sex and lifestyle interaction, this model was equivalent toyi=0+lil+aia+sis+did+ei(5)

For each of the 11 models, we extracted the P value associated with the early-life effect (d) and corrected for multiple hypothesis testing (79). We considered a given variable to show support for the DC hypothesis if the FDR-corrected P value was less than 0.05. Results for all models described in this section are presented in table S4A. Results for parallel analyses that use log10 population density for the sampling location to define the adult environment (rather than a binary urban/rural lifestyle variable) are presented in table S4B. All statistical analyses were performed in R (78).

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Urbanization and market integration have strong, nonlinear effects on cardiometabolic health in the Turkana - Science Advances

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